diff options
63 files changed, 1681 insertions, 1348 deletions
diff --git a/Doc/library/inspect.rst b/Doc/library/inspect.rst index 3b62e7f..4357090 100644 --- a/Doc/library/inspect.rst +++ b/Doc/library/inspect.rst @@ -227,24 +227,6 @@ attributes: listed in the metaclass' custom :meth:`__dir__`. -.. function:: getmoduleinfo(path) - - Returns a :term:`named tuple` ``ModuleInfo(name, suffix, mode, module_type)`` - of values that describe how Python will interpret the file identified by - *path* if it is a module, or ``None`` if it would not be identified as a - module. In that tuple, *name* is the name of the module without the name of - any enclosing package, *suffix* is the trailing part of the file name (which - may not be a dot-delimited extension), *mode* is the :func:`open` mode that - would be used (``'r'`` or ``'rb'``), and *module_type* is an integer giving - the type of the module. *module_type* will have a value which can be - compared to the constants defined in the :mod:`imp` module; see the - documentation for that module for more information on module types. - - .. deprecated:: 3.3 - You may check the file path's suffix against the supported suffixes - listed in :mod:`importlib.machinery` to infer the same information. - - .. function:: getmodulename(path) Return the name of the module named by the file *path*, without including the @@ -258,8 +240,7 @@ attributes: still return ``None``. .. versionchanged:: 3.3 - This function is now based directly on :mod:`importlib` rather than the - deprecated :func:`getmoduleinfo`. + The function is based directly on :mod:`importlib`. .. function:: ismodule(object) @@ -808,24 +789,6 @@ Classes and functions classes using multiple inheritance and their descendants will appear multiple times. - -.. function:: getargspec(func) - - Get the names and default values of a Python function's arguments. A - :term:`named tuple` ``ArgSpec(args, varargs, keywords, defaults)`` is - returned. *args* is a list of the argument names. *varargs* and *keywords* - are the names of the ``*`` and ``**`` arguments or ``None``. *defaults* is a - tuple of default argument values or ``None`` if there are no default - arguments; if this tuple has *n* elements, they correspond to the last - *n* elements listed in *args*. - - .. deprecated:: 3.0 - Use :func:`signature` and - :ref:`Signature Object <inspect-signature-object>`, which provide a - better introspecting API for callables. This function will be removed - in Python 3.6. - - .. function:: getfullargspec(func) Get the names and default values of a Python function's arguments. A @@ -842,8 +805,6 @@ Classes and functions from kwonlyargs to defaults. *annotations* is a dictionary mapping argument names to annotations. - The first four items in the tuple correspond to :func:`getargspec`. - .. versionchanged:: 3.4 This function is now based on :func:`signature`, but still ignores ``__wrapped__`` attributes and includes the already bound first @@ -872,7 +833,7 @@ Classes and functions .. function:: formatargspec(args[, varargs, varkw, defaults, kwonlyargs, kwonlydefaults, annotations[, formatarg, formatvarargs, formatvarkw, formatvalue, formatreturns, formatannotations]]) Format a pretty argument spec from the values returned by - :func:`getargspec` or :func:`getfullargspec`. + :func:`getfullargspec`. The first seven arguments are (``args``, ``varargs``, ``varkw``, ``defaults``, ``kwonlyargs``, ``kwonlydefaults``, ``annotations``). diff --git a/Doc/library/multiprocessing.rst b/Doc/library/multiprocessing.rst index 8703f8f..e74430d 100644 --- a/Doc/library/multiprocessing.rst +++ b/Doc/library/multiprocessing.rst @@ -869,8 +869,13 @@ Miscellaneous .. function:: cpu_count() - Return the number of CPUs in the system. May raise - :exc:`NotImplementedError`. + Return the number of CPUs in the system. + + This number is not equivalent to the number of CPUs the current process can + use. The number of usable CPUs can be obtained with + ``len(os.sched_getaffinity(0))`` + + May raise :exc:`NotImplementedError`. .. seealso:: :func:`os.cpu_count` diff --git a/Doc/library/os.rst b/Doc/library/os.rst index d4032e0..cb34f3e 100644 --- a/Doc/library/os.rst +++ b/Doc/library/os.rst @@ -3596,6 +3596,11 @@ Miscellaneous System Information Return the number of CPUs in the system. Returns None if undetermined. + This number is not equivalent to the number of CPUs the current process can + use. The number of usable CPUs can be obtained with + ``len(os.sched_getaffinity(0))`` + + .. versionadded:: 3.4 diff --git a/Doc/library/urllib.parse.rst b/Doc/library/urllib.parse.rst index 40098d0..7c075ad 100644 --- a/Doc/library/urllib.parse.rst +++ b/Doc/library/urllib.parse.rst @@ -115,8 +115,9 @@ or on combining URL components into a URL string. | | | if present | | +------------------+-------+--------------------------+----------------------+ - See section :ref:`urlparse-result-object` for more information on the result - object. + Reading the :attr:`port` attribute will raise a :exc:`ValueError` if + an invalid port is specified in the URL. See section + :ref:`urlparse-result-object` for more information on the result object. .. versionchanged:: 3.2 Added IPv6 URL parsing capabilities. @@ -126,6 +127,10 @@ or on combining URL components into a URL string. false), in accordance with :rfc:`3986`. Previously, a whitelist of schemes that support fragments existed. + .. versionchanged:: 3.6 + Out-of-range port numbers now raise :exc:`ValueError`, instead of + returning :const:`None`. + .. function:: parse_qs(qs, keep_blank_values=False, strict_parsing=False, encoding='utf-8', errors='replace') @@ -228,8 +233,13 @@ or on combining URL components into a URL string. | | | if present | | +------------------+-------+-------------------------+----------------------+ - See section :ref:`urlparse-result-object` for more information on the result - object. + Reading the :attr:`port` attribute will raise a :exc:`ValueError` if + an invalid port is specified in the URL. See section + :ref:`urlparse-result-object` for more information on the result object. + + .. versionchanged:: 3.6 + Out-of-range port numbers now raise :exc:`ValueError`, instead of + returning :const:`None`. .. function:: urlunsplit(parts) diff --git a/Doc/tools/extensions/pyspecific.py b/Doc/tools/extensions/pyspecific.py index d44b052..9b78184 100644 --- a/Doc/tools/extensions/pyspecific.py +++ b/Doc/tools/extensions/pyspecific.py @@ -34,7 +34,7 @@ import suspicious ISSUE_URI = 'https://bugs.python.org/issue%s' -SOURCE_URI = 'https://hg.python.org/cpython/file/3.5/%s' +SOURCE_URI = 'https://hg.python.org/cpython/file/default/%s' # monkey-patch reST parser to disable alphabetic and roman enumerated lists from docutils.parsers.rst.states import Body diff --git a/Doc/tutorial/interpreter.rst b/Doc/tutorial/interpreter.rst index d5789a6..db0be32 100644 --- a/Doc/tutorial/interpreter.rst +++ b/Doc/tutorial/interpreter.rst @@ -1,4 +1,4 @@ -.. _tut-using: +3.6.. _tut-using: **************************** Using the Python Interpreter @@ -10,13 +10,13 @@ Using the Python Interpreter Invoking the Interpreter ======================== -The Python interpreter is usually installed as :file:`/usr/local/bin/python3.5` +The Python interpreter is usually installed as :file:`/usr/local/bin/python3.6` on those machines where it is available; putting :file:`/usr/local/bin` in your Unix shell's search path makes it possible to start it by typing the command: .. code-block:: text - python3.5 + python3.6 to the shell. [#]_ Since the choice of the directory where the interpreter lives is an installation option, other places are possible; check with your local @@ -24,11 +24,11 @@ Python guru or system administrator. (E.g., :file:`/usr/local/python` is a popular alternative location.) On Windows machines, the Python installation is usually placed in -:file:`C:\\Python35`, though you can change this when you're running the +:file:`C:\\Python36`, though you can change this when you're running the installer. To add this directory to your path, you can type the following command into the command prompt in a DOS box:: - set path=%path%;C:\python35 + set path=%path%;C:\python36 Typing an end-of-file character (:kbd:`Control-D` on Unix, :kbd:`Control-Z` on Windows) at the primary prompt causes the interpreter to exit with a zero exit @@ -96,8 +96,8 @@ with the *secondary prompt*, by default three dots (``...``). The interpreter prints a welcome message stating its version number and a copyright notice before printing the first prompt:: - $ python3.5 - Python 3.5 (default, Sep 16 2015, 09:25:04) + $ python3.6 + Python 3.6 (default, Sep 16 2015, 09:25:04) [GCC 4.8.2] on linux Type "help", "copyright", "credits" or "license" for more information. >>> diff --git a/Doc/tutorial/stdlib.rst b/Doc/tutorial/stdlib.rst index 0954eba..f9ed46d 100644 --- a/Doc/tutorial/stdlib.rst +++ b/Doc/tutorial/stdlib.rst @@ -15,7 +15,7 @@ operating system:: >>> import os >>> os.getcwd() # Return the current working directory - 'C:\\Python35' + 'C:\\Python36' >>> os.chdir('/server/accesslogs') # Change current working directory >>> os.system('mkdir today') # Run the command mkdir in the system shell 0 diff --git a/Doc/tutorial/stdlib2.rst b/Doc/tutorial/stdlib2.rst index f7d2a0a..71194b0 100644 --- a/Doc/tutorial/stdlib2.rst +++ b/Doc/tutorial/stdlib2.rst @@ -277,7 +277,7 @@ applications include caching objects that are expensive to create:: Traceback (most recent call last): File "<stdin>", line 1, in <module> d['primary'] # entry was automatically removed - File "C:/python35/lib/weakref.py", line 46, in __getitem__ + File "C:/python36/lib/weakref.py", line 46, in __getitem__ o = self.data[key]() KeyError: 'primary' diff --git a/Doc/whatsnew/3.6.rst b/Doc/whatsnew/3.6.rst new file mode 100644 index 0000000..e2aa1e2 --- /dev/null +++ b/Doc/whatsnew/3.6.rst @@ -0,0 +1,174 @@ +**************************** + What's New In Python 3.6 +**************************** + +:Release: |release| +:Date: |today| + +.. Rules for maintenance: + + * Anyone can add text to this document. Do not spend very much time + on the wording of your changes, because your text will probably + get rewritten to some degree. + + * The maintainer will go through Misc/NEWS periodically and add + changes; it's therefore more important to add your changes to + Misc/NEWS than to this file. + + * This is not a complete list of every single change; completeness + is the purpose of Misc/NEWS. Some changes I consider too small + or esoteric to include. If such a change is added to the text, + I'll just remove it. (This is another reason you shouldn't spend + too much time on writing your addition.) + + * If you want to draw your new text to the attention of the + maintainer, add 'XXX' to the beginning of the paragraph or + section. + + * It's OK to just add a fragmentary note about a change. For + example: "XXX Describe the transmogrify() function added to the + socket module." The maintainer will research the change and + write the necessary text. + + * You can comment out your additions if you like, but it's not + necessary (especially when a final release is some months away). + + * Credit the author of a patch or bugfix. Just the name is + sufficient; the e-mail address isn't necessary. + + * It's helpful to add the bug/patch number as a comment: + + XXX Describe the transmogrify() function added to the socket + module. + (Contributed by P.Y. Developer in :issue:`12345`.) + + This saves the maintainer the effort of going through the Mercurial log + when researching a change. + +This article explains the new features in Python 3.6, compared to 3.5. + +For full details, see the :source:`Misc/NEWS` file. + +.. note:: + + Prerelease users should be aware that this document is currently in draft + form. It will be updated substantially as Python 3.6 moves towards release, + so it's worth checking back even after reading earlier versions. + + +Summary -- Release highlights +============================= + +.. This section singles out the most important changes in Python 3.6. + Brevity is key. + +* None yet. + +.. PEP-sized items next. + +.. _pep-4XX: + +.. PEP 4XX: Virtual Environments +.. ============================= + + +.. (Implemented by Foo Bar.) + +.. .. seealso:: + + :pep:`4XX` - Python Virtual Environments + PEP written by Carl Meyer + + +Other Language Changes +====================== + +* None yet. + + +New Modules +=========== + +* None yet. + + +Improved Modules +================ + +* None yet. + + +Optimizations +============= + +* None yet. + + +Build and C API Changes +======================= + +* None yet. + + +Deprecated +========== + +New Keywords +------------ + +``async`` and ``await`` are not recommended to be used as variable, class, +function or module names. Introduced by :pep:`492` in Python 3.5, they will +become proper keywords in Python 3.7. + + +Deprecated Python modules, functions and methods +------------------------------------------------ + +* None yet. + + +Deprecated functions and types of the C API +------------------------------------------- + +* None yet. + + +Deprecated features +------------------- + +* None yet. + + +Removed +======= + +API and Feature Removals +------------------------ + +* ``inspect.getargspec()`` was removed (was deprecated since CPython 3.0). + :func:`inspect.getfullargspec` is an almost drop in replacement. + +* ``inspect.getmoduleinfo()`` was removed (was deprecated since CPython 3.3). + :func:`inspect.getmodulename` should be used for obtaining the module + name for a given path. + + +Porting to Python 3.6 +===================== + +This section lists previously described changes and other bugfixes +that may require changes to your code. + +Changes in the Python API +------------------------- + +* Reading the :attr:`~urllib.parse.SplitResult.port` attribute of + :func:`urllib.parse.urlsplit` and :func:`~urllib.parse.urlparse` results + now raises :exc:`ValueError` for out-of-range values, rather than + returning :const:`None`. See :issue:`20059`. + + +Changes in the C API +-------------------- + +* None yet. diff --git a/Doc/whatsnew/index.rst b/Doc/whatsnew/index.rst index edb5502..7c92524 100644 --- a/Doc/whatsnew/index.rst +++ b/Doc/whatsnew/index.rst @@ -11,6 +11,7 @@ anyone wishing to stay up-to-date after a new release. .. toctree:: :maxdepth: 2 + 3.6.rst 3.5.rst 3.4.rst 3.3.rst diff --git a/Include/patchlevel.h b/Include/patchlevel.h index eb056c5..246eba8 100644 --- a/Include/patchlevel.h +++ b/Include/patchlevel.h @@ -17,13 +17,13 @@ /* Version parsed out into numeric values */ /*--start constants--*/ #define PY_MAJOR_VERSION 3 -#define PY_MINOR_VERSION 5 +#define PY_MINOR_VERSION 6 #define PY_MICRO_VERSION 0 -#define PY_RELEASE_LEVEL PY_RELEASE_LEVEL_BETA -#define PY_RELEASE_SERIAL 4 +#define PY_RELEASE_LEVEL PY_RELEASE_LEVEL_ALPHA +#define PY_RELEASE_SERIAL 0 /* Version as a string */ -#define PY_VERSION "3.5.0b4+" +#define PY_VERSION "3.6.0a0" /*--end constants--*/ /* Version as a single 4-byte hex number, e.g. 0x010502B2 == 1.5.2b2. diff --git a/Include/setobject.h b/Include/setobject.h index f17bc1b..87ec1c8 100644 --- a/Include/setobject.h +++ b/Include/setobject.h @@ -10,12 +10,13 @@ extern "C" { /* There are three kinds of entries in the table: -1. Unused: key == NULL -2. Active: key != NULL and key != dummy -3. Dummy: key == dummy +1. Unused: key == NULL and hash == 0 +2. Dummy: key == dummy and hash == -1 +3. Active: key != NULL and key != dummy and hash != -1 -The hash field of Unused slots have no meaning. -The hash field of Dummny slots are set to -1 +The hash field of Unused slots is always zero. + +The hash field of Dummy slots are set to -1 meaning that dummy entries can be detected by either entry->key==dummy or by entry->hash==-1. */ diff --git a/Include/unicodeobject.h b/Include/unicodeobject.h index 4ba6328..33e8f19 100644 --- a/Include/unicodeobject.h +++ b/Include/unicodeobject.h @@ -2261,6 +2261,10 @@ PyAPI_FUNC(PyObject*) _PyUnicode_FromId(_Py_Identifier*); /* Clear all static strings. */ PyAPI_FUNC(void) _PyUnicode_ClearStaticStrings(void); +/* Fast equality check when the inputs are known to be exact unicode types + and where the hash values are equal (i.e. a very probable match) */ +PyAPI_FUNC(int) _PyUnicode_EQ(PyObject *, PyObject *); + #ifdef __cplusplus } #endif diff --git a/Lib/_pyio.py b/Lib/_pyio.py index 50ad9ff..33d8a3f 100644 --- a/Lib/_pyio.py +++ b/Lib/_pyio.py @@ -181,8 +181,8 @@ def open(file, mode="r", buffering=-1, encoding=None, errors=None, text = "t" in modes binary = "b" in modes if "U" in modes: - if creating or writing or appending: - raise ValueError("can't use U and writing mode at once") + if creating or writing or appending or updating: + raise ValueError("mode U cannot be combined with 'x', 'w', 'a', or '+'") import warnings warnings.warn("'U' mode is deprecated", DeprecationWarning, 2) diff --git a/Lib/argparse.py b/Lib/argparse.py index 9a06719..cc53841 100644 --- a/Lib/argparse.py +++ b/Lib/argparse.py @@ -118,10 +118,16 @@ class _AttributeHolder(object): def __repr__(self): type_name = type(self).__name__ arg_strings = [] + star_args = {} for arg in self._get_args(): arg_strings.append(repr(arg)) for name, value in self._get_kwargs(): - arg_strings.append('%s=%r' % (name, value)) + if name.isidentifier(): + arg_strings.append('%s=%r' % (name, value)) + else: + star_args[name] = value + if star_args: + arg_strings.append('**%s' % repr(star_args)) return '%s(%s)' % (type_name, ', '.join(arg_strings)) def _get_kwargs(self): diff --git a/Lib/distutils/core.py b/Lib/distutils/core.py index f05b34b..d603d4a 100644 --- a/Lib/distutils/core.py +++ b/Lib/distutils/core.py @@ -204,16 +204,15 @@ def run_setup (script_name, script_args=None, stop_after="run"): global _setup_stop_after, _setup_distribution _setup_stop_after = stop_after - save_argv = sys.argv + save_argv = sys.argv.copy() g = {'__file__': script_name} - l = {} try: try: sys.argv[0] = script_name if script_args is not None: sys.argv[1:] = script_args with open(script_name, 'rb') as f: - exec(f.read(), g, l) + exec(f.read(), g) finally: sys.argv = save_argv _setup_stop_after = None diff --git a/Lib/distutils/tests/test_core.py b/Lib/distutils/tests/test_core.py index 41321f7..57856f1 100644 --- a/Lib/distutils/tests/test_core.py +++ b/Lib/distutils/tests/test_core.py @@ -28,6 +28,21 @@ from distutils.core import setup setup() """ +setup_does_nothing = """\ +from distutils.core import setup +setup() +""" + + +setup_defines_subclass = """\ +from distutils.core import setup +from distutils.command.install import install as _install + +class install(_install): + sub_commands = _install.sub_commands + ['cmd'] + +setup(cmdclass={'install': install}) +""" class CoreTestCase(support.EnvironGuard, unittest.TestCase): @@ -65,6 +80,21 @@ class CoreTestCase(support.EnvironGuard, unittest.TestCase): distutils.core.run_setup( self.write_setup(setup_using___file__)) + def test_run_setup_preserves_sys_argv(self): + # Make sure run_setup does not clobber sys.argv + argv_copy = sys.argv.copy() + distutils.core.run_setup( + self.write_setup(setup_does_nothing)) + self.assertEqual(sys.argv, argv_copy) + + def test_run_setup_defines_subclass(self): + # Make sure the script can use __file__; if that's missing, the test + # setup.py script will raise NameError. + dist = distutils.core.run_setup( + self.write_setup(setup_defines_subclass)) + install = dist.get_command_obj('install') + self.assertIn('cmd', install.sub_commands) + def test_run_setup_uses_current_dir(self): # This tests that the setup script is run with the current directory # as its own current directory; this was temporarily broken by a diff --git a/Lib/inspect.py b/Lib/inspect.py index bf4f87d..a089be6 100644 --- a/Lib/inspect.py +++ b/Lib/inspect.py @@ -16,7 +16,7 @@ Here are some of the useful functions provided by this module: getmodule() - determine the module that an object came from getclasstree() - arrange classes so as to represent their hierarchy - getargspec(), getargvalues(), getcallargs() - get info about function arguments + getargvalues(), getcallargs() - get info about function arguments getfullargspec() - same, with support for Python 3 features formatargspec(), formatargvalues() - format an argument spec getouterframes(), getinnerframes() - get info about frames @@ -623,23 +623,6 @@ def getfile(object): raise TypeError('{!r} is not a module, class, method, ' 'function, traceback, frame, or code object'.format(object)) -ModuleInfo = namedtuple('ModuleInfo', 'name suffix mode module_type') - -def getmoduleinfo(path): - """Get the module name, suffix, mode, and module type for a given file.""" - warnings.warn('inspect.getmoduleinfo() is deprecated', DeprecationWarning, - 2) - with warnings.catch_warnings(): - warnings.simplefilter('ignore', PendingDeprecationWarning) - import imp - filename = os.path.basename(path) - suffixes = [(-len(suffix), suffix, mode, mtype) - for suffix, mode, mtype in imp.get_suffixes()] - suffixes.sort() # try longest suffixes first, in case they overlap - for neglen, suffix, mode, mtype in suffixes: - if filename[neglen:] == suffix: - return ModuleInfo(filename[:neglen], suffix, mode, mtype) - def getmodulename(path): """Return the module name for a given file, or None.""" fname = os.path.basename(path) @@ -1020,31 +1003,6 @@ def _getfullargs(co): varkw = co.co_varnames[nargs] return args, varargs, kwonlyargs, varkw - -ArgSpec = namedtuple('ArgSpec', 'args varargs keywords defaults') - -def getargspec(func): - """Get the names and default values of a function's arguments. - - A tuple of four things is returned: (args, varargs, keywords, defaults). - 'args' is a list of the argument names, including keyword-only argument names. - 'varargs' and 'keywords' are the names of the * and ** arguments or None. - 'defaults' is an n-tuple of the default values of the last n arguments. - - Use the getfullargspec() API for Python 3 code, as annotations - and keyword arguments are supported. getargspec() will raise ValueError - if the func has either annotations or keyword arguments. - """ - warnings.warn("inspect.getargspec() is deprecated, " - "use inspect.signature() instead", DeprecationWarning, - stacklevel=2) - args, varargs, varkw, defaults, kwonlyargs, kwonlydefaults, ann = \ - getfullargspec(func) - if kwonlyargs or ann: - raise ValueError("Function has keyword-only arguments or annotations" - ", use getfullargspec() API which can support them") - return ArgSpec(args, varargs, varkw, defaults) - FullArgSpec = namedtuple('FullArgSpec', 'args, varargs, varkw, defaults, kwonlyargs, kwonlydefaults, annotations') @@ -1060,8 +1018,6 @@ def getfullargspec(func): 'kwonlydefaults' is a dictionary mapping names from kwonlyargs to defaults. 'annotations' is a dictionary mapping argument names to annotations. - The first four items in the tuple correspond to getargspec(). - This function is deprecated, use inspect.signature() instead. """ @@ -1172,8 +1128,7 @@ def formatargspec(args, varargs=None, varkw=None, defaults=None, formatvalue=lambda value: '=' + repr(value), formatreturns=lambda text: ' -> ' + text, formatannotation=formatannotation): - """Format an argument spec from the values returned by getargspec - or getfullargspec. + """Format an argument spec from the values returned by getfullargspec. The first seven arguments are (args, varargs, varkw, defaults, kwonlyargs, kwonlydefaults, annotations). The other five arguments diff --git a/Lib/lib2to3/fixes/fix_types.py b/Lib/lib2to3/fixes/fix_types.py index db34104..00327a7 100644 --- a/Lib/lib2to3/fixes/fix_types.py +++ b/Lib/lib2to3/fixes/fix_types.py @@ -42,7 +42,7 @@ _TYPE_MAPPING = { 'NotImplementedType' : 'type(NotImplemented)', 'SliceType' : 'slice', 'StringType': 'bytes', # XXX ? - 'StringTypes' : 'str', # XXX ? + 'StringTypes' : '(str,)', # XXX ? 'TupleType': 'tuple', 'TypeType' : 'type', 'UnicodeType': 'str', diff --git a/Lib/lib2to3/tests/test_fixers.py b/Lib/lib2to3/tests/test_fixers.py index 06b0033..def9b0e 100644 --- a/Lib/lib2to3/tests/test_fixers.py +++ b/Lib/lib2to3/tests/test_fixers.py @@ -3322,6 +3322,10 @@ class Test_types(FixerTestCase): a = """type(None)""" self.check(b, a) + b = "types.StringTypes" + a = "(str,)" + self.check(b, a) + class Test_idioms(FixerTestCase): fixer = "idioms" diff --git a/Lib/pydoc_data/topics.py b/Lib/pydoc_data/topics.py index ce5442f..38857d2 100644 --- a/Lib/pydoc_data/topics.py +++ b/Lib/pydoc_data/topics.py @@ -1,5 +1,5 @@ # -*- coding: utf-8 -*- -# Autogenerated by Sphinx on Sat Jul 25 14:16:44 2015 +# Autogenerated by Sphinx on Sat May 23 17:38:41 2015 topics = {'assert': u'\nThe "assert" statement\n**********************\n\nAssert statements are a convenient way to insert debugging assertions\ninto a program:\n\n assert_stmt ::= "assert" expression ["," expression]\n\nThe simple form, "assert expression", is equivalent to\n\n if __debug__:\n if not expression: raise AssertionError\n\nThe extended form, "assert expression1, expression2", is equivalent to\n\n if __debug__:\n if not expression1: raise AssertionError(expression2)\n\nThese equivalences assume that "__debug__" and "AssertionError" refer\nto the built-in variables with those names. In the current\nimplementation, the built-in variable "__debug__" is "True" under\nnormal circumstances, "False" when optimization is requested (command\nline option -O). The current code generator emits no code for an\nassert statement when optimization is requested at compile time. Note\nthat it is unnecessary to include the source code for the expression\nthat failed in the error message; it will be displayed as part of the\nstack trace.\n\nAssignments to "__debug__" are illegal. The value for the built-in\nvariable is determined when the interpreter starts.\n', 'assignment': u'\nAssignment statements\n*********************\n\nAssignment statements are used to (re)bind names to values and to\nmodify attributes or items of mutable objects:\n\n assignment_stmt ::= (target_list "=")+ (expression_list | yield_expression)\n target_list ::= target ("," target)* [","]\n target ::= identifier\n | "(" target_list ")"\n | "[" target_list "]"\n | attributeref\n | subscription\n | slicing\n | "*" target\n\n(See section *Primaries* for the syntax definitions for\n*attributeref*, *subscription*, and *slicing*.)\n\nAn assignment statement evaluates the expression list (remember that\nthis can be a single expression or a comma-separated list, the latter\nyielding a tuple) and assigns the single resulting object to each of\nthe target lists, from left to right.\n\nAssignment is defined recursively depending on the form of the target\n(list). When a target is part of a mutable object (an attribute\nreference, subscription or slicing), the mutable object must\nultimately perform the assignment and decide about its validity, and\nmay raise an exception if the assignment is unacceptable. The rules\nobserved by various types and the exceptions raised are given with the\ndefinition of the object types (see section *The standard type\nhierarchy*).\n\nAssignment of an object to a target list, optionally enclosed in\nparentheses or square brackets, is recursively defined as follows.\n\n* If the target list is a single target: The object is assigned to\n that target.\n\n* If the target list is a comma-separated list of targets: The\n object must be an iterable with the same number of items as there\n are targets in the target list, and the items are assigned, from\n left to right, to the corresponding targets.\n\n * If the target list contains one target prefixed with an\n asterisk, called a "starred" target: The object must be a sequence\n with at least as many items as there are targets in the target\n list, minus one. The first items of the sequence are assigned,\n from left to right, to the targets before the starred target. The\n final items of the sequence are assigned to the targets after the\n starred target. A list of the remaining items in the sequence is\n then assigned to the starred target (the list can be empty).\n\n * Else: The object must be a sequence with the same number of\n items as there are targets in the target list, and the items are\n assigned, from left to right, to the corresponding targets.\n\nAssignment of an object to a single target is recursively defined as\nfollows.\n\n* If the target is an identifier (name):\n\n * If the name does not occur in a "global" or "nonlocal" statement\n in the current code block: the name is bound to the object in the\n current local namespace.\n\n * Otherwise: the name is bound to the object in the global\n namespace or the outer namespace determined by "nonlocal",\n respectively.\n\n The name is rebound if it was already bound. This may cause the\n reference count for the object previously bound to the name to reach\n zero, causing the object to be deallocated and its destructor (if it\n has one) to be called.\n\n* If the target is a target list enclosed in parentheses or in\n square brackets: The object must be an iterable with the same number\n of items as there are targets in the target list, and its items are\n assigned, from left to right, to the corresponding targets.\n\n* If the target is an attribute reference: The primary expression in\n the reference is evaluated. It should yield an object with\n assignable attributes; if this is not the case, "TypeError" is\n raised. That object is then asked to assign the assigned object to\n the given attribute; if it cannot perform the assignment, it raises\n an exception (usually but not necessarily "AttributeError").\n\n Note: If the object is a class instance and the attribute reference\n occurs on both sides of the assignment operator, the RHS expression,\n "a.x" can access either an instance attribute or (if no instance\n attribute exists) a class attribute. The LHS target "a.x" is always\n set as an instance attribute, creating it if necessary. Thus, the\n two occurrences of "a.x" do not necessarily refer to the same\n attribute: if the RHS expression refers to a class attribute, the\n LHS creates a new instance attribute as the target of the\n assignment:\n\n class Cls:\n x = 3 # class variable\n inst = Cls()\n inst.x = inst.x + 1 # writes inst.x as 4 leaving Cls.x as 3\n\n This description does not necessarily apply to descriptor\n attributes, such as properties created with "property()".\n\n* If the target is a subscription: The primary expression in the\n reference is evaluated. It should yield either a mutable sequence\n object (such as a list) or a mapping object (such as a dictionary).\n Next, the subscript expression is evaluated.\n\n If the primary is a mutable sequence object (such as a list), the\n subscript must yield an integer. If it is negative, the sequence\'s\n length is added to it. The resulting value must be a nonnegative\n integer less than the sequence\'s length, and the sequence is asked\n to assign the assigned object to its item with that index. If the\n index is out of range, "IndexError" is raised (assignment to a\n subscripted sequence cannot add new items to a list).\n\n If the primary is a mapping object (such as a dictionary), the\n subscript must have a type compatible with the mapping\'s key type,\n and the mapping is then asked to create a key/datum pair which maps\n the subscript to the assigned object. This can either replace an\n existing key/value pair with the same key value, or insert a new\n key/value pair (if no key with the same value existed).\n\n For user-defined objects, the "__setitem__()" method is called with\n appropriate arguments.\n\n* If the target is a slicing: The primary expression in the\n reference is evaluated. It should yield a mutable sequence object\n (such as a list). The assigned object should be a sequence object\n of the same type. Next, the lower and upper bound expressions are\n evaluated, insofar they are present; defaults are zero and the\n sequence\'s length. The bounds should evaluate to integers. If\n either bound is negative, the sequence\'s length is added to it. The\n resulting bounds are clipped to lie between zero and the sequence\'s\n length, inclusive. Finally, the sequence object is asked to replace\n the slice with the items of the assigned sequence. The length of\n the slice may be different from the length of the assigned sequence,\n thus changing the length of the target sequence, if the target\n sequence allows it.\n\n**CPython implementation detail:** In the current implementation, the\nsyntax for targets is taken to be the same as for expressions, and\ninvalid syntax is rejected during the code generation phase, causing\nless detailed error messages.\n\nAlthough the definition of assignment implies that overlaps between\nthe left-hand side and the right-hand side are \'simultanenous\' (for\nexample "a, b = b, a" swaps two variables), overlaps *within* the\ncollection of assigned-to variables occur left-to-right, sometimes\nresulting in confusion. For instance, the following program prints\n"[0, 2]":\n\n x = [0, 1]\n i = 0\n i, x[i] = 1, 2 # i is updated, then x[i] is updated\n print(x)\n\nSee also: **PEP 3132** - Extended Iterable Unpacking\n\n The specification for the "*target" feature.\n\n\nAugmented assignment statements\n===============================\n\nAugmented assignment is the combination, in a single statement, of a\nbinary operation and an assignment statement:\n\n augmented_assignment_stmt ::= augtarget augop (expression_list | yield_expression)\n augtarget ::= identifier | attributeref | subscription | slicing\n augop ::= "+=" | "-=" | "*=" | "@=" | "/=" | "//=" | "%=" | "**="\n | ">>=" | "<<=" | "&=" | "^=" | "|="\n\n(See section *Primaries* for the syntax definitions of the last three\nsymbols.)\n\nAn augmented assignment evaluates the target (which, unlike normal\nassignment statements, cannot be an unpacking) and the expression\nlist, performs the binary operation specific to the type of assignment\non the two operands, and assigns the result to the original target.\nThe target is only evaluated once.\n\nAn augmented assignment expression like "x += 1" can be rewritten as\n"x = x + 1" to achieve a similar, but not exactly equal effect. In the\naugmented version, "x" is only evaluated once. Also, when possible,\nthe actual operation is performed *in-place*, meaning that rather than\ncreating a new object and assigning that to the target, the old object\nis modified instead.\n\nUnlike normal assignments, augmented assignments evaluate the left-\nhand side *before* evaluating the right-hand side. For example, "a[i]\n+= f(x)" first looks-up "a[i]", then it evaluates "f(x)" and performs\nthe addition, and lastly, it writes the result back to "a[i]".\n\nWith the exception of assigning to tuples and multiple targets in a\nsingle statement, the assignment done by augmented assignment\nstatements is handled the same way as normal assignments. Similarly,\nwith the exception of the possible *in-place* behavior, the binary\noperation performed by augmented assignment is the same as the normal\nbinary operations.\n\nFor targets which are attribute references, the same *caveat about\nclass and instance attributes* applies as for regular assignments.\n', 'atom-identifiers': u'\nIdentifiers (Names)\n*******************\n\nAn identifier occurring as an atom is a name. See section\n*Identifiers and keywords* for lexical definition and section *Naming\nand binding* for documentation of naming and binding.\n\nWhen the name is bound to an object, evaluation of the atom yields\nthat object. When a name is not bound, an attempt to evaluate it\nraises a "NameError" exception.\n\n**Private name mangling:** When an identifier that textually occurs in\na class definition begins with two or more underscore characters and\ndoes not end in two or more underscores, it is considered a *private\nname* of that class. Private names are transformed to a longer form\nbefore code is generated for them. The transformation inserts the\nclass name, with leading underscores removed and a single underscore\ninserted, in front of the name. For example, the identifier "__spam"\noccurring in a class named "Ham" will be transformed to "_Ham__spam".\nThis transformation is independent of the syntactical context in which\nthe identifier is used. If the transformed name is extremely long\n(longer than 255 characters), implementation defined truncation may\nhappen. If the class name consists only of underscores, no\ntransformation is done.\n', @@ -18,8 +18,8 @@ topics = {'assert': u'\nThe "assert" statement\n**********************\n\nAssert 'callable-types': u'\nEmulating callable objects\n**************************\n\nobject.__call__(self[, args...])\n\n Called when the instance is "called" as a function; if this method\n is defined, "x(arg1, arg2, ...)" is a shorthand for\n "x.__call__(arg1, arg2, ...)".\n', 'calls': u'\nCalls\n*****\n\nA call calls a callable object (e.g., a *function*) with a possibly\nempty series of *arguments*:\n\n call ::= primary "(" [argument_list [","] | comprehension] ")"\n argument_list ::= positional_arguments ["," keyword_arguments]\n ["," "*" expression] ["," keyword_arguments]\n ["," "**" expression]\n | keyword_arguments ["," "*" expression]\n ["," keyword_arguments] ["," "**" expression]\n | "*" expression ["," keyword_arguments] ["," "**" expression]\n | "**" expression\n positional_arguments ::= expression ("," expression)*\n keyword_arguments ::= keyword_item ("," keyword_item)*\n keyword_item ::= identifier "=" expression\n\nAn optional trailing comma may be present after the positional and\nkeyword arguments but does not affect the semantics.\n\nThe primary must evaluate to a callable object (user-defined\nfunctions, built-in functions, methods of built-in objects, class\nobjects, methods of class instances, and all objects having a\n"__call__()" method are callable). All argument expressions are\nevaluated before the call is attempted. Please refer to section\n*Function definitions* for the syntax of formal *parameter* lists.\n\nIf keyword arguments are present, they are first converted to\npositional arguments, as follows. First, a list of unfilled slots is\ncreated for the formal parameters. If there are N positional\narguments, they are placed in the first N slots. Next, for each\nkeyword argument, the identifier is used to determine the\ncorresponding slot (if the identifier is the same as the first formal\nparameter name, the first slot is used, and so on). If the slot is\nalready filled, a "TypeError" exception is raised. Otherwise, the\nvalue of the argument is placed in the slot, filling it (even if the\nexpression is "None", it fills the slot). When all arguments have\nbeen processed, the slots that are still unfilled are filled with the\ncorresponding default value from the function definition. (Default\nvalues are calculated, once, when the function is defined; thus, a\nmutable object such as a list or dictionary used as default value will\nbe shared by all calls that don\'t specify an argument value for the\ncorresponding slot; this should usually be avoided.) If there are any\nunfilled slots for which no default value is specified, a "TypeError"\nexception is raised. Otherwise, the list of filled slots is used as\nthe argument list for the call.\n\n**CPython implementation detail:** An implementation may provide\nbuilt-in functions whose positional parameters do not have names, even\nif they are \'named\' for the purpose of documentation, and which\ntherefore cannot be supplied by keyword. In CPython, this is the case\nfor functions implemented in C that use "PyArg_ParseTuple()" to parse\ntheir arguments.\n\nIf there are more positional arguments than there are formal parameter\nslots, a "TypeError" exception is raised, unless a formal parameter\nusing the syntax "*identifier" is present; in this case, that formal\nparameter receives a tuple containing the excess positional arguments\n(or an empty tuple if there were no excess positional arguments).\n\nIf any keyword argument does not correspond to a formal parameter\nname, a "TypeError" exception is raised, unless a formal parameter\nusing the syntax "**identifier" is present; in this case, that formal\nparameter receives a dictionary containing the excess keyword\narguments (using the keywords as keys and the argument values as\ncorresponding values), or a (new) empty dictionary if there were no\nexcess keyword arguments.\n\nIf the syntax "*expression" appears in the function call, "expression"\nmust evaluate to an iterable. Elements from this iterable are treated\nas if they were additional positional arguments; if there are\npositional arguments *x1*, ..., *xN*, and "expression" evaluates to a\nsequence *y1*, ..., *yM*, this is equivalent to a call with M+N\npositional arguments *x1*, ..., *xN*, *y1*, ..., *yM*.\n\nA consequence of this is that although the "*expression" syntax may\nappear *after* some keyword arguments, it is processed *before* the\nkeyword arguments (and the "**expression" argument, if any -- see\nbelow). So:\n\n >>> def f(a, b):\n ... print(a, b)\n ...\n >>> f(b=1, *(2,))\n 2 1\n >>> f(a=1, *(2,))\n Traceback (most recent call last):\n File "<stdin>", line 1, in ?\n TypeError: f() got multiple values for keyword argument \'a\'\n >>> f(1, *(2,))\n 1 2\n\nIt is unusual for both keyword arguments and the "*expression" syntax\nto be used in the same call, so in practice this confusion does not\narise.\n\nIf the syntax "**expression" appears in the function call,\n"expression" must evaluate to a mapping, the contents of which are\ntreated as additional keyword arguments. In the case of a keyword\nappearing in both "expression" and as an explicit keyword argument, a\n"TypeError" exception is raised.\n\nFormal parameters using the syntax "*identifier" or "**identifier"\ncannot be used as positional argument slots or as keyword argument\nnames.\n\nA call always returns some value, possibly "None", unless it raises an\nexception. How this value is computed depends on the type of the\ncallable object.\n\nIf it is---\n\na user-defined function:\n The code block for the function is executed, passing it the\n argument list. The first thing the code block will do is bind the\n formal parameters to the arguments; this is described in section\n *Function definitions*. When the code block executes a "return"\n statement, this specifies the return value of the function call.\n\na built-in function or method:\n The result is up to the interpreter; see *Built-in Functions* for\n the descriptions of built-in functions and methods.\n\na class object:\n A new instance of that class is returned.\n\na class instance method:\n The corresponding user-defined function is called, with an argument\n list that is one longer than the argument list of the call: the\n instance becomes the first argument.\n\na class instance:\n The class must define a "__call__()" method; the effect is then the\n same as if that method was called.\n', 'class': u'\nClass definitions\n*****************\n\nA class definition defines a class object (see section *The standard\ntype hierarchy*):\n\n classdef ::= [decorators] "class" classname [inheritance] ":" suite\n inheritance ::= "(" [parameter_list] ")"\n classname ::= identifier\n\nA class definition is an executable statement. The inheritance list\nusually gives a list of base classes (see *Customizing class creation*\nfor more advanced uses), so each item in the list should evaluate to a\nclass object which allows subclassing. Classes without an inheritance\nlist inherit, by default, from the base class "object"; hence,\n\n class Foo:\n pass\n\nis equivalent to\n\n class Foo(object):\n pass\n\nThe class\'s suite is then executed in a new execution frame (see\n*Naming and binding*), using a newly created local namespace and the\noriginal global namespace. (Usually, the suite contains mostly\nfunction definitions.) When the class\'s suite finishes execution, its\nexecution frame is discarded but its local namespace is saved. [4] A\nclass object is then created using the inheritance list for the base\nclasses and the saved local namespace for the attribute dictionary.\nThe class name is bound to this class object in the original local\nnamespace.\n\nClass creation can be customized heavily using *metaclasses*.\n\nClasses can also be decorated: just like when decorating functions,\n\n @f1(arg)\n @f2\n class Foo: pass\n\nis equivalent to\n\n class Foo: pass\n Foo = f1(arg)(f2(Foo))\n\nThe evaluation rules for the decorator expressions are the same as for\nfunction decorators. The result must be a class object, which is then\nbound to the class name.\n\n**Programmer\'s note:** Variables defined in the class definition are\nclass attributes; they are shared by instances. Instance attributes\ncan be set in a method with "self.name = value". Both class and\ninstance attributes are accessible through the notation ""self.name"",\nand an instance attribute hides a class attribute with the same name\nwhen accessed in this way. Class attributes can be used as defaults\nfor instance attributes, but using mutable values there can lead to\nunexpected results. *Descriptors* can be used to create instance\nvariables with different implementation details.\n\nSee also: **PEP 3115** - Metaclasses in Python 3 **PEP 3129** -\n Class Decorators\n', - 'comparisons': u'\nComparisons\n***********\n\nUnlike C, all comparison operations in Python have the same priority,\nwhich is lower than that of any arithmetic, shifting or bitwise\noperation. Also unlike C, expressions like "a < b < c" have the\ninterpretation that is conventional in mathematics:\n\n comparison ::= or_expr ( comp_operator or_expr )*\n comp_operator ::= "<" | ">" | "==" | ">=" | "<=" | "!="\n | "is" ["not"] | ["not"] "in"\n\nComparisons yield boolean values: "True" or "False".\n\nComparisons can be chained arbitrarily, e.g., "x < y <= z" is\nequivalent to "x < y and y <= z", except that "y" is evaluated only\nonce (but in both cases "z" is not evaluated at all when "x < y" is\nfound to be false).\n\nFormally, if *a*, *b*, *c*, ..., *y*, *z* are expressions and *op1*,\n*op2*, ..., *opN* are comparison operators, then "a op1 b op2 c ... y\nopN z" is equivalent to "a op1 b and b op2 c and ... y opN z", except\nthat each expression is evaluated at most once.\n\nNote that "a op1 b op2 c" doesn\'t imply any kind of comparison between\n*a* and *c*, so that, e.g., "x < y > z" is perfectly legal (though\nperhaps not pretty).\n\nThe operators "<", ">", "==", ">=", "<=", and "!=" compare the values\nof two objects. The objects need not have the same type. If both are\nnumbers, they are converted to a common type. Otherwise, the "==" and\n"!=" operators *always* consider objects of different types to be\nunequal, while the "<", ">", ">=" and "<=" operators raise a\n"TypeError" when comparing objects of different types that do not\nimplement these operators for the given pair of types. You can\ncontrol comparison behavior of objects of non-built-in types by\ndefining rich comparison methods like "__gt__()", described in section\n*Basic customization*.\n\nComparison of objects of the same type depends on the type:\n\n* Numbers are compared arithmetically.\n\n* The values "float(\'NaN\')" and "Decimal(\'NaN\')" are special. They\n are identical to themselves, "x is x" but are not equal to\n themselves, "x != x". Additionally, comparing any value to a\n not-a-number value will return "False". For example, both "3 <\n float(\'NaN\')" and "float(\'NaN\') < 3" will return "False".\n\n* Bytes objects are compared lexicographically using the numeric\n values of their elements.\n\n* Strings are compared lexicographically using the numeric\n equivalents (the result of the built-in function "ord()") of their\n characters. [3] String and bytes object can\'t be compared!\n\n* Tuples and lists are compared lexicographically using comparison\n of corresponding elements. This means that to compare equal, each\n element must compare equal and the two sequences must be of the same\n type and have the same length.\n\n If not equal, the sequences are ordered the same as their first\n differing elements. For example, "[1,2,x] <= [1,2,y]" has the same\n value as "x <= y". If the corresponding element does not exist, the\n shorter sequence is ordered first (for example, "[1,2] < [1,2,3]").\n\n* Mappings (dictionaries) compare equal if and only if they have the\n same "(key, value)" pairs. Order comparisons "(\'<\', \'<=\', \'>=\',\n \'>\')" raise "TypeError".\n\n* Sets and frozensets define comparison operators to mean subset and\n superset tests. Those relations do not define total orderings (the\n two sets "{1,2}" and "{2,3}" are not equal, nor subsets of one\n another, nor supersets of one another). Accordingly, sets are not\n appropriate arguments for functions which depend on total ordering.\n For example, "min()", "max()", and "sorted()" produce undefined\n results given a list of sets as inputs.\n\n* Most other objects of built-in types compare unequal unless they\n are the same object; the choice whether one object is considered\n smaller or larger than another one is made arbitrarily but\n consistently within one execution of a program.\n\nComparison of objects of differing types depends on whether either of\nthe types provide explicit support for the comparison. Most numeric\ntypes can be compared with one another. When cross-type comparison is\nnot supported, the comparison method returns "NotImplemented".\n\nThe operators "in" and "not in" test for membership. "x in s"\nevaluates to true if *x* is a member of *s*, and false otherwise. "x\nnot in s" returns the negation of "x in s". All built-in sequences\nand set types support this as well as dictionary, for which "in" tests\nwhether the dictionary has a given key. For container types such as\nlist, tuple, set, frozenset, dict, or collections.deque, the\nexpression "x in y" is equivalent to "any(x is e or x == e for e in\ny)".\n\nFor the string and bytes types, "x in y" is true if and only if *x* is\na substring of *y*. An equivalent test is "y.find(x) != -1". Empty\nstrings are always considered to be a substring of any other string,\nso """ in "abc"" will return "True".\n\nFor user-defined classes which define the "__contains__()" method, "x\nin y" is true if and only if "y.__contains__(x)" is true.\n\nFor user-defined classes which do not define "__contains__()" but do\ndefine "__iter__()", "x in y" is true if some value "z" with "x == z"\nis produced while iterating over "y". If an exception is raised\nduring the iteration, it is as if "in" raised that exception.\n\nLastly, the old-style iteration protocol is tried: if a class defines\n"__getitem__()", "x in y" is true if and only if there is a non-\nnegative integer index *i* such that "x == y[i]", and all lower\ninteger indices do not raise "IndexError" exception. (If any other\nexception is raised, it is as if "in" raised that exception).\n\nThe operator "not in" is defined to have the inverse true value of\n"in".\n\nThe operators "is" and "is not" test for object identity: "x is y" is\ntrue if and only if *x* and *y* are the same object. "x is not y"\nyields the inverse truth value. [4]\n', - 'compound': u'\nCompound statements\n*******************\n\nCompound statements contain (groups of) other statements; they affect\nor control the execution of those other statements in some way. In\ngeneral, compound statements span multiple lines, although in simple\nincarnations a whole compound statement may be contained in one line.\n\nThe "if", "while" and "for" statements implement traditional control\nflow constructs. "try" specifies exception handlers and/or cleanup\ncode for a group of statements, while the "with" statement allows the\nexecution of initialization and finalization code around a block of\ncode. Function and class definitions are also syntactically compound\nstatements.\n\nA compound statement consists of one or more \'clauses.\' A clause\nconsists of a header and a \'suite.\' The clause headers of a\nparticular compound statement are all at the same indentation level.\nEach clause header begins with a uniquely identifying keyword and ends\nwith a colon. A suite is a group of statements controlled by a\nclause. A suite can be one or more semicolon-separated simple\nstatements on the same line as the header, following the header\'s\ncolon, or it can be one or more indented statements on subsequent\nlines. Only the latter form of a suite can contain nested compound\nstatements; the following is illegal, mostly because it wouldn\'t be\nclear to which "if" clause a following "else" clause would belong:\n\n if test1: if test2: print(x)\n\nAlso note that the semicolon binds tighter than the colon in this\ncontext, so that in the following example, either all or none of the\n"print()" calls are executed:\n\n if x < y < z: print(x); print(y); print(z)\n\nSummarizing:\n\n compound_stmt ::= if_stmt\n | while_stmt\n | for_stmt\n | try_stmt\n | with_stmt\n | funcdef\n | classdef\n | async_with_stmt\n | async_for_stmt\n | async_funcdef\n suite ::= stmt_list NEWLINE | NEWLINE INDENT statement+ DEDENT\n statement ::= stmt_list NEWLINE | compound_stmt\n stmt_list ::= simple_stmt (";" simple_stmt)* [";"]\n\nNote that statements always end in a "NEWLINE" possibly followed by a\n"DEDENT". Also note that optional continuation clauses always begin\nwith a keyword that cannot start a statement, thus there are no\nambiguities (the \'dangling "else"\' problem is solved in Python by\nrequiring nested "if" statements to be indented).\n\nThe formatting of the grammar rules in the following sections places\neach clause on a separate line for clarity.\n\n\nThe "if" statement\n==================\n\nThe "if" statement is used for conditional execution:\n\n if_stmt ::= "if" expression ":" suite\n ( "elif" expression ":" suite )*\n ["else" ":" suite]\n\nIt selects exactly one of the suites by evaluating the expressions one\nby one until one is found to be true (see section *Boolean operations*\nfor the definition of true and false); then that suite is executed\n(and no other part of the "if" statement is executed or evaluated).\nIf all expressions are false, the suite of the "else" clause, if\npresent, is executed.\n\n\nThe "while" statement\n=====================\n\nThe "while" statement is used for repeated execution as long as an\nexpression is true:\n\n while_stmt ::= "while" expression ":" suite\n ["else" ":" suite]\n\nThis repeatedly tests the expression and, if it is true, executes the\nfirst suite; if the expression is false (which may be the first time\nit is tested) the suite of the "else" clause, if present, is executed\nand the loop terminates.\n\nA "break" statement executed in the first suite terminates the loop\nwithout executing the "else" clause\'s suite. A "continue" statement\nexecuted in the first suite skips the rest of the suite and goes back\nto testing the expression.\n\n\nThe "for" statement\n===================\n\nThe "for" statement is used to iterate over the elements of a sequence\n(such as a string, tuple or list) or other iterable object:\n\n for_stmt ::= "for" target_list "in" expression_list ":" suite\n ["else" ":" suite]\n\nThe expression list is evaluated once; it should yield an iterable\nobject. An iterator is created for the result of the\n"expression_list". The suite is then executed once for each item\nprovided by the iterator, in the order returned by the iterator. Each\nitem in turn is assigned to the target list using the standard rules\nfor assignments (see *Assignment statements*), and then the suite is\nexecuted. When the items are exhausted (which is immediately when the\nsequence is empty or an iterator raises a "StopIteration" exception),\nthe suite in the "else" clause, if present, is executed, and the loop\nterminates.\n\nA "break" statement executed in the first suite terminates the loop\nwithout executing the "else" clause\'s suite. A "continue" statement\nexecuted in the first suite skips the rest of the suite and continues\nwith the next item, or with the "else" clause if there is no next\nitem.\n\nThe for-loop makes assignments to the variables(s) in the target list.\nThis overwrites all previous assignments to those variables including\nthose made in the suite of the for-loop:\n\n for i in range(10):\n print(i)\n i = 5 # this will not affect the for-loop\n # because i will be overwritten with the next\n # index in the range\n\nNames in the target list are not deleted when the loop is finished,\nbut if the sequence is empty, they will not have been assigned to at\nall by the loop. Hint: the built-in function "range()" returns an\niterator of integers suitable to emulate the effect of Pascal\'s "for i\n:= a to b do"; e.g., "list(range(3))" returns the list "[0, 1, 2]".\n\nNote: There is a subtlety when the sequence is being modified by the\n loop (this can only occur for mutable sequences, i.e. lists). An\n internal counter is used to keep track of which item is used next,\n and this is incremented on each iteration. When this counter has\n reached the length of the sequence the loop terminates. This means\n that if the suite deletes the current (or a previous) item from the\n sequence, the next item will be skipped (since it gets the index of\n the current item which has already been treated). Likewise, if the\n suite inserts an item in the sequence before the current item, the\n current item will be treated again the next time through the loop.\n This can lead to nasty bugs that can be avoided by making a\n temporary copy using a slice of the whole sequence, e.g.,\n\n for x in a[:]:\n if x < 0: a.remove(x)\n\n\nThe "try" statement\n===================\n\nThe "try" statement specifies exception handlers and/or cleanup code\nfor a group of statements:\n\n try_stmt ::= try1_stmt | try2_stmt\n try1_stmt ::= "try" ":" suite\n ("except" [expression ["as" identifier]] ":" suite)+\n ["else" ":" suite]\n ["finally" ":" suite]\n try2_stmt ::= "try" ":" suite\n "finally" ":" suite\n\nThe "except" clause(s) specify one or more exception handlers. When no\nexception occurs in the "try" clause, no exception handler is\nexecuted. When an exception occurs in the "try" suite, a search for an\nexception handler is started. This search inspects the except clauses\nin turn until one is found that matches the exception. An expression-\nless except clause, if present, must be last; it matches any\nexception. For an except clause with an expression, that expression\nis evaluated, and the clause matches the exception if the resulting\nobject is "compatible" with the exception. An object is compatible\nwith an exception if it is the class or a base class of the exception\nobject or a tuple containing an item compatible with the exception.\n\nIf no except clause matches the exception, the search for an exception\nhandler continues in the surrounding code and on the invocation stack.\n[1]\n\nIf the evaluation of an expression in the header of an except clause\nraises an exception, the original search for a handler is canceled and\na search starts for the new exception in the surrounding code and on\nthe call stack (it is treated as if the entire "try" statement raised\nthe exception).\n\nWhen a matching except clause is found, the exception is assigned to\nthe target specified after the "as" keyword in that except clause, if\npresent, and the except clause\'s suite is executed. All except\nclauses must have an executable block. When the end of this block is\nreached, execution continues normally after the entire try statement.\n(This means that if two nested handlers exist for the same exception,\nand the exception occurs in the try clause of the inner handler, the\nouter handler will not handle the exception.)\n\nWhen an exception has been assigned using "as target", it is cleared\nat the end of the except clause. This is as if\n\n except E as N:\n foo\n\nwas translated to\n\n except E as N:\n try:\n foo\n finally:\n del N\n\nThis means the exception must be assigned to a different name to be\nable to refer to it after the except clause. Exceptions are cleared\nbecause with the traceback attached to them, they form a reference\ncycle with the stack frame, keeping all locals in that frame alive\nuntil the next garbage collection occurs.\n\nBefore an except clause\'s suite is executed, details about the\nexception are stored in the "sys" module and can be accessed via\n"sys.exc_info()". "sys.exc_info()" returns a 3-tuple consisting of the\nexception class, the exception instance and a traceback object (see\nsection *The standard type hierarchy*) identifying the point in the\nprogram where the exception occurred. "sys.exc_info()" values are\nrestored to their previous values (before the call) when returning\nfrom a function that handled an exception.\n\nThe optional "else" clause is executed if and when control flows off\nthe end of the "try" clause. [2] Exceptions in the "else" clause are\nnot handled by the preceding "except" clauses.\n\nIf "finally" is present, it specifies a \'cleanup\' handler. The "try"\nclause is executed, including any "except" and "else" clauses. If an\nexception occurs in any of the clauses and is not handled, the\nexception is temporarily saved. The "finally" clause is executed. If\nthere is a saved exception it is re-raised at the end of the "finally"\nclause. If the "finally" clause raises another exception, the saved\nexception is set as the context of the new exception. If the "finally"\nclause executes a "return" or "break" statement, the saved exception\nis discarded:\n\n >>> def f():\n ... try:\n ... 1/0\n ... finally:\n ... return 42\n ...\n >>> f()\n 42\n\nThe exception information is not available to the program during\nexecution of the "finally" clause.\n\nWhen a "return", "break" or "continue" statement is executed in the\n"try" suite of a "try"..."finally" statement, the "finally" clause is\nalso executed \'on the way out.\' A "continue" statement is illegal in\nthe "finally" clause. (The reason is a problem with the current\nimplementation --- this restriction may be lifted in the future).\n\nThe return value of a function is determined by the last "return"\nstatement executed. Since the "finally" clause always executes, a\n"return" statement executed in the "finally" clause will always be the\nlast one executed:\n\n >>> def foo():\n ... try:\n ... return \'try\'\n ... finally:\n ... return \'finally\'\n ...\n >>> foo()\n \'finally\'\n\nAdditional information on exceptions can be found in section\n*Exceptions*, and information on using the "raise" statement to\ngenerate exceptions may be found in section *The raise statement*.\n\n\nThe "with" statement\n====================\n\nThe "with" statement is used to wrap the execution of a block with\nmethods defined by a context manager (see section *With Statement\nContext Managers*). This allows common "try"..."except"..."finally"\nusage patterns to be encapsulated for convenient reuse.\n\n with_stmt ::= "with" with_item ("," with_item)* ":" suite\n with_item ::= expression ["as" target]\n\nThe execution of the "with" statement with one "item" proceeds as\nfollows:\n\n1. The context expression (the expression given in the "with_item")\n is evaluated to obtain a context manager.\n\n2. The context manager\'s "__exit__()" is loaded for later use.\n\n3. The context manager\'s "__enter__()" method is invoked.\n\n4. If a target was included in the "with" statement, the return\n value from "__enter__()" is assigned to it.\n\n Note: The "with" statement guarantees that if the "__enter__()"\n method returns without an error, then "__exit__()" will always be\n called. Thus, if an error occurs during the assignment to the\n target list, it will be treated the same as an error occurring\n within the suite would be. See step 6 below.\n\n5. The suite is executed.\n\n6. The context manager\'s "__exit__()" method is invoked. If an\n exception caused the suite to be exited, its type, value, and\n traceback are passed as arguments to "__exit__()". Otherwise, three\n "None" arguments are supplied.\n\n If the suite was exited due to an exception, and the return value\n from the "__exit__()" method was false, the exception is reraised.\n If the return value was true, the exception is suppressed, and\n execution continues with the statement following the "with"\n statement.\n\n If the suite was exited for any reason other than an exception, the\n return value from "__exit__()" is ignored, and execution proceeds\n at the normal location for the kind of exit that was taken.\n\nWith more than one item, the context managers are processed as if\nmultiple "with" statements were nested:\n\n with A() as a, B() as b:\n suite\n\nis equivalent to\n\n with A() as a:\n with B() as b:\n suite\n\nChanged in version 3.1: Support for multiple context expressions.\n\nSee also: **PEP 0343** - The "with" statement\n\n The specification, background, and examples for the Python "with"\n statement.\n\n\nFunction definitions\n====================\n\nA function definition defines a user-defined function object (see\nsection *The standard type hierarchy*):\n\n funcdef ::= [decorators] "def" funcname "(" [parameter_list] ")" ["->" expression] ":" suite\n decorators ::= decorator+\n decorator ::= "@" dotted_name ["(" [parameter_list [","]] ")"] NEWLINE\n dotted_name ::= identifier ("." identifier)*\n parameter_list ::= (defparameter ",")*\n | "*" [parameter] ("," defparameter)* ["," "**" parameter]\n | "**" parameter\n | defparameter [","] )\n parameter ::= identifier [":" expression]\n defparameter ::= parameter ["=" expression]\n funcname ::= identifier\n\nA function definition is an executable statement. Its execution binds\nthe function name in the current local namespace to a function object\n(a wrapper around the executable code for the function). This\nfunction object contains a reference to the current global namespace\nas the global namespace to be used when the function is called.\n\nThe function definition does not execute the function body; this gets\nexecuted only when the function is called. [3]\n\nA function definition may be wrapped by one or more *decorator*\nexpressions. Decorator expressions are evaluated when the function is\ndefined, in the scope that contains the function definition. The\nresult must be a callable, which is invoked with the function object\nas the only argument. The returned value is bound to the function name\ninstead of the function object. Multiple decorators are applied in\nnested fashion. For example, the following code\n\n @f1(arg)\n @f2\n def func(): pass\n\nis equivalent to\n\n def func(): pass\n func = f1(arg)(f2(func))\n\nWhen one or more *parameters* have the form *parameter* "="\n*expression*, the function is said to have "default parameter values."\nFor a parameter with a default value, the corresponding *argument* may\nbe omitted from a call, in which case the parameter\'s default value is\nsubstituted. If a parameter has a default value, all following\nparameters up until the ""*"" must also have a default value --- this\nis a syntactic restriction that is not expressed by the grammar.\n\n**Default parameter values are evaluated from left to right when the\nfunction definition is executed.** This means that the expression is\nevaluated once, when the function is defined, and that the same "pre-\ncomputed" value is used for each call. This is especially important\nto understand when a default parameter is a mutable object, such as a\nlist or a dictionary: if the function modifies the object (e.g. by\nappending an item to a list), the default value is in effect modified.\nThis is generally not what was intended. A way around this is to use\n"None" as the default, and explicitly test for it in the body of the\nfunction, e.g.:\n\n def whats_on_the_telly(penguin=None):\n if penguin is None:\n penguin = []\n penguin.append("property of the zoo")\n return penguin\n\nFunction call semantics are described in more detail in section\n*Calls*. A function call always assigns values to all parameters\nmentioned in the parameter list, either from position arguments, from\nkeyword arguments, or from default values. If the form\n""*identifier"" is present, it is initialized to a tuple receiving any\nexcess positional parameters, defaulting to the empty tuple. If the\nform ""**identifier"" is present, it is initialized to a new\ndictionary receiving any excess keyword arguments, defaulting to a new\nempty dictionary. Parameters after ""*"" or ""*identifier"" are\nkeyword-only parameters and may only be passed used keyword arguments.\n\nParameters may have annotations of the form "": expression"" following\nthe parameter name. Any parameter may have an annotation even those\nof the form "*identifier" or "**identifier". Functions may have\n"return" annotation of the form ""-> expression"" after the parameter\nlist. These annotations can be any valid Python expression and are\nevaluated when the function definition is executed. Annotations may\nbe evaluated in a different order than they appear in the source code.\nThe presence of annotations does not change the semantics of a\nfunction. The annotation values are available as values of a\ndictionary keyed by the parameters\' names in the "__annotations__"\nattribute of the function object.\n\nIt is also possible to create anonymous functions (functions not bound\nto a name), for immediate use in expressions. This uses lambda\nexpressions, described in section *Lambdas*. Note that the lambda\nexpression is merely a shorthand for a simplified function definition;\na function defined in a ""def"" statement can be passed around or\nassigned to another name just like a function defined by a lambda\nexpression. The ""def"" form is actually more powerful since it\nallows the execution of multiple statements and annotations.\n\n**Programmer\'s note:** Functions are first-class objects. A ""def""\nstatement executed inside a function definition defines a local\nfunction that can be returned or passed around. Free variables used\nin the nested function can access the local variables of the function\ncontaining the def. See section *Naming and binding* for details.\n\nSee also: **PEP 3107** - Function Annotations\n\n The original specification for function annotations.\n\n\nClass definitions\n=================\n\nA class definition defines a class object (see section *The standard\ntype hierarchy*):\n\n classdef ::= [decorators] "class" classname [inheritance] ":" suite\n inheritance ::= "(" [parameter_list] ")"\n classname ::= identifier\n\nA class definition is an executable statement. The inheritance list\nusually gives a list of base classes (see *Customizing class creation*\nfor more advanced uses), so each item in the list should evaluate to a\nclass object which allows subclassing. Classes without an inheritance\nlist inherit, by default, from the base class "object"; hence,\n\n class Foo:\n pass\n\nis equivalent to\n\n class Foo(object):\n pass\n\nThe class\'s suite is then executed in a new execution frame (see\n*Naming and binding*), using a newly created local namespace and the\noriginal global namespace. (Usually, the suite contains mostly\nfunction definitions.) When the class\'s suite finishes execution, its\nexecution frame is discarded but its local namespace is saved. [4] A\nclass object is then created using the inheritance list for the base\nclasses and the saved local namespace for the attribute dictionary.\nThe class name is bound to this class object in the original local\nnamespace.\n\nClass creation can be customized heavily using *metaclasses*.\n\nClasses can also be decorated: just like when decorating functions,\n\n @f1(arg)\n @f2\n class Foo: pass\n\nis equivalent to\n\n class Foo: pass\n Foo = f1(arg)(f2(Foo))\n\nThe evaluation rules for the decorator expressions are the same as for\nfunction decorators. The result must be a class object, which is then\nbound to the class name.\n\n**Programmer\'s note:** Variables defined in the class definition are\nclass attributes; they are shared by instances. Instance attributes\ncan be set in a method with "self.name = value". Both class and\ninstance attributes are accessible through the notation ""self.name"",\nand an instance attribute hides a class attribute with the same name\nwhen accessed in this way. Class attributes can be used as defaults\nfor instance attributes, but using mutable values there can lead to\nunexpected results. *Descriptors* can be used to create instance\nvariables with different implementation details.\n\nSee also: **PEP 3115** - Metaclasses in Python 3 **PEP 3129** -\n Class Decorators\n\n\nCoroutines\n==========\n\nNew in version 3.5.\n\n\nCoroutine function definition\n-----------------------------\n\n async_funcdef ::= "async" funcdef\n\nExecution of Python coroutines can be suspended and resumed at many\npoints (see *coroutine*). In the body of a coroutine, any "await" and\n"async" identifiers become reserved keywords; "await" expressions,\n"async for" and "async with" can only be used in coroutine bodies.\n\nFunctions defined with "async def" syntax are always coroutine\nfunctions, even if they do not contain "await" or "async" keywords.\n\nIt is a "SyntaxError" to use "yield" expressions in "async def"\ncoroutines.\n\nAn example of a coroutine function:\n\n async def func(param1, param2):\n do_stuff()\n await some_coroutine()\n\n\nThe "async for" statement\n-------------------------\n\n async_for_stmt ::= "async" for_stmt\n\nAn *asynchronous iterable* is able to call asynchronous code in its\n*iter* implementation, and *asynchronous iterator* can call\nasynchronous code in its *next* method.\n\nThe "async for" statement allows convenient iteration over\nasynchronous iterators.\n\nThe following code:\n\n async for TARGET in ITER:\n BLOCK\n else:\n BLOCK2\n\nIs semantically equivalent to:\n\n iter = (ITER)\n iter = await type(iter).__aiter__(iter)\n running = True\n while running:\n try:\n TARGET = await type(iter).__anext__(iter)\n except StopAsyncIteration:\n running = False\n else:\n BLOCK\n else:\n BLOCK2\n\nSee also "__aiter__()" and "__anext__()" for details.\n\nIt is a "SyntaxError" to use "async for" statement outside of an\n"async def" function.\n\n\nThe "async with" statement\n--------------------------\n\n async_with_stmt ::= "async" with_stmt\n\nAn *asynchronous context manager* is a *context manager* that is able\nto suspend execution in its *enter* and *exit* methods.\n\nThe following code:\n\n async with EXPR as VAR:\n BLOCK\n\nIs semantically equivalent to:\n\n mgr = (EXPR)\n aexit = type(mgr).__aexit__\n aenter = type(mgr).__aenter__(mgr)\n exc = True\n\n VAR = await aenter\n try:\n BLOCK\n except:\n if not await aexit(mgr, *sys.exc_info()):\n raise\n else:\n await aexit(mgr, None, None, None)\n\nSee also "__aenter__()" and "__aexit__()" for details.\n\nIt is a "SyntaxError" to use "async with" statement outside of an\n"async def" function.\n\nSee also: **PEP 492** - Coroutines with async and await syntax\n\n-[ Footnotes ]-\n\n[1] The exception is propagated to the invocation stack unless\n there is a "finally" clause which happens to raise another\n exception. That new exception causes the old one to be lost.\n\n[2] Currently, control "flows off the end" except in the case of\n an exception or the execution of a "return", "continue", or\n "break" statement.\n\n[3] A string literal appearing as the first statement in the\n function body is transformed into the function\'s "__doc__"\n attribute and therefore the function\'s *docstring*.\n\n[4] A string literal appearing as the first statement in the class\n body is transformed into the namespace\'s "__doc__" item and\n therefore the class\'s *docstring*.\n', + 'comparisons': u'\nComparisons\n***********\n\nUnlike C, all comparison operations in Python have the same priority,\nwhich is lower than that of any arithmetic, shifting or bitwise\noperation. Also unlike C, expressions like "a < b < c" have the\ninterpretation that is conventional in mathematics:\n\n comparison ::= or_expr ( comp_operator or_expr )*\n comp_operator ::= "<" | ">" | "==" | ">=" | "<=" | "!="\n | "is" ["not"] | ["not"] "in"\n\nComparisons yield boolean values: "True" or "False".\n\nComparisons can be chained arbitrarily, e.g., "x < y <= z" is\nequivalent to "x < y and y <= z", except that "y" is evaluated only\nonce (but in both cases "z" is not evaluated at all when "x < y" is\nfound to be false).\n\nFormally, if *a*, *b*, *c*, ..., *y*, *z* are expressions and *op1*,\n*op2*, ..., *opN* are comparison operators, then "a op1 b op2 c ... y\nopN z" is equivalent to "a op1 b and b op2 c and ... y opN z", except\nthat each expression is evaluated at most once.\n\nNote that "a op1 b op2 c" doesn\'t imply any kind of comparison between\n*a* and *c*, so that, e.g., "x < y > z" is perfectly legal (though\nperhaps not pretty).\n\nThe operators "<", ">", "==", ">=", "<=", and "!=" compare the values\nof two objects. The objects need not have the same type. If both are\nnumbers, they are converted to a common type. Otherwise, the "==" and\n"!=" operators *always* consider objects of different types to be\nunequal, while the "<", ">", ">=" and "<=" operators raise a\n"TypeError" when comparing objects of different types that do not\nimplement these operators for the given pair of types. You can\ncontrol comparison behavior of objects of non-built-in types by\ndefining rich comparison methods like "__gt__()", described in section\n*Basic customization*.\n\nComparison of objects of the same type depends on the type:\n\n* Numbers are compared arithmetically.\n\n* The values "float(\'NaN\')" and "Decimal(\'NaN\')" are special. They\n are identical to themselves, "x is x" but are not equal to\n themselves, "x != x". Additionally, comparing any value to a\n not-a-number value will return "False". For example, both "3 <\n float(\'NaN\')" and "float(\'NaN\') < 3" will return "False".\n\n* Bytes objects are compared lexicographically using the numeric\n values of their elements.\n\n* Strings are compared lexicographically using the numeric\n equivalents (the result of the built-in function "ord()") of their\n characters. [3] String and bytes object can\'t be compared!\n\n* Tuples and lists are compared lexicographically using comparison\n of corresponding elements. This means that to compare equal, each\n element must compare equal and the two sequences must be of the same\n type and have the same length.\n\n If not equal, the sequences are ordered the same as their first\n differing elements. For example, "[1,2,x] <= [1,2,y]" has the same\n value as "x <= y". If the corresponding element does not exist, the\n shorter sequence is ordered first (for example, "[1,2] < [1,2,3]").\n\n* Mappings (dictionaries) compare equal if and only if they have the\n same "(key, value)" pairs. Order comparisons "(\'<\', \'<=\', \'>=\',\n \'>\')" raise "TypeError".\n\n* Sets and frozensets define comparison operators to mean subset and\n superset tests. Those relations do not define total orderings (the\n two sets "{1,2}" and {2,3} are not equal, nor subsets of one\n another, nor supersets of one another). Accordingly, sets are not\n appropriate arguments for functions which depend on total ordering.\n For example, "min()", "max()", and "sorted()" produce undefined\n results given a list of sets as inputs.\n\n* Most other objects of built-in types compare unequal unless they\n are the same object; the choice whether one object is considered\n smaller or larger than another one is made arbitrarily but\n consistently within one execution of a program.\n\nComparison of objects of differing types depends on whether either of\nthe types provide explicit support for the comparison. Most numeric\ntypes can be compared with one another. When cross-type comparison is\nnot supported, the comparison method returns "NotImplemented".\n\nThe operators "in" and "not in" test for membership. "x in s"\nevaluates to true if *x* is a member of *s*, and false otherwise. "x\nnot in s" returns the negation of "x in s". All built-in sequences\nand set types support this as well as dictionary, for which "in" tests\nwhether the dictionary has a given key. For container types such as\nlist, tuple, set, frozenset, dict, or collections.deque, the\nexpression "x in y" is equivalent to "any(x is e or x == e for e in\ny)".\n\nFor the string and bytes types, "x in y" is true if and only if *x* is\na substring of *y*. An equivalent test is "y.find(x) != -1". Empty\nstrings are always considered to be a substring of any other string,\nso """ in "abc"" will return "True".\n\nFor user-defined classes which define the "__contains__()" method, "x\nin y" is true if and only if "y.__contains__(x)" is true.\n\nFor user-defined classes which do not define "__contains__()" but do\ndefine "__iter__()", "x in y" is true if some value "z" with "x == z"\nis produced while iterating over "y". If an exception is raised\nduring the iteration, it is as if "in" raised that exception.\n\nLastly, the old-style iteration protocol is tried: if a class defines\n"__getitem__()", "x in y" is true if and only if there is a non-\nnegative integer index *i* such that "x == y[i]", and all lower\ninteger indices do not raise "IndexError" exception. (If any other\nexception is raised, it is as if "in" raised that exception).\n\nThe operator "not in" is defined to have the inverse true value of\n"in".\n\nThe operators "is" and "is not" test for object identity: "x is y" is\ntrue if and only if *x* and *y* are the same object. "x is not y"\nyields the inverse truth value. [4]\n', + 'compound': u'\nCompound statements\n*******************\n\nCompound statements contain (groups of) other statements; they affect\nor control the execution of those other statements in some way. In\ngeneral, compound statements span multiple lines, although in simple\nincarnations a whole compound statement may be contained in one line.\n\nThe "if", "while" and "for" statements implement traditional control\nflow constructs. "try" specifies exception handlers and/or cleanup\ncode for a group of statements, while the "with" statement allows the\nexecution of initialization and finalization code around a block of\ncode. Function and class definitions are also syntactically compound\nstatements.\n\nA compound statement consists of one or more \'clauses.\' A clause\nconsists of a header and a \'suite.\' The clause headers of a\nparticular compound statement are all at the same indentation level.\nEach clause header begins with a uniquely identifying keyword and ends\nwith a colon. A suite is a group of statements controlled by a\nclause. A suite can be one or more semicolon-separated simple\nstatements on the same line as the header, following the header\'s\ncolon, or it can be one or more indented statements on subsequent\nlines. Only the latter form of a suite can contain nested compound\nstatements; the following is illegal, mostly because it wouldn\'t be\nclear to which "if" clause a following "else" clause would belong:\n\n if test1: if test2: print(x)\n\nAlso note that the semicolon binds tighter than the colon in this\ncontext, so that in the following example, either all or none of the\n"print()" calls are executed:\n\n if x < y < z: print(x); print(y); print(z)\n\nSummarizing:\n\n compound_stmt ::= if_stmt\n | while_stmt\n | for_stmt\n | try_stmt\n | with_stmt\n | funcdef\n | classdef\n | async_with_stmt\n | async_for_stmt\n | async_funcdef\n suite ::= stmt_list NEWLINE | NEWLINE INDENT statement+ DEDENT\n statement ::= stmt_list NEWLINE | compound_stmt\n stmt_list ::= simple_stmt (";" simple_stmt)* [";"]\n\nNote that statements always end in a "NEWLINE" possibly followed by a\n"DEDENT". Also note that optional continuation clauses always begin\nwith a keyword that cannot start a statement, thus there are no\nambiguities (the \'dangling "else"\' problem is solved in Python by\nrequiring nested "if" statements to be indented).\n\nThe formatting of the grammar rules in the following sections places\neach clause on a separate line for clarity.\n\n\nThe "if" statement\n==================\n\nThe "if" statement is used for conditional execution:\n\n if_stmt ::= "if" expression ":" suite\n ( "elif" expression ":" suite )*\n ["else" ":" suite]\n\nIt selects exactly one of the suites by evaluating the expressions one\nby one until one is found to be true (see section *Boolean operations*\nfor the definition of true and false); then that suite is executed\n(and no other part of the "if" statement is executed or evaluated).\nIf all expressions are false, the suite of the "else" clause, if\npresent, is executed.\n\n\nThe "while" statement\n=====================\n\nThe "while" statement is used for repeated execution as long as an\nexpression is true:\n\n while_stmt ::= "while" expression ":" suite\n ["else" ":" suite]\n\nThis repeatedly tests the expression and, if it is true, executes the\nfirst suite; if the expression is false (which may be the first time\nit is tested) the suite of the "else" clause, if present, is executed\nand the loop terminates.\n\nA "break" statement executed in the first suite terminates the loop\nwithout executing the "else" clause\'s suite. A "continue" statement\nexecuted in the first suite skips the rest of the suite and goes back\nto testing the expression.\n\n\nThe "for" statement\n===================\n\nThe "for" statement is used to iterate over the elements of a sequence\n(such as a string, tuple or list) or other iterable object:\n\n for_stmt ::= "for" target_list "in" expression_list ":" suite\n ["else" ":" suite]\n\nThe expression list is evaluated once; it should yield an iterable\nobject. An iterator is created for the result of the\n"expression_list". The suite is then executed once for each item\nprovided by the iterator, in the order returned by the iterator. Each\nitem in turn is assigned to the target list using the standard rules\nfor assignments (see *Assignment statements*), and then the suite is\nexecuted. When the items are exhausted (which is immediately when the\nsequence is empty or an iterator raises a "StopIteration" exception),\nthe suite in the "else" clause, if present, is executed, and the loop\nterminates.\n\nA "break" statement executed in the first suite terminates the loop\nwithout executing the "else" clause\'s suite. A "continue" statement\nexecuted in the first suite skips the rest of the suite and continues\nwith the next item, or with the "else" clause if there is no next\nitem.\n\nThe for-loop makes assignments to the variables(s) in the target list.\nThis overwrites all previous assignments to those variables including\nthose made in the suite of the for-loop:\n\n for i in range(10):\n print(i)\n i = 5 # this will not affect the for-loop\n # because i will be overwritten with the next\n # index in the range\n\nNames in the target list are not deleted when the loop is finished,\nbut if the sequence is empty, they will not have been assigned to at\nall by the loop. Hint: the built-in function "range()" returns an\niterator of integers suitable to emulate the effect of Pascal\'s "for i\n:= a to b do"; e.g., "list(range(3))" returns the list "[0, 1, 2]".\n\nNote: There is a subtlety when the sequence is being modified by the\n loop (this can only occur for mutable sequences, i.e. lists). An\n internal counter is used to keep track of which item is used next,\n and this is incremented on each iteration. When this counter has\n reached the length of the sequence the loop terminates. This means\n that if the suite deletes the current (or a previous) item from the\n sequence, the next item will be skipped (since it gets the index of\n the current item which has already been treated). Likewise, if the\n suite inserts an item in the sequence before the current item, the\n current item will be treated again the next time through the loop.\n This can lead to nasty bugs that can be avoided by making a\n temporary copy using a slice of the whole sequence, e.g.,\n\n for x in a[:]:\n if x < 0: a.remove(x)\n\n\nThe "try" statement\n===================\n\nThe "try" statement specifies exception handlers and/or cleanup code\nfor a group of statements:\n\n try_stmt ::= try1_stmt | try2_stmt\n try1_stmt ::= "try" ":" suite\n ("except" [expression ["as" identifier]] ":" suite)+\n ["else" ":" suite]\n ["finally" ":" suite]\n try2_stmt ::= "try" ":" suite\n "finally" ":" suite\n\nThe "except" clause(s) specify one or more exception handlers. When no\nexception occurs in the "try" clause, no exception handler is\nexecuted. When an exception occurs in the "try" suite, a search for an\nexception handler is started. This search inspects the except clauses\nin turn until one is found that matches the exception. An expression-\nless except clause, if present, must be last; it matches any\nexception. For an except clause with an expression, that expression\nis evaluated, and the clause matches the exception if the resulting\nobject is "compatible" with the exception. An object is compatible\nwith an exception if it is the class or a base class of the exception\nobject or a tuple containing an item compatible with the exception.\n\nIf no except clause matches the exception, the search for an exception\nhandler continues in the surrounding code and on the invocation stack.\n[1]\n\nIf the evaluation of an expression in the header of an except clause\nraises an exception, the original search for a handler is canceled and\na search starts for the new exception in the surrounding code and on\nthe call stack (it is treated as if the entire "try" statement raised\nthe exception).\n\nWhen a matching except clause is found, the exception is assigned to\nthe target specified after the "as" keyword in that except clause, if\npresent, and the except clause\'s suite is executed. All except\nclauses must have an executable block. When the end of this block is\nreached, execution continues normally after the entire try statement.\n(This means that if two nested handlers exist for the same exception,\nand the exception occurs in the try clause of the inner handler, the\nouter handler will not handle the exception.)\n\nWhen an exception has been assigned using "as target", it is cleared\nat the end of the except clause. This is as if\n\n except E as N:\n foo\n\nwas translated to\n\n except E as N:\n try:\n foo\n finally:\n del N\n\nThis means the exception must be assigned to a different name to be\nable to refer to it after the except clause. Exceptions are cleared\nbecause with the traceback attached to them, they form a reference\ncycle with the stack frame, keeping all locals in that frame alive\nuntil the next garbage collection occurs.\n\nBefore an except clause\'s suite is executed, details about the\nexception are stored in the "sys" module and can be accessed via\n"sys.exc_info()". "sys.exc_info()" returns a 3-tuple consisting of the\nexception class, the exception instance and a traceback object (see\nsection *The standard type hierarchy*) identifying the point in the\nprogram where the exception occurred. "sys.exc_info()" values are\nrestored to their previous values (before the call) when returning\nfrom a function that handled an exception.\n\nThe optional "else" clause is executed if and when control flows off\nthe end of the "try" clause. [2] Exceptions in the "else" clause are\nnot handled by the preceding "except" clauses.\n\nIf "finally" is present, it specifies a \'cleanup\' handler. The "try"\nclause is executed, including any "except" and "else" clauses. If an\nexception occurs in any of the clauses and is not handled, the\nexception is temporarily saved. The "finally" clause is executed. If\nthere is a saved exception it is re-raised at the end of the "finally"\nclause. If the "finally" clause raises another exception, the saved\nexception is set as the context of the new exception. If the "finally"\nclause executes a "return" or "break" statement, the saved exception\nis discarded:\n\n >>> def f():\n ... try:\n ... 1/0\n ... finally:\n ... return 42\n ...\n >>> f()\n 42\n\nThe exception information is not available to the program during\nexecution of the "finally" clause.\n\nWhen a "return", "break" or "continue" statement is executed in the\n"try" suite of a "try"..."finally" statement, the "finally" clause is\nalso executed \'on the way out.\' A "continue" statement is illegal in\nthe "finally" clause. (The reason is a problem with the current\nimplementation --- this restriction may be lifted in the future).\n\nThe return value of a function is determined by the last "return"\nstatement executed. Since the "finally" clause always executes, a\n"return" statement executed in the "finally" clause will always be the\nlast one executed:\n\n >>> def foo():\n ... try:\n ... return \'try\'\n ... finally:\n ... return \'finally\'\n ...\n >>> foo()\n \'finally\'\n\nAdditional information on exceptions can be found in section\n*Exceptions*, and information on using the "raise" statement to\ngenerate exceptions may be found in section *The raise statement*.\n\n\nThe "with" statement\n====================\n\nThe "with" statement is used to wrap the execution of a block with\nmethods defined by a context manager (see section *With Statement\nContext Managers*). This allows common "try"..."except"..."finally"\nusage patterns to be encapsulated for convenient reuse.\n\n with_stmt ::= "with" with_item ("," with_item)* ":" suite\n with_item ::= expression ["as" target]\n\nThe execution of the "with" statement with one "item" proceeds as\nfollows:\n\n1. The context expression (the expression given in the "with_item")\n is evaluated to obtain a context manager.\n\n2. The context manager\'s "__exit__()" is loaded for later use.\n\n3. The context manager\'s "__enter__()" method is invoked.\n\n4. If a target was included in the "with" statement, the return\n value from "__enter__()" is assigned to it.\n\n Note: The "with" statement guarantees that if the "__enter__()"\n method returns without an error, then "__exit__()" will always be\n called. Thus, if an error occurs during the assignment to the\n target list, it will be treated the same as an error occurring\n within the suite would be. See step 6 below.\n\n5. The suite is executed.\n\n6. The context manager\'s "__exit__()" method is invoked. If an\n exception caused the suite to be exited, its type, value, and\n traceback are passed as arguments to "__exit__()". Otherwise, three\n "None" arguments are supplied.\n\n If the suite was exited due to an exception, and the return value\n from the "__exit__()" method was false, the exception is reraised.\n If the return value was true, the exception is suppressed, and\n execution continues with the statement following the "with"\n statement.\n\n If the suite was exited for any reason other than an exception, the\n return value from "__exit__()" is ignored, and execution proceeds\n at the normal location for the kind of exit that was taken.\n\nWith more than one item, the context managers are processed as if\nmultiple "with" statements were nested:\n\n with A() as a, B() as b:\n suite\n\nis equivalent to\n\n with A() as a:\n with B() as b:\n suite\n\nChanged in version 3.1: Support for multiple context expressions.\n\nSee also: **PEP 0343** - The "with" statement\n\n The specification, background, and examples for the Python "with"\n statement.\n\n\nFunction definitions\n====================\n\nA function definition defines a user-defined function object (see\nsection *The standard type hierarchy*):\n\n funcdef ::= [decorators] "def" funcname "(" [parameter_list] ")" ["->" expression] ":" suite\n decorators ::= decorator+\n decorator ::= "@" dotted_name ["(" [parameter_list [","]] ")"] NEWLINE\n dotted_name ::= identifier ("." identifier)*\n parameter_list ::= (defparameter ",")*\n | "*" [parameter] ("," defparameter)* ["," "**" parameter]\n | "**" parameter\n | defparameter [","] )\n parameter ::= identifier [":" expression]\n defparameter ::= parameter ["=" expression]\n funcname ::= identifier\n\nA function definition is an executable statement. Its execution binds\nthe function name in the current local namespace to a function object\n(a wrapper around the executable code for the function). This\nfunction object contains a reference to the current global namespace\nas the global namespace to be used when the function is called.\n\nThe function definition does not execute the function body; this gets\nexecuted only when the function is called. [3]\n\nA function definition may be wrapped by one or more *decorator*\nexpressions. Decorator expressions are evaluated when the function is\ndefined, in the scope that contains the function definition. The\nresult must be a callable, which is invoked with the function object\nas the only argument. The returned value is bound to the function name\ninstead of the function object. Multiple decorators are applied in\nnested fashion. For example, the following code\n\n @f1(arg)\n @f2\n def func(): pass\n\nis equivalent to\n\n def func(): pass\n func = f1(arg)(f2(func))\n\nWhen one or more *parameters* have the form *parameter* "="\n*expression*, the function is said to have "default parameter values."\nFor a parameter with a default value, the corresponding *argument* may\nbe omitted from a call, in which case the parameter\'s default value is\nsubstituted. If a parameter has a default value, all following\nparameters up until the ""*"" must also have a default value --- this\nis a syntactic restriction that is not expressed by the grammar.\n\n**Default parameter values are evaluated from left to right when the\nfunction definition is executed.** This means that the expression is\nevaluated once, when the function is defined, and that the same "pre-\ncomputed" value is used for each call. This is especially important\nto understand when a default parameter is a mutable object, such as a\nlist or a dictionary: if the function modifies the object (e.g. by\nappending an item to a list), the default value is in effect modified.\nThis is generally not what was intended. A way around this is to use\n"None" as the default, and explicitly test for it in the body of the\nfunction, e.g.:\n\n def whats_on_the_telly(penguin=None):\n if penguin is None:\n penguin = []\n penguin.append("property of the zoo")\n return penguin\n\nFunction call semantics are described in more detail in section\n*Calls*. A function call always assigns values to all parameters\nmentioned in the parameter list, either from position arguments, from\nkeyword arguments, or from default values. If the form\n""*identifier"" is present, it is initialized to a tuple receiving any\nexcess positional parameters, defaulting to the empty tuple. If the\nform ""**identifier"" is present, it is initialized to a new\ndictionary receiving any excess keyword arguments, defaulting to a new\nempty dictionary. Parameters after ""*"" or ""*identifier"" are\nkeyword-only parameters and may only be passed used keyword arguments.\n\nParameters may have annotations of the form "": expression"" following\nthe parameter name. Any parameter may have an annotation even those\nof the form "*identifier" or "**identifier". Functions may have\n"return" annotation of the form ""-> expression"" after the parameter\nlist. These annotations can be any valid Python expression and are\nevaluated when the function definition is executed. Annotations may\nbe evaluated in a different order than they appear in the source code.\nThe presence of annotations does not change the semantics of a\nfunction. The annotation values are available as values of a\ndictionary keyed by the parameters\' names in the "__annotations__"\nattribute of the function object.\n\nIt is also possible to create anonymous functions (functions not bound\nto a name), for immediate use in expressions. This uses lambda\nexpressions, described in section *Lambdas*. Note that the lambda\nexpression is merely a shorthand for a simplified function definition;\na function defined in a ""def"" statement can be passed around or\nassigned to another name just like a function defined by a lambda\nexpression. The ""def"" form is actually more powerful since it\nallows the execution of multiple statements and annotations.\n\n**Programmer\'s note:** Functions are first-class objects. A ""def""\nstatement executed inside a function definition defines a local\nfunction that can be returned or passed around. Free variables used\nin the nested function can access the local variables of the function\ncontaining the def. See section *Naming and binding* for details.\n\nSee also: **PEP 3107** - Function Annotations\n\n The original specification for function annotations.\n\n\nClass definitions\n=================\n\nA class definition defines a class object (see section *The standard\ntype hierarchy*):\n\n classdef ::= [decorators] "class" classname [inheritance] ":" suite\n inheritance ::= "(" [parameter_list] ")"\n classname ::= identifier\n\nA class definition is an executable statement. The inheritance list\nusually gives a list of base classes (see *Customizing class creation*\nfor more advanced uses), so each item in the list should evaluate to a\nclass object which allows subclassing. Classes without an inheritance\nlist inherit, by default, from the base class "object"; hence,\n\n class Foo:\n pass\n\nis equivalent to\n\n class Foo(object):\n pass\n\nThe class\'s suite is then executed in a new execution frame (see\n*Naming and binding*), using a newly created local namespace and the\noriginal global namespace. (Usually, the suite contains mostly\nfunction definitions.) When the class\'s suite finishes execution, its\nexecution frame is discarded but its local namespace is saved. [4] A\nclass object is then created using the inheritance list for the base\nclasses and the saved local namespace for the attribute dictionary.\nThe class name is bound to this class object in the original local\nnamespace.\n\nClass creation can be customized heavily using *metaclasses*.\n\nClasses can also be decorated: just like when decorating functions,\n\n @f1(arg)\n @f2\n class Foo: pass\n\nis equivalent to\n\n class Foo: pass\n Foo = f1(arg)(f2(Foo))\n\nThe evaluation rules for the decorator expressions are the same as for\nfunction decorators. The result must be a class object, which is then\nbound to the class name.\n\n**Programmer\'s note:** Variables defined in the class definition are\nclass attributes; they are shared by instances. Instance attributes\ncan be set in a method with "self.name = value". Both class and\ninstance attributes are accessible through the notation ""self.name"",\nand an instance attribute hides a class attribute with the same name\nwhen accessed in this way. Class attributes can be used as defaults\nfor instance attributes, but using mutable values there can lead to\nunexpected results. *Descriptors* can be used to create instance\nvariables with different implementation details.\n\nSee also: **PEP 3115** - Metaclasses in Python 3 **PEP 3129** -\n Class Decorators\n\n\nCoroutines\n==========\n\n\nCoroutine function definition\n-----------------------------\n\n async_funcdef ::= "async" funcdef\n\nExecution of Python coroutines can be suspended and resumed at many\npoints (see *coroutine*.) "await" expressions, "async for" and "async\nwith" can only be used in their bodies.\n\nFunctions defined with "async def" syntax are always coroutine\nfunctions, even if they do not contain "await" or "async" keywords.\n\nIt is a "SyntaxError" to use "yield" expressions in coroutines.\n\nNew in version 3.5.\n\n\nThe "async for" statement\n-------------------------\n\n async_for_stmt ::= "async" for_stmt\n\nAn *asynchronous iterable* is able to call asynchronous code in its\n*iter* implementation, and *asynchronous iterator* can call\nasynchronous code in its *next* method.\n\nThe "async for" statement allows convenient iteration over\nasynchronous iterators.\n\nThe following code:\n\n async for TARGET in ITER:\n BLOCK\n else:\n BLOCK2\n\nIs semantically equivalent to:\n\n iter = (ITER)\n iter = await type(iter).__aiter__(iter)\n running = True\n while running:\n try:\n TARGET = await type(iter).__anext__(iter)\n except StopAsyncIteration:\n running = False\n else:\n BLOCK\n else:\n BLOCK2\n\nSee also "__aiter__()" and "__anext__()" for details.\n\nNew in version 3.5.\n\n\nThe "async with" statement\n--------------------------\n\n async_with_stmt ::= "async" with_stmt\n\nAn *asynchronous context manager* is a *context manager* that is able\nto suspend execution in its *enter* and *exit* methods.\n\nThe following code:\n\n async with EXPR as VAR:\n BLOCK\n\nIs semantically equivalent to:\n\n mgr = (EXPR)\n aexit = type(mgr).__aexit__\n aenter = type(mgr).__aenter__(mgr)\n exc = True\n\n VAR = await aenter\n try:\n BLOCK\n except:\n if not await aexit(mgr, *sys.exc_info()):\n raise\n else:\n await aexit(mgr, None, None, None)\n\nSee also "__aenter__()" and "__aexit__()" for details.\n\nNew in version 3.5.\n\nSee also: **PEP 492** - Coroutines with async and await syntax\n\n-[ Footnotes ]-\n\n[1] The exception is propagated to the invocation stack unless\n there is a "finally" clause which happens to raise another\n exception. That new exception causes the old one to be lost.\n\n[2] Currently, control "flows off the end" except in the case of\n an exception or the execution of a "return", "continue", or\n "break" statement.\n\n[3] A string literal appearing as the first statement in the\n function body is transformed into the function\'s "__doc__"\n attribute and therefore the function\'s *docstring*.\n\n[4] A string literal appearing as the first statement in the class\n body is transformed into the namespace\'s "__doc__" item and\n therefore the class\'s *docstring*.\n', 'context-managers': u'\nWith Statement Context Managers\n*******************************\n\nA *context manager* is an object that defines the runtime context to\nbe established when executing a "with" statement. The context manager\nhandles the entry into, and the exit from, the desired runtime context\nfor the execution of the block of code. Context managers are normally\ninvoked using the "with" statement (described in section *The with\nstatement*), but can also be used by directly invoking their methods.\n\nTypical uses of context managers include saving and restoring various\nkinds of global state, locking and unlocking resources, closing opened\nfiles, etc.\n\nFor more information on context managers, see *Context Manager Types*.\n\nobject.__enter__(self)\n\n Enter the runtime context related to this object. The "with"\n statement will bind this method\'s return value to the target(s)\n specified in the "as" clause of the statement, if any.\n\nobject.__exit__(self, exc_type, exc_value, traceback)\n\n Exit the runtime context related to this object. The parameters\n describe the exception that caused the context to be exited. If the\n context was exited without an exception, all three arguments will\n be "None".\n\n If an exception is supplied, and the method wishes to suppress the\n exception (i.e., prevent it from being propagated), it should\n return a true value. Otherwise, the exception will be processed\n normally upon exit from this method.\n\n Note that "__exit__()" methods should not reraise the passed-in\n exception; this is the caller\'s responsibility.\n\nSee also: **PEP 0343** - The "with" statement\n\n The specification, background, and examples for the Python "with"\n statement.\n', 'continue': u'\nThe "continue" statement\n************************\n\n continue_stmt ::= "continue"\n\n"continue" may only occur syntactically nested in a "for" or "while"\nloop, but not nested in a function or class definition or "finally"\nclause within that loop. It continues with the next cycle of the\nnearest enclosing loop.\n\nWhen "continue" passes control out of a "try" statement with a\n"finally" clause, that "finally" clause is executed before really\nstarting the next loop cycle.\n', 'conversions': u'\nArithmetic conversions\n**********************\n\nWhen a description of an arithmetic operator below uses the phrase\n"the numeric arguments are converted to a common type," this means\nthat the operator implementation for built-in types works as follows:\n\n* If either argument is a complex number, the other is converted to\n complex;\n\n* otherwise, if either argument is a floating point number, the\n other is converted to floating point;\n\n* otherwise, both must be integers and no conversion is necessary.\n\nSome additional rules apply for certain operators (e.g., a string as a\nleft argument to the \'%\' operator). Extensions must define their own\nconversion behavior.\n', @@ -42,7 +42,7 @@ topics = {'assert': u'\nThe "assert" statement\n**********************\n\nAssert 'if': u'\nThe "if" statement\n******************\n\nThe "if" statement is used for conditional execution:\n\n if_stmt ::= "if" expression ":" suite\n ( "elif" expression ":" suite )*\n ["else" ":" suite]\n\nIt selects exactly one of the suites by evaluating the expressions one\nby one until one is found to be true (see section *Boolean operations*\nfor the definition of true and false); then that suite is executed\n(and no other part of the "if" statement is executed or evaluated).\nIf all expressions are false, the suite of the "else" clause, if\npresent, is executed.\n', 'imaginary': u'\nImaginary literals\n******************\n\nImaginary literals are described by the following lexical definitions:\n\n imagnumber ::= (floatnumber | intpart) ("j" | "J")\n\nAn imaginary literal yields a complex number with a real part of 0.0.\nComplex numbers are represented as a pair of floating point numbers\nand have the same restrictions on their range. To create a complex\nnumber with a nonzero real part, add a floating point number to it,\ne.g., "(3+4j)". Some examples of imaginary literals:\n\n 3.14j 10.j 10j .001j 1e100j 3.14e-10j\n', 'import': u'\nThe "import" statement\n**********************\n\n import_stmt ::= "import" module ["as" name] ( "," module ["as" name] )*\n | "from" relative_module "import" identifier ["as" name]\n ( "," identifier ["as" name] )*\n | "from" relative_module "import" "(" identifier ["as" name]\n ( "," identifier ["as" name] )* [","] ")"\n | "from" module "import" "*"\n module ::= (identifier ".")* identifier\n relative_module ::= "."* module | "."+\n name ::= identifier\n\nThe basic import statement (no "from" clause) is executed in two\nsteps:\n\n1. find a module, loading and initializing it if necessary\n\n2. define a name or names in the local namespace for the scope\n where the "import" statement occurs.\n\nWhen the statement contains multiple clauses (separated by commas) the\ntwo steps are carried out separately for each clause, just as though\nthe clauses had been separated out into individiual import statements.\n\nThe details of the first step, finding and loading modules are\ndescribed in greater detail in the section on the *import system*,\nwhich also describes the various types of packages and modules that\ncan be imported, as well as all the hooks that can be used to\ncustomize the import system. Note that failures in this step may\nindicate either that the module could not be located, *or* that an\nerror occurred while initializing the module, which includes execution\nof the module\'s code.\n\nIf the requested module is retrieved successfully, it will be made\navailable in the local namespace in one of three ways:\n\n* If the module name is followed by "as", then the name following\n "as" is bound directly to the imported module.\n\n* If no other name is specified, and the module being imported is a\n top level module, the module\'s name is bound in the local namespace\n as a reference to the imported module\n\n* If the module being imported is *not* a top level module, then the\n name of the top level package that contains the module is bound in\n the local namespace as a reference to the top level package. The\n imported module must be accessed using its full qualified name\n rather than directly\n\nThe "from" form uses a slightly more complex process:\n\n1. find the module specified in the "from" clause, loading and\n initializing it if necessary;\n\n2. for each of the identifiers specified in the "import" clauses:\n\n 1. check if the imported module has an attribute by that name\n\n 2. if not, attempt to import a submodule with that name and then\n check the imported module again for that attribute\n\n 3. if the attribute is not found, "ImportError" is raised.\n\n 4. otherwise, a reference to that value is stored in the local\n namespace, using the name in the "as" clause if it is present,\n otherwise using the attribute name\n\nExamples:\n\n import foo # foo imported and bound locally\n import foo.bar.baz # foo.bar.baz imported, foo bound locally\n import foo.bar.baz as fbb # foo.bar.baz imported and bound as fbb\n from foo.bar import baz # foo.bar.baz imported and bound as baz\n from foo import attr # foo imported and foo.attr bound as attr\n\nIf the list of identifiers is replaced by a star ("\'*\'"), all public\nnames defined in the module are bound in the local namespace for the\nscope where the "import" statement occurs.\n\nThe *public names* defined by a module are determined by checking the\nmodule\'s namespace for a variable named "__all__"; if defined, it must\nbe a sequence of strings which are names defined or imported by that\nmodule. The names given in "__all__" are all considered public and\nare required to exist. If "__all__" is not defined, the set of public\nnames includes all names found in the module\'s namespace which do not\nbegin with an underscore character ("\'_\'"). "__all__" should contain\nthe entire public API. It is intended to avoid accidentally exporting\nitems that are not part of the API (such as library modules which were\nimported and used within the module).\n\nThe wild card form of import --- "from module import *" --- is only\nallowed at the module level. Attempting to use it in class or\nfunction definitions will raise a "SyntaxError".\n\nWhen specifying what module to import you do not have to specify the\nabsolute name of the module. When a module or package is contained\nwithin another package it is possible to make a relative import within\nthe same top package without having to mention the package name. By\nusing leading dots in the specified module or package after "from" you\ncan specify how high to traverse up the current package hierarchy\nwithout specifying exact names. One leading dot means the current\npackage where the module making the import exists. Two dots means up\none package level. Three dots is up two levels, etc. So if you execute\n"from . import mod" from a module in the "pkg" package then you will\nend up importing "pkg.mod". If you execute "from ..subpkg2 import mod"\nfrom within "pkg.subpkg1" you will import "pkg.subpkg2.mod". The\nspecification for relative imports is contained within **PEP 328**.\n\n"importlib.import_module()" is provided to support applications that\ndetermine dynamically the modules to be loaded.\n\n\nFuture statements\n=================\n\nA *future statement* is a directive to the compiler that a particular\nmodule should be compiled using syntax or semantics that will be\navailable in a specified future release of Python where the feature\nbecomes standard.\n\nThe future statement is intended to ease migration to future versions\nof Python that introduce incompatible changes to the language. It\nallows use of the new features on a per-module basis before the\nrelease in which the feature becomes standard.\n\n future_statement ::= "from" "__future__" "import" feature ["as" name]\n ("," feature ["as" name])*\n | "from" "__future__" "import" "(" feature ["as" name]\n ("," feature ["as" name])* [","] ")"\n feature ::= identifier\n name ::= identifier\n\nA future statement must appear near the top of the module. The only\nlines that can appear before a future statement are:\n\n* the module docstring (if any),\n\n* comments,\n\n* blank lines, and\n\n* other future statements.\n\nThe features recognized by Python 3.0 are "absolute_import",\n"division", "generators", "unicode_literals", "print_function",\n"nested_scopes" and "with_statement". They are all redundant because\nthey are always enabled, and only kept for backwards compatibility.\n\nA future statement is recognized and treated specially at compile\ntime: Changes to the semantics of core constructs are often\nimplemented by generating different code. It may even be the case\nthat a new feature introduces new incompatible syntax (such as a new\nreserved word), in which case the compiler may need to parse the\nmodule differently. Such decisions cannot be pushed off until\nruntime.\n\nFor any given release, the compiler knows which feature names have\nbeen defined, and raises a compile-time error if a future statement\ncontains a feature not known to it.\n\nThe direct runtime semantics are the same as for any import statement:\nthere is a standard module "__future__", described later, and it will\nbe imported in the usual way at the time the future statement is\nexecuted.\n\nThe interesting runtime semantics depend on the specific feature\nenabled by the future statement.\n\nNote that there is nothing special about the statement:\n\n import __future__ [as name]\n\nThat is not a future statement; it\'s an ordinary import statement with\nno special semantics or syntax restrictions.\n\nCode compiled by calls to the built-in functions "exec()" and\n"compile()" that occur in a module "M" containing a future statement\nwill, by default, use the new syntax or semantics associated with the\nfuture statement. This can be controlled by optional arguments to\n"compile()" --- see the documentation of that function for details.\n\nA future statement typed at an interactive interpreter prompt will\ntake effect for the rest of the interpreter session. If an\ninterpreter is started with the *-i* option, is passed a script name\nto execute, and the script includes a future statement, it will be in\neffect in the interactive session started after the script is\nexecuted.\n\nSee also: **PEP 236** - Back to the __future__\n\n The original proposal for the __future__ mechanism.\n', - 'in': u'\nComparisons\n***********\n\nUnlike C, all comparison operations in Python have the same priority,\nwhich is lower than that of any arithmetic, shifting or bitwise\noperation. Also unlike C, expressions like "a < b < c" have the\ninterpretation that is conventional in mathematics:\n\n comparison ::= or_expr ( comp_operator or_expr )*\n comp_operator ::= "<" | ">" | "==" | ">=" | "<=" | "!="\n | "is" ["not"] | ["not"] "in"\n\nComparisons yield boolean values: "True" or "False".\n\nComparisons can be chained arbitrarily, e.g., "x < y <= z" is\nequivalent to "x < y and y <= z", except that "y" is evaluated only\nonce (but in both cases "z" is not evaluated at all when "x < y" is\nfound to be false).\n\nFormally, if *a*, *b*, *c*, ..., *y*, *z* are expressions and *op1*,\n*op2*, ..., *opN* are comparison operators, then "a op1 b op2 c ... y\nopN z" is equivalent to "a op1 b and b op2 c and ... y opN z", except\nthat each expression is evaluated at most once.\n\nNote that "a op1 b op2 c" doesn\'t imply any kind of comparison between\n*a* and *c*, so that, e.g., "x < y > z" is perfectly legal (though\nperhaps not pretty).\n\nThe operators "<", ">", "==", ">=", "<=", and "!=" compare the values\nof two objects. The objects need not have the same type. If both are\nnumbers, they are converted to a common type. Otherwise, the "==" and\n"!=" operators *always* consider objects of different types to be\nunequal, while the "<", ">", ">=" and "<=" operators raise a\n"TypeError" when comparing objects of different types that do not\nimplement these operators for the given pair of types. You can\ncontrol comparison behavior of objects of non-built-in types by\ndefining rich comparison methods like "__gt__()", described in section\n*Basic customization*.\n\nComparison of objects of the same type depends on the type:\n\n* Numbers are compared arithmetically.\n\n* The values "float(\'NaN\')" and "Decimal(\'NaN\')" are special. They\n are identical to themselves, "x is x" but are not equal to\n themselves, "x != x". Additionally, comparing any value to a\n not-a-number value will return "False". For example, both "3 <\n float(\'NaN\')" and "float(\'NaN\') < 3" will return "False".\n\n* Bytes objects are compared lexicographically using the numeric\n values of their elements.\n\n* Strings are compared lexicographically using the numeric\n equivalents (the result of the built-in function "ord()") of their\n characters. [3] String and bytes object can\'t be compared!\n\n* Tuples and lists are compared lexicographically using comparison\n of corresponding elements. This means that to compare equal, each\n element must compare equal and the two sequences must be of the same\n type and have the same length.\n\n If not equal, the sequences are ordered the same as their first\n differing elements. For example, "[1,2,x] <= [1,2,y]" has the same\n value as "x <= y". If the corresponding element does not exist, the\n shorter sequence is ordered first (for example, "[1,2] < [1,2,3]").\n\n* Mappings (dictionaries) compare equal if and only if they have the\n same "(key, value)" pairs. Order comparisons "(\'<\', \'<=\', \'>=\',\n \'>\')" raise "TypeError".\n\n* Sets and frozensets define comparison operators to mean subset and\n superset tests. Those relations do not define total orderings (the\n two sets "{1,2}" and "{2,3}" are not equal, nor subsets of one\n another, nor supersets of one another). Accordingly, sets are not\n appropriate arguments for functions which depend on total ordering.\n For example, "min()", "max()", and "sorted()" produce undefined\n results given a list of sets as inputs.\n\n* Most other objects of built-in types compare unequal unless they\n are the same object; the choice whether one object is considered\n smaller or larger than another one is made arbitrarily but\n consistently within one execution of a program.\n\nComparison of objects of differing types depends on whether either of\nthe types provide explicit support for the comparison. Most numeric\ntypes can be compared with one another. When cross-type comparison is\nnot supported, the comparison method returns "NotImplemented".\n\nThe operators "in" and "not in" test for membership. "x in s"\nevaluates to true if *x* is a member of *s*, and false otherwise. "x\nnot in s" returns the negation of "x in s". All built-in sequences\nand set types support this as well as dictionary, for which "in" tests\nwhether the dictionary has a given key. For container types such as\nlist, tuple, set, frozenset, dict, or collections.deque, the\nexpression "x in y" is equivalent to "any(x is e or x == e for e in\ny)".\n\nFor the string and bytes types, "x in y" is true if and only if *x* is\na substring of *y*. An equivalent test is "y.find(x) != -1". Empty\nstrings are always considered to be a substring of any other string,\nso """ in "abc"" will return "True".\n\nFor user-defined classes which define the "__contains__()" method, "x\nin y" is true if and only if "y.__contains__(x)" is true.\n\nFor user-defined classes which do not define "__contains__()" but do\ndefine "__iter__()", "x in y" is true if some value "z" with "x == z"\nis produced while iterating over "y". If an exception is raised\nduring the iteration, it is as if "in" raised that exception.\n\nLastly, the old-style iteration protocol is tried: if a class defines\n"__getitem__()", "x in y" is true if and only if there is a non-\nnegative integer index *i* such that "x == y[i]", and all lower\ninteger indices do not raise "IndexError" exception. (If any other\nexception is raised, it is as if "in" raised that exception).\n\nThe operator "not in" is defined to have the inverse true value of\n"in".\n\nThe operators "is" and "is not" test for object identity: "x is y" is\ntrue if and only if *x* and *y* are the same object. "x is not y"\nyields the inverse truth value. [4]\n', + 'in': u'\nComparisons\n***********\n\nUnlike C, all comparison operations in Python have the same priority,\nwhich is lower than that of any arithmetic, shifting or bitwise\noperation. Also unlike C, expressions like "a < b < c" have the\ninterpretation that is conventional in mathematics:\n\n comparison ::= or_expr ( comp_operator or_expr )*\n comp_operator ::= "<" | ">" | "==" | ">=" | "<=" | "!="\n | "is" ["not"] | ["not"] "in"\n\nComparisons yield boolean values: "True" or "False".\n\nComparisons can be chained arbitrarily, e.g., "x < y <= z" is\nequivalent to "x < y and y <= z", except that "y" is evaluated only\nonce (but in both cases "z" is not evaluated at all when "x < y" is\nfound to be false).\n\nFormally, if *a*, *b*, *c*, ..., *y*, *z* are expressions and *op1*,\n*op2*, ..., *opN* are comparison operators, then "a op1 b op2 c ... y\nopN z" is equivalent to "a op1 b and b op2 c and ... y opN z", except\nthat each expression is evaluated at most once.\n\nNote that "a op1 b op2 c" doesn\'t imply any kind of comparison between\n*a* and *c*, so that, e.g., "x < y > z" is perfectly legal (though\nperhaps not pretty).\n\nThe operators "<", ">", "==", ">=", "<=", and "!=" compare the values\nof two objects. The objects need not have the same type. If both are\nnumbers, they are converted to a common type. Otherwise, the "==" and\n"!=" operators *always* consider objects of different types to be\nunequal, while the "<", ">", ">=" and "<=" operators raise a\n"TypeError" when comparing objects of different types that do not\nimplement these operators for the given pair of types. You can\ncontrol comparison behavior of objects of non-built-in types by\ndefining rich comparison methods like "__gt__()", described in section\n*Basic customization*.\n\nComparison of objects of the same type depends on the type:\n\n* Numbers are compared arithmetically.\n\n* The values "float(\'NaN\')" and "Decimal(\'NaN\')" are special. They\n are identical to themselves, "x is x" but are not equal to\n themselves, "x != x". Additionally, comparing any value to a\n not-a-number value will return "False". For example, both "3 <\n float(\'NaN\')" and "float(\'NaN\') < 3" will return "False".\n\n* Bytes objects are compared lexicographically using the numeric\n values of their elements.\n\n* Strings are compared lexicographically using the numeric\n equivalents (the result of the built-in function "ord()") of their\n characters. [3] String and bytes object can\'t be compared!\n\n* Tuples and lists are compared lexicographically using comparison\n of corresponding elements. This means that to compare equal, each\n element must compare equal and the two sequences must be of the same\n type and have the same length.\n\n If not equal, the sequences are ordered the same as their first\n differing elements. For example, "[1,2,x] <= [1,2,y]" has the same\n value as "x <= y". If the corresponding element does not exist, the\n shorter sequence is ordered first (for example, "[1,2] < [1,2,3]").\n\n* Mappings (dictionaries) compare equal if and only if they have the\n same "(key, value)" pairs. Order comparisons "(\'<\', \'<=\', \'>=\',\n \'>\')" raise "TypeError".\n\n* Sets and frozensets define comparison operators to mean subset and\n superset tests. Those relations do not define total orderings (the\n two sets "{1,2}" and {2,3} are not equal, nor subsets of one\n another, nor supersets of one another). Accordingly, sets are not\n appropriate arguments for functions which depend on total ordering.\n For example, "min()", "max()", and "sorted()" produce undefined\n results given a list of sets as inputs.\n\n* Most other objects of built-in types compare unequal unless they\n are the same object; the choice whether one object is considered\n smaller or larger than another one is made arbitrarily but\n consistently within one execution of a program.\n\nComparison of objects of differing types depends on whether either of\nthe types provide explicit support for the comparison. Most numeric\ntypes can be compared with one another. When cross-type comparison is\nnot supported, the comparison method returns "NotImplemented".\n\nThe operators "in" and "not in" test for membership. "x in s"\nevaluates to true if *x* is a member of *s*, and false otherwise. "x\nnot in s" returns the negation of "x in s". All built-in sequences\nand set types support this as well as dictionary, for which "in" tests\nwhether the dictionary has a given key. For container types such as\nlist, tuple, set, frozenset, dict, or collections.deque, the\nexpression "x in y" is equivalent to "any(x is e or x == e for e in\ny)".\n\nFor the string and bytes types, "x in y" is true if and only if *x* is\na substring of *y*. An equivalent test is "y.find(x) != -1". Empty\nstrings are always considered to be a substring of any other string,\nso """ in "abc"" will return "True".\n\nFor user-defined classes which define the "__contains__()" method, "x\nin y" is true if and only if "y.__contains__(x)" is true.\n\nFor user-defined classes which do not define "__contains__()" but do\ndefine "__iter__()", "x in y" is true if some value "z" with "x == z"\nis produced while iterating over "y". If an exception is raised\nduring the iteration, it is as if "in" raised that exception.\n\nLastly, the old-style iteration protocol is tried: if a class defines\n"__getitem__()", "x in y" is true if and only if there is a non-\nnegative integer index *i* such that "x == y[i]", and all lower\ninteger indices do not raise "IndexError" exception. (If any other\nexception is raised, it is as if "in" raised that exception).\n\nThe operator "not in" is defined to have the inverse true value of\n"in".\n\nThe operators "is" and "is not" test for object identity: "x is y" is\ntrue if and only if *x* and *y* are the same object. "x is not y"\nyields the inverse truth value. [4]\n', 'integers': u'\nInteger literals\n****************\n\nInteger literals are described by the following lexical definitions:\n\n integer ::= decimalinteger | octinteger | hexinteger | bininteger\n decimalinteger ::= nonzerodigit digit* | "0"+\n nonzerodigit ::= "1"..."9"\n digit ::= "0"..."9"\n octinteger ::= "0" ("o" | "O") octdigit+\n hexinteger ::= "0" ("x" | "X") hexdigit+\n bininteger ::= "0" ("b" | "B") bindigit+\n octdigit ::= "0"..."7"\n hexdigit ::= digit | "a"..."f" | "A"..."F"\n bindigit ::= "0" | "1"\n\nThere is no limit for the length of integer literals apart from what\ncan be stored in available memory.\n\nNote that leading zeros in a non-zero decimal number are not allowed.\nThis is for disambiguation with C-style octal literals, which Python\nused before version 3.0.\n\nSome examples of integer literals:\n\n 7 2147483647 0o177 0b100110111\n 3 79228162514264337593543950336 0o377 0xdeadbeef\n', 'lambda': u'\nLambdas\n*******\n\n lambda_expr ::= "lambda" [parameter_list]: expression\n lambda_expr_nocond ::= "lambda" [parameter_list]: expression_nocond\n\nLambda expressions (sometimes called lambda forms) are used to create\nanonymous functions. The expression "lambda arguments: expression"\nyields a function object. The unnamed object behaves like a function\nobject defined with\n\n def <lambda>(arguments):\n return expression\n\nSee section *Function definitions* for the syntax of parameter lists.\nNote that functions created with lambda expressions cannot contain\nstatements or annotations.\n', 'lists': u'\nList displays\n*************\n\nA list display is a possibly empty series of expressions enclosed in\nsquare brackets:\n\n list_display ::= "[" [expression_list | comprehension] "]"\n\nA list display yields a new list object, the contents being specified\nby either a list of expressions or a comprehension. When a comma-\nseparated list of expressions is supplied, its elements are evaluated\nfrom left to right and placed into the list object in that order.\nWhen a comprehension is supplied, the list is constructed from the\nelements resulting from the comprehension.\n', @@ -51,7 +51,7 @@ topics = {'assert': u'\nThe "assert" statement\n**********************\n\nAssert 'numbers': u'\nNumeric literals\n****************\n\nThere are three types of numeric literals: integers, floating point\nnumbers, and imaginary numbers. There are no complex literals\n(complex numbers can be formed by adding a real number and an\nimaginary number).\n\nNote that numeric literals do not include a sign; a phrase like "-1"\nis actually an expression composed of the unary operator \'"-"\' and the\nliteral "1".\n', 'numeric-types': u'\nEmulating numeric types\n***********************\n\nThe following methods can be defined to emulate numeric objects.\nMethods corresponding to operations that are not supported by the\nparticular kind of number implemented (e.g., bitwise operations for\nnon-integral numbers) should be left undefined.\n\nobject.__add__(self, other)\nobject.__sub__(self, other)\nobject.__mul__(self, other)\nobject.__matmul__(self, other)\nobject.__truediv__(self, other)\nobject.__floordiv__(self, other)\nobject.__mod__(self, other)\nobject.__divmod__(self, other)\nobject.__pow__(self, other[, modulo])\nobject.__lshift__(self, other)\nobject.__rshift__(self, other)\nobject.__and__(self, other)\nobject.__xor__(self, other)\nobject.__or__(self, other)\n\n These methods are called to implement the binary arithmetic\n operations ("+", "-", "*", "@", "/", "//", "%", "divmod()",\n "pow()", "**", "<<", ">>", "&", "^", "|"). For instance, to\n evaluate the expression "x + y", where *x* is an instance of a\n class that has an "__add__()" method, "x.__add__(y)" is called.\n The "__divmod__()" method should be the equivalent to using\n "__floordiv__()" and "__mod__()"; it should not be related to\n "__truediv__()". Note that "__pow__()" should be defined to accept\n an optional third argument if the ternary version of the built-in\n "pow()" function is to be supported.\n\n If one of those methods does not support the operation with the\n supplied arguments, it should return "NotImplemented".\n\nobject.__radd__(self, other)\nobject.__rsub__(self, other)\nobject.__rmul__(self, other)\nobject.__rmatmul__(self, other)\nobject.__rtruediv__(self, other)\nobject.__rfloordiv__(self, other)\nobject.__rmod__(self, other)\nobject.__rdivmod__(self, other)\nobject.__rpow__(self, other)\nobject.__rlshift__(self, other)\nobject.__rrshift__(self, other)\nobject.__rand__(self, other)\nobject.__rxor__(self, other)\nobject.__ror__(self, other)\n\n These methods are called to implement the binary arithmetic\n operations ("+", "-", "*", "@", "/", "//", "%", "divmod()",\n "pow()", "**", "<<", ">>", "&", "^", "|") with reflected (swapped)\n operands. These functions are only called if the left operand does\n not support the corresponding operation and the operands are of\n different types. [2] For instance, to evaluate the expression "x -\n y", where *y* is an instance of a class that has an "__rsub__()"\n method, "y.__rsub__(x)" is called if "x.__sub__(y)" returns\n *NotImplemented*.\n\n Note that ternary "pow()" will not try calling "__rpow__()" (the\n coercion rules would become too complicated).\n\n Note: If the right operand\'s type is a subclass of the left\n operand\'s type and that subclass provides the reflected method\n for the operation, this method will be called before the left\n operand\'s non-reflected method. This behavior allows subclasses\n to override their ancestors\' operations.\n\nobject.__iadd__(self, other)\nobject.__isub__(self, other)\nobject.__imul__(self, other)\nobject.__imatmul__(self, other)\nobject.__itruediv__(self, other)\nobject.__ifloordiv__(self, other)\nobject.__imod__(self, other)\nobject.__ipow__(self, other[, modulo])\nobject.__ilshift__(self, other)\nobject.__irshift__(self, other)\nobject.__iand__(self, other)\nobject.__ixor__(self, other)\nobject.__ior__(self, other)\n\n These methods are called to implement the augmented arithmetic\n assignments ("+=", "-=", "*=", "@=", "/=", "//=", "%=", "**=",\n "<<=", ">>=", "&=", "^=", "|="). These methods should attempt to\n do the operation in-place (modifying *self*) and return the result\n (which could be, but does not have to be, *self*). If a specific\n method is not defined, the augmented assignment falls back to the\n normal methods. For instance, if *x* is an instance of a class\n with an "__iadd__()" method, "x += y" is equivalent to "x =\n x.__iadd__(y)" . Otherwise, "x.__add__(y)" and "y.__radd__(x)" are\n considered, as with the evaluation of "x + y". In certain\n situations, augmented assignment can result in unexpected errors\n (see *Why does a_tuple[i] += [\'item\'] raise an exception when the\n addition works?*), but this behavior is in fact part of the data\n model.\n\nobject.__neg__(self)\nobject.__pos__(self)\nobject.__abs__(self)\nobject.__invert__(self)\n\n Called to implement the unary arithmetic operations ("-", "+",\n "abs()" and "~").\n\nobject.__complex__(self)\nobject.__int__(self)\nobject.__float__(self)\nobject.__round__(self[, n])\n\n Called to implement the built-in functions "complex()", "int()",\n "float()" and "round()". Should return a value of the appropriate\n type.\n\nobject.__index__(self)\n\n Called to implement "operator.index()", and whenever Python needs\n to losslessly convert the numeric object to an integer object (such\n as in slicing, or in the built-in "bin()", "hex()" and "oct()"\n functions). Presence of this method indicates that the numeric\n object is an integer type. Must return an integer.\n\n Note: In order to have a coherent integer type class, when\n "__index__()" is defined "__int__()" should also be defined, and\n both should return the same value.\n', 'objects': u'\nObjects, values and types\n*************************\n\n*Objects* are Python\'s abstraction for data. All data in a Python\nprogram is represented by objects or by relations between objects. (In\na sense, and in conformance to Von Neumann\'s model of a "stored\nprogram computer," code is also represented by objects.)\n\nEvery object has an identity, a type and a value. An object\'s\n*identity* never changes once it has been created; you may think of it\nas the object\'s address in memory. The \'"is"\' operator compares the\nidentity of two objects; the "id()" function returns an integer\nrepresenting its identity.\n\n**CPython implementation detail:** For CPython, "id(x)" is the memory\naddress where "x" is stored.\n\nAn object\'s type determines the operations that the object supports\n(e.g., "does it have a length?") and also defines the possible values\nfor objects of that type. The "type()" function returns an object\'s\ntype (which is an object itself). Like its identity, an object\'s\n*type* is also unchangeable. [1]\n\nThe *value* of some objects can change. Objects whose value can\nchange are said to be *mutable*; objects whose value is unchangeable\nonce they are created are called *immutable*. (The value of an\nimmutable container object that contains a reference to a mutable\nobject can change when the latter\'s value is changed; however the\ncontainer is still considered immutable, because the collection of\nobjects it contains cannot be changed. So, immutability is not\nstrictly the same as having an unchangeable value, it is more subtle.)\nAn object\'s mutability is determined by its type; for instance,\nnumbers, strings and tuples are immutable, while dictionaries and\nlists are mutable.\n\nObjects are never explicitly destroyed; however, when they become\nunreachable they may be garbage-collected. An implementation is\nallowed to postpone garbage collection or omit it altogether --- it is\na matter of implementation quality how garbage collection is\nimplemented, as long as no objects are collected that are still\nreachable.\n\n**CPython implementation detail:** CPython currently uses a reference-\ncounting scheme with (optional) delayed detection of cyclically linked\ngarbage, which collects most objects as soon as they become\nunreachable, but is not guaranteed to collect garbage containing\ncircular references. See the documentation of the "gc" module for\ninformation on controlling the collection of cyclic garbage. Other\nimplementations act differently and CPython may change. Do not depend\non immediate finalization of objects when they become unreachable (so\nyou should always close files explicitly).\n\nNote that the use of the implementation\'s tracing or debugging\nfacilities may keep objects alive that would normally be collectable.\nAlso note that catching an exception with a \'"try"..."except"\'\nstatement may keep objects alive.\n\nSome objects contain references to "external" resources such as open\nfiles or windows. It is understood that these resources are freed\nwhen the object is garbage-collected, but since garbage collection is\nnot guaranteed to happen, such objects also provide an explicit way to\nrelease the external resource, usually a "close()" method. Programs\nare strongly recommended to explicitly close such objects. The\n\'"try"..."finally"\' statement and the \'"with"\' statement provide\nconvenient ways to do this.\n\nSome objects contain references to other objects; these are called\n*containers*. Examples of containers are tuples, lists and\ndictionaries. The references are part of a container\'s value. In\nmost cases, when we talk about the value of a container, we imply the\nvalues, not the identities of the contained objects; however, when we\ntalk about the mutability of a container, only the identities of the\nimmediately contained objects are implied. So, if an immutable\ncontainer (like a tuple) contains a reference to a mutable object, its\nvalue changes if that mutable object is changed.\n\nTypes affect almost all aspects of object behavior. Even the\nimportance of object identity is affected in some sense: for immutable\ntypes, operations that compute new values may actually return a\nreference to any existing object with the same type and value, while\nfor mutable objects this is not allowed. E.g., after "a = 1; b = 1",\n"a" and "b" may or may not refer to the same object with the value\none, depending on the implementation, but after "c = []; d = []", "c"\nand "d" are guaranteed to refer to two different, unique, newly\ncreated empty lists. (Note that "c = d = []" assigns the same object\nto both "c" and "d".)\n', - 'operator-summary': u'\nOperator precedence\n*******************\n\nThe following table summarizes the operator precedence in Python, from\nlowest precedence (least binding) to highest precedence (most\nbinding). Operators in the same box have the same precedence. Unless\nthe syntax is explicitly given, operators are binary. Operators in\nthe same box group left to right (except for exponentiation, which\ngroups from right to left).\n\nNote that comparisons, membership tests, and identity tests, all have\nthe same precedence and have a left-to-right chaining feature as\ndescribed in the *Comparisons* section.\n\n+-------------------------------------------------+---------------------------------------+\n| Operator | Description |\n+=================================================+=======================================+\n| "lambda" | Lambda expression |\n+-------------------------------------------------+---------------------------------------+\n| "if" -- "else" | Conditional expression |\n+-------------------------------------------------+---------------------------------------+\n| "or" | Boolean OR |\n+-------------------------------------------------+---------------------------------------+\n| "and" | Boolean AND |\n+-------------------------------------------------+---------------------------------------+\n| "not" "x" | Boolean NOT |\n+-------------------------------------------------+---------------------------------------+\n| "in", "not in", "is", "is not", "<", "<=", ">", | Comparisons, including membership |\n| ">=", "!=", "==" | tests and identity tests |\n+-------------------------------------------------+---------------------------------------+\n| "|" | Bitwise OR |\n+-------------------------------------------------+---------------------------------------+\n| "^" | Bitwise XOR |\n+-------------------------------------------------+---------------------------------------+\n| "&" | Bitwise AND |\n+-------------------------------------------------+---------------------------------------+\n| "<<", ">>" | Shifts |\n+-------------------------------------------------+---------------------------------------+\n| "+", "-" | Addition and subtraction |\n+-------------------------------------------------+---------------------------------------+\n| "*", "@", "/", "//", "%" | Multiplication, matrix multiplication |\n| | division, remainder [5] |\n+-------------------------------------------------+---------------------------------------+\n| "+x", "-x", "~x" | Positive, negative, bitwise NOT |\n+-------------------------------------------------+---------------------------------------+\n| "**" | Exponentiation [6] |\n+-------------------------------------------------+---------------------------------------+\n| "await" "x" | Await expression |\n+-------------------------------------------------+---------------------------------------+\n| "x[index]", "x[index:index]", | Subscription, slicing, call, |\n| "x(arguments...)", "x.attribute" | attribute reference |\n+-------------------------------------------------+---------------------------------------+\n| "(expressions...)", "[expressions...]", "{key: | Binding or tuple display, list |\n| value...}", "{expressions...}" | display, dictionary display, set |\n| | display |\n+-------------------------------------------------+---------------------------------------+\n\n-[ Footnotes ]-\n\n[1] While "abs(x%y) < abs(y)" is true mathematically, for floats\n it may not be true numerically due to roundoff. For example, and\n assuming a platform on which a Python float is an IEEE 754 double-\n precision number, in order that "-1e-100 % 1e100" have the same\n sign as "1e100", the computed result is "-1e-100 + 1e100", which\n is numerically exactly equal to "1e100". The function\n "math.fmod()" returns a result whose sign matches the sign of the\n first argument instead, and so returns "-1e-100" in this case.\n Which approach is more appropriate depends on the application.\n\n[2] If x is very close to an exact integer multiple of y, it\'s\n possible for "x//y" to be one larger than "(x-x%y)//y" due to\n rounding. In such cases, Python returns the latter result, in\n order to preserve that "divmod(x,y)[0] * y + x % y" be very close\n to "x".\n\n[3] While comparisons between strings make sense at the byte\n level, they may be counter-intuitive to users. For example, the\n strings ""\\u00C7"" and ""\\u0043\\u0327"" compare differently, even\n though they both represent the same unicode character (LATIN\n CAPITAL LETTER C WITH CEDILLA). To compare strings in a human\n recognizable way, compare using "unicodedata.normalize()".\n\n[4] Due to automatic garbage-collection, free lists, and the\n dynamic nature of descriptors, you may notice seemingly unusual\n behaviour in certain uses of the "is" operator, like those\n involving comparisons between instance methods, or constants.\n Check their documentation for more info.\n\n[5] The "%" operator is also used for string formatting; the same\n precedence applies.\n\n[6] The power operator "**" binds less tightly than an arithmetic\n or bitwise unary operator on its right, that is, "2**-1" is "0.5".\n', + 'operator-summary': u'\nOperator precedence\n*******************\n\nThe following table summarizes the operator precedence in Python, from\nlowest precedence (least binding) to highest precedence (most\nbinding). Operators in the same box have the same precedence. Unless\nthe syntax is explicitly given, operators are binary. Operators in\nthe same box group left to right (except for exponentiation, which\ngroups from right to left).\n\nNote that comparisons, membership tests, and identity tests, all have\nthe same precedence and have a left-to-right chaining feature as\ndescribed in the *Comparisons* section.\n\n+-------------------------------------------------+---------------------------------------+\n| Operator | Description |\n+=================================================+=======================================+\n| "lambda" | Lambda expression |\n+-------------------------------------------------+---------------------------------------+\n| "if" -- "else" | Conditional expression |\n+-------------------------------------------------+---------------------------------------+\n| "or" | Boolean OR |\n+-------------------------------------------------+---------------------------------------+\n| "and" | Boolean AND |\n+-------------------------------------------------+---------------------------------------+\n| "not" "x" | Boolean NOT |\n+-------------------------------------------------+---------------------------------------+\n| "in", "not in", "is", "is not", "<", "<=", ">", | Comparisons, including membership |\n| ">=", "!=", "==" | tests and identity tests |\n+-------------------------------------------------+---------------------------------------+\n| "|" | Bitwise OR |\n+-------------------------------------------------+---------------------------------------+\n| "^" | Bitwise XOR |\n+-------------------------------------------------+---------------------------------------+\n| "&" | Bitwise AND |\n+-------------------------------------------------+---------------------------------------+\n| "<<", ">>" | Shifts |\n+-------------------------------------------------+---------------------------------------+\n| "+", "-" | Addition and subtraction |\n+-------------------------------------------------+---------------------------------------+\n| "*", "@", "/", "//", "%" | Multiplication, matrix multiplication |\n| | division, remainder [5] |\n+-------------------------------------------------+---------------------------------------+\n| "+x", "-x", "~x" | Positive, negative, bitwise NOT |\n+-------------------------------------------------+---------------------------------------+\n| "**" | Exponentiation [6] |\n+-------------------------------------------------+---------------------------------------+\n| "await" "x" | Await expression |\n+-------------------------------------------------+---------------------------------------+\n| "x[index]", "x[index:index]", | Subscription, slicing, call, |\n| "x(arguments...)", "x.attribute" | attribute reference |\n+-------------------------------------------------+---------------------------------------+\n| "(expressions...)", "[expressions...]", "{key: | Binding or tuple display, list |\n| value...}", "{expressions...}" | display, dictionary display, set |\n| | display |\n+-------------------------------------------------+---------------------------------------+\n\n-[ Footnotes ]-\n\n[1] While "abs(x%y) < abs(y)" is true mathematically, for floats\n it may not be true numerically due to roundoff. For example, and\n assuming a platform on which a Python float is an IEEE 754 double-\n precision number, in order that "-1e-100 % 1e100" have the same\n sign as "1e100", the computed result is "-1e-100 + 1e100", which\n is numerically exactly equal to "1e100". The function\n "math.fmod()" returns a result whose sign matches the sign of the\n first argument instead, and so returns "-1e-100" in this case.\n Which approach is more appropriate depends on the application.\n\n[2] If x is very close to an exact integer multiple of y, it\'s\n possible for "x//y" to be one larger than "(x-x%y)//y" due to\n rounding. In such cases, Python returns the latter result, in\n order to preserve that "divmod(x,y)[0] * y + x % y" be very close\n to "x".\n\n[3] While comparisons between strings make sense at the byte\n level, they may be counter-intuitive to users. For example, the\n strings ""\\u00C7"" and ""\\u0327\\u0043"" compare differently, even\n though they both represent the same unicode character (LATIN\n CAPITAL LETTER C WITH CEDILLA). To compare strings in a human\n recognizable way, compare using "unicodedata.normalize()".\n\n[4] Due to automatic garbage-collection, free lists, and the\n dynamic nature of descriptors, you may notice seemingly unusual\n behaviour in certain uses of the "is" operator, like those\n involving comparisons between instance methods, or constants.\n Check their documentation for more info.\n\n[5] The "%" operator is also used for string formatting; the same\n precedence applies.\n\n[6] The power operator "**" binds less tightly than an arithmetic\n or bitwise unary operator on its right, that is, "2**-1" is "0.5".\n', 'pass': u'\nThe "pass" statement\n********************\n\n pass_stmt ::= "pass"\n\n"pass" is a null operation --- when it is executed, nothing happens.\nIt is useful as a placeholder when a statement is required\nsyntactically, but no code needs to be executed, for example:\n\n def f(arg): pass # a function that does nothing (yet)\n\n class C: pass # a class with no methods (yet)\n', 'power': u'\nThe power operator\n******************\n\nThe power operator binds more tightly than unary operators on its\nleft; it binds less tightly than unary operators on its right. The\nsyntax is:\n\n power ::= await ["**" u_expr]\n\nThus, in an unparenthesized sequence of power and unary operators, the\noperators are evaluated from right to left (this does not constrain\nthe evaluation order for the operands): "-1**2" results in "-1".\n\nThe power operator has the same semantics as the built-in "pow()"\nfunction, when called with two arguments: it yields its left argument\nraised to the power of its right argument. The numeric arguments are\nfirst converted to a common type, and the result is of that type.\n\nFor int operands, the result has the same type as the operands unless\nthe second argument is negative; in that case, all arguments are\nconverted to float and a float result is delivered. For example,\n"10**2" returns "100", but "10**-2" returns "0.01".\n\nRaising "0.0" to a negative power results in a "ZeroDivisionError".\nRaising a negative number to a fractional power results in a "complex"\nnumber. (In earlier versions it raised a "ValueError".)\n', 'raise': u'\nThe "raise" statement\n*********************\n\n raise_stmt ::= "raise" [expression ["from" expression]]\n\nIf no expressions are present, "raise" re-raises the last exception\nthat was active in the current scope. If no exception is active in\nthe current scope, a "RuntimeError" exception is raised indicating\nthat this is an error.\n\nOtherwise, "raise" evaluates the first expression as the exception\nobject. It must be either a subclass or an instance of\n"BaseException". If it is a class, the exception instance will be\nobtained when needed by instantiating the class with no arguments.\n\nThe *type* of the exception is the exception instance\'s class, the\n*value* is the instance itself.\n\nA traceback object is normally created automatically when an exception\nis raised and attached to it as the "__traceback__" attribute, which\nis writable. You can create an exception and set your own traceback in\none step using the "with_traceback()" exception method (which returns\nthe same exception instance, with its traceback set to its argument),\nlike so:\n\n raise Exception("foo occurred").with_traceback(tracebackobj)\n\nThe "from" clause is used for exception chaining: if given, the second\n*expression* must be another exception class or instance, which will\nthen be attached to the raised exception as the "__cause__" attribute\n(which is writable). If the raised exception is not handled, both\nexceptions will be printed:\n\n >>> try:\n ... print(1 / 0)\n ... except Exception as exc:\n ... raise RuntimeError("Something bad happened") from exc\n ...\n Traceback (most recent call last):\n File "<stdin>", line 2, in <module>\n ZeroDivisionError: int division or modulo by zero\n\n The above exception was the direct cause of the following exception:\n\n Traceback (most recent call last):\n File "<stdin>", line 4, in <module>\n RuntimeError: Something bad happened\n\nA similar mechanism works implicitly if an exception is raised inside\nan exception handler or a "finally" clause: the previous exception is\nthen attached as the new exception\'s "__context__" attribute:\n\n >>> try:\n ... print(1 / 0)\n ... except:\n ... raise RuntimeError("Something bad happened")\n ...\n Traceback (most recent call last):\n File "<stdin>", line 2, in <module>\n ZeroDivisionError: int division or modulo by zero\n\n During handling of the above exception, another exception occurred:\n\n Traceback (most recent call last):\n File "<stdin>", line 4, in <module>\n RuntimeError: Something bad happened\n\nAdditional information on exceptions can be found in section\n*Exceptions*, and information about handling exceptions is in section\n*The try statement*.\n', @@ -66,9 +66,9 @@ topics = {'assert': u'\nThe "assert" statement\n**********************\n\nAssert 'subscriptions': u'\nSubscriptions\n*************\n\nA subscription selects an item of a sequence (string, tuple or list)\nor mapping (dictionary) object:\n\n subscription ::= primary "[" expression_list "]"\n\nThe primary must evaluate to an object that supports subscription\n(lists or dictionaries for example). User-defined objects can support\nsubscription by defining a "__getitem__()" method.\n\nFor built-in objects, there are two types of objects that support\nsubscription:\n\nIf the primary is a mapping, the expression list must evaluate to an\nobject whose value is one of the keys of the mapping, and the\nsubscription selects the value in the mapping that corresponds to that\nkey. (The expression list is a tuple except if it has exactly one\nitem.)\n\nIf the primary is a sequence, the expression (list) must evaluate to\nan integer or a slice (as discussed in the following section).\n\nThe formal syntax makes no special provision for negative indices in\nsequences; however, built-in sequences all provide a "__getitem__()"\nmethod that interprets negative indices by adding the length of the\nsequence to the index (so that "x[-1]" selects the last item of "x").\nThe resulting value must be a nonnegative integer less than the number\nof items in the sequence, and the subscription selects the item whose\nindex is that value (counting from zero). Since the support for\nnegative indices and slicing occurs in the object\'s "__getitem__()"\nmethod, subclasses overriding this method will need to explicitly add\nthat support.\n\nA string\'s items are characters. A character is not a separate data\ntype but a string of exactly one character.\n', 'truth': u'\nTruth Value Testing\n*******************\n\nAny object can be tested for truth value, for use in an "if" or\n"while" condition or as operand of the Boolean operations below. The\nfollowing values are considered false:\n\n* "None"\n\n* "False"\n\n* zero of any numeric type, for example, "0", "0.0", "0j".\n\n* any empty sequence, for example, "\'\'", "()", "[]".\n\n* any empty mapping, for example, "{}".\n\n* instances of user-defined classes, if the class defines a\n "__bool__()" or "__len__()" method, when that method returns the\n integer zero or "bool" value "False". [1]\n\nAll other values are considered true --- so objects of many types are\nalways true.\n\nOperations and built-in functions that have a Boolean result always\nreturn "0" or "False" for false and "1" or "True" for true, unless\notherwise stated. (Important exception: the Boolean operations "or"\nand "and" always return one of their operands.)\n', 'try': u'\nThe "try" statement\n*******************\n\nThe "try" statement specifies exception handlers and/or cleanup code\nfor a group of statements:\n\n try_stmt ::= try1_stmt | try2_stmt\n try1_stmt ::= "try" ":" suite\n ("except" [expression ["as" identifier]] ":" suite)+\n ["else" ":" suite]\n ["finally" ":" suite]\n try2_stmt ::= "try" ":" suite\n "finally" ":" suite\n\nThe "except" clause(s) specify one or more exception handlers. When no\nexception occurs in the "try" clause, no exception handler is\nexecuted. When an exception occurs in the "try" suite, a search for an\nexception handler is started. This search inspects the except clauses\nin turn until one is found that matches the exception. An expression-\nless except clause, if present, must be last; it matches any\nexception. For an except clause with an expression, that expression\nis evaluated, and the clause matches the exception if the resulting\nobject is "compatible" with the exception. An object is compatible\nwith an exception if it is the class or a base class of the exception\nobject or a tuple containing an item compatible with the exception.\n\nIf no except clause matches the exception, the search for an exception\nhandler continues in the surrounding code and on the invocation stack.\n[1]\n\nIf the evaluation of an expression in the header of an except clause\nraises an exception, the original search for a handler is canceled and\na search starts for the new exception in the surrounding code and on\nthe call stack (it is treated as if the entire "try" statement raised\nthe exception).\n\nWhen a matching except clause is found, the exception is assigned to\nthe target specified after the "as" keyword in that except clause, if\npresent, and the except clause\'s suite is executed. All except\nclauses must have an executable block. When the end of this block is\nreached, execution continues normally after the entire try statement.\n(This means that if two nested handlers exist for the same exception,\nand the exception occurs in the try clause of the inner handler, the\nouter handler will not handle the exception.)\n\nWhen an exception has been assigned using "as target", it is cleared\nat the end of the except clause. This is as if\n\n except E as N:\n foo\n\nwas translated to\n\n except E as N:\n try:\n foo\n finally:\n del N\n\nThis means the exception must be assigned to a different name to be\nable to refer to it after the except clause. Exceptions are cleared\nbecause with the traceback attached to them, they form a reference\ncycle with the stack frame, keeping all locals in that frame alive\nuntil the next garbage collection occurs.\n\nBefore an except clause\'s suite is executed, details about the\nexception are stored in the "sys" module and can be accessed via\n"sys.exc_info()". "sys.exc_info()" returns a 3-tuple consisting of the\nexception class, the exception instance and a traceback object (see\nsection *The standard type hierarchy*) identifying the point in the\nprogram where the exception occurred. "sys.exc_info()" values are\nrestored to their previous values (before the call) when returning\nfrom a function that handled an exception.\n\nThe optional "else" clause is executed if and when control flows off\nthe end of the "try" clause. [2] Exceptions in the "else" clause are\nnot handled by the preceding "except" clauses.\n\nIf "finally" is present, it specifies a \'cleanup\' handler. The "try"\nclause is executed, including any "except" and "else" clauses. If an\nexception occurs in any of the clauses and is not handled, the\nexception is temporarily saved. The "finally" clause is executed. If\nthere is a saved exception it is re-raised at the end of the "finally"\nclause. If the "finally" clause raises another exception, the saved\nexception is set as the context of the new exception. If the "finally"\nclause executes a "return" or "break" statement, the saved exception\nis discarded:\n\n >>> def f():\n ... try:\n ... 1/0\n ... finally:\n ... return 42\n ...\n >>> f()\n 42\n\nThe exception information is not available to the program during\nexecution of the "finally" clause.\n\nWhen a "return", "break" or "continue" statement is executed in the\n"try" suite of a "try"..."finally" statement, the "finally" clause is\nalso executed \'on the way out.\' A "continue" statement is illegal in\nthe "finally" clause. (The reason is a problem with the current\nimplementation --- this restriction may be lifted in the future).\n\nThe return value of a function is determined by the last "return"\nstatement executed. Since the "finally" clause always executes, a\n"return" statement executed in the "finally" clause will always be the\nlast one executed:\n\n >>> def foo():\n ... try:\n ... return \'try\'\n ... finally:\n ... return \'finally\'\n ...\n >>> foo()\n \'finally\'\n\nAdditional information on exceptions can be found in section\n*Exceptions*, and information on using the "raise" statement to\ngenerate exceptions may be found in section *The raise statement*.\n', - 'types': u'\nThe standard type hierarchy\n***************************\n\nBelow is a list of the types that are built into Python. Extension\nmodules (written in C, Java, or other languages, depending on the\nimplementation) can define additional types. Future versions of\nPython may add types to the type hierarchy (e.g., rational numbers,\nefficiently stored arrays of integers, etc.), although such additions\nwill often be provided via the standard library instead.\n\nSome of the type descriptions below contain a paragraph listing\n\'special attributes.\' These are attributes that provide access to the\nimplementation and are not intended for general use. Their definition\nmay change in the future.\n\nNone\n This type has a single value. There is a single object with this\n value. This object is accessed through the built-in name "None". It\n is used to signify the absence of a value in many situations, e.g.,\n it is returned from functions that don\'t explicitly return\n anything. Its truth value is false.\n\nNotImplemented\n This type has a single value. There is a single object with this\n value. This object is accessed through the built-in name\n "NotImplemented". Numeric methods and rich comparison methods\n should return this value if they do not implement the operation for\n the operands provided. (The interpreter will then try the\n reflected operation, or some other fallback, depending on the\n operator.) Its truth value is true.\n\n See *Implementing the arithmetic operations* for more details.\n\nEllipsis\n This type has a single value. There is a single object with this\n value. This object is accessed through the literal "..." or the\n built-in name "Ellipsis". Its truth value is true.\n\n"numbers.Number"\n These are created by numeric literals and returned as results by\n arithmetic operators and arithmetic built-in functions. Numeric\n objects are immutable; once created their value never changes.\n Python numbers are of course strongly related to mathematical\n numbers, but subject to the limitations of numerical representation\n in computers.\n\n Python distinguishes between integers, floating point numbers, and\n complex numbers:\n\n "numbers.Integral"\n These represent elements from the mathematical set of integers\n (positive and negative).\n\n There are two types of integers:\n\n Integers ("int")\n\n These represent numbers in an unlimited range, subject to\n available (virtual) memory only. For the purpose of shift\n and mask operations, a binary representation is assumed, and\n negative numbers are represented in a variant of 2\'s\n complement which gives the illusion of an infinite string of\n sign bits extending to the left.\n\n Booleans ("bool")\n These represent the truth values False and True. The two\n objects representing the values "False" and "True" are the\n only Boolean objects. The Boolean type is a subtype of the\n integer type, and Boolean values behave like the values 0 and\n 1, respectively, in almost all contexts, the exception being\n that when converted to a string, the strings ""False"" or\n ""True"" are returned, respectively.\n\n The rules for integer representation are intended to give the\n most meaningful interpretation of shift and mask operations\n involving negative integers.\n\n "numbers.Real" ("float")\n These represent machine-level double precision floating point\n numbers. You are at the mercy of the underlying machine\n architecture (and C or Java implementation) for the accepted\n range and handling of overflow. Python does not support single-\n precision floating point numbers; the savings in processor and\n memory usage that are usually the reason for using these are\n dwarfed by the overhead of using objects in Python, so there is\n no reason to complicate the language with two kinds of floating\n point numbers.\n\n "numbers.Complex" ("complex")\n These represent complex numbers as a pair of machine-level\n double precision floating point numbers. The same caveats apply\n as for floating point numbers. The real and imaginary parts of a\n complex number "z" can be retrieved through the read-only\n attributes "z.real" and "z.imag".\n\nSequences\n These represent finite ordered sets indexed by non-negative\n numbers. The built-in function "len()" returns the number of items\n of a sequence. When the length of a sequence is *n*, the index set\n contains the numbers 0, 1, ..., *n*-1. Item *i* of sequence *a* is\n selected by "a[i]".\n\n Sequences also support slicing: "a[i:j]" selects all items with\n index *k* such that *i* "<=" *k* "<" *j*. When used as an\n expression, a slice is a sequence of the same type. This implies\n that the index set is renumbered so that it starts at 0.\n\n Some sequences also support "extended slicing" with a third "step"\n parameter: "a[i:j:k]" selects all items of *a* with index *x* where\n "x = i + n*k", *n* ">=" "0" and *i* "<=" *x* "<" *j*.\n\n Sequences are distinguished according to their mutability:\n\n Immutable sequences\n An object of an immutable sequence type cannot change once it is\n created. (If the object contains references to other objects,\n these other objects may be mutable and may be changed; however,\n the collection of objects directly referenced by an immutable\n object cannot change.)\n\n The following types are immutable sequences:\n\n Strings\n A string is a sequence of values that represent Unicode code\n points. All the code points in the range "U+0000 - U+10FFFF"\n can be represented in a string. Python doesn\'t have a "char"\n type; instead, every code point in the string is represented\n as a string object with length "1". The built-in function\n "ord()" converts a code point from its string form to an\n integer in the range "0 - 10FFFF"; "chr()" converts an\n integer in the range "0 - 10FFFF" to the corresponding length\n "1" string object. "str.encode()" can be used to convert a\n "str" to "bytes" using the given text encoding, and\n "bytes.decode()" can be used to achieve the opposite.\n\n Tuples\n The items of a tuple are arbitrary Python objects. Tuples of\n two or more items are formed by comma-separated lists of\n expressions. A tuple of one item (a \'singleton\') can be\n formed by affixing a comma to an expression (an expression by\n itself does not create a tuple, since parentheses must be\n usable for grouping of expressions). An empty tuple can be\n formed by an empty pair of parentheses.\n\n Bytes\n A bytes object is an immutable array. The items are 8-bit\n bytes, represented by integers in the range 0 <= x < 256.\n Bytes literals (like "b\'abc\'") and the built-in function\n "bytes()" can be used to construct bytes objects. Also,\n bytes objects can be decoded to strings via the "decode()"\n method.\n\n Mutable sequences\n Mutable sequences can be changed after they are created. The\n subscription and slicing notations can be used as the target of\n assignment and "del" (delete) statements.\n\n There are currently two intrinsic mutable sequence types:\n\n Lists\n The items of a list are arbitrary Python objects. Lists are\n formed by placing a comma-separated list of expressions in\n square brackets. (Note that there are no special cases needed\n to form lists of length 0 or 1.)\n\n Byte Arrays\n A bytearray object is a mutable array. They are created by\n the built-in "bytearray()" constructor. Aside from being\n mutable (and hence unhashable), byte arrays otherwise provide\n the same interface and functionality as immutable bytes\n objects.\n\n The extension module "array" provides an additional example of a\n mutable sequence type, as does the "collections" module.\n\nSet types\n These represent unordered, finite sets of unique, immutable\n objects. As such, they cannot be indexed by any subscript. However,\n they can be iterated over, and the built-in function "len()"\n returns the number of items in a set. Common uses for sets are fast\n membership testing, removing duplicates from a sequence, and\n computing mathematical operations such as intersection, union,\n difference, and symmetric difference.\n\n For set elements, the same immutability rules apply as for\n dictionary keys. Note that numeric types obey the normal rules for\n numeric comparison: if two numbers compare equal (e.g., "1" and\n "1.0"), only one of them can be contained in a set.\n\n There are currently two intrinsic set types:\n\n Sets\n These represent a mutable set. They are created by the built-in\n "set()" constructor and can be modified afterwards by several\n methods, such as "add()".\n\n Frozen sets\n These represent an immutable set. They are created by the\n built-in "frozenset()" constructor. As a frozenset is immutable\n and *hashable*, it can be used again as an element of another\n set, or as a dictionary key.\n\nMappings\n These represent finite sets of objects indexed by arbitrary index\n sets. The subscript notation "a[k]" selects the item indexed by "k"\n from the mapping "a"; this can be used in expressions and as the\n target of assignments or "del" statements. The built-in function\n "len()" returns the number of items in a mapping.\n\n There is currently a single intrinsic mapping type:\n\n Dictionaries\n These represent finite sets of objects indexed by nearly\n arbitrary values. The only types of values not acceptable as\n keys are values containing lists or dictionaries or other\n mutable types that are compared by value rather than by object\n identity, the reason being that the efficient implementation of\n dictionaries requires a key\'s hash value to remain constant.\n Numeric types used for keys obey the normal rules for numeric\n comparison: if two numbers compare equal (e.g., "1" and "1.0")\n then they can be used interchangeably to index the same\n dictionary entry.\n\n Dictionaries are mutable; they can be created by the "{...}"\n notation (see section *Dictionary displays*).\n\n The extension modules "dbm.ndbm" and "dbm.gnu" provide\n additional examples of mapping types, as does the "collections"\n module.\n\nCallable types\n These are the types to which the function call operation (see\n section *Calls*) can be applied:\n\n User-defined functions\n A user-defined function object is created by a function\n definition (see section *Function definitions*). It should be\n called with an argument list containing the same number of items\n as the function\'s formal parameter list.\n\n Special attributes:\n\n +---------------------------+---------------------------------+-------------+\n | Attribute | Meaning | |\n +===========================+=================================+=============+\n | "__doc__" | The function\'s documentation | Writable |\n | | string, or "None" if | |\n | | unavailable; not inherited by | |\n | | subclasses | |\n +---------------------------+---------------------------------+-------------+\n | "__name__" | The function\'s name | Writable |\n +---------------------------+---------------------------------+-------------+\n | "__qualname__" | The function\'s *qualified name* | Writable |\n | | New in version 3.3. | |\n +---------------------------+---------------------------------+-------------+\n | "__module__" | The name of the module the | Writable |\n | | function was defined in, or | |\n | | "None" if unavailable. | |\n +---------------------------+---------------------------------+-------------+\n | "__defaults__" | A tuple containing default | Writable |\n | | argument values for those | |\n | | arguments that have defaults, | |\n | | or "None" if no arguments have | |\n | | a default value | |\n +---------------------------+---------------------------------+-------------+\n | "__code__" | The code object representing | Writable |\n | | the compiled function body. | |\n +---------------------------+---------------------------------+-------------+\n | "__globals__" | A reference to the dictionary | Read-only |\n | | that holds the function\'s | |\n | | global variables --- the global | |\n | | namespace of the module in | |\n | | which the function was defined. | |\n +---------------------------+---------------------------------+-------------+\n | "__dict__" | The namespace supporting | Writable |\n | | arbitrary function attributes. | |\n +---------------------------+---------------------------------+-------------+\n | "__closure__" | "None" or a tuple of cells that | Read-only |\n | | contain bindings for the | |\n | | function\'s free variables. | |\n +---------------------------+---------------------------------+-------------+\n | "__annotations__" | A dict containing annotations | Writable |\n | | of parameters. The keys of the | |\n | | dict are the parameter names, | |\n | | and "\'return\'" for the return | |\n | | annotation, if provided. | |\n +---------------------------+---------------------------------+-------------+\n | "__kwdefaults__" | A dict containing defaults for | Writable |\n | | keyword-only parameters. | |\n +---------------------------+---------------------------------+-------------+\n\n Most of the attributes labelled "Writable" check the type of the\n assigned value.\n\n Function objects also support getting and setting arbitrary\n attributes, which can be used, for example, to attach metadata\n to functions. Regular attribute dot-notation is used to get and\n set such attributes. *Note that the current implementation only\n supports function attributes on user-defined functions. Function\n attributes on built-in functions may be supported in the\n future.*\n\n Additional information about a function\'s definition can be\n retrieved from its code object; see the description of internal\n types below.\n\n Instance methods\n An instance method object combines a class, a class instance and\n any callable object (normally a user-defined function).\n\n Special read-only attributes: "__self__" is the class instance\n object, "__func__" is the function object; "__doc__" is the\n method\'s documentation (same as "__func__.__doc__"); "__name__"\n is the method name (same as "__func__.__name__"); "__module__"\n is the name of the module the method was defined in, or "None"\n if unavailable.\n\n Methods also support accessing (but not setting) the arbitrary\n function attributes on the underlying function object.\n\n User-defined method objects may be created when getting an\n attribute of a class (perhaps via an instance of that class), if\n that attribute is a user-defined function object or a class\n method object.\n\n When an instance method object is created by retrieving a user-\n defined function object from a class via one of its instances,\n its "__self__" attribute is the instance, and the method object\n is said to be bound. The new method\'s "__func__" attribute is\n the original function object.\n\n When a user-defined method object is created by retrieving\n another method object from a class or instance, the behaviour is\n the same as for a function object, except that the "__func__"\n attribute of the new instance is not the original method object\n but its "__func__" attribute.\n\n When an instance method object is created by retrieving a class\n method object from a class or instance, its "__self__" attribute\n is the class itself, and its "__func__" attribute is the\n function object underlying the class method.\n\n When an instance method object is called, the underlying\n function ("__func__") is called, inserting the class instance\n ("__self__") in front of the argument list. For instance, when\n "C" is a class which contains a definition for a function "f()",\n and "x" is an instance of "C", calling "x.f(1)" is equivalent to\n calling "C.f(x, 1)".\n\n When an instance method object is derived from a class method\n object, the "class instance" stored in "__self__" will actually\n be the class itself, so that calling either "x.f(1)" or "C.f(1)"\n is equivalent to calling "f(C,1)" where "f" is the underlying\n function.\n\n Note that the transformation from function object to instance\n method object happens each time the attribute is retrieved from\n the instance. In some cases, a fruitful optimization is to\n assign the attribute to a local variable and call that local\n variable. Also notice that this transformation only happens for\n user-defined functions; other callable objects (and all non-\n callable objects) are retrieved without transformation. It is\n also important to note that user-defined functions which are\n attributes of a class instance are not converted to bound\n methods; this *only* happens when the function is an attribute\n of the class.\n\n Generator functions\n A function or method which uses the "yield" statement (see\n section *The yield statement*) is called a *generator function*.\n Such a function, when called, always returns an iterator object\n which can be used to execute the body of the function: calling\n the iterator\'s "iterator.__next__()" method will cause the\n function to execute until it provides a value using the "yield"\n statement. When the function executes a "return" statement or\n falls off the end, a "StopIteration" exception is raised and the\n iterator will have reached the end of the set of values to be\n returned.\n\n Coroutine functions\n A function or method which is defined using "async def" is\n called a *coroutine function*. Such a function, when called,\n returns a *coroutine* object. It may contain "await"\n expressions, as well as "async with" and "async for" statements.\n See also the *Coroutine Objects* section.\n\n Built-in functions\n A built-in function object is a wrapper around a C function.\n Examples of built-in functions are "len()" and "math.sin()"\n ("math" is a standard built-in module). The number and type of\n the arguments are determined by the C function. Special read-\n only attributes: "__doc__" is the function\'s documentation\n string, or "None" if unavailable; "__name__" is the function\'s\n name; "__self__" is set to "None" (but see the next item);\n "__module__" is the name of the module the function was defined\n in or "None" if unavailable.\n\n Built-in methods\n This is really a different disguise of a built-in function, this\n time containing an object passed to the C function as an\n implicit extra argument. An example of a built-in method is\n "alist.append()", assuming *alist* is a list object. In this\n case, the special read-only attribute "__self__" is set to the\n object denoted by *alist*.\n\n Classes\n Classes are callable. These objects normally act as factories\n for new instances of themselves, but variations are possible for\n class types that override "__new__()". The arguments of the\n call are passed to "__new__()" and, in the typical case, to\n "__init__()" to initialize the new instance.\n\n Class Instances\n Instances of arbitrary classes can be made callable by defining\n a "__call__()" method in their class.\n\nModules\n Modules are a basic organizational unit of Python code, and are\n created by the *import system* as invoked either by the "import"\n statement (see "import"), or by calling functions such as\n "importlib.import_module()" and built-in "__import__()". A module\n object has a namespace implemented by a dictionary object (this is\n the dictionary referenced by the "__globals__" attribute of\n functions defined in the module). Attribute references are\n translated to lookups in this dictionary, e.g., "m.x" is equivalent\n to "m.__dict__["x"]". A module object does not contain the code\n object used to initialize the module (since it isn\'t needed once\n the initialization is done).\n\n Attribute assignment updates the module\'s namespace dictionary,\n e.g., "m.x = 1" is equivalent to "m.__dict__["x"] = 1".\n\n Special read-only attribute: "__dict__" is the module\'s namespace\n as a dictionary object.\n\n **CPython implementation detail:** Because of the way CPython\n clears module dictionaries, the module dictionary will be cleared\n when the module falls out of scope even if the dictionary still has\n live references. To avoid this, copy the dictionary or keep the\n module around while using its dictionary directly.\n\n Predefined (writable) attributes: "__name__" is the module\'s name;\n "__doc__" is the module\'s documentation string, or "None" if\n unavailable; "__file__" is the pathname of the file from which the\n module was loaded, if it was loaded from a file. The "__file__"\n attribute may be missing for certain types of modules, such as C\n modules that are statically linked into the interpreter; for\n extension modules loaded dynamically from a shared library, it is\n the pathname of the shared library file.\n\nCustom classes\n Custom class types are typically created by class definitions (see\n section *Class definitions*). A class has a namespace implemented\n by a dictionary object. Class attribute references are translated\n to lookups in this dictionary, e.g., "C.x" is translated to\n "C.__dict__["x"]" (although there are a number of hooks which allow\n for other means of locating attributes). When the attribute name is\n not found there, the attribute search continues in the base\n classes. This search of the base classes uses the C3 method\n resolution order which behaves correctly even in the presence of\n \'diamond\' inheritance structures where there are multiple\n inheritance paths leading back to a common ancestor. Additional\n details on the C3 MRO used by Python can be found in the\n documentation accompanying the 2.3 release at\n https://www.python.org/download/releases/2.3/mro/.\n\n When a class attribute reference (for class "C", say) would yield a\n class method object, it is transformed into an instance method\n object whose "__self__" attributes is "C". When it would yield a\n static method object, it is transformed into the object wrapped by\n the static method object. See section *Implementing Descriptors*\n for another way in which attributes retrieved from a class may\n differ from those actually contained in its "__dict__".\n\n Class attribute assignments update the class\'s dictionary, never\n the dictionary of a base class.\n\n A class object can be called (see above) to yield a class instance\n (see below).\n\n Special attributes: "__name__" is the class name; "__module__" is\n the module name in which the class was defined; "__dict__" is the\n dictionary containing the class\'s namespace; "__bases__" is a tuple\n (possibly empty or a singleton) containing the base classes, in the\n order of their occurrence in the base class list; "__doc__" is the\n class\'s documentation string, or None if undefined.\n\nClass instances\n A class instance is created by calling a class object (see above).\n A class instance has a namespace implemented as a dictionary which\n is the first place in which attribute references are searched.\n When an attribute is not found there, and the instance\'s class has\n an attribute by that name, the search continues with the class\n attributes. If a class attribute is found that is a user-defined\n function object, it is transformed into an instance method object\n whose "__self__" attribute is the instance. Static method and\n class method objects are also transformed; see above under\n "Classes". See section *Implementing Descriptors* for another way\n in which attributes of a class retrieved via its instances may\n differ from the objects actually stored in the class\'s "__dict__".\n If no class attribute is found, and the object\'s class has a\n "__getattr__()" method, that is called to satisfy the lookup.\n\n Attribute assignments and deletions update the instance\'s\n dictionary, never a class\'s dictionary. If the class has a\n "__setattr__()" or "__delattr__()" method, this is called instead\n of updating the instance dictionary directly.\n\n Class instances can pretend to be numbers, sequences, or mappings\n if they have methods with certain special names. See section\n *Special method names*.\n\n Special attributes: "__dict__" is the attribute dictionary;\n "__class__" is the instance\'s class.\n\nI/O objects (also known as file objects)\n A *file object* represents an open file. Various shortcuts are\n available to create file objects: the "open()" built-in function,\n and also "os.popen()", "os.fdopen()", and the "makefile()" method\n of socket objects (and perhaps by other functions or methods\n provided by extension modules).\n\n The objects "sys.stdin", "sys.stdout" and "sys.stderr" are\n initialized to file objects corresponding to the interpreter\'s\n standard input, output and error streams; they are all open in text\n mode and therefore follow the interface defined by the\n "io.TextIOBase" abstract class.\n\nInternal types\n A few types used internally by the interpreter are exposed to the\n user. Their definitions may change with future versions of the\n interpreter, but they are mentioned here for completeness.\n\n Code objects\n Code objects represent *byte-compiled* executable Python code,\n or *bytecode*. The difference between a code object and a\n function object is that the function object contains an explicit\n reference to the function\'s globals (the module in which it was\n defined), while a code object contains no context; also the\n default argument values are stored in the function object, not\n in the code object (because they represent values calculated at\n run-time). Unlike function objects, code objects are immutable\n and contain no references (directly or indirectly) to mutable\n objects.\n\n Special read-only attributes: "co_name" gives the function name;\n "co_argcount" is the number of positional arguments (including\n arguments with default values); "co_nlocals" is the number of\n local variables used by the function (including arguments);\n "co_varnames" is a tuple containing the names of the local\n variables (starting with the argument names); "co_cellvars" is a\n tuple containing the names of local variables that are\n referenced by nested functions; "co_freevars" is a tuple\n containing the names of free variables; "co_code" is a string\n representing the sequence of bytecode instructions; "co_consts"\n is a tuple containing the literals used by the bytecode;\n "co_names" is a tuple containing the names used by the bytecode;\n "co_filename" is the filename from which the code was compiled;\n "co_firstlineno" is the first line number of the function;\n "co_lnotab" is a string encoding the mapping from bytecode\n offsets to line numbers (for details see the source code of the\n interpreter); "co_stacksize" is the required stack size\n (including local variables); "co_flags" is an integer encoding a\n number of flags for the interpreter.\n\n The following flag bits are defined for "co_flags": bit "0x04"\n is set if the function uses the "*arguments" syntax to accept an\n arbitrary number of positional arguments; bit "0x08" is set if\n the function uses the "**keywords" syntax to accept arbitrary\n keyword arguments; bit "0x20" is set if the function is a\n generator.\n\n Future feature declarations ("from __future__ import division")\n also use bits in "co_flags" to indicate whether a code object\n was compiled with a particular feature enabled: bit "0x2000" is\n set if the function was compiled with future division enabled;\n bits "0x10" and "0x1000" were used in earlier versions of\n Python.\n\n Other bits in "co_flags" are reserved for internal use.\n\n If a code object represents a function, the first item in\n "co_consts" is the documentation string of the function, or\n "None" if undefined.\n\n Frame objects\n Frame objects represent execution frames. They may occur in\n traceback objects (see below).\n\n Special read-only attributes: "f_back" is to the previous stack\n frame (towards the caller), or "None" if this is the bottom\n stack frame; "f_code" is the code object being executed in this\n frame; "f_locals" is the dictionary used to look up local\n variables; "f_globals" is used for global variables;\n "f_builtins" is used for built-in (intrinsic) names; "f_lasti"\n gives the precise instruction (this is an index into the\n bytecode string of the code object).\n\n Special writable attributes: "f_trace", if not "None", is a\n function called at the start of each source code line (this is\n used by the debugger); "f_lineno" is the current line number of\n the frame --- writing to this from within a trace function jumps\n to the given line (only for the bottom-most frame). A debugger\n can implement a Jump command (aka Set Next Statement) by writing\n to f_lineno.\n\n Frame objects support one method:\n\n frame.clear()\n\n This method clears all references to local variables held by\n the frame. Also, if the frame belonged to a generator, the\n generator is finalized. This helps break reference cycles\n involving frame objects (for example when catching an\n exception and storing its traceback for later use).\n\n "RuntimeError" is raised if the frame is currently executing.\n\n New in version 3.4.\n\n Traceback objects\n Traceback objects represent a stack trace of an exception. A\n traceback object is created when an exception occurs. When the\n search for an exception handler unwinds the execution stack, at\n each unwound level a traceback object is inserted in front of\n the current traceback. When an exception handler is entered,\n the stack trace is made available to the program. (See section\n *The try statement*.) It is accessible as the third item of the\n tuple returned by "sys.exc_info()". When the program contains no\n suitable handler, the stack trace is written (nicely formatted)\n to the standard error stream; if the interpreter is interactive,\n it is also made available to the user as "sys.last_traceback".\n\n Special read-only attributes: "tb_next" is the next level in the\n stack trace (towards the frame where the exception occurred), or\n "None" if there is no next level; "tb_frame" points to the\n execution frame of the current level; "tb_lineno" gives the line\n number where the exception occurred; "tb_lasti" indicates the\n precise instruction. The line number and last instruction in\n the traceback may differ from the line number of its frame\n object if the exception occurred in a "try" statement with no\n matching except clause or with a finally clause.\n\n Slice objects\n Slice objects are used to represent slices for "__getitem__()"\n methods. They are also created by the built-in "slice()"\n function.\n\n Special read-only attributes: "start" is the lower bound; "stop"\n is the upper bound; "step" is the step value; each is "None" if\n omitted. These attributes can have any type.\n\n Slice objects support one method:\n\n slice.indices(self, length)\n\n This method takes a single integer argument *length* and\n computes information about the slice that the slice object\n would describe if applied to a sequence of *length* items.\n It returns a tuple of three integers; respectively these are\n the *start* and *stop* indices and the *step* or stride\n length of the slice. Missing or out-of-bounds indices are\n handled in a manner consistent with regular slices.\n\n Static method objects\n Static method objects provide a way of defeating the\n transformation of function objects to method objects described\n above. A static method object is a wrapper around any other\n object, usually a user-defined method object. When a static\n method object is retrieved from a class or a class instance, the\n object actually returned is the wrapped object, which is not\n subject to any further transformation. Static method objects are\n not themselves callable, although the objects they wrap usually\n are. Static method objects are created by the built-in\n "staticmethod()" constructor.\n\n Class method objects\n A class method object, like a static method object, is a wrapper\n around another object that alters the way in which that object\n is retrieved from classes and class instances. The behaviour of\n class method objects upon such retrieval is described above,\n under "User-defined methods". Class method objects are created\n by the built-in "classmethod()" constructor.\n', + 'types': u'\nThe standard type hierarchy\n***************************\n\nBelow is a list of the types that are built into Python. Extension\nmodules (written in C, Java, or other languages, depending on the\nimplementation) can define additional types. Future versions of\nPython may add types to the type hierarchy (e.g., rational numbers,\nefficiently stored arrays of integers, etc.), although such additions\nwill often be provided via the standard library instead.\n\nSome of the type descriptions below contain a paragraph listing\n\'special attributes.\' These are attributes that provide access to the\nimplementation and are not intended for general use. Their definition\nmay change in the future.\n\nNone\n This type has a single value. There is a single object with this\n value. This object is accessed through the built-in name "None". It\n is used to signify the absence of a value in many situations, e.g.,\n it is returned from functions that don\'t explicitly return\n anything. Its truth value is false.\n\nNotImplemented\n This type has a single value. There is a single object with this\n value. This object is accessed through the built-in name\n "NotImplemented". Numeric methods and rich comparison methods\n should return this value if they do not implement the operation for\n the operands provided. (The interpreter will then try the\n reflected operation, or some other fallback, depending on the\n operator.) Its truth value is true.\n\n See *Implementing the arithmetic operations* for more details.\n\nEllipsis\n This type has a single value. There is a single object with this\n value. This object is accessed through the literal "..." or the\n built-in name "Ellipsis". Its truth value is true.\n\n"numbers.Number"\n These are created by numeric literals and returned as results by\n arithmetic operators and arithmetic built-in functions. Numeric\n objects are immutable; once created their value never changes.\n Python numbers are of course strongly related to mathematical\n numbers, but subject to the limitations of numerical representation\n in computers.\n\n Python distinguishes between integers, floating point numbers, and\n complex numbers:\n\n "numbers.Integral"\n These represent elements from the mathematical set of integers\n (positive and negative).\n\n There are two types of integers:\n\n Integers ("int")\n\n These represent numbers in an unlimited range, subject to\n available (virtual) memory only. For the purpose of shift\n and mask operations, a binary representation is assumed, and\n negative numbers are represented in a variant of 2\'s\n complement which gives the illusion of an infinite string of\n sign bits extending to the left.\n\n Booleans ("bool")\n These represent the truth values False and True. The two\n objects representing the values "False" and "True" are the\n only Boolean objects. The Boolean type is a subtype of the\n integer type, and Boolean values behave like the values 0 and\n 1, respectively, in almost all contexts, the exception being\n that when converted to a string, the strings ""False"" or\n ""True"" are returned, respectively.\n\n The rules for integer representation are intended to give the\n most meaningful interpretation of shift and mask operations\n involving negative integers.\n\n "numbers.Real" ("float")\n These represent machine-level double precision floating point\n numbers. You are at the mercy of the underlying machine\n architecture (and C or Java implementation) for the accepted\n range and handling of overflow. Python does not support single-\n precision floating point numbers; the savings in processor and\n memory usage that are usually the reason for using these are\n dwarfed by the overhead of using objects in Python, so there is\n no reason to complicate the language with two kinds of floating\n point numbers.\n\n "numbers.Complex" ("complex")\n These represent complex numbers as a pair of machine-level\n double precision floating point numbers. The same caveats apply\n as for floating point numbers. The real and imaginary parts of a\n complex number "z" can be retrieved through the read-only\n attributes "z.real" and "z.imag".\n\nSequences\n These represent finite ordered sets indexed by non-negative\n numbers. The built-in function "len()" returns the number of items\n of a sequence. When the length of a sequence is *n*, the index set\n contains the numbers 0, 1, ..., *n*-1. Item *i* of sequence *a* is\n selected by "a[i]".\n\n Sequences also support slicing: "a[i:j]" selects all items with\n index *k* such that *i* "<=" *k* "<" *j*. When used as an\n expression, a slice is a sequence of the same type. This implies\n that the index set is renumbered so that it starts at 0.\n\n Some sequences also support "extended slicing" with a third "step"\n parameter: "a[i:j:k]" selects all items of *a* with index *x* where\n "x = i + n*k", *n* ">=" "0" and *i* "<=" *x* "<" *j*.\n\n Sequences are distinguished according to their mutability:\n\n Immutable sequences\n An object of an immutable sequence type cannot change once it is\n created. (If the object contains references to other objects,\n these other objects may be mutable and may be changed; however,\n the collection of objects directly referenced by an immutable\n object cannot change.)\n\n The following types are immutable sequences:\n\n Strings\n A string is a sequence of values that represent Unicode code\n points. All the code points in the range "U+0000 - U+10FFFF"\n can be represented in a string. Python doesn\'t have a "char"\n type; instead, every code point in the string is represented\n as a string object with length "1". The built-in function\n "ord()" converts a code point from its string form to an\n integer in the range "0 - 10FFFF"; "chr()" converts an\n integer in the range "0 - 10FFFF" to the corresponding length\n "1" string object. "str.encode()" can be used to convert a\n "str" to "bytes" using the given text encoding, and\n "bytes.decode()" can be used to achieve the opposite.\n\n Tuples\n The items of a tuple are arbitrary Python objects. Tuples of\n two or more items are formed by comma-separated lists of\n expressions. A tuple of one item (a \'singleton\') can be\n formed by affixing a comma to an expression (an expression by\n itself does not create a tuple, since parentheses must be\n usable for grouping of expressions). An empty tuple can be\n formed by an empty pair of parentheses.\n\n Bytes\n A bytes object is an immutable array. The items are 8-bit\n bytes, represented by integers in the range 0 <= x < 256.\n Bytes literals (like "b\'abc\'") and the built-in function\n "bytes()" can be used to construct bytes objects. Also,\n bytes objects can be decoded to strings via the "decode()"\n method.\n\n Mutable sequences\n Mutable sequences can be changed after they are created. The\n subscription and slicing notations can be used as the target of\n assignment and "del" (delete) statements.\n\n There are currently two intrinsic mutable sequence types:\n\n Lists\n The items of a list are arbitrary Python objects. Lists are\n formed by placing a comma-separated list of expressions in\n square brackets. (Note that there are no special cases needed\n to form lists of length 0 or 1.)\n\n Byte Arrays\n A bytearray object is a mutable array. They are created by\n the built-in "bytearray()" constructor. Aside from being\n mutable (and hence unhashable), byte arrays otherwise provide\n the same interface and functionality as immutable bytes\n objects.\n\n The extension module "array" provides an additional example of a\n mutable sequence type, as does the "collections" module.\n\nSet types\n These represent unordered, finite sets of unique, immutable\n objects. As such, they cannot be indexed by any subscript. However,\n they can be iterated over, and the built-in function "len()"\n returns the number of items in a set. Common uses for sets are fast\n membership testing, removing duplicates from a sequence, and\n computing mathematical operations such as intersection, union,\n difference, and symmetric difference.\n\n For set elements, the same immutability rules apply as for\n dictionary keys. Note that numeric types obey the normal rules for\n numeric comparison: if two numbers compare equal (e.g., "1" and\n "1.0"), only one of them can be contained in a set.\n\n There are currently two intrinsic set types:\n\n Sets\n These represent a mutable set. They are created by the built-in\n "set()" constructor and can be modified afterwards by several\n methods, such as "add()".\n\n Frozen sets\n These represent an immutable set. They are created by the\n built-in "frozenset()" constructor. As a frozenset is immutable\n and *hashable*, it can be used again as an element of another\n set, or as a dictionary key.\n\nMappings\n These represent finite sets of objects indexed by arbitrary index\n sets. The subscript notation "a[k]" selects the item indexed by "k"\n from the mapping "a"; this can be used in expressions and as the\n target of assignments or "del" statements. The built-in function\n "len()" returns the number of items in a mapping.\n\n There is currently a single intrinsic mapping type:\n\n Dictionaries\n These represent finite sets of objects indexed by nearly\n arbitrary values. The only types of values not acceptable as\n keys are values containing lists or dictionaries or other\n mutable types that are compared by value rather than by object\n identity, the reason being that the efficient implementation of\n dictionaries requires a key\'s hash value to remain constant.\n Numeric types used for keys obey the normal rules for numeric\n comparison: if two numbers compare equal (e.g., "1" and "1.0")\n then they can be used interchangeably to index the same\n dictionary entry.\n\n Dictionaries are mutable; they can be created by the "{...}"\n notation (see section *Dictionary displays*).\n\n The extension modules "dbm.ndbm" and "dbm.gnu" provide\n additional examples of mapping types, as does the "collections"\n module.\n\nCallable types\n These are the types to which the function call operation (see\n section *Calls*) can be applied:\n\n User-defined functions\n A user-defined function object is created by a function\n definition (see section *Function definitions*). It should be\n called with an argument list containing the same number of items\n as the function\'s formal parameter list.\n\n Special attributes:\n\n +---------------------------+---------------------------------+-------------+\n | Attribute | Meaning | |\n +===========================+=================================+=============+\n | "__doc__" | The function\'s documentation | Writable |\n | | string, or "None" if | |\n | | unavailable; not inherited by | |\n | | subclasses | |\n +---------------------------+---------------------------------+-------------+\n | "__name__" | The function\'s name | Writable |\n +---------------------------+---------------------------------+-------------+\n | "__qualname__" | The function\'s *qualified name* | Writable |\n | | New in version 3.3. | |\n +---------------------------+---------------------------------+-------------+\n | "__module__" | The name of the module the | Writable |\n | | function was defined in, or | |\n | | "None" if unavailable. | |\n +---------------------------+---------------------------------+-------------+\n | "__defaults__" | A tuple containing default | Writable |\n | | argument values for those | |\n | | arguments that have defaults, | |\n | | or "None" if no arguments have | |\n | | a default value | |\n +---------------------------+---------------------------------+-------------+\n | "__code__" | The code object representing | Writable |\n | | the compiled function body. | |\n +---------------------------+---------------------------------+-------------+\n | "__globals__" | A reference to the dictionary | Read-only |\n | | that holds the function\'s | |\n | | global variables --- the global | |\n | | namespace of the module in | |\n | | which the function was defined. | |\n +---------------------------+---------------------------------+-------------+\n | "__dict__" | The namespace supporting | Writable |\n | | arbitrary function attributes. | |\n +---------------------------+---------------------------------+-------------+\n | "__closure__" | "None" or a tuple of cells that | Read-only |\n | | contain bindings for the | |\n | | function\'s free variables. | |\n +---------------------------+---------------------------------+-------------+\n | "__annotations__" | A dict containing annotations | Writable |\n | | of parameters. The keys of the | |\n | | dict are the parameter names, | |\n | | and "\'return\'" for the return | |\n | | annotation, if provided. | |\n +---------------------------+---------------------------------+-------------+\n | "__kwdefaults__" | A dict containing defaults for | Writable |\n | | keyword-only parameters. | |\n +---------------------------+---------------------------------+-------------+\n\n Most of the attributes labelled "Writable" check the type of the\n assigned value.\n\n Function objects also support getting and setting arbitrary\n attributes, which can be used, for example, to attach metadata\n to functions. Regular attribute dot-notation is used to get and\n set such attributes. *Note that the current implementation only\n supports function attributes on user-defined functions. Function\n attributes on built-in functions may be supported in the\n future.*\n\n Additional information about a function\'s definition can be\n retrieved from its code object; see the description of internal\n types below.\n\n Instance methods\n An instance method object combines a class, a class instance and\n any callable object (normally a user-defined function).\n\n Special read-only attributes: "__self__" is the class instance\n object, "__func__" is the function object; "__doc__" is the\n method\'s documentation (same as "__func__.__doc__"); "__name__"\n is the method name (same as "__func__.__name__"); "__module__"\n is the name of the module the method was defined in, or "None"\n if unavailable.\n\n Methods also support accessing (but not setting) the arbitrary\n function attributes on the underlying function object.\n\n User-defined method objects may be created when getting an\n attribute of a class (perhaps via an instance of that class), if\n that attribute is a user-defined function object or a class\n method object.\n\n When an instance method object is created by retrieving a user-\n defined function object from a class via one of its instances,\n its "__self__" attribute is the instance, and the method object\n is said to be bound. The new method\'s "__func__" attribute is\n the original function object.\n\n When a user-defined method object is created by retrieving\n another method object from a class or instance, the behaviour is\n the same as for a function object, except that the "__func__"\n attribute of the new instance is not the original method object\n but its "__func__" attribute.\n\n When an instance method object is created by retrieving a class\n method object from a class or instance, its "__self__" attribute\n is the class itself, and its "__func__" attribute is the\n function object underlying the class method.\n\n When an instance method object is called, the underlying\n function ("__func__") is called, inserting the class instance\n ("__self__") in front of the argument list. For instance, when\n "C" is a class which contains a definition for a function "f()",\n and "x" is an instance of "C", calling "x.f(1)" is equivalent to\n calling "C.f(x, 1)".\n\n When an instance method object is derived from a class method\n object, the "class instance" stored in "__self__" will actually\n be the class itself, so that calling either "x.f(1)" or "C.f(1)"\n is equivalent to calling "f(C,1)" where "f" is the underlying\n function.\n\n Note that the transformation from function object to instance\n method object happens each time the attribute is retrieved from\n the instance. In some cases, a fruitful optimization is to\n assign the attribute to a local variable and call that local\n variable. Also notice that this transformation only happens for\n user-defined functions; other callable objects (and all non-\n callable objects) are retrieved without transformation. It is\n also important to note that user-defined functions which are\n attributes of a class instance are not converted to bound\n methods; this *only* happens when the function is an attribute\n of the class.\n\n Generator functions\n A function or method which uses the "yield" statement (see\n section *The yield statement*) is called a *generator function*.\n Such a function, when called, always returns an iterator object\n which can be used to execute the body of the function: calling\n the iterator\'s "iterator.__next__()" method will cause the\n function to execute until it provides a value using the "yield"\n statement. When the function executes a "return" statement or\n falls off the end, a "StopIteration" exception is raised and the\n iterator will have reached the end of the set of values to be\n returned.\n\n Coroutine functions\n A function or method which is defined using "async def" is\n called a *coroutine function*. Such a function, when called,\n returns a *coroutine* object. It may contain "await"\n expressions, as well as "async with" and "async for" statements.\n See also *Coroutines* section.\n\n Built-in functions\n A built-in function object is a wrapper around a C function.\n Examples of built-in functions are "len()" and "math.sin()"\n ("math" is a standard built-in module). The number and type of\n the arguments are determined by the C function. Special read-\n only attributes: "__doc__" is the function\'s documentation\n string, or "None" if unavailable; "__name__" is the function\'s\n name; "__self__" is set to "None" (but see the next item);\n "__module__" is the name of the module the function was defined\n in or "None" if unavailable.\n\n Built-in methods\n This is really a different disguise of a built-in function, this\n time containing an object passed to the C function as an\n implicit extra argument. An example of a built-in method is\n "alist.append()", assuming *alist* is a list object. In this\n case, the special read-only attribute "__self__" is set to the\n object denoted by *alist*.\n\n Classes\n Classes are callable. These objects normally act as factories\n for new instances of themselves, but variations are possible for\n class types that override "__new__()". The arguments of the\n call are passed to "__new__()" and, in the typical case, to\n "__init__()" to initialize the new instance.\n\n Class Instances\n Instances of arbitrary classes can be made callable by defining\n a "__call__()" method in their class.\n\nModules\n Modules are a basic organizational unit of Python code, and are\n created by the *import system* as invoked either by the "import"\n statement (see "import"), or by calling functions such as\n "importlib.import_module()" and built-in "__import__()". A module\n object has a namespace implemented by a dictionary object (this is\n the dictionary referenced by the "__globals__" attribute of\n functions defined in the module). Attribute references are\n translated to lookups in this dictionary, e.g., "m.x" is equivalent\n to "m.__dict__["x"]". A module object does not contain the code\n object used to initialize the module (since it isn\'t needed once\n the initialization is done).\n\n Attribute assignment updates the module\'s namespace dictionary,\n e.g., "m.x = 1" is equivalent to "m.__dict__["x"] = 1".\n\n Special read-only attribute: "__dict__" is the module\'s namespace\n as a dictionary object.\n\n **CPython implementation detail:** Because of the way CPython\n clears module dictionaries, the module dictionary will be cleared\n when the module falls out of scope even if the dictionary still has\n live references. To avoid this, copy the dictionary or keep the\n module around while using its dictionary directly.\n\n Predefined (writable) attributes: "__name__" is the module\'s name;\n "__doc__" is the module\'s documentation string, or "None" if\n unavailable; "__file__" is the pathname of the file from which the\n module was loaded, if it was loaded from a file. The "__file__"\n attribute may be missing for certain types of modules, such as C\n modules that are statically linked into the interpreter; for\n extension modules loaded dynamically from a shared library, it is\n the pathname of the shared library file.\n\nCustom classes\n Custom class types are typically created by class definitions (see\n section *Class definitions*). A class has a namespace implemented\n by a dictionary object. Class attribute references are translated\n to lookups in this dictionary, e.g., "C.x" is translated to\n "C.__dict__["x"]" (although there are a number of hooks which allow\n for other means of locating attributes). When the attribute name is\n not found there, the attribute search continues in the base\n classes. This search of the base classes uses the C3 method\n resolution order which behaves correctly even in the presence of\n \'diamond\' inheritance structures where there are multiple\n inheritance paths leading back to a common ancestor. Additional\n details on the C3 MRO used by Python can be found in the\n documentation accompanying the 2.3 release at\n https://www.python.org/download/releases/2.3/mro/.\n\n When a class attribute reference (for class "C", say) would yield a\n class method object, it is transformed into an instance method\n object whose "__self__" attributes is "C". When it would yield a\n static method object, it is transformed into the object wrapped by\n the static method object. See section *Implementing Descriptors*\n for another way in which attributes retrieved from a class may\n differ from those actually contained in its "__dict__".\n\n Class attribute assignments update the class\'s dictionary, never\n the dictionary of a base class.\n\n A class object can be called (see above) to yield a class instance\n (see below).\n\n Special attributes: "__name__" is the class name; "__module__" is\n the module name in which the class was defined; "__dict__" is the\n dictionary containing the class\'s namespace; "__bases__" is a tuple\n (possibly empty or a singleton) containing the base classes, in the\n order of their occurrence in the base class list; "__doc__" is the\n class\'s documentation string, or None if undefined.\n\nClass instances\n A class instance is created by calling a class object (see above).\n A class instance has a namespace implemented as a dictionary which\n is the first place in which attribute references are searched.\n When an attribute is not found there, and the instance\'s class has\n an attribute by that name, the search continues with the class\n attributes. If a class attribute is found that is a user-defined\n function object, it is transformed into an instance method object\n whose "__self__" attribute is the instance. Static method and\n class method objects are also transformed; see above under\n "Classes". See section *Implementing Descriptors* for another way\n in which attributes of a class retrieved via its instances may\n differ from the objects actually stored in the class\'s "__dict__".\n If no class attribute is found, and the object\'s class has a\n "__getattr__()" method, that is called to satisfy the lookup.\n\n Attribute assignments and deletions update the instance\'s\n dictionary, never a class\'s dictionary. If the class has a\n "__setattr__()" or "__delattr__()" method, this is called instead\n of updating the instance dictionary directly.\n\n Class instances can pretend to be numbers, sequences, or mappings\n if they have methods with certain special names. See section\n *Special method names*.\n\n Special attributes: "__dict__" is the attribute dictionary;\n "__class__" is the instance\'s class.\n\nI/O objects (also known as file objects)\n A *file object* represents an open file. Various shortcuts are\n available to create file objects: the "open()" built-in function,\n and also "os.popen()", "os.fdopen()", and the "makefile()" method\n of socket objects (and perhaps by other functions or methods\n provided by extension modules).\n\n The objects "sys.stdin", "sys.stdout" and "sys.stderr" are\n initialized to file objects corresponding to the interpreter\'s\n standard input, output and error streams; they are all open in text\n mode and therefore follow the interface defined by the\n "io.TextIOBase" abstract class.\n\nInternal types\n A few types used internally by the interpreter are exposed to the\n user. Their definitions may change with future versions of the\n interpreter, but they are mentioned here for completeness.\n\n Code objects\n Code objects represent *byte-compiled* executable Python code,\n or *bytecode*. The difference between a code object and a\n function object is that the function object contains an explicit\n reference to the function\'s globals (the module in which it was\n defined), while a code object contains no context; also the\n default argument values are stored in the function object, not\n in the code object (because they represent values calculated at\n run-time). Unlike function objects, code objects are immutable\n and contain no references (directly or indirectly) to mutable\n objects.\n\n Special read-only attributes: "co_name" gives the function name;\n "co_argcount" is the number of positional arguments (including\n arguments with default values); "co_nlocals" is the number of\n local variables used by the function (including arguments);\n "co_varnames" is a tuple containing the names of the local\n variables (starting with the argument names); "co_cellvars" is a\n tuple containing the names of local variables that are\n referenced by nested functions; "co_freevars" is a tuple\n containing the names of free variables; "co_code" is a string\n representing the sequence of bytecode instructions; "co_consts"\n is a tuple containing the literals used by the bytecode;\n "co_names" is a tuple containing the names used by the bytecode;\n "co_filename" is the filename from which the code was compiled;\n "co_firstlineno" is the first line number of the function;\n "co_lnotab" is a string encoding the mapping from bytecode\n offsets to line numbers (for details see the source code of the\n interpreter); "co_stacksize" is the required stack size\n (including local variables); "co_flags" is an integer encoding a\n number of flags for the interpreter.\n\n The following flag bits are defined for "co_flags": bit "0x04"\n is set if the function uses the "*arguments" syntax to accept an\n arbitrary number of positional arguments; bit "0x08" is set if\n the function uses the "**keywords" syntax to accept arbitrary\n keyword arguments; bit "0x20" is set if the function is a\n generator.\n\n Future feature declarations ("from __future__ import division")\n also use bits in "co_flags" to indicate whether a code object\n was compiled with a particular feature enabled: bit "0x2000" is\n set if the function was compiled with future division enabled;\n bits "0x10" and "0x1000" were used in earlier versions of\n Python.\n\n Other bits in "co_flags" are reserved for internal use.\n\n If a code object represents a function, the first item in\n "co_consts" is the documentation string of the function, or\n "None" if undefined.\n\n Frame objects\n Frame objects represent execution frames. They may occur in\n traceback objects (see below).\n\n Special read-only attributes: "f_back" is to the previous stack\n frame (towards the caller), or "None" if this is the bottom\n stack frame; "f_code" is the code object being executed in this\n frame; "f_locals" is the dictionary used to look up local\n variables; "f_globals" is used for global variables;\n "f_builtins" is used for built-in (intrinsic) names; "f_lasti"\n gives the precise instruction (this is an index into the\n bytecode string of the code object).\n\n Special writable attributes: "f_trace", if not "None", is a\n function called at the start of each source code line (this is\n used by the debugger); "f_lineno" is the current line number of\n the frame --- writing to this from within a trace function jumps\n to the given line (only for the bottom-most frame). A debugger\n can implement a Jump command (aka Set Next Statement) by writing\n to f_lineno.\n\n Frame objects support one method:\n\n frame.clear()\n\n This method clears all references to local variables held by\n the frame. Also, if the frame belonged to a generator, the\n generator is finalized. This helps break reference cycles\n involving frame objects (for example when catching an\n exception and storing its traceback for later use).\n\n "RuntimeError" is raised if the frame is currently executing.\n\n New in version 3.4.\n\n Traceback objects\n Traceback objects represent a stack trace of an exception. A\n traceback object is created when an exception occurs. When the\n search for an exception handler unwinds the execution stack, at\n each unwound level a traceback object is inserted in front of\n the current traceback. When an exception handler is entered,\n the stack trace is made available to the program. (See section\n *The try statement*.) It is accessible as the third item of the\n tuple returned by "sys.exc_info()". When the program contains no\n suitable handler, the stack trace is written (nicely formatted)\n to the standard error stream; if the interpreter is interactive,\n it is also made available to the user as "sys.last_traceback".\n\n Special read-only attributes: "tb_next" is the next level in the\n stack trace (towards the frame where the exception occurred), or\n "None" if there is no next level; "tb_frame" points to the\n execution frame of the current level; "tb_lineno" gives the line\n number where the exception occurred; "tb_lasti" indicates the\n precise instruction. The line number and last instruction in\n the traceback may differ from the line number of its frame\n object if the exception occurred in a "try" statement with no\n matching except clause or with a finally clause.\n\n Slice objects\n Slice objects are used to represent slices for "__getitem__()"\n methods. They are also created by the built-in "slice()"\n function.\n\n Special read-only attributes: "start" is the lower bound; "stop"\n is the upper bound; "step" is the step value; each is "None" if\n omitted. These attributes can have any type.\n\n Slice objects support one method:\n\n slice.indices(self, length)\n\n This method takes a single integer argument *length* and\n computes information about the slice that the slice object\n would describe if applied to a sequence of *length* items.\n It returns a tuple of three integers; respectively these are\n the *start* and *stop* indices and the *step* or stride\n length of the slice. Missing or out-of-bounds indices are\n handled in a manner consistent with regular slices.\n\n Static method objects\n Static method objects provide a way of defeating the\n transformation of function objects to method objects described\n above. A static method object is a wrapper around any other\n object, usually a user-defined method object. When a static\n method object is retrieved from a class or a class instance, the\n object actually returned is the wrapped object, which is not\n subject to any further transformation. Static method objects are\n not themselves callable, although the objects they wrap usually\n are. Static method objects are created by the built-in\n "staticmethod()" constructor.\n\n Class method objects\n A class method object, like a static method object, is a wrapper\n around another object that alters the way in which that object\n is retrieved from classes and class instances. The behaviour of\n class method objects upon such retrieval is described above,\n under "User-defined methods". Class method objects are created\n by the built-in "classmethod()" constructor.\n', 'typesfunctions': u'\nFunctions\n*********\n\nFunction objects are created by function definitions. The only\noperation on a function object is to call it: "func(argument-list)".\n\nThere are really two flavors of function objects: built-in functions\nand user-defined functions. Both support the same operation (to call\nthe function), but the implementation is different, hence the\ndifferent object types.\n\nSee *Function definitions* for more information.\n', - 'typesmapping': u'\nMapping Types --- "dict"\n************************\n\nA *mapping* object maps *hashable* values to arbitrary objects.\nMappings are mutable objects. There is currently only one standard\nmapping type, the *dictionary*. (For other containers see the built-\nin "list", "set", and "tuple" classes, and the "collections" module.)\n\nA dictionary\'s keys are *almost* arbitrary values. Values that are\nnot *hashable*, that is, values containing lists, dictionaries or\nother mutable types (that are compared by value rather than by object\nidentity) may not be used as keys. Numeric types used for keys obey\nthe normal rules for numeric comparison: if two numbers compare equal\n(such as "1" and "1.0") then they can be used interchangeably to index\nthe same dictionary entry. (Note however, that since computers store\nfloating-point numbers as approximations it is usually unwise to use\nthem as dictionary keys.)\n\nDictionaries can be created by placing a comma-separated list of "key:\nvalue" pairs within braces, for example: "{\'jack\': 4098, \'sjoerd\':\n4127}" or "{4098: \'jack\', 4127: \'sjoerd\'}", or by the "dict"\nconstructor.\n\nclass class dict(**kwarg)\nclass class dict(mapping, **kwarg)\nclass class dict(iterable, **kwarg)\n\n Return a new dictionary initialized from an optional positional\n argument and a possibly empty set of keyword arguments.\n\n If no positional argument is given, an empty dictionary is created.\n If a positional argument is given and it is a mapping object, a\n dictionary is created with the same key-value pairs as the mapping\n object. Otherwise, the positional argument must be an *iterable*\n object. Each item in the iterable must itself be an iterable with\n exactly two objects. The first object of each item becomes a key\n in the new dictionary, and the second object the corresponding\n value. If a key occurs more than once, the last value for that key\n becomes the corresponding value in the new dictionary.\n\n If keyword arguments are given, the keyword arguments and their\n values are added to the dictionary created from the positional\n argument. If a key being added is already present, the value from\n the keyword argument replaces the value from the positional\n argument.\n\n To illustrate, the following examples all return a dictionary equal\n to "{"one": 1, "two": 2, "three": 3}":\n\n >>> a = dict(one=1, two=2, three=3)\n >>> b = {\'one\': 1, \'two\': 2, \'three\': 3}\n >>> c = dict(zip([\'one\', \'two\', \'three\'], [1, 2, 3]))\n >>> d = dict([(\'two\', 2), (\'one\', 1), (\'three\', 3)])\n >>> e = dict({\'three\': 3, \'one\': 1, \'two\': 2})\n >>> a == b == c == d == e\n True\n\n Providing keyword arguments as in the first example only works for\n keys that are valid Python identifiers. Otherwise, any valid keys\n can be used.\n\n These are the operations that dictionaries support (and therefore,\n custom mapping types should support too):\n\n len(d)\n\n Return the number of items in the dictionary *d*.\n\n d[key]\n\n Return the item of *d* with key *key*. Raises a "KeyError" if\n *key* is not in the map.\n\n If a subclass of dict defines a method "__missing__()" and *key*\n is not present, the "d[key]" operation calls that method with\n the key *key* as argument. The "d[key]" operation then returns\n or raises whatever is returned or raised by the\n "__missing__(key)" call. No other operations or methods invoke\n "__missing__()". If "__missing__()" is not defined, "KeyError"\n is raised. "__missing__()" must be a method; it cannot be an\n instance variable:\n\n >>> class Counter(dict):\n ... def __missing__(self, key):\n ... return 0\n >>> c = Counter()\n >>> c[\'red\']\n 0\n >>> c[\'red\'] += 1\n >>> c[\'red\']\n 1\n\n The example above shows part of the implementation of\n "collections.Counter". A different "__missing__" method is used\n by "collections.defaultdict".\n\n d[key] = value\n\n Set "d[key]" to *value*.\n\n del d[key]\n\n Remove "d[key]" from *d*. Raises a "KeyError" if *key* is not\n in the map.\n\n key in d\n\n Return "True" if *d* has a key *key*, else "False".\n\n key not in d\n\n Equivalent to "not key in d".\n\n iter(d)\n\n Return an iterator over the keys of the dictionary. This is a\n shortcut for "iter(d.keys())".\n\n clear()\n\n Remove all items from the dictionary.\n\n copy()\n\n Return a shallow copy of the dictionary.\n\n classmethod fromkeys(seq[, value])\n\n Create a new dictionary with keys from *seq* and values set to\n *value*.\n\n "fromkeys()" is a class method that returns a new dictionary.\n *value* defaults to "None".\n\n get(key[, default])\n\n Return the value for *key* if *key* is in the dictionary, else\n *default*. If *default* is not given, it defaults to "None", so\n that this method never raises a "KeyError".\n\n items()\n\n Return a new view of the dictionary\'s items ("(key, value)"\n pairs). See the *documentation of view objects*.\n\n keys()\n\n Return a new view of the dictionary\'s keys. See the\n *documentation of view objects*.\n\n pop(key[, default])\n\n If *key* is in the dictionary, remove it and return its value,\n else return *default*. If *default* is not given and *key* is\n not in the dictionary, a "KeyError" is raised.\n\n popitem()\n\n Remove and return an arbitrary "(key, value)" pair from the\n dictionary.\n\n "popitem()" is useful to destructively iterate over a\n dictionary, as often used in set algorithms. If the dictionary\n is empty, calling "popitem()" raises a "KeyError".\n\n setdefault(key[, default])\n\n If *key* is in the dictionary, return its value. If not, insert\n *key* with a value of *default* and return *default*. *default*\n defaults to "None".\n\n update([other])\n\n Update the dictionary with the key/value pairs from *other*,\n overwriting existing keys. Return "None".\n\n "update()" accepts either another dictionary object or an\n iterable of key/value pairs (as tuples or other iterables of\n length two). If keyword arguments are specified, the dictionary\n is then updated with those key/value pairs: "d.update(red=1,\n blue=2)".\n\n values()\n\n Return a new view of the dictionary\'s values. See the\n *documentation of view objects*.\n\n Dictionaries compare equal if and only if they have the same "(key,\n value)" pairs. Order comparisons (\'<\', \'<=\', \'>=\', \'>\') raise\n "TypeError".\n\nSee also: "types.MappingProxyType" can be used to create a read-only\n view of a "dict".\n\n\nDictionary view objects\n=======================\n\nThe objects returned by "dict.keys()", "dict.values()" and\n"dict.items()" are *view objects*. They provide a dynamic view on the\ndictionary\'s entries, which means that when the dictionary changes,\nthe view reflects these changes.\n\nDictionary views can be iterated over to yield their respective data,\nand support membership tests:\n\nlen(dictview)\n\n Return the number of entries in the dictionary.\n\niter(dictview)\n\n Return an iterator over the keys, values or items (represented as\n tuples of "(key, value)") in the dictionary.\n\n Keys and values are iterated over in an arbitrary order which is\n non-random, varies across Python implementations, and depends on\n the dictionary\'s history of insertions and deletions. If keys,\n values and items views are iterated over with no intervening\n modifications to the dictionary, the order of items will directly\n correspond. This allows the creation of "(value, key)" pairs using\n "zip()": "pairs = zip(d.values(), d.keys())". Another way to\n create the same list is "pairs = [(v, k) for (k, v) in d.items()]".\n\n Iterating views while adding or deleting entries in the dictionary\n may raise a "RuntimeError" or fail to iterate over all entries.\n\nx in dictview\n\n Return "True" if *x* is in the underlying dictionary\'s keys, values\n or items (in the latter case, *x* should be a "(key, value)"\n tuple).\n\nKeys views are set-like since their entries are unique and hashable.\nIf all values are hashable, so that "(key, value)" pairs are unique\nand hashable, then the items view is also set-like. (Values views are\nnot treated as set-like since the entries are generally not unique.)\nFor set-like views, all of the operations defined for the abstract\nbase class "collections.abc.Set" are available (for example, "==",\n"<", or "^").\n\nAn example of dictionary view usage:\n\n >>> dishes = {\'eggs\': 2, \'sausage\': 1, \'bacon\': 1, \'spam\': 500}\n >>> keys = dishes.keys()\n >>> values = dishes.values()\n\n >>> # iteration\n >>> n = 0\n >>> for val in values:\n ... n += val\n >>> print(n)\n 504\n\n >>> # keys and values are iterated over in the same order\n >>> list(keys)\n [\'eggs\', \'bacon\', \'sausage\', \'spam\']\n >>> list(values)\n [2, 1, 1, 500]\n\n >>> # view objects are dynamic and reflect dict changes\n >>> del dishes[\'eggs\']\n >>> del dishes[\'sausage\']\n >>> list(keys)\n [\'spam\', \'bacon\']\n\n >>> # set operations\n >>> keys & {\'eggs\', \'bacon\', \'salad\'}\n {\'bacon\'}\n >>> keys ^ {\'sausage\', \'juice\'}\n {\'juice\', \'sausage\', \'bacon\', \'spam\'}\n', + 'typesmapping': u'\nMapping Types --- "dict"\n************************\n\nA *mapping* object maps *hashable* values to arbitrary objects.\nMappings are mutable objects. There is currently only one standard\nmapping type, the *dictionary*. (For other containers see the built-\nin "list", "set", and "tuple" classes, and the "collections" module.)\n\nA dictionary\'s keys are *almost* arbitrary values. Values that are\nnot *hashable*, that is, values containing lists, dictionaries or\nother mutable types (that are compared by value rather than by object\nidentity) may not be used as keys. Numeric types used for keys obey\nthe normal rules for numeric comparison: if two numbers compare equal\n(such as "1" and "1.0") then they can be used interchangeably to index\nthe same dictionary entry. (Note however, that since computers store\nfloating-point numbers as approximations it is usually unwise to use\nthem as dictionary keys.)\n\nDictionaries can be created by placing a comma-separated list of "key:\nvalue" pairs within braces, for example: "{\'jack\': 4098, \'sjoerd\':\n4127}" or "{4098: \'jack\', 4127: \'sjoerd\'}", or by the "dict"\nconstructor.\n\nclass class dict(**kwarg)\nclass class dict(mapping, **kwarg)\nclass class dict(iterable, **kwarg)\n\n Return a new dictionary initialized from an optional positional\n argument and a possibly empty set of keyword arguments.\n\n If no positional argument is given, an empty dictionary is created.\n If a positional argument is given and it is a mapping object, a\n dictionary is created with the same key-value pairs as the mapping\n object. Otherwise, the positional argument must be an *iterable*\n object. Each item in the iterable must itself be an iterable with\n exactly two objects. The first object of each item becomes a key\n in the new dictionary, and the second object the corresponding\n value. If a key occurs more than once, the last value for that key\n becomes the corresponding value in the new dictionary.\n\n If keyword arguments are given, the keyword arguments and their\n values are added to the dictionary created from the positional\n argument. If a key being added is already present, the value from\n the keyword argument replaces the value from the positional\n argument.\n\n To illustrate, the following examples all return a dictionary equal\n to "{"one": 1, "two": 2, "three": 3}":\n\n >>> a = dict(one=1, two=2, three=3)\n >>> b = {\'one\': 1, \'two\': 2, \'three\': 3}\n >>> c = dict(zip([\'one\', \'two\', \'three\'], [1, 2, 3]))\n >>> d = dict([(\'two\', 2), (\'one\', 1), (\'three\', 3)])\n >>> e = dict({\'three\': 3, \'one\': 1, \'two\': 2})\n >>> a == b == c == d == e\n True\n\n Providing keyword arguments as in the first example only works for\n keys that are valid Python identifiers. Otherwise, any valid keys\n can be used.\n\n These are the operations that dictionaries support (and therefore,\n custom mapping types should support too):\n\n len(d)\n\n Return the number of items in the dictionary *d*.\n\n d[key]\n\n Return the item of *d* with key *key*. Raises a "KeyError" if\n *key* is not in the map.\n\n If a subclass of dict defines a method "__missing__()" and *key*\n is not present, the "d[key]" operation calls that method with\n the key *key* as argument. The "d[key]" operation then returns\n or raises whatever is returned or raised by the\n "__missing__(key)" call. No other operations or methods invoke\n "__missing__()". If "__missing__()" is not defined, "KeyError"\n is raised. "__missing__()" must be a method; it cannot be an\n instance variable:\n\n >>> class Counter(dict):\n ... def __missing__(self, key):\n ... return 0\n >>> c = Counter()\n >>> c[\'red\']\n 0\n >>> c[\'red\'] += 1\n >>> c[\'red\']\n 1\n\n The example above shows part of the implementation of\n "collections.Counter". A different "__missing__" method is used\n by "collections.defaultdict".\n\n d[key] = value\n\n Set "d[key]" to *value*.\n\n del d[key]\n\n Remove "d[key]" from *d*. Raises a "KeyError" if *key* is not\n in the map.\n\n key in d\n\n Return "True" if *d* has a key *key*, else "False".\n\n key not in d\n\n Equivalent to "not key in d".\n\n iter(d)\n\n Return an iterator over the keys of the dictionary. This is a\n shortcut for "iter(d.keys())".\n\n clear()\n\n Remove all items from the dictionary.\n\n copy()\n\n Return a shallow copy of the dictionary.\n\n classmethod fromkeys(seq[, value])\n\n Create a new dictionary with keys from *seq* and values set to\n *value*.\n\n "fromkeys()" is a class method that returns a new dictionary.\n *value* defaults to "None".\n\n get(key[, default])\n\n Return the value for *key* if *key* is in the dictionary, else\n *default*. If *default* is not given, it defaults to "None", so\n that this method never raises a "KeyError".\n\n items()\n\n Return a new view of the dictionary\'s items ("(key, value)"\n pairs). See the *documentation of view objects*.\n\n keys()\n\n Return a new view of the dictionary\'s keys. See the\n *documentation of view objects*.\n\n pop(key[, default])\n\n If *key* is in the dictionary, remove it and return its value,\n else return *default*. If *default* is not given and *key* is\n not in the dictionary, a "KeyError" is raised.\n\n popitem()\n\n Remove and return an arbitrary "(key, value)" pair from the\n dictionary.\n\n "popitem()" is useful to destructively iterate over a\n dictionary, as often used in set algorithms. If the dictionary\n is empty, calling "popitem()" raises a "KeyError".\n\n setdefault(key[, default])\n\n If *key* is in the dictionary, return its value. If not, insert\n *key* with a value of *default* and return *default*. *default*\n defaults to "None".\n\n update([other])\n\n Update the dictionary with the key/value pairs from *other*,\n overwriting existing keys. Return "None".\n\n "update()" accepts either another dictionary object or an\n iterable of key/value pairs (as tuples or other iterables of\n length two). If keyword arguments are specified, the dictionary\n is then updated with those key/value pairs: "d.update(red=1,\n blue=2)".\n\n values()\n\n Return a new view of the dictionary\'s values. See the\n *documentation of view objects*.\n\nSee also: "types.MappingProxyType" can be used to create a read-only\n view of a "dict".\n\n\nDictionary view objects\n=======================\n\nThe objects returned by "dict.keys()", "dict.values()" and\n"dict.items()" are *view objects*. They provide a dynamic view on the\ndictionary\'s entries, which means that when the dictionary changes,\nthe view reflects these changes.\n\nDictionary views can be iterated over to yield their respective data,\nand support membership tests:\n\nlen(dictview)\n\n Return the number of entries in the dictionary.\n\niter(dictview)\n\n Return an iterator over the keys, values or items (represented as\n tuples of "(key, value)") in the dictionary.\n\n Keys and values are iterated over in an arbitrary order which is\n non-random, varies across Python implementations, and depends on\n the dictionary\'s history of insertions and deletions. If keys,\n values and items views are iterated over with no intervening\n modifications to the dictionary, the order of items will directly\n correspond. This allows the creation of "(value, key)" pairs using\n "zip()": "pairs = zip(d.values(), d.keys())". Another way to\n create the same list is "pairs = [(v, k) for (k, v) in d.items()]".\n\n Iterating views while adding or deleting entries in the dictionary\n may raise a "RuntimeError" or fail to iterate over all entries.\n\nx in dictview\n\n Return "True" if *x* is in the underlying dictionary\'s keys, values\n or items (in the latter case, *x* should be a "(key, value)"\n tuple).\n\nKeys views are set-like since their entries are unique and hashable.\nIf all values are hashable, so that "(key, value)" pairs are unique\nand hashable, then the items view is also set-like. (Values views are\nnot treated as set-like since the entries are generally not unique.)\nFor set-like views, all of the operations defined for the abstract\nbase class "collections.abc.Set" are available (for example, "==",\n"<", or "^").\n\nAn example of dictionary view usage:\n\n >>> dishes = {\'eggs\': 2, \'sausage\': 1, \'bacon\': 1, \'spam\': 500}\n >>> keys = dishes.keys()\n >>> values = dishes.values()\n\n >>> # iteration\n >>> n = 0\n >>> for val in values:\n ... n += val\n >>> print(n)\n 504\n\n >>> # keys and values are iterated over in the same order\n >>> list(keys)\n [\'eggs\', \'bacon\', \'sausage\', \'spam\']\n >>> list(values)\n [2, 1, 1, 500]\n\n >>> # view objects are dynamic and reflect dict changes\n >>> del dishes[\'eggs\']\n >>> del dishes[\'sausage\']\n >>> list(keys)\n [\'spam\', \'bacon\']\n\n >>> # set operations\n >>> keys & {\'eggs\', \'bacon\', \'salad\'}\n {\'bacon\'}\n >>> keys ^ {\'sausage\', \'juice\'}\n {\'juice\', \'sausage\', \'bacon\', \'spam\'}\n', 'typesmethods': u'\nMethods\n*******\n\nMethods are functions that are called using the attribute notation.\nThere are two flavors: built-in methods (such as "append()" on lists)\nand class instance methods. Built-in methods are described with the\ntypes that support them.\n\nIf you access a method (a function defined in a class namespace)\nthrough an instance, you get a special object: a *bound method* (also\ncalled *instance method*) object. When called, it will add the "self"\nargument to the argument list. Bound methods have two special read-\nonly attributes: "m.__self__" is the object on which the method\noperates, and "m.__func__" is the function implementing the method.\nCalling "m(arg-1, arg-2, ..., arg-n)" is completely equivalent to\ncalling "m.__func__(m.__self__, arg-1, arg-2, ..., arg-n)".\n\nLike function objects, bound method objects support getting arbitrary\nattributes. However, since method attributes are actually stored on\nthe underlying function object ("meth.__func__"), setting method\nattributes on bound methods is disallowed. Attempting to set an\nattribute on a method results in an "AttributeError" being raised. In\norder to set a method attribute, you need to explicitly set it on the\nunderlying function object:\n\n >>> class C:\n ... def method(self):\n ... pass\n ...\n >>> c = C()\n >>> c.method.whoami = \'my name is method\' # can\'t set on the method\n Traceback (most recent call last):\n File "<stdin>", line 1, in <module>\n AttributeError: \'method\' object has no attribute \'whoami\'\n >>> c.method.__func__.whoami = \'my name is method\'\n >>> c.method.whoami\n \'my name is method\'\n\nSee *The standard type hierarchy* for more information.\n', 'typesmodules': u'\nModules\n*******\n\nThe only special operation on a module is attribute access: "m.name",\nwhere *m* is a module and *name* accesses a name defined in *m*\'s\nsymbol table. Module attributes can be assigned to. (Note that the\n"import" statement is not, strictly speaking, an operation on a module\nobject; "import foo" does not require a module object named *foo* to\nexist, rather it requires an (external) *definition* for a module\nnamed *foo* somewhere.)\n\nA special attribute of every module is "__dict__". This is the\ndictionary containing the module\'s symbol table. Modifying this\ndictionary will actually change the module\'s symbol table, but direct\nassignment to the "__dict__" attribute is not possible (you can write\n"m.__dict__[\'a\'] = 1", which defines "m.a" to be "1", but you can\'t\nwrite "m.__dict__ = {}"). Modifying "__dict__" directly is not\nrecommended.\n\nModules built into the interpreter are written like this: "<module\n\'sys\' (built-in)>". If loaded from a file, they are written as\n"<module \'os\' from \'/usr/local/lib/pythonX.Y/os.pyc\'>".\n', 'typesseq': u'\nSequence Types --- "list", "tuple", "range"\n*******************************************\n\nThere are three basic sequence types: lists, tuples, and range\nobjects. Additional sequence types tailored for processing of *binary\ndata* and *text strings* are described in dedicated sections.\n\n\nCommon Sequence Operations\n==========================\n\nThe operations in the following table are supported by most sequence\ntypes, both mutable and immutable. The "collections.abc.Sequence" ABC\nis provided to make it easier to correctly implement these operations\non custom sequence types.\n\nThis table lists the sequence operations sorted in ascending priority.\nIn the table, *s* and *t* are sequences of the same type, *n*, *i*,\n*j* and *k* are integers and *x* is an arbitrary object that meets any\ntype and value restrictions imposed by *s*.\n\nThe "in" and "not in" operations have the same priorities as the\ncomparison operations. The "+" (concatenation) and "*" (repetition)\noperations have the same priority as the corresponding numeric\noperations.\n\n+----------------------------+----------------------------------+------------+\n| Operation | Result | Notes |\n+============================+==================================+============+\n| "x in s" | "True" if an item of *s* is | (1) |\n| | equal to *x*, else "False" | |\n+----------------------------+----------------------------------+------------+\n| "x not in s" | "False" if an item of *s* is | (1) |\n| | equal to *x*, else "True" | |\n+----------------------------+----------------------------------+------------+\n| "s + t" | the concatenation of *s* and *t* | (6)(7) |\n+----------------------------+----------------------------------+------------+\n| "s * n" or "n * s" | *n* shallow copies of *s* | (2)(7) |\n| | concatenated | |\n+----------------------------+----------------------------------+------------+\n| "s[i]" | *i*th item of *s*, origin 0 | (3) |\n+----------------------------+----------------------------------+------------+\n| "s[i:j]" | slice of *s* from *i* to *j* | (3)(4) |\n+----------------------------+----------------------------------+------------+\n| "s[i:j:k]" | slice of *s* from *i* to *j* | (3)(5) |\n| | with step *k* | |\n+----------------------------+----------------------------------+------------+\n| "len(s)" | length of *s* | |\n+----------------------------+----------------------------------+------------+\n| "min(s)" | smallest item of *s* | |\n+----------------------------+----------------------------------+------------+\n| "max(s)" | largest item of *s* | |\n+----------------------------+----------------------------------+------------+\n| "s.index(x[, i[, j]])" | index of the first occurrence of | (8) |\n| | *x* in *s* (at or after index | |\n| | *i* and before index *j*) | |\n+----------------------------+----------------------------------+------------+\n| "s.count(x)" | total number of occurrences of | |\n| | *x* in *s* | |\n+----------------------------+----------------------------------+------------+\n\nSequences of the same type also support comparisons. In particular,\ntuples and lists are compared lexicographically by comparing\ncorresponding elements. This means that to compare equal, every\nelement must compare equal and the two sequences must be of the same\ntype and have the same length. (For full details see *Comparisons* in\nthe language reference.)\n\nNotes:\n\n1. While the "in" and "not in" operations are used only for simple\n containment testing in the general case, some specialised sequences\n (such as "str", "bytes" and "bytearray") also use them for\n subsequence testing:\n\n >>> "gg" in "eggs"\n True\n\n2. Values of *n* less than "0" are treated as "0" (which yields an\n empty sequence of the same type as *s*). Note also that the copies\n are shallow; nested structures are not copied. This often haunts\n new Python programmers; consider:\n\n >>> lists = [[]] * 3\n >>> lists\n [[], [], []]\n >>> lists[0].append(3)\n >>> lists\n [[3], [3], [3]]\n\n What has happened is that "[[]]" is a one-element list containing\n an empty list, so all three elements of "[[]] * 3" are (pointers\n to) this single empty list. Modifying any of the elements of\n "lists" modifies this single list. You can create a list of\n different lists this way:\n\n >>> lists = [[] for i in range(3)]\n >>> lists[0].append(3)\n >>> lists[1].append(5)\n >>> lists[2].append(7)\n >>> lists\n [[3], [5], [7]]\n\n3. If *i* or *j* is negative, the index is relative to the end of\n the string: "len(s) + i" or "len(s) + j" is substituted. But note\n that "-0" is still "0".\n\n4. The slice of *s* from *i* to *j* is defined as the sequence of\n items with index *k* such that "i <= k < j". If *i* or *j* is\n greater than "len(s)", use "len(s)". If *i* is omitted or "None",\n use "0". If *j* is omitted or "None", use "len(s)". If *i* is\n greater than or equal to *j*, the slice is empty.\n\n5. The slice of *s* from *i* to *j* with step *k* is defined as the\n sequence of items with index "x = i + n*k" such that "0 <= n <\n (j-i)/k". In other words, the indices are "i", "i+k", "i+2*k",\n "i+3*k" and so on, stopping when *j* is reached (but never\n including *j*). If *i* or *j* is greater than "len(s)", use\n "len(s)". If *i* or *j* are omitted or "None", they become "end"\n values (which end depends on the sign of *k*). Note, *k* cannot be\n zero. If *k* is "None", it is treated like "1".\n\n6. Concatenating immutable sequences always results in a new\n object. This means that building up a sequence by repeated\n concatenation will have a quadratic runtime cost in the total\n sequence length. To get a linear runtime cost, you must switch to\n one of the alternatives below:\n\n * if concatenating "str" objects, you can build a list and use\n "str.join()" at the end or else write to a "io.StringIO" instance\n and retrieve its value when complete\n\n * if concatenating "bytes" objects, you can similarly use\n "bytes.join()" or "io.BytesIO", or you can do in-place\n concatenation with a "bytearray" object. "bytearray" objects are\n mutable and have an efficient overallocation mechanism\n\n * if concatenating "tuple" objects, extend a "list" instead\n\n * for other types, investigate the relevant class documentation\n\n7. Some sequence types (such as "range") only support item\n sequences that follow specific patterns, and hence don\'t support\n sequence concatenation or repetition.\n\n8. "index" raises "ValueError" when *x* is not found in *s*. When\n supported, the additional arguments to the index method allow\n efficient searching of subsections of the sequence. Passing the\n extra arguments is roughly equivalent to using "s[i:j].index(x)",\n only without copying any data and with the returned index being\n relative to the start of the sequence rather than the start of the\n slice.\n\n\nImmutable Sequence Types\n========================\n\nThe only operation that immutable sequence types generally implement\nthat is not also implemented by mutable sequence types is support for\nthe "hash()" built-in.\n\nThis support allows immutable sequences, such as "tuple" instances, to\nbe used as "dict" keys and stored in "set" and "frozenset" instances.\n\nAttempting to hash an immutable sequence that contains unhashable\nvalues will result in "TypeError".\n\n\nMutable Sequence Types\n======================\n\nThe operations in the following table are defined on mutable sequence\ntypes. The "collections.abc.MutableSequence" ABC is provided to make\nit easier to correctly implement these operations on custom sequence\ntypes.\n\nIn the table *s* is an instance of a mutable sequence type, *t* is any\niterable object and *x* is an arbitrary object that meets any type and\nvalue restrictions imposed by *s* (for example, "bytearray" only\naccepts integers that meet the value restriction "0 <= x <= 255").\n\n+--------------------------------+----------------------------------+-----------------------+\n| Operation | Result | Notes |\n+================================+==================================+=======================+\n| "s[i] = x" | item *i* of *s* is replaced by | |\n| | *x* | |\n+--------------------------------+----------------------------------+-----------------------+\n| "s[i:j] = t" | slice of *s* from *i* to *j* is | |\n| | replaced by the contents of the | |\n| | iterable *t* | |\n+--------------------------------+----------------------------------+-----------------------+\n| "del s[i:j]" | same as "s[i:j] = []" | |\n+--------------------------------+----------------------------------+-----------------------+\n| "s[i:j:k] = t" | the elements of "s[i:j:k]" are | (1) |\n| | replaced by those of *t* | |\n+--------------------------------+----------------------------------+-----------------------+\n| "del s[i:j:k]" | removes the elements of | |\n| | "s[i:j:k]" from the list | |\n+--------------------------------+----------------------------------+-----------------------+\n| "s.append(x)" | appends *x* to the end of the | |\n| | sequence (same as | |\n| | "s[len(s):len(s)] = [x]") | |\n+--------------------------------+----------------------------------+-----------------------+\n| "s.clear()" | removes all items from "s" (same | (5) |\n| | as "del s[:]") | |\n+--------------------------------+----------------------------------+-----------------------+\n| "s.copy()" | creates a shallow copy of "s" | (5) |\n| | (same as "s[:]") | |\n+--------------------------------+----------------------------------+-----------------------+\n| "s.extend(t)" | extends *s* with the contents of | |\n| | *t* (same as "s[len(s):len(s)] = | |\n| | t") | |\n+--------------------------------+----------------------------------+-----------------------+\n| "s.insert(i, x)" | inserts *x* into *s* at the | |\n| | index given by *i* (same as | |\n| | "s[i:i] = [x]") | |\n+--------------------------------+----------------------------------+-----------------------+\n| "s.pop([i])" | retrieves the item at *i* and | (2) |\n| | also removes it from *s* | |\n+--------------------------------+----------------------------------+-----------------------+\n| "s.remove(x)" | remove the first item from *s* | (3) |\n| | where "s[i] == x" | |\n+--------------------------------+----------------------------------+-----------------------+\n| "s.reverse()" | reverses the items of *s* in | (4) |\n| | place | |\n+--------------------------------+----------------------------------+-----------------------+\n\nNotes:\n\n1. *t* must have the same length as the slice it is replacing.\n\n2. The optional argument *i* defaults to "-1", so that by default\n the last item is removed and returned.\n\n3. "remove" raises "ValueError" when *x* is not found in *s*.\n\n4. The "reverse()" method modifies the sequence in place for\n economy of space when reversing a large sequence. To remind users\n that it operates by side effect, it does not return the reversed\n sequence.\n\n5. "clear()" and "copy()" are included for consistency with the\n interfaces of mutable containers that don\'t support slicing\n operations (such as "dict" and "set")\n\n New in version 3.3: "clear()" and "copy()" methods.\n\n\nLists\n=====\n\nLists are mutable sequences, typically used to store collections of\nhomogeneous items (where the precise degree of similarity will vary by\napplication).\n\nclass class list([iterable])\n\n Lists may be constructed in several ways:\n\n * Using a pair of square brackets to denote the empty list: "[]"\n\n * Using square brackets, separating items with commas: "[a]",\n "[a, b, c]"\n\n * Using a list comprehension: "[x for x in iterable]"\n\n * Using the type constructor: "list()" or "list(iterable)"\n\n The constructor builds a list whose items are the same and in the\n same order as *iterable*\'s items. *iterable* may be either a\n sequence, a container that supports iteration, or an iterator\n object. If *iterable* is already a list, a copy is made and\n returned, similar to "iterable[:]". For example, "list(\'abc\')"\n returns "[\'a\', \'b\', \'c\']" and "list( (1, 2, 3) )" returns "[1, 2,\n 3]". If no argument is given, the constructor creates a new empty\n list, "[]".\n\n Many other operations also produce lists, including the "sorted()"\n built-in.\n\n Lists implement all of the *common* and *mutable* sequence\n operations. Lists also provide the following additional method:\n\n sort(*, key=None, reverse=None)\n\n This method sorts the list in place, using only "<" comparisons\n between items. Exceptions are not suppressed - if any comparison\n operations fail, the entire sort operation will fail (and the\n list will likely be left in a partially modified state).\n\n "sort()" accepts two arguments that can only be passed by\n keyword (*keyword-only arguments*):\n\n *key* specifies a function of one argument that is used to\n extract a comparison key from each list element (for example,\n "key=str.lower"). The key corresponding to each item in the list\n is calculated once and then used for the entire sorting process.\n The default value of "None" means that list items are sorted\n directly without calculating a separate key value.\n\n The "functools.cmp_to_key()" utility is available to convert a\n 2.x style *cmp* function to a *key* function.\n\n *reverse* is a boolean value. If set to "True", then the list\n elements are sorted as if each comparison were reversed.\n\n This method modifies the sequence in place for economy of space\n when sorting a large sequence. To remind users that it operates\n by side effect, it does not return the sorted sequence (use\n "sorted()" to explicitly request a new sorted list instance).\n\n The "sort()" method is guaranteed to be stable. A sort is\n stable if it guarantees not to change the relative order of\n elements that compare equal --- this is helpful for sorting in\n multiple passes (for example, sort by department, then by salary\n grade).\n\n **CPython implementation detail:** While a list is being sorted,\n the effect of attempting to mutate, or even inspect, the list is\n undefined. The C implementation of Python makes the list appear\n empty for the duration, and raises "ValueError" if it can detect\n that the list has been mutated during a sort.\n\n\nTuples\n======\n\nTuples are immutable sequences, typically used to store collections of\nheterogeneous data (such as the 2-tuples produced by the "enumerate()"\nbuilt-in). Tuples are also used for cases where an immutable sequence\nof homogeneous data is needed (such as allowing storage in a "set" or\n"dict" instance).\n\nclass class tuple([iterable])\n\n Tuples may be constructed in a number of ways:\n\n * Using a pair of parentheses to denote the empty tuple: "()"\n\n * Using a trailing comma for a singleton tuple: "a," or "(a,)"\n\n * Separating items with commas: "a, b, c" or "(a, b, c)"\n\n * Using the "tuple()" built-in: "tuple()" or "tuple(iterable)"\n\n The constructor builds a tuple whose items are the same and in the\n same order as *iterable*\'s items. *iterable* may be either a\n sequence, a container that supports iteration, or an iterator\n object. If *iterable* is already a tuple, it is returned\n unchanged. For example, "tuple(\'abc\')" returns "(\'a\', \'b\', \'c\')"\n and "tuple( [1, 2, 3] )" returns "(1, 2, 3)". If no argument is\n given, the constructor creates a new empty tuple, "()".\n\n Note that it is actually the comma which makes a tuple, not the\n parentheses. The parentheses are optional, except in the empty\n tuple case, or when they are needed to avoid syntactic ambiguity.\n For example, "f(a, b, c)" is a function call with three arguments,\n while "f((a, b, c))" is a function call with a 3-tuple as the sole\n argument.\n\n Tuples implement all of the *common* sequence operations.\n\nFor heterogeneous collections of data where access by name is clearer\nthan access by index, "collections.namedtuple()" may be a more\nappropriate choice than a simple tuple object.\n\n\nRanges\n======\n\nThe "range" type represents an immutable sequence of numbers and is\ncommonly used for looping a specific number of times in "for" loops.\n\nclass class range(stop)\nclass class range(start, stop[, step])\n\n The arguments to the range constructor must be integers (either\n built-in "int" or any object that implements the "__index__"\n special method). If the *step* argument is omitted, it defaults to\n "1". If the *start* argument is omitted, it defaults to "0". If\n *step* is zero, "ValueError" is raised.\n\n For a positive *step*, the contents of a range "r" are determined\n by the formula "r[i] = start + step*i" where "i >= 0" and "r[i] <\n stop".\n\n For a negative *step*, the contents of the range are still\n determined by the formula "r[i] = start + step*i", but the\n constraints are "i >= 0" and "r[i] > stop".\n\n A range object will be empty if "r[0]" does not meet the value\n constraint. Ranges do support negative indices, but these are\n interpreted as indexing from the end of the sequence determined by\n the positive indices.\n\n Ranges containing absolute values larger than "sys.maxsize" are\n permitted but some features (such as "len()") may raise\n "OverflowError".\n\n Range examples:\n\n >>> list(range(10))\n [0, 1, 2, 3, 4, 5, 6, 7, 8, 9]\n >>> list(range(1, 11))\n [1, 2, 3, 4, 5, 6, 7, 8, 9, 10]\n >>> list(range(0, 30, 5))\n [0, 5, 10, 15, 20, 25]\n >>> list(range(0, 10, 3))\n [0, 3, 6, 9]\n >>> list(range(0, -10, -1))\n [0, -1, -2, -3, -4, -5, -6, -7, -8, -9]\n >>> list(range(0))\n []\n >>> list(range(1, 0))\n []\n\n Ranges implement all of the *common* sequence operations except\n concatenation and repetition (due to the fact that range objects\n can only represent sequences that follow a strict pattern and\n repetition and concatenation will usually violate that pattern).\n\nThe advantage of the "range" type over a regular "list" or "tuple" is\nthat a "range" object will always take the same (small) amount of\nmemory, no matter the size of the range it represents (as it only\nstores the "start", "stop" and "step" values, calculating individual\nitems and subranges as needed).\n\nRange objects implement the "collections.abc.Sequence" ABC, and\nprovide features such as containment tests, element index lookup,\nslicing and support for negative indices (see *Sequence Types ---\nlist, tuple, range*):\n\n>>> r = range(0, 20, 2)\n>>> r\nrange(0, 20, 2)\n>>> 11 in r\nFalse\n>>> 10 in r\nTrue\n>>> r.index(10)\n5\n>>> r[5]\n10\n>>> r[:5]\nrange(0, 10, 2)\n>>> r[-1]\n18\n\nTesting range objects for equality with "==" and "!=" compares them as\nsequences. That is, two range objects are considered equal if they\nrepresent the same sequence of values. (Note that two range objects\nthat compare equal might have different "start", "stop" and "step"\nattributes, for example "range(0) == range(2, 1, 3)" or "range(0, 3,\n2) == range(0, 4, 2)".)\n\nChanged in version 3.2: Implement the Sequence ABC. Support slicing\nand negative indices. Test "int" objects for membership in constant\ntime instead of iterating through all items.\n\nChanged in version 3.3: Define \'==\' and \'!=\' to compare range objects\nbased on the sequence of values they define (instead of comparing\nbased on object identity).\n\nNew in version 3.3: The "start", "stop" and "step" attributes.\n', diff --git a/Lib/sre_compile.py b/Lib/sre_compile.py index 502b061..4edb03f 100644 --- a/Lib/sre_compile.py +++ b/Lib/sre_compile.py @@ -409,57 +409,39 @@ def _generate_overlap_table(prefix): table[i] = idx + 1 return table -def _compile_info(code, pattern, flags): - # internal: compile an info block. in the current version, - # this contains min/max pattern width, and an optional literal - # prefix or a character map - lo, hi = pattern.getwidth() - if hi > MAXCODE: - hi = MAXCODE - if lo == 0: - code.extend([INFO, 4, 0, lo, hi]) - return - # look for a literal prefix +def _get_literal_prefix(pattern): + # look for literal prefix prefix = [] prefixappend = prefix.append - prefix_skip = 0 + prefix_skip = None + got_all = True + for op, av in pattern.data: + if op is LITERAL: + prefixappend(av) + elif op is SUBPATTERN: + prefix1, prefix_skip1, got_all = _get_literal_prefix(av[1]) + if prefix_skip is None: + if av[0] is not None: + prefix_skip = len(prefix) + elif prefix_skip1 is not None: + prefix_skip = len(prefix) + prefix_skip1 + prefix.extend(prefix1) + if not got_all: + break + else: + got_all = False + break + return prefix, prefix_skip, got_all + +def _get_charset_prefix(pattern): charset = [] # not used charsetappend = charset.append - if not (flags & SRE_FLAG_IGNORECASE): - # look for literal prefix - for op, av in pattern.data: + if pattern.data: + op, av = pattern.data[0] + if op is SUBPATTERN and av[1]: + op, av = av[1][0] if op is LITERAL: - if len(prefix) == prefix_skip: - prefix_skip = prefix_skip + 1 - prefixappend(av) - elif op is SUBPATTERN and len(av[1]) == 1: - op, av = av[1][0] - if op is LITERAL: - prefixappend(av) - else: - break - else: - break - # if no prefix, look for charset prefix - if not prefix and pattern.data: - op, av = pattern.data[0] - if op is SUBPATTERN and av[1]: - op, av = av[1][0] - if op is LITERAL: - charsetappend((op, av)) - elif op is BRANCH: - c = [] - cappend = c.append - for p in av[1]: - if not p: - break - op, av = p[0] - if op is LITERAL: - cappend((op, av)) - else: - break - else: - charset = c + charsetappend((op, av)) elif op is BRANCH: c = [] cappend = c.append @@ -473,8 +455,43 @@ def _compile_info(code, pattern, flags): break else: charset = c - elif op is IN: - charset = av + elif op is BRANCH: + c = [] + cappend = c.append + for p in av[1]: + if not p: + break + op, av = p[0] + if op is LITERAL: + cappend((op, av)) + else: + break + else: + charset = c + elif op is IN: + charset = av + return charset + +def _compile_info(code, pattern, flags): + # internal: compile an info block. in the current version, + # this contains min/max pattern width, and an optional literal + # prefix or a character map + lo, hi = pattern.getwidth() + if hi > MAXCODE: + hi = MAXCODE + if lo == 0: + code.extend([INFO, 4, 0, lo, hi]) + return + # look for a literal prefix + prefix = [] + prefix_skip = 0 + charset = [] # not used + if not (flags & SRE_FLAG_IGNORECASE): + # look for literal prefix + prefix, prefix_skip, got_all = _get_literal_prefix(pattern) + # if no prefix, look for charset prefix + if not prefix: + charset = _get_charset_prefix(pattern) ## if prefix: ## print("*** PREFIX", prefix, prefix_skip) ## if charset: @@ -487,7 +504,7 @@ def _compile_info(code, pattern, flags): mask = 0 if prefix: mask = SRE_INFO_PREFIX - if len(prefix) == prefix_skip == len(pattern.data): + if prefix_skip is None and got_all: mask = mask | SRE_INFO_LITERAL elif charset: mask = mask | SRE_INFO_CHARSET @@ -502,6 +519,8 @@ def _compile_info(code, pattern, flags): # add literal prefix if prefix: emit(len(prefix)) # length + if prefix_skip is None: + prefix_skip = len(prefix) emit(prefix_skip) # skip code.extend(prefix) # generate overlap table diff --git a/Lib/string.py b/Lib/string.py index f3365c6..e7b692d 100644 --- a/Lib/string.py +++ b/Lib/string.py @@ -112,10 +112,7 @@ class Template(metaclass=_TemplateMetaclass): # Check the most common path first. named = mo.group('named') or mo.group('braced') if named is not None: - val = mapping[named] - # We use this idiom instead of str() because the latter will - # fail if val is a Unicode containing non-ASCII characters. - return '%s' % (val,) + return str(mapping[named]) if mo.group('escaped') is not None: return self.delimiter if mo.group('invalid') is not None: @@ -142,9 +139,7 @@ class Template(metaclass=_TemplateMetaclass): named = mo.group('named') or mo.group('braced') if named is not None: try: - # We use this idiom instead of str() because the latter - # will fail if val is a Unicode containing non-ASCII - return '%s' % (mapping[named],) + return str(mapping[named]) except KeyError: return mo.group() if mo.group('escaped') is not None: diff --git a/Lib/test/test_argparse.py b/Lib/test/test_argparse.py index 27bfad5..893ec39 100644 --- a/Lib/test/test_argparse.py +++ b/Lib/test/test_argparse.py @@ -4512,6 +4512,21 @@ class TestStrings(TestCase): string = "Namespace(bar='spam', foo=42)" self.assertStringEqual(ns, string) + def test_namespace_starkwargs_notidentifier(self): + ns = argparse.Namespace(**{'"': 'quote'}) + string = """Namespace(**{'"': 'quote'})""" + self.assertStringEqual(ns, string) + + def test_namespace_kwargs_and_starkwargs_notidentifier(self): + ns = argparse.Namespace(a=1, **{'"': 'quote'}) + string = """Namespace(a=1, **{'"': 'quote'})""" + self.assertStringEqual(ns, string) + + def test_namespace_starkwargs_identifier(self): + ns = argparse.Namespace(**{'valid': True}) + string = "Namespace(valid=True)" + self.assertStringEqual(ns, string) + def test_parser(self): parser = argparse.ArgumentParser(prog='PROG') string = ( diff --git a/Lib/test/test_collections.py b/Lib/test/test_collections.py index c2d03ee..57f6e52 100644 --- a/Lib/test/test_collections.py +++ b/Lib/test/test_collections.py @@ -1992,6 +1992,14 @@ class OrderedDictTests: od = OrderedDict(**d) self.assertGreater(sys.getsizeof(od), sys.getsizeof(d)) + def test_views(self): + OrderedDict = self.module.OrderedDict + # See http://bugs.python.org/issue24286 + s = 'the quick brown fox jumped over a lazy dog yesterday before dawn'.split() + od = OrderedDict.fromkeys(s) + self.assertEqual(od.keys(), dict(od).keys()) + self.assertEqual(od.items(), dict(od).items()) + def test_override_update(self): OrderedDict = self.module.OrderedDict # Verify that subclasses can override update() without breaking __init__() diff --git a/Lib/test/test_dictviews.py b/Lib/test/test_dictviews.py index 8d33801..fcb6814 100644 --- a/Lib/test/test_dictviews.py +++ b/Lib/test/test_dictviews.py @@ -1,3 +1,4 @@ +import collections import unittest class DictSetTest(unittest.TestCase): @@ -197,6 +198,27 @@ class DictSetTest(unittest.TestCase): d[42] = d.values() self.assertRaises(RecursionError, repr, d) + def test_abc_registry(self): + d = dict(a=1) + + self.assertIsInstance(d.keys(), collections.KeysView) + self.assertIsInstance(d.keys(), collections.MappingView) + self.assertIsInstance(d.keys(), collections.Set) + self.assertIsInstance(d.keys(), collections.Sized) + self.assertIsInstance(d.keys(), collections.Iterable) + self.assertIsInstance(d.keys(), collections.Container) + + self.assertIsInstance(d.values(), collections.ValuesView) + self.assertIsInstance(d.values(), collections.MappingView) + self.assertIsInstance(d.values(), collections.Sized) + + self.assertIsInstance(d.items(), collections.ItemsView) + self.assertIsInstance(d.items(), collections.MappingView) + self.assertIsInstance(d.items(), collections.Set) + self.assertIsInstance(d.items(), collections.Sized) + self.assertIsInstance(d.items(), collections.Iterable) + self.assertIsInstance(d.items(), collections.Container) + if __name__ == "__main__": unittest.main() diff --git a/Lib/test/test_file.py b/Lib/test/test_file.py index 4e392b7..67c3d86 100644 --- a/Lib/test/test_file.py +++ b/Lib/test/test_file.py @@ -139,7 +139,7 @@ class OtherFileTests: def testModeStrings(self): # check invalid mode strings - for mode in ("", "aU", "wU+"): + for mode in ("", "aU", "wU+", "U+", "+U", "rU+"): try: f = self.open(TESTFN, mode) except ValueError: diff --git a/Lib/test/test_inspect.py b/Lib/test/test_inspect.py index 955b2ad..db15b39 100644 --- a/Lib/test/test_inspect.py +++ b/Lib/test/test_inspect.py @@ -38,7 +38,7 @@ from test.test_import import _ready_to_import # ismodule, isclass, ismethod, isfunction, istraceback, isframe, iscode, # isbuiltin, isroutine, isgenerator, isgeneratorfunction, getmembers, # getdoc, getfile, getmodule, getsourcefile, getcomments, getsource, -# getclasstree, getargspec, getargvalues, formatargspec, formatargvalues, +# getclasstree, getargvalues, formatargspec, formatargvalues, # currentframe, stack, trace, isdatadescriptor # NOTE: There are some additional tests relating to interaction with @@ -628,18 +628,6 @@ class TestClassesAndFunctions(unittest.TestCase): got = inspect.getmro(D) self.assertEqual(expected, got) - def assertArgSpecEquals(self, routine, args_e, varargs_e=None, - varkw_e=None, defaults_e=None, formatted=None): - with self.assertWarns(DeprecationWarning): - args, varargs, varkw, defaults = inspect.getargspec(routine) - self.assertEqual(args, args_e) - self.assertEqual(varargs, varargs_e) - self.assertEqual(varkw, varkw_e) - self.assertEqual(defaults, defaults_e) - if formatted is not None: - self.assertEqual(inspect.formatargspec(args, varargs, varkw, defaults), - formatted) - def assertFullArgSpecEquals(self, routine, args_e, varargs_e=None, varkw_e=None, defaults_e=None, kwonlyargs_e=[], kwonlydefaults_e=None, @@ -658,23 +646,6 @@ class TestClassesAndFunctions(unittest.TestCase): kwonlyargs, kwonlydefaults, ann), formatted) - def test_getargspec(self): - self.assertArgSpecEquals(mod.eggs, ['x', 'y'], formatted='(x, y)') - - self.assertArgSpecEquals(mod.spam, - ['a', 'b', 'c', 'd', 'e', 'f'], - 'g', 'h', (3, 4, 5), - '(a, b, c, d=3, e=4, f=5, *g, **h)') - - self.assertRaises(ValueError, self.assertArgSpecEquals, - mod2.keyworded, []) - - self.assertRaises(ValueError, self.assertArgSpecEquals, - mod2.annotated, []) - self.assertRaises(ValueError, self.assertArgSpecEquals, - mod2.keyword_only_arg, []) - - def test_getfullargspec(self): self.assertFullArgSpecEquals(mod2.keyworded, [], varargs_e='arg1', kwonlyargs_e=['arg2'], @@ -688,20 +659,19 @@ class TestClassesAndFunctions(unittest.TestCase): kwonlyargs_e=['arg'], formatted='(*, arg)') - def test_argspec_api_ignores_wrapped(self): + def test_fullargspec_api_ignores_wrapped(self): # Issue 20684: low level introspection API must ignore __wrapped__ @functools.wraps(mod.spam) def ham(x, y): pass # Basic check - self.assertArgSpecEquals(ham, ['x', 'y'], formatted='(x, y)') self.assertFullArgSpecEquals(ham, ['x', 'y'], formatted='(x, y)') self.assertFullArgSpecEquals(functools.partial(ham), ['x', 'y'], formatted='(x, y)') # Other variants def check_method(f): - self.assertArgSpecEquals(f, ['self', 'x', 'y'], - formatted='(self, x, y)') + self.assertFullArgSpecEquals(f, ['self', 'x', 'y'], + formatted='(self, x, y)') class C: @functools.wraps(mod.spam) def ham(self, x, y): @@ -779,11 +749,11 @@ class TestClassesAndFunctions(unittest.TestCase): with self.assertRaises(TypeError): inspect.getfullargspec(builtin) - def test_getargspec_method(self): + def test_getfullargspec_method(self): class A(object): def m(self): pass - self.assertArgSpecEquals(A.m, ['self']) + self.assertFullArgSpecEquals(A.m, ['self']) def test_classify_newstyle(self): class A(object): diff --git a/Lib/test/test_operator.py b/Lib/test/test_operator.py index da9c8ef..54fd1f4 100644 --- a/Lib/test/test_operator.py +++ b/Lib/test/test_operator.py @@ -120,63 +120,63 @@ class OperatorTestCase: operator = self.module self.assertRaises(TypeError, operator.add) self.assertRaises(TypeError, operator.add, None, None) - self.assertTrue(operator.add(3, 4) == 7) + self.assertEqual(operator.add(3, 4), 7) def test_bitwise_and(self): operator = self.module self.assertRaises(TypeError, operator.and_) self.assertRaises(TypeError, operator.and_, None, None) - self.assertTrue(operator.and_(0xf, 0xa) == 0xa) + self.assertEqual(operator.and_(0xf, 0xa), 0xa) def test_concat(self): operator = self.module self.assertRaises(TypeError, operator.concat) self.assertRaises(TypeError, operator.concat, None, None) - self.assertTrue(operator.concat('py', 'thon') == 'python') - self.assertTrue(operator.concat([1, 2], [3, 4]) == [1, 2, 3, 4]) - self.assertTrue(operator.concat(Seq1([5, 6]), Seq1([7])) == [5, 6, 7]) - self.assertTrue(operator.concat(Seq2([5, 6]), Seq2([7])) == [5, 6, 7]) + self.assertEqual(operator.concat('py', 'thon'), 'python') + self.assertEqual(operator.concat([1, 2], [3, 4]), [1, 2, 3, 4]) + self.assertEqual(operator.concat(Seq1([5, 6]), Seq1([7])), [5, 6, 7]) + self.assertEqual(operator.concat(Seq2([5, 6]), Seq2([7])), [5, 6, 7]) self.assertRaises(TypeError, operator.concat, 13, 29) def test_countOf(self): operator = self.module self.assertRaises(TypeError, operator.countOf) self.assertRaises(TypeError, operator.countOf, None, None) - self.assertTrue(operator.countOf([1, 2, 1, 3, 1, 4], 3) == 1) - self.assertTrue(operator.countOf([1, 2, 1, 3, 1, 4], 5) == 0) + self.assertEqual(operator.countOf([1, 2, 1, 3, 1, 4], 3), 1) + self.assertEqual(operator.countOf([1, 2, 1, 3, 1, 4], 5), 0) def test_delitem(self): operator = self.module a = [4, 3, 2, 1] self.assertRaises(TypeError, operator.delitem, a) self.assertRaises(TypeError, operator.delitem, a, None) - self.assertTrue(operator.delitem(a, 1) is None) - self.assertTrue(a == [4, 2, 1]) + self.assertIsNone(operator.delitem(a, 1)) + self.assertEqual(a, [4, 2, 1]) def test_floordiv(self): operator = self.module self.assertRaises(TypeError, operator.floordiv, 5) self.assertRaises(TypeError, operator.floordiv, None, None) - self.assertTrue(operator.floordiv(5, 2) == 2) + self.assertEqual(operator.floordiv(5, 2), 2) def test_truediv(self): operator = self.module self.assertRaises(TypeError, operator.truediv, 5) self.assertRaises(TypeError, operator.truediv, None, None) - self.assertTrue(operator.truediv(5, 2) == 2.5) + self.assertEqual(operator.truediv(5, 2), 2.5) def test_getitem(self): operator = self.module a = range(10) self.assertRaises(TypeError, operator.getitem) self.assertRaises(TypeError, operator.getitem, a, None) - self.assertTrue(operator.getitem(a, 2) == 2) + self.assertEqual(operator.getitem(a, 2), 2) def test_indexOf(self): operator = self.module self.assertRaises(TypeError, operator.indexOf) self.assertRaises(TypeError, operator.indexOf, None, None) - self.assertTrue(operator.indexOf([4, 3, 2, 1], 3) == 1) + self.assertEqual(operator.indexOf([4, 3, 2, 1], 3), 1) self.assertRaises(ValueError, operator.indexOf, [4, 3, 2, 1], 0) def test_invert(self): @@ -189,21 +189,21 @@ class OperatorTestCase: operator = self.module self.assertRaises(TypeError, operator.lshift) self.assertRaises(TypeError, operator.lshift, None, 42) - self.assertTrue(operator.lshift(5, 1) == 10) - self.assertTrue(operator.lshift(5, 0) == 5) + self.assertEqual(operator.lshift(5, 1), 10) + self.assertEqual(operator.lshift(5, 0), 5) self.assertRaises(ValueError, operator.lshift, 2, -1) def test_mod(self): operator = self.module self.assertRaises(TypeError, operator.mod) self.assertRaises(TypeError, operator.mod, None, 42) - self.assertTrue(operator.mod(5, 2) == 1) + self.assertEqual(operator.mod(5, 2), 1) def test_mul(self): operator = self.module self.assertRaises(TypeError, operator.mul) self.assertRaises(TypeError, operator.mul, None, None) - self.assertTrue(operator.mul(5, 2) == 10) + self.assertEqual(operator.mul(5, 2), 10) def test_matmul(self): operator = self.module @@ -227,7 +227,7 @@ class OperatorTestCase: operator = self.module self.assertRaises(TypeError, operator.or_) self.assertRaises(TypeError, operator.or_, None, None) - self.assertTrue(operator.or_(0xa, 0x5) == 0xf) + self.assertEqual(operator.or_(0xa, 0x5), 0xf) def test_pos(self): operator = self.module @@ -250,8 +250,8 @@ class OperatorTestCase: operator = self.module self.assertRaises(TypeError, operator.rshift) self.assertRaises(TypeError, operator.rshift, None, 42) - self.assertTrue(operator.rshift(5, 1) == 2) - self.assertTrue(operator.rshift(5, 0) == 5) + self.assertEqual(operator.rshift(5, 1), 2) + self.assertEqual(operator.rshift(5, 0), 5) self.assertRaises(ValueError, operator.rshift, 2, -1) def test_contains(self): @@ -266,15 +266,15 @@ class OperatorTestCase: a = list(range(3)) self.assertRaises(TypeError, operator.setitem, a) self.assertRaises(TypeError, operator.setitem, a, None, None) - self.assertTrue(operator.setitem(a, 0, 2) is None) - self.assertTrue(a == [2, 1, 2]) + self.assertIsNone(operator.setitem(a, 0, 2)) + self.assertEqual(a, [2, 1, 2]) self.assertRaises(IndexError, operator.setitem, a, 4, 2) def test_sub(self): operator = self.module self.assertRaises(TypeError, operator.sub) self.assertRaises(TypeError, operator.sub, None, None) - self.assertTrue(operator.sub(5, 2) == 3) + self.assertEqual(operator.sub(5, 2), 3) def test_truth(self): operator = self.module @@ -292,7 +292,7 @@ class OperatorTestCase: operator = self.module self.assertRaises(TypeError, operator.xor) self.assertRaises(TypeError, operator.xor, None, None) - self.assertTrue(operator.xor(0xb, 0xc) == 0x7) + self.assertEqual(operator.xor(0xb, 0xc), 0x7) def test_is(self): operator = self.module diff --git a/Lib/test/test_os.py b/Lib/test/test_os.py index d91f58c..b3cf207 100644 --- a/Lib/test/test_os.py +++ b/Lib/test/test_os.py @@ -213,15 +213,10 @@ class FileTests(unittest.TestCase): # Test attributes on return values from os.*stat* family. class StatAttributeTests(unittest.TestCase): def setUp(self): - os.mkdir(support.TESTFN) - self.fname = os.path.join(support.TESTFN, "f1") - f = open(self.fname, 'wb') - f.write(b"ABC") - f.close() - - def tearDown(self): - os.unlink(self.fname) - os.rmdir(support.TESTFN) + self.fname = support.TESTFN + self.addCleanup(support.unlink, self.fname) + with open(self.fname, 'wb') as fp: + fp.write(b"ABC") @unittest.skipUnless(hasattr(os, 'stat'), 'test needs os.stat()') def check_stat_attributes(self, fname): @@ -413,7 +408,11 @@ class StatAttributeTests(unittest.TestCase): 0) # test directory st_file_attributes (FILE_ATTRIBUTE_DIRECTORY set) - result = os.stat(support.TESTFN) + dirname = support.TESTFN + "dir" + os.mkdir(dirname) + self.addCleanup(os.rmdir, dirname) + + result = os.stat(dirname) self.check_file_attributes(result) self.assertEqual( result.st_file_attributes & stat.FILE_ATTRIBUTE_DIRECTORY, diff --git a/Lib/test/test_set.py b/Lib/test/test_set.py index 54de508..ade39fb 100644 --- a/Lib/test/test_set.py +++ b/Lib/test/test_set.py @@ -10,6 +10,8 @@ import sys import warnings import collections import collections.abc +import itertools +import string class PassThru(Exception): pass @@ -711,6 +713,28 @@ class TestFrozenSet(TestJointOps, unittest.TestCase): addhashvalue(hash(frozenset([e for e, m in elemmasks if m&i]))) self.assertEqual(len(hashvalues), 2**n) + def letter_range(n): + return string.ascii_letters[:n] + + def zf_range(n): + # https://en.wikipedia.org/wiki/Set-theoretic_definition_of_natural_numbers + nums = [frozenset()] + for i in range(n-1): + num = frozenset(nums) + nums.append(num) + return nums[:n] + + def powerset(s): + for i in range(len(s)+1): + yield from map(frozenset, itertools.combinations(s, i)) + + for n in range(18): + t = 2 ** n + mask = t - 1 + for nums in (range, letter_range, zf_range): + u = len({h & mask for h in map(hash, powerset(nums(n)))}) + self.assertGreater(4*u, t) + class FrozenSetSubclass(frozenset): pass diff --git a/Lib/test/test_symbol.py b/Lib/test/test_symbol.py new file mode 100644 index 0000000..4475bbc --- /dev/null +++ b/Lib/test/test_symbol.py @@ -0,0 +1,45 @@ +import unittest +from test import support +import filecmp +import os +import sys +import subprocess + + +SYMBOL_FILE = support.findfile('symbol.py') +GRAMMAR_FILE = os.path.join(os.path.dirname(__file__), + '..', '..', 'Include', 'graminit.h') +TEST_PY_FILE = 'symbol_test.py' + + +class TestSymbolGeneration(unittest.TestCase): + + def _copy_file_without_generated_symbols(self, source_file, dest_file): + with open(source_file, 'rb') as fp: + lines = fp.readlines() + nl = lines[0][len(lines[0].rstrip()):] + with open(dest_file, 'wb') as fp: + fp.writelines(lines[:lines.index(b"#--start constants--" + nl) + 1]) + fp.writelines(lines[lines.index(b"#--end constants--" + nl):]) + + def _generate_symbols(self, grammar_file, target_symbol_py_file): + proc = subprocess.Popen([sys.executable, + SYMBOL_FILE, + grammar_file, + target_symbol_py_file], stderr=subprocess.PIPE) + stderr = proc.communicate()[1] + return proc.returncode, stderr + + @unittest.skipIf(not os.path.exists(GRAMMAR_FILE), + 'test only works from source build directory') + def test_real_grammar_and_symbol_file(self): + self._copy_file_without_generated_symbols(SYMBOL_FILE, TEST_PY_FILE) + self.addCleanup(support.unlink, TEST_PY_FILE) + self.assertFalse(filecmp.cmp(SYMBOL_FILE, TEST_PY_FILE)) + self.assertEqual((0, b''), self._generate_symbols(GRAMMAR_FILE, + TEST_PY_FILE)) + self.assertTrue(filecmp.cmp(SYMBOL_FILE, TEST_PY_FILE)) + + +if __name__ == "__main__": + unittest.main() diff --git a/Lib/test/test_urlparse.py b/Lib/test/test_urlparse.py index 0552f90..fcf5082 100644 --- a/Lib/test/test_urlparse.py +++ b/Lib/test/test_urlparse.py @@ -554,29 +554,27 @@ class UrlParseTestCase(unittest.TestCase): self.assertEqual(p.port, 80) self.assertEqual(p.geturl(), url) - # Verify an illegal port is returned as None + # Verify an illegal port raises ValueError url = b"HTTP://WWW.PYTHON.ORG:65536/doc/#frag" p = urllib.parse.urlsplit(url) - self.assertEqual(p.port, None) + with self.assertRaisesRegex(ValueError, "out of range"): + p.port def test_attributes_bad_port(self): - """Check handling of non-integer ports.""" - p = urllib.parse.urlsplit("http://www.example.net:foo") - self.assertEqual(p.netloc, "www.example.net:foo") - self.assertRaises(ValueError, lambda: p.port) - - p = urllib.parse.urlparse("http://www.example.net:foo") - self.assertEqual(p.netloc, "www.example.net:foo") - self.assertRaises(ValueError, lambda: p.port) - - # Once again, repeat ourselves to test bytes - p = urllib.parse.urlsplit(b"http://www.example.net:foo") - self.assertEqual(p.netloc, b"www.example.net:foo") - self.assertRaises(ValueError, lambda: p.port) - - p = urllib.parse.urlparse(b"http://www.example.net:foo") - self.assertEqual(p.netloc, b"www.example.net:foo") - self.assertRaises(ValueError, lambda: p.port) + """Check handling of invalid ports.""" + for bytes in (False, True): + for parse in (urllib.parse.urlsplit, urllib.parse.urlparse): + for port in ("foo", "1.5", "-1", "0x10"): + with self.subTest(bytes=bytes, parse=parse, port=port): + netloc = "www.example.net:" + port + url = "http://" + netloc + if bytes: + netloc = netloc.encode("ascii") + url = url.encode("ascii") + p = parse(url) + self.assertEqual(p.netloc, netloc) + with self.assertRaises(ValueError): + p.port def test_attributes_without_netloc(self): # This example is straight from RFC 3261. It looks like it diff --git a/Lib/test/test_zipimport.py b/Lib/test/test_zipimport.py index a97a778..4f19535 100644 --- a/Lib/test/test_zipimport.py +++ b/Lib/test/test_zipimport.py @@ -214,7 +214,8 @@ class UncompressedZipImportTestCase(ImportHooksBaseTestCase): packdir2 = packdir + TESTPACK2 + os.sep files = {packdir + "__init__" + pyc_ext: (NOW, test_pyc), packdir2 + "__init__" + pyc_ext: (NOW, test_pyc), - packdir2 + TESTMOD + pyc_ext: (NOW, test_pyc)} + packdir2 + TESTMOD + pyc_ext: (NOW, test_pyc), + "spam" + pyc_ext: (NOW, test_pyc)} z = ZipFile(TEMP_ZIP, "w") try: @@ -228,6 +229,14 @@ class UncompressedZipImportTestCase(ImportHooksBaseTestCase): zi = zipimport.zipimporter(TEMP_ZIP) self.assertEqual(zi.archive, TEMP_ZIP) self.assertEqual(zi.is_package(TESTPACK), True) + + find_mod = zi.find_module('spam') + self.assertIsNotNone(find_mod) + self.assertIsInstance(find_mod, zipimport.zipimporter) + self.assertFalse(find_mod.is_package('spam')) + load_mod = find_mod.load_module('spam') + self.assertEqual(find_mod.get_filename('spam'), load_mod.__file__) + mod = zi.load_module(TESTPACK) self.assertEqual(zi.get_filename(TESTPACK), mod.__file__) @@ -287,6 +296,16 @@ class UncompressedZipImportTestCase(ImportHooksBaseTestCase): self.assertEqual( zi.is_package(TESTPACK2 + os.sep + TESTMOD), False) + pkg_path = TEMP_ZIP + os.sep + packdir + TESTPACK2 + zi2 = zipimport.zipimporter(pkg_path) + find_mod_dotted = zi2.find_module(TESTMOD) + self.assertIsNotNone(find_mod_dotted) + self.assertIsInstance(find_mod_dotted, zipimport.zipimporter) + self.assertFalse(zi2.is_package(TESTMOD)) + load_mod = find_mod_dotted.load_module(TESTMOD) + self.assertEqual( + find_mod_dotted.get_filename(TESTMOD), load_mod.__file__) + mod_path = TESTPACK2 + os.sep + TESTMOD mod_name = module_path_to_dotted_name(mod_path) __import__(mod_name) diff --git a/Lib/tkinter/ttk.py b/Lib/tkinter/ttk.py index b9c57ad..bad9596 100644 --- a/Lib/tkinter/ttk.py +++ b/Lib/tkinter/ttk.py @@ -381,7 +381,9 @@ class Style(object): a sequence identifying the value for that option.""" if query_opt is not None: kw[query_opt] = None - return _val_or_dict(self.tk, kw, self._name, "configure", style) + result = _val_or_dict(self.tk, kw, self._name, "configure", style) + if result or query_opt: + return result def map(self, style, query_opt=None, **kw): @@ -466,12 +468,14 @@ class Style(object): def element_names(self): """Returns the list of elements defined in the current theme.""" - return self.tk.splitlist(self.tk.call(self._name, "element", "names")) + return tuple(n.lstrip('-') for n in self.tk.splitlist( + self.tk.call(self._name, "element", "names"))) def element_options(self, elementname): """Return the list of elementname's options.""" - return self.tk.splitlist(self.tk.call(self._name, "element", "options", elementname)) + return tuple(o.lstrip('-') for o in self.tk.splitlist( + self.tk.call(self._name, "element", "options", elementname))) def theme_create(self, themename, parent=None, settings=None): diff --git a/Lib/traceback.py b/Lib/traceback.py index 02edeb6..3d2e5e0 100644 --- a/Lib/traceback.py +++ b/Lib/traceback.py @@ -477,10 +477,9 @@ class TracebackException: self._load_lines() @classmethod - def from_exception(self, exc, *args, **kwargs): + def from_exception(cls, exc, *args, **kwargs): """Create a TracebackException from an exception.""" - return TracebackException( - type(exc), exc, exc.__traceback__, *args, **kwargs) + return cls(type(exc), exc, exc.__traceback__, *args, **kwargs) def _load_lines(self): """Private API. force all lines in the stack to be loaded.""" diff --git a/Lib/urllib/parse.py b/Lib/urllib/parse.py index 01c9e58..5e2155c 100644 --- a/Lib/urllib/parse.py +++ b/Lib/urllib/parse.py @@ -156,9 +156,8 @@ class _NetlocResultMixinBase(object): port = self._hostinfo[1] if port is not None: port = int(port, 10) - # Return None on an illegal port if not ( 0 <= port <= 65535): - return None + raise ValueError("Port out of range 0-65535") return port @@ -1394,6 +1394,7 @@ William Tanksley Christian Tanzer Steven Taschuk Amy Taylor +Julian Taylor Monty Taylor Anatoly Techtonik Gustavo Temple @@ -2,10 +2,10 @@ Python News +++++++++++ -What's New in Python 3.5.0 release candidate 1? -=============================================== +What's New in Python 3.6.0 alpha 1? +=================================== -Release date: 2015-08-09 +Release date: XXXX-XX-XX Core and Builtins ----------------- @@ -15,13 +15,12 @@ Core and Builtins Library ------- +- Issue #20059: urllib.parse raises ValueError on all invalid ports. + Patch by Martin Panter. + - Issue #24824: Signatures of codecs.encode() and codecs.decode() now are compatible with pydoc. -- Issue #24634: Importing uuid should not try to load libc on Windows - -- Issue #24798: _msvccompiler.py doesn't properly support manifests - - Issue #4395: Better testing and documentation of binary operators. Patch by Martin Panter. @@ -42,20 +41,41 @@ Library - Issue #23779: imaplib raises TypeError if authenticator tries to abort. Patch from Craig Holmquist. +- Issue #24360: Improve __repr__ of argparse.Namespace() for invalid + identifiers. Patch by Matthias Bussonnier. + - Issue #23319: Fix ctypes.BigEndianStructure, swap correctly bytes. Patch written by Matthieu Gautier. +- Issue #19450: Update Windows and OS X installer builds to use SQLite 3.8.11. + - Issue #23254: Document how to close the TCPServer listening socket. Patch from Martin Panter. -- Issue #19450: Update Windows and OS X installer builds to use SQLite 3.8.11. +- Issue #23426: run_setup was broken in distutils. + Patch from Alexander Belopolsky. - Issue #17527: Add PATCH to wsgiref.validator. Patch from Luca Sbardella. -- Issue #23812: Fix asyncio.Queue.get() to avoid loosing items on cancellation. - Patch by Gustavo J. A. M. Carneiro. +- Issue #13938: 2to3 converts StringTypes to a tuple. Patch from Mark Hammond. + +- Issue #2091: open() accepted a 'U' mode string containing '+', but 'U' can + only be used with 'r'. Patch from Jeff Balogh and John O'Connor. + +- Issue #8585: improved tests for zipimporter2. Patch from Mark Lawrence. + +- Issue #18622: unittest.mock.mock_open().reset_mock would recurse infinitely. + Patch from Nicola Palumbo and Laurent De Buyst. -- Issue #24791: Fix grammar regression for call syntax: 'g(*a or b)'. +- Issue #24426: Fast searching optimization in regular expressions now works + for patterns that starts with capturing groups. Fast searching optimization + now can't be disabled at compile time. + +- Issue #23661: unittest.mock side_effects can now be exceptions again. This + was a regression vs Python 3.4. Patch from Ignacio Rossi + +- Issue #13248: Remove deprecated inspect.getargspec and inspect.getmoduleinfo + functions. Documentation ------------- @@ -139,12 +159,6 @@ Library - Issue #24631: Fixed regression in the timeit module with multiline setup. -- Issue #18622: unittest.mock.mock_open().reset_mock would recurse infinitely. - Patch from Nicola Palumbo and Laurent De Buyst. - -- Issue #23661: unittest.mock side_effects can now be exceptions again. This - was a regression vs Python 3.4. Patch from Ignacio Rossi - - Issue #24608: chunk.Chunk.read() now always returns bytes, not str. - Issue #18684: Fixed reading out of the buffer in the re module. @@ -155,6 +169,9 @@ Library - Issue #15014: SMTP.auth() and SMTP.login() now support RFC 4954's optional initial-response argument to the SMTP AUTH command. +- Issue #6549: Remove hyphen from ttk.Style().element options. Only return result + from ttk.Style().configure if a result was generated or a query submitted. + - Issue #24669: Fix inspect.getsource() for 'async def' functions. Patch by Kai Groner. @@ -166,7 +183,6 @@ Build - Issue #24603: Update Windows builds and OS X 10.5 installer to use OpenSSL 1.0.2d. - What's New in Python 3.5.0 beta 3? ================================== @@ -330,6 +346,9 @@ Core and Builtins - Issue #24268: PEP 489: Multi-phase extension module initialization. Patch by Petr Viktorin. +- Issue #23359: Optimize set object internals by specializing the + hash table search into a lookup function and an insert function. + - Issue #23955: Add pyvenv.cfg option to suppress registry/environment lookup for generating sys.path on Windows. diff --git a/Modules/_collectionsmodule.c b/Modules/_collectionsmodule.c index 830c5b8..749cf6b 100644 --- a/Modules/_collectionsmodule.c +++ b/Modules/_collectionsmodule.c @@ -788,7 +788,7 @@ deque_reverse(dequeobject *deque, PyObject *unused) block *rightblock = deque->rightblock; Py_ssize_t leftindex = deque->leftindex; Py_ssize_t rightindex = deque->rightindex; - Py_ssize_t n = Py_SIZE(deque) / 2; + Py_ssize_t n = Py_SIZE(deque) >> 1; Py_ssize_t i; PyObject *tmp; @@ -1047,7 +1047,7 @@ deque_clear(dequeobject *deque) static int valid_index(Py_ssize_t i, Py_ssize_t limit) { - /* The cast to size_t let us use just a single comparison + /* The cast to size_t lets us use just a single comparison to check whether i is in the range: 0 <= i < limit */ return (size_t) i < (size_t) limit; } diff --git a/Modules/_heapqmodule.c b/Modules/_heapqmodule.c index c343862..28604af 100644 --- a/Modules/_heapqmodule.c +++ b/Modules/_heapqmodule.c @@ -66,7 +66,7 @@ siftup(PyListObject *heap, Py_ssize_t pos) /* Bubble up the smaller child until hitting a leaf. */ arr = _PyList_ITEMS(heap); - limit = endpos / 2; /* smallest pos that has no child */ + limit = endpos >> 1; /* smallest pos that has no child */ while (pos < limit) { /* Set childpos to index of smaller child. */ childpos = 2*pos + 1; /* leftmost child position */ @@ -347,7 +347,7 @@ heapify_internal(PyObject *heap, int siftup_func(PyListObject *, Py_ssize_t)) n is odd = 2*j+1, this is (2*j+1-1)/2 = j so j-1 is the largest, and that's again n//2-1. */ - for (i = n/2 - 1 ; i >= 0 ; i--) + for (i = (n >> 1) - 1 ; i >= 0 ; i--) if (siftup_func((PyListObject *)heap, i)) return NULL; Py_RETURN_NONE; @@ -420,7 +420,7 @@ siftup_max(PyListObject *heap, Py_ssize_t pos) /* Bubble up the smaller child until hitting a leaf. */ arr = _PyList_ITEMS(heap); - limit = endpos / 2; /* smallest pos that has no child */ + limit = endpos >> 1; /* smallest pos that has no child */ while (pos < limit) { /* Set childpos to index of smaller child. */ childpos = 2*pos + 1; /* leftmost child position */ diff --git a/Modules/_io/_iomodule.c b/Modules/_io/_iomodule.c index 528bcd4..1c2d3a0 100644 --- a/Modules/_io/_iomodule.c +++ b/Modules/_io/_iomodule.c @@ -248,8 +248,8 @@ _io_open_impl(PyModuleDef *module, PyObject *file, const char *mode, _Py_IDENTIFIER(close); if (!PyUnicode_Check(file) && - !PyBytes_Check(file) && - !PyNumber_Check(file)) { + !PyBytes_Check(file) && + !PyNumber_Check(file)) { PyErr_Format(PyExc_TypeError, "invalid file: %R", file); return NULL; } @@ -307,9 +307,9 @@ _io_open_impl(PyModuleDef *module, PyObject *file, const char *mode, /* Parameters validation */ if (universal) { - if (writing || appending) { + if (creating || writing || appending || updating) { PyErr_SetString(PyExc_ValueError, - "can't use U and writing mode at once"); + "mode U cannot be combined with x', 'w', 'a', or '+'"); return NULL; } if (PyErr_WarnEx(PyExc_DeprecationWarning, @@ -437,10 +437,10 @@ _io_open_impl(PyModuleDef *module, PyObject *file, const char *mode, /* wraps into a TextIOWrapper */ wrapper = PyObject_CallFunction((PyObject *)&PyTextIOWrapper_Type, - "Osssi", - buffer, - encoding, errors, newline, - line_buffering); + "Osssi", + buffer, + encoding, errors, newline, + line_buffering); if (wrapper == NULL) goto error; result = wrapper; diff --git a/Modules/_sre.c b/Modules/_sre.c index 957ccbc..6a3d811 100644 --- a/Modules/_sre.c +++ b/Modules/_sre.c @@ -62,9 +62,6 @@ static char copyright[] = /* -------------------------------------------------------------------- */ /* optional features */ -/* enables fast searching */ -#define USE_FAST_SEARCH - /* enables copy/deepcopy handling (work in progress) */ #undef USE_BUILTIN_COPY diff --git a/Modules/nismodule.c b/Modules/nismodule.c index 64eb5db..b6a855c 100644 --- a/Modules/nismodule.c +++ b/Modules/nismodule.c @@ -76,11 +76,7 @@ nis_mapname (char *map, int *pfix) *pfix = 0; for (i=0; aliases[i].alias != 0L; i++) { - if (!strcmp (aliases[i].alias, map)) { - *pfix = aliases[i].fix; - return aliases[i].map; - } - if (!strcmp (aliases[i].map, map)) { + if (!strcmp (aliases[i].alias, map) || !strcmp (aliases[i].map, map)) { *pfix = aliases[i].fix; return aliases[i].map; } diff --git a/Modules/posixmodule.c b/Modules/posixmodule.c index ec8c526..23d74a3 100644 --- a/Modules/posixmodule.c +++ b/Modules/posixmodule.c @@ -5760,7 +5760,7 @@ os.sched_getaffinity pid: pid_t / -Return the affinity of the process identified by pid. +Return the affinity of the process identified by pid (or the current process if zero). The affinity is returned as a set of CPU identifiers. [clinic start generated code]*/ @@ -11201,7 +11201,9 @@ get_terminal_size(PyObject *self, PyObject *args) /*[clinic input] os.cpu_count -Return the number of CPUs in the system; return None if indeterminable. +Return the number of CPUs in the system; return None if indeterminable. This +number is not equivalent to the number of CPUs the current process can use. +The number of usable CPUs can be obtained with ``len(os.sched_getaffinity(0))`` [clinic start generated code]*/ static PyObject * diff --git a/Modules/sre_lib.h b/Modules/sre_lib.h index 128c71e..6ad2ab7 100644 --- a/Modules/sre_lib.h +++ b/Modules/sre_lib.h @@ -1256,7 +1256,32 @@ SRE(search)(SRE_STATE* state, SRE_CODE* pattern) prefix, prefix_len, prefix_skip)); TRACE(("charset = %p\n", charset)); -#if defined(USE_FAST_SEARCH) + if (prefix_len == 1) { + /* pattern starts with a literal character */ + SRE_CHAR c = (SRE_CHAR) prefix[0]; +#if SIZEOF_SRE_CHAR < 4 + if ((SRE_CODE) c != prefix[0]) + return 0; /* literal can't match: doesn't fit in char width */ +#endif + end = (SRE_CHAR *)state->end; + while (ptr < end) { + while (*ptr != c) { + if (++ptr >= end) + return 0; + } + TRACE(("|%p|%p|SEARCH LITERAL\n", pattern, ptr)); + state->start = ptr; + state->ptr = ptr + prefix_skip; + if (flags & SRE_INFO_LITERAL) + return 1; /* we got all of it */ + status = SRE(match)(state, pattern + 2*prefix_skip, 0); + if (status != 0) + return status; + ++ptr; + } + return 0; + } + if (prefix_len > 1) { /* pattern starts with a known prefix. use the overlap table to skip forward as fast as we possibly can */ @@ -1305,32 +1330,8 @@ SRE(search)(SRE_STATE* state, SRE_CODE* pattern) } return 0; } -#endif - if (pattern[0] == SRE_OP_LITERAL) { - /* pattern starts with a literal character. this is used - for short prefixes, and if fast search is disabled */ - SRE_CHAR c = (SRE_CHAR) pattern[1]; -#if SIZEOF_SRE_CHAR < 4 - if ((SRE_CODE) c != pattern[1]) - return 0; /* literal can't match: doesn't fit in char width */ -#endif - end = (SRE_CHAR *)state->end; - while (ptr < end) { - while (*ptr != c) { - if (++ptr >= end) - return 0; - } - TRACE(("|%p|%p|SEARCH LITERAL\n", pattern, ptr)); - state->start = ptr; - state->ptr = ++ptr; - if (flags & SRE_INFO_LITERAL) - return 1; /* we got all of it */ - status = SRE(match)(state, pattern + 2, 0); - if (status != 0) - break; - } - } else if (charset) { + if (charset) { /* pattern starts with a character from a known set */ end = (SRE_CHAR *)state->end; for (;;) { diff --git a/Objects/abstract.c b/Objects/abstract.c index 31cc0a8..039a4ca 100644 --- a/Objects/abstract.c +++ b/Objects/abstract.c @@ -2131,7 +2131,7 @@ PyObject_Call(PyObject *func, PyObject *arg, PyObject *kw) /* PyObject_Call() must not be called with an exception set, because it may clear it (directly or indirectly) and so the - caller looses its exception */ + caller loses its exception */ assert(!PyErr_Occurred()); call = func->ob_type->tp_call; diff --git a/Objects/setobject.c b/Objects/setobject.c index 704d7e2..03bb230 100644 --- a/Objects/setobject.c +++ b/Objects/setobject.c @@ -29,7 +29,6 @@ #include "Python.h" #include "structmember.h" -#include "stringlib/eq.h" /* Object used as dummy key to fill deleted entries */ static PyObject _dummy_struct; @@ -51,19 +50,20 @@ static PyObject _dummy_struct; static setentry * set_lookkey(PySetObject *so, PyObject *key, Py_hash_t hash) { - setentry *table = so->table; - setentry *freeslot = NULL; + setentry *table; setentry *entry; - size_t perturb = hash; + size_t perturb; size_t mask = so->mask; size_t i = (size_t)hash & mask; /* Unsigned for defined overflow behavior */ size_t j; int cmp; - entry = &table[i]; + entry = &so->table[i]; if (entry->key == NULL) return entry; + perturb = hash; + while (1) { if (entry->hash == hash) { PyObject *startkey = entry->key; @@ -73,8 +73,9 @@ set_lookkey(PySetObject *so, PyObject *key, Py_hash_t hash) return entry; if (PyUnicode_CheckExact(startkey) && PyUnicode_CheckExact(key) - && unicode_eq(startkey, key)) + && _PyUnicode_EQ(startkey, key)) return entry; + table = so->table; Py_INCREF(startkey); cmp = PyObject_RichCompareBool(startkey, key, Py_EQ); Py_DECREF(startkey); @@ -86,14 +87,12 @@ set_lookkey(PySetObject *so, PyObject *key, Py_hash_t hash) return entry; mask = so->mask; /* help avoid a register spill */ } - if (entry->hash == -1 && freeslot == NULL) - freeslot = entry; if (i + LINEAR_PROBES <= mask) { for (j = 0 ; j < LINEAR_PROBES ; j++) { entry++; - if (entry->key == NULL) - goto found_null; + if (entry->hash == 0 && entry->key == NULL) + return entry; if (entry->hash == hash) { PyObject *startkey = entry->key; assert(startkey != dummy); @@ -101,8 +100,9 @@ set_lookkey(PySetObject *so, PyObject *key, Py_hash_t hash) return entry; if (PyUnicode_CheckExact(startkey) && PyUnicode_CheckExact(key) - && unicode_eq(startkey, key)) + && _PyUnicode_EQ(startkey, key)) return entry; + table = so->table; Py_INCREF(startkey); cmp = PyObject_RichCompareBool(startkey, key, Py_EQ); Py_DECREF(startkey); @@ -114,7 +114,104 @@ set_lookkey(PySetObject *so, PyObject *key, Py_hash_t hash) return entry; mask = so->mask; } - if (entry->hash == -1 && freeslot == NULL) + } + } + + perturb >>= PERTURB_SHIFT; + i = (i * 5 + 1 + perturb) & mask; + + entry = &so->table[i]; + if (entry->key == NULL) + return entry; + } +} + +static int set_table_resize(PySetObject *, Py_ssize_t); + +static int +set_add_entry(PySetObject *so, PyObject *key, Py_hash_t hash) +{ + setentry *table; + setentry *freeslot; + setentry *entry; + size_t perturb; + size_t mask; + size_t i; /* Unsigned for defined overflow behavior */ + size_t j; + int cmp; + + /* Pre-increment is necessary to prevent arbitrary code in the rich + comparison from deallocating the key just before the insertion. */ + Py_INCREF(key); + + restart: + + mask = so->mask; + i = (size_t)hash & mask; + + entry = &so->table[i]; + if (entry->key == NULL) + goto found_unused; + + freeslot = NULL; + perturb = hash; + + while (1) { + if (entry->hash == hash) { + PyObject *startkey = entry->key; + /* startkey cannot be a dummy because the dummy hash field is -1 */ + assert(startkey != dummy); + if (startkey == key) + goto found_active; + if (PyUnicode_CheckExact(startkey) + && PyUnicode_CheckExact(key) + && _PyUnicode_EQ(startkey, key)) + goto found_active; + table = so->table; + Py_INCREF(startkey); + cmp = PyObject_RichCompareBool(startkey, key, Py_EQ); + Py_DECREF(startkey); + if (cmp > 0) /* likely */ + goto found_active; + if (cmp < 0) + goto comparison_error; + /* Continuing the search from the current entry only makes + sense if the table and entry are unchanged; otherwise, + we have to restart from the beginning */ + if (table != so->table || entry->key != startkey) + goto restart; + mask = so->mask; /* help avoid a register spill */ + } + else if (entry->hash == -1 && freeslot == NULL) + freeslot = entry; + + if (i + LINEAR_PROBES <= mask) { + for (j = 0 ; j < LINEAR_PROBES ; j++) { + entry++; + if (entry->hash == 0 && entry->key == NULL) + goto found_unused_or_dummy; + if (entry->hash == hash) { + PyObject *startkey = entry->key; + assert(startkey != dummy); + if (startkey == key) + goto found_active; + if (PyUnicode_CheckExact(startkey) + && PyUnicode_CheckExact(key) + && _PyUnicode_EQ(startkey, key)) + goto found_active; + table = so->table; + Py_INCREF(startkey); + cmp = PyObject_RichCompareBool(startkey, key, Py_EQ); + Py_DECREF(startkey); + if (cmp > 0) + goto found_active; + if (cmp < 0) + goto comparison_error; + if (table != so->table || entry->key != startkey) + goto restart; + mask = so->mask; + } + else if (entry->hash == -1 && freeslot == NULL) freeslot = entry; } } @@ -122,12 +219,35 @@ set_lookkey(PySetObject *so, PyObject *key, Py_hash_t hash) perturb >>= PERTURB_SHIFT; i = (i * 5 + 1 + perturb) & mask; - entry = &table[i]; + entry = &so->table[i]; if (entry->key == NULL) - goto found_null; + goto found_unused_or_dummy; } - found_null: - return freeslot == NULL ? entry : freeslot; + + found_unused_or_dummy: + if (freeslot == NULL) + goto found_unused; + so->used++; + freeslot->key = key; + freeslot->hash = hash; + return 0; + + found_unused: + so->fill++; + so->used++; + entry->key = key; + entry->hash = hash; + if ((size_t)so->fill*3 < mask*2) + return 0; + return set_table_resize(so, so->used); + + found_active: + Py_DECREF(key); + return 0; + + comparison_error: + Py_DECREF(key); + return -1; } /* @@ -172,38 +292,6 @@ set_insert_clean(PySetObject *so, PyObject *key, Py_hash_t hash) /* ======== End logic for probing the hash table ========================== */ /* ======================================================================== */ - -/* -Internal routine to insert a new key into the table. -Used by the public insert routine. -Eats a reference to key. -*/ -static int -set_insert_key(PySetObject *so, PyObject *key, Py_hash_t hash) -{ - setentry *entry; - - entry = set_lookkey(so, key, hash); - if (entry == NULL) - return -1; - if (entry->key == NULL) { - /* UNUSED */ - entry->key = key; - entry->hash = hash; - so->fill++; - so->used++; - } else if (entry->key == dummy) { - /* DUMMY */ - entry->key = key; - entry->hash = hash; - so->used++; - } else { - /* ACTIVE */ - Py_DECREF(key); - } - return 0; -} - /* Restructure the table by allocating a new table and reinserting all keys again. When entries have been deleted, the new table may @@ -220,6 +308,7 @@ set_table_resize(PySetObject *so, Py_ssize_t minused) setentry small_copy[PySet_MINSIZE]; assert(minused >= 0); + minused = (minused > 50000) ? minused * 2 : minused * 4; /* Find the smallest table size > minused. */ /* XXX speed-up with intrinsics */ @@ -295,31 +384,42 @@ set_table_resize(PySetObject *so, Py_ssize_t minused) return 0; } -/* CAUTION: set_add_key/entry() must guarantee it won't resize the table */ +static int +set_contains_entry(PySetObject *so, PyObject *key, Py_hash_t hash) +{ + setentry *entry; + + entry = set_lookkey(so, key, hash); + if (entry != NULL) + return entry->key != NULL; + return -1; +} + +#define DISCARD_NOTFOUND 0 +#define DISCARD_FOUND 1 static int -set_add_entry(PySetObject *so, setentry *entry) +set_discard_entry(PySetObject *so, PyObject *key, Py_hash_t hash) { - Py_ssize_t n_used; - PyObject *key = entry->key; - Py_hash_t hash = entry->hash; + setentry *entry; + PyObject *old_key; - assert(so->fill <= so->mask); /* at least one empty slot */ - n_used = so->used; - Py_INCREF(key); - if (set_insert_key(so, key, hash)) { - Py_DECREF(key); + entry = set_lookkey(so, key, hash); + if (entry == NULL) return -1; - } - if (!(so->used > n_used && so->fill*3 >= (so->mask+1)*2)) - return 0; - return set_table_resize(so, so->used>50000 ? so->used*2 : so->used*4); + if (entry->key == NULL) + return DISCARD_NOTFOUND; + old_key = entry->key; + entry->key = dummy; + entry->hash = -1; + so->used--; + Py_DECREF(old_key); + return DISCARD_FOUND; } static int set_add_key(PySetObject *so, PyObject *key) { - setentry entry; Py_hash_t hash; if (!PyUnicode_CheckExact(key) || @@ -328,50 +428,35 @@ set_add_key(PySetObject *so, PyObject *key) if (hash == -1) return -1; } - entry.key = key; - entry.hash = hash; - return set_add_entry(so, &entry); + return set_add_entry(so, key, hash); } -#define DISCARD_NOTFOUND 0 -#define DISCARD_FOUND 1 - static int -set_discard_entry(PySetObject *so, setentry *oldentry) +set_contains_key(PySetObject *so, PyObject *key) { - setentry *entry; - PyObject *old_key; + Py_hash_t hash; - entry = set_lookkey(so, oldentry->key, oldentry->hash); - if (entry == NULL) - return -1; - if (entry->key == NULL || entry->key == dummy) - return DISCARD_NOTFOUND; - old_key = entry->key; - entry->key = dummy; - entry->hash = -1; - so->used--; - Py_DECREF(old_key); - return DISCARD_FOUND; + if (!PyUnicode_CheckExact(key) || + (hash = ((PyASCIIObject *) key)->hash) == -1) { + hash = PyObject_Hash(key); + if (hash == -1) + return -1; + } + return set_contains_entry(so, key, hash); } static int set_discard_key(PySetObject *so, PyObject *key) { - setentry entry; Py_hash_t hash; - assert (PyAnySet_Check(so)); - if (!PyUnicode_CheckExact(key) || (hash = ((PyASCIIObject *) key)->hash) == -1) { hash = PyObject_Hash(key); if (hash == -1) return -1; } - entry.key = key; - entry.hash = hash; - return set_discard_entry(so, &entry); + return set_discard_entry(so, key, hash); } static void @@ -452,20 +537,22 @@ set_next(PySetObject *so, Py_ssize_t *pos_ptr, setentry **entry_ptr) { Py_ssize_t i; Py_ssize_t mask; - setentry *table; + setentry *entry; assert (PyAnySet_Check(so)); i = *pos_ptr; assert(i >= 0); - table = so->table; mask = so->mask; - while (i <= mask && (table[i].key == NULL || table[i].key == dummy)) + entry = &so->table[i]; + while (i <= mask && (entry->key == NULL || entry->key == dummy)) { i++; + entry++; + } *pos_ptr = i+1; if (i > mask) return 0; - assert(table[i].key != NULL); - *entry_ptr = &table[i]; + assert(entry != NULL); + *entry_ptr = entry; return 1; } @@ -563,8 +650,8 @@ set_merge(PySetObject *so, PyObject *otherset) * incrementally resizing as we insert new keys. Expect * that there will be no (or few) overlapping keys. */ - if ((so->fill + other->used)*3 >= (so->mask+1)*2) { - if (set_table_resize(so, (so->used + other->used)*2) != 0) + if ((so->fill + other->used)*3 >= so->mask*2) { + if (set_table_resize(so, so->used + other->used) != 0) return -1; } so_entry = so->table; @@ -604,46 +691,13 @@ set_merge(PySetObject *so, PyObject *otherset) other_entry = &other->table[i]; key = other_entry->key; if (key != NULL && key != dummy) { - Py_INCREF(key); - if (set_insert_key(so, key, other_entry->hash)) { - Py_DECREF(key); + if (set_add_entry(so, key, other_entry->hash)) return -1; - } } } return 0; } -static int -set_contains_entry(PySetObject *so, setentry *entry) -{ - PyObject *key; - setentry *lu_entry; - - lu_entry = set_lookkey(so, entry->key, entry->hash); - if (lu_entry == NULL) - return -1; - key = lu_entry->key; - return key != NULL && key != dummy; -} - -static int -set_contains_key(PySetObject *so, PyObject *key) -{ - setentry entry; - Py_hash_t hash; - - if (!PyUnicode_CheckExact(key) || - (hash = ((PyASCIIObject *) key)->hash) == -1) { - hash = PyObject_Hash(key); - if (hash == -1) - return -1; - } - entry.key = key; - entry.hash = hash; - return set_contains_entry(so, &entry); -} - static PyObject * set_pop(PySetObject *so) { @@ -685,43 +739,64 @@ set_traverse(PySetObject *so, visitproc visit, void *arg) return 0; } -static Py_hash_t -frozenset_hash(PyObject *self) +/* Work to increase the bit dispersion for closely spaced hash values. + This is important because some use cases have many combinations of a + small number of elements with nearby hashes so that many distinct + combinations collapse to only a handful of distinct hash values. */ + +static Py_uhash_t +_shuffle_bits(Py_uhash_t h) { - /* Most of the constants in this hash algorithm are randomly choosen - large primes with "interesting bit patterns" and that passed - tests for good collision statistics on a variety of problematic - datasets such as: + return ((h ^ 89869747UL) ^ (h << 16)) * 3644798167UL; +} - ps = [] - for r in range(21): - ps += itertools.combinations(range(20), r) - num_distinct_hashes = len({hash(frozenset(s)) for s in ps}) +/* Most of the constants in this hash algorithm are randomly chosen + large primes with "interesting bit patterns" and that passed tests + for good collision statistics on a variety of problematic datasets + including powersets and graph structures (such as David Eppstein's + graph recipes in Lib/test/test_set.py) */ - */ +static Py_hash_t +frozenset_hash(PyObject *self) +{ PySetObject *so = (PySetObject *)self; - Py_uhash_t h, hash = 1927868237UL; + Py_uhash_t hash = 0; setentry *entry; - Py_ssize_t pos = 0; if (so->hash != -1) return so->hash; - hash *= (Py_uhash_t)PySet_GET_SIZE(self) + 1; - while (set_next(so, &pos, &entry)) { - /* Work to increase the bit dispersion for closely spaced hash - values. This is important because some use cases have many - combinations of a small number of elements with nearby - hashes so that many distinct combinations collapse to only - a handful of distinct hash values. */ - h = entry->hash; - hash ^= ((h ^ 89869747UL) ^ (h << 16)) * 3644798167UL; - } - /* Make the final result spread-out in a different pattern - than the algorithm for tuples or other python objects. */ + /* Xor-in shuffled bits from every entry's hash field because xor is + commutative and a frozenset hash should be independent of order. + + For speed, include null entries and dummy entries and then + subtract out their effect afterwards so that the final hash + depends only on active entries. This allows the code to be + vectorized by the compiler and it saves the unpredictable + branches that would arise when trying to exclude null and dummy + entries on every iteration. */ + + for (entry = so->table; entry <= &so->table[so->mask]; entry++) + hash ^= _shuffle_bits(entry->hash); + + /* Remove the effect of an odd number of NULL entries */ + if ((so->mask + 1 - so->fill) & 1) + hash ^= _shuffle_bits(0); + + /* Remove the effect of an odd number of dummy entries */ + if ((so->fill - so->used) & 1) + hash ^= _shuffle_bits(-1); + + /* Factor in the number of active entries */ + hash ^= ((Py_uhash_t)PySet_GET_SIZE(self) + 1) * 1927868237UL; + + /* Disperse patterns arising in nested frozensets */ hash = hash * 69069U + 907133923UL; + + /* -1 is reserved as an error code */ if (hash == (Py_uhash_t)-1) hash = 590923713UL; + so->hash = hash; return hash; } @@ -868,7 +943,7 @@ PyTypeObject PySetIter_Type = { PyObject_GenericGetAttr, /* tp_getattro */ 0, /* tp_setattro */ 0, /* tp_as_buffer */ - Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC,/* tp_flags */ + Py_TPFLAGS_DEFAULT | Py_TPFLAGS_HAVE_GC, /* tp_flags */ 0, /* tp_doc */ (traverseproc)setiter_traverse, /* tp_traverse */ 0, /* tp_clear */ @@ -913,18 +988,14 @@ set_update_internal(PySetObject *so, PyObject *other) * incrementally resizing as we insert new keys. Expect * that there will be no (or few) overlapping keys. */ - if (dictsize == -1) + if (dictsize < 0) return -1; - if ((so->fill + dictsize)*3 >= (so->mask+1)*2) { - if (set_table_resize(so, (so->used + dictsize)*2) != 0) + if ((so->fill + dictsize)*3 >= so->mask*2) { + if (set_table_resize(so, so->used + dictsize) != 0) return -1; } while (_PyDict_Next(other, &pos, &key, &value, &hash)) { - setentry an_entry; - - an_entry.hash = hash; - an_entry.key = key; - if (set_add_entry(so, &an_entry)) + if (set_add_entry(so, key, hash)) return -1; } return 0; @@ -1204,6 +1275,8 @@ set_intersection(PySetObject *so, PyObject *other) { PySetObject *result; PyObject *key, *it, *tmp; + Py_hash_t hash; + int rv; if ((PyObject *)so == other) return set_copy(so); @@ -1223,13 +1296,15 @@ set_intersection(PySetObject *so, PyObject *other) } while (set_next((PySetObject *)other, &pos, &entry)) { - int rv = set_contains_entry(so, entry); - if (rv == -1) { + key = entry->key; + hash = entry->hash; + rv = set_contains_entry(so, key, hash); + if (rv < 0) { Py_DECREF(result); return NULL; } if (rv) { - if (set_add_entry(result, entry)) { + if (set_add_entry(result, key, hash)) { Py_DECREF(result); return NULL; } @@ -1245,32 +1320,15 @@ set_intersection(PySetObject *so, PyObject *other) } while ((key = PyIter_Next(it)) != NULL) { - int rv; - setentry entry; - Py_hash_t hash = PyObject_Hash(key); - - if (hash == -1) { - Py_DECREF(it); - Py_DECREF(result); - Py_DECREF(key); - return NULL; - } - entry.hash = hash; - entry.key = key; - rv = set_contains_entry(so, &entry); - if (rv == -1) { - Py_DECREF(it); - Py_DECREF(result); - Py_DECREF(key); - return NULL; - } + hash = PyObject_Hash(key); + if (hash == -1) + goto error; + rv = set_contains_entry(so, key, hash); + if (rv < 0) + goto error; if (rv) { - if (set_add_entry(result, &entry)) { - Py_DECREF(it); - Py_DECREF(result); - Py_DECREF(key); - return NULL; - } + if (set_add_entry(result, key, hash)) + goto error; } Py_DECREF(key); } @@ -1280,6 +1338,11 @@ set_intersection(PySetObject *so, PyObject *other) return NULL; } return (PyObject *)result; + error: + Py_DECREF(it); + Py_DECREF(result); + Py_DECREF(key); + return NULL; } static PyObject * @@ -1366,6 +1429,7 @@ static PyObject * set_isdisjoint(PySetObject *so, PyObject *other) { PyObject *key, *it, *tmp; + int rv; if ((PyObject *)so == other) { if (PySet_GET_SIZE(so) == 0) @@ -1384,8 +1448,8 @@ set_isdisjoint(PySetObject *so, PyObject *other) other = tmp; } while (set_next((PySetObject *)other, &pos, &entry)) { - int rv = set_contains_entry(so, entry); - if (rv == -1) + rv = set_contains_entry(so, entry->key, entry->hash); + if (rv < 0) return NULL; if (rv) Py_RETURN_FALSE; @@ -1398,8 +1462,6 @@ set_isdisjoint(PySetObject *so, PyObject *other) return NULL; while ((key = PyIter_Next(it)) != NULL) { - int rv; - setentry entry; Py_hash_t hash = PyObject_Hash(key); if (hash == -1) { @@ -1407,11 +1469,9 @@ set_isdisjoint(PySetObject *so, PyObject *other) Py_DECREF(it); return NULL; } - entry.hash = hash; - entry.key = key; - rv = set_contains_entry(so, &entry); + rv = set_contains_entry(so, key, hash); Py_DECREF(key); - if (rv == -1) { + if (rv < 0) { Py_DECREF(it); return NULL; } @@ -1440,7 +1500,7 @@ set_difference_update_internal(PySetObject *so, PyObject *other) Py_ssize_t pos = 0; while (set_next((PySetObject *)other, &pos, &entry)) - if (set_discard_entry(so, entry) == -1) + if (set_discard_entry(so, entry->key, entry->hash) < 0) return -1; } else { PyObject *key, *it; @@ -1449,7 +1509,7 @@ set_difference_update_internal(PySetObject *so, PyObject *other) return -1; while ((key = PyIter_Next(it)) != NULL) { - if (set_discard_key(so, key) == -1) { + if (set_discard_key(so, key) < 0) { Py_DECREF(it); Py_DECREF(key); return -1; @@ -1460,10 +1520,10 @@ set_difference_update_internal(PySetObject *so, PyObject *other) if (PyErr_Occurred()) return -1; } - /* If more than 1/5 are dummies, then resize them away. */ - if ((so->fill - so->used) * 5 < so->mask) + /* If more than 1/4th are dummies, then resize them away. */ + if ((size_t)(so->fill - so->used) <= (size_t)so->mask / 4) return 0; - return set_table_resize(so, so->used>50000 ? so->used*2 : so->used*4); + return set_table_resize(so, so->used); } static PyObject * @@ -1490,7 +1550,7 @@ set_copy_and_difference(PySetObject *so, PyObject *other) result = set_copy(so); if (result == NULL) return NULL; - if (set_difference_update_internal((PySetObject *) result, other) != -1) + if (set_difference_update_internal((PySetObject *) result, other) == 0) return result; Py_DECREF(result); return NULL; @@ -1500,8 +1560,11 @@ static PyObject * set_difference(PySetObject *so, PyObject *other) { PyObject *result; + PyObject *key; + Py_hash_t hash; setentry *entry; Py_ssize_t pos = 0; + int rv; if (!PyAnySet_Check(other) && !PyDict_CheckExact(other)) { return set_copy_and_difference(so, other); @@ -1519,17 +1582,15 @@ set_difference(PySetObject *so, PyObject *other) if (PyDict_CheckExact(other)) { while (set_next(so, &pos, &entry)) { - setentry entrycopy; - int rv; - entrycopy.hash = entry->hash; - entrycopy.key = entry->key; - rv = _PyDict_Contains(other, entry->key, entry->hash); + key = entry->key; + hash = entry->hash; + rv = _PyDict_Contains(other, key, hash); if (rv < 0) { Py_DECREF(result); return NULL; } if (!rv) { - if (set_add_entry((PySetObject *)result, &entrycopy)) { + if (set_add_entry((PySetObject *)result, key, hash)) { Py_DECREF(result); return NULL; } @@ -1540,13 +1601,15 @@ set_difference(PySetObject *so, PyObject *other) /* Iterate over so, checking for common elements in other. */ while (set_next(so, &pos, &entry)) { - int rv = set_contains_entry((PySetObject *)other, entry); - if (rv == -1) { + key = entry->key; + hash = entry->hash; + rv = set_contains_entry((PySetObject *)other, key, hash); + if (rv < 0) { Py_DECREF(result); return NULL; } if (!rv) { - if (set_add_entry((PySetObject *)result, entry)) { + if (set_add_entry((PySetObject *)result, key, hash)) { Py_DECREF(result); return NULL; } @@ -1608,29 +1671,24 @@ set_symmetric_difference_update(PySetObject *so, PyObject *other) PySetObject *otherset; PyObject *key; Py_ssize_t pos = 0; + Py_hash_t hash; setentry *entry; + int rv; if ((PyObject *)so == other) return set_clear(so); if (PyDict_CheckExact(other)) { PyObject *value; - int rv; - Py_hash_t hash; while (_PyDict_Next(other, &pos, &key, &value, &hash)) { - setentry an_entry; - Py_INCREF(key); - an_entry.hash = hash; - an_entry.key = key; - - rv = set_discard_entry(so, &an_entry); - if (rv == -1) { + rv = set_discard_entry(so, key, hash); + if (rv < 0) { Py_DECREF(key); return NULL; } if (rv == DISCARD_NOTFOUND) { - if (set_add_entry(so, &an_entry)) { + if (set_add_entry(so, key, hash)) { Py_DECREF(key); return NULL; } @@ -1650,13 +1708,15 @@ set_symmetric_difference_update(PySetObject *so, PyObject *other) } while (set_next(otherset, &pos, &entry)) { - int rv = set_discard_entry(so, entry); - if (rv == -1) { + key = entry->key; + hash = entry->hash; + rv = set_discard_entry(so, key, hash); + if (rv < 0) { Py_DECREF(otherset); return NULL; } if (rv == DISCARD_NOTFOUND) { - if (set_add_entry(so, entry)) { + if (set_add_entry(so, key, hash)) { Py_DECREF(otherset); return NULL; } @@ -1718,6 +1778,7 @@ set_issubset(PySetObject *so, PyObject *other) { setentry *entry; Py_ssize_t pos = 0; + int rv; if (!PyAnySet_Check(other)) { PyObject *tmp, *result; @@ -1732,8 +1793,8 @@ set_issubset(PySetObject *so, PyObject *other) Py_RETURN_FALSE; while (set_next(so, &pos, &entry)) { - int rv = set_contains_entry((PySetObject *)other, entry); - if (rv == -1) + rv = set_contains_entry((PySetObject *)other, entry->key, entry->hash); + if (rv < 0) return NULL; if (!rv) Py_RETURN_FALSE; @@ -1824,7 +1885,7 @@ set_contains(PySetObject *so, PyObject *key) int rv; rv = set_contains_key(so, key); - if (rv == -1) { + if (rv < 0) { if (!PySet_Check(key) || !PyErr_ExceptionMatches(PyExc_TypeError)) return -1; PyErr_Clear(); @@ -1843,7 +1904,7 @@ set_direct_contains(PySetObject *so, PyObject *key) long result; result = set_contains(so, key); - if (result == -1) + if (result < 0) return NULL; return PyBool_FromLong(result); } @@ -1857,7 +1918,7 @@ set_remove(PySetObject *so, PyObject *key) int rv; rv = set_discard_key(so, key); - if (rv == -1) { + if (rv < 0) { if (!PySet_Check(key) || !PyErr_ExceptionMatches(PyExc_TypeError)) return NULL; PyErr_Clear(); @@ -1866,7 +1927,7 @@ set_remove(PySetObject *so, PyObject *key) return NULL; rv = set_discard_key(so, tmpkey); Py_DECREF(tmpkey); - if (rv == -1) + if (rv < 0) return NULL; } @@ -1889,7 +1950,7 @@ set_discard(PySetObject *so, PyObject *key) int rv; rv = set_discard_key(so, key); - if (rv == -1) { + if (rv < 0) { if (!PySet_Check(key) || !PyErr_ExceptionMatches(PyExc_TypeError)) return NULL; PyErr_Clear(); @@ -1898,7 +1959,7 @@ set_discard(PySetObject *so, PyObject *key) return NULL; rv = set_discard_key(so, tmpkey); Py_DECREF(tmpkey); - if (rv == -1) + if (rv < 0) return NULL; } Py_RETURN_NONE; @@ -2125,7 +2186,7 @@ static PyMethodDef frozenset_methods[] = { copy_doc}, {"difference", (PyCFunction)set_difference_multi, METH_VARARGS, difference_doc}, - {"intersection",(PyCFunction)set_intersection_multi, METH_VARARGS, + {"intersection", (PyCFunction)set_intersection_multi, METH_VARARGS, intersection_doc}, {"isdisjoint", (PyCFunction)set_isdisjoint, METH_O, isdisjoint_doc}, @@ -2196,7 +2257,7 @@ PyTypeObject PyFrozenSet_Type = { (traverseproc)set_traverse, /* tp_traverse */ (inquiry)set_clear_internal, /* tp_clear */ (richcmpfunc)set_richcompare, /* tp_richcompare */ - offsetof(PySetObject, weakreflist), /* tp_weaklistoffset */ + offsetof(PySetObject, weakreflist), /* tp_weaklistoffset */ (getiterfunc)set_iter, /* tp_iter */ 0, /* tp_iternext */ frozenset_methods, /* tp_methods */ diff --git a/Objects/unicodeobject.c b/Objects/unicodeobject.c index 9223c99..0709789 100644 --- a/Objects/unicodeobject.c +++ b/Objects/unicodeobject.c @@ -42,6 +42,7 @@ OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE. #include "Python.h" #include "ucnhash.h" #include "bytes_methods.h" +#include "stringlib/eq.h" #ifdef MS_WINDOWS #include <windows.h> @@ -10887,6 +10888,12 @@ PyUnicode_RichCompare(PyObject *left, PyObject *right, int op) } int +_PyUnicode_EQ(PyObject *aa, PyObject *bb) +{ + return unicode_eq(aa, bb); +} + +int PyUnicode_Contains(PyObject *container, PyObject *element) { PyObject *str, *sub; diff --git a/PC/example_nt/example.vcproj b/PC/example_nt/example.vcproj index d82f76e..958eb78 100644 --- a/PC/example_nt/example.vcproj +++ b/PC/example_nt/example.vcproj @@ -39,7 +39,7 @@ <Tool
Name="VCLinkerTool"
AdditionalOptions="/export:initexample"
- AdditionalDependencies="odbc32.lib odbccp32.lib python35.lib"
+ AdditionalDependencies="odbc32.lib odbccp32.lib python36.lib"
OutputFile=".\Release/example.pyd"
LinkIncremental="1"
SuppressStartupBanner="TRUE"
@@ -105,7 +105,7 @@ <Tool
Name="VCLinkerTool"
AdditionalOptions="/export:initexample"
- AdditionalDependencies="odbc32.lib odbccp32.lib python35_d.lib"
+ AdditionalDependencies="odbc32.lib odbccp32.lib python36_d.lib"
OutputFile=".\Debug/example_d.pyd"
LinkIncremental="1"
SuppressStartupBanner="TRUE"
diff --git a/PC/pyconfig.h b/PC/pyconfig.h index 324a130..40c9305 100644 --- a/PC/pyconfig.h +++ b/PC/pyconfig.h @@ -304,11 +304,11 @@ Py_NO_ENABLE_SHARED to find out. Also support MS_NO_COREDLL for b/w compat */ their Makefile (other compilers are generally taken care of by distutils.) */ # if defined(_DEBUG) -# pragma comment(lib,"python35_d.lib") +# pragma comment(lib,"python36_d.lib") # elif defined(Py_LIMITED_API) # pragma comment(lib,"python3.lib") # else -# pragma comment(lib,"python35.lib") +# pragma comment(lib,"python36.lib") # endif /* _DEBUG */ # endif /* _MSC_VER */ # endif /* Py_BUILD_CORE */ diff --git a/PC/python3.def b/PC/python3.def index 88c0742..e146e8f 100644 --- a/PC/python3.def +++ b/PC/python3.def @@ -2,712 +2,712 @@ ; It is used when building python3dll.vcxproj LIBRARY "python3" EXPORTS - PyArg_Parse=python35.PyArg_Parse - PyArg_ParseTuple=python35.PyArg_ParseTuple - PyArg_ParseTupleAndKeywords=python35.PyArg_ParseTupleAndKeywords - PyArg_UnpackTuple=python35.PyArg_UnpackTuple - PyArg_VaParse=python35.PyArg_VaParse - PyArg_VaParseTupleAndKeywords=python35.PyArg_VaParseTupleAndKeywords - PyArg_ValidateKeywordArguments=python35.PyArg_ValidateKeywordArguments - PyBaseObject_Type=python35.PyBaseObject_Type DATA - PyBool_FromLong=python35.PyBool_FromLong - PyBool_Type=python35.PyBool_Type DATA - PyByteArrayIter_Type=python35.PyByteArrayIter_Type DATA - PyByteArray_AsString=python35.PyByteArray_AsString - PyByteArray_Concat=python35.PyByteArray_Concat - PyByteArray_FromObject=python35.PyByteArray_FromObject - PyByteArray_FromStringAndSize=python35.PyByteArray_FromStringAndSize - PyByteArray_Resize=python35.PyByteArray_Resize - PyByteArray_Size=python35.PyByteArray_Size - PyByteArray_Type=python35.PyByteArray_Type DATA - PyBytesIter_Type=python35.PyBytesIter_Type DATA - PyBytes_AsString=python35.PyBytes_AsString - PyBytes_AsStringAndSize=python35.PyBytes_AsStringAndSize - PyBytes_Concat=python35.PyBytes_Concat - PyBytes_ConcatAndDel=python35.PyBytes_ConcatAndDel - PyBytes_DecodeEscape=python35.PyBytes_DecodeEscape - PyBytes_FromFormat=python35.PyBytes_FromFormat - PyBytes_FromFormatV=python35.PyBytes_FromFormatV - PyBytes_FromObject=python35.PyBytes_FromObject - PyBytes_FromString=python35.PyBytes_FromString - PyBytes_FromStringAndSize=python35.PyBytes_FromStringAndSize - PyBytes_Repr=python35.PyBytes_Repr - PyBytes_Size=python35.PyBytes_Size - PyBytes_Type=python35.PyBytes_Type DATA - PyCFunction_Call=python35.PyCFunction_Call - PyCFunction_ClearFreeList=python35.PyCFunction_ClearFreeList - PyCFunction_GetFlags=python35.PyCFunction_GetFlags - PyCFunction_GetFunction=python35.PyCFunction_GetFunction - PyCFunction_GetSelf=python35.PyCFunction_GetSelf - PyCFunction_New=python35.PyCFunction_New - PyCFunction_NewEx=python35.PyCFunction_NewEx - PyCFunction_Type=python35.PyCFunction_Type DATA - PyCallIter_New=python35.PyCallIter_New - PyCallIter_Type=python35.PyCallIter_Type DATA - PyCallable_Check=python35.PyCallable_Check - PyCapsule_GetContext=python35.PyCapsule_GetContext - PyCapsule_GetDestructor=python35.PyCapsule_GetDestructor - PyCapsule_GetName=python35.PyCapsule_GetName - PyCapsule_GetPointer=python35.PyCapsule_GetPointer - PyCapsule_Import=python35.PyCapsule_Import - PyCapsule_IsValid=python35.PyCapsule_IsValid - PyCapsule_New=python35.PyCapsule_New - PyCapsule_SetContext=python35.PyCapsule_SetContext - PyCapsule_SetDestructor=python35.PyCapsule_SetDestructor - PyCapsule_SetName=python35.PyCapsule_SetName - PyCapsule_SetPointer=python35.PyCapsule_SetPointer - PyCapsule_Type=python35.PyCapsule_Type DATA - PyClassMethodDescr_Type=python35.PyClassMethodDescr_Type DATA - PyCodec_BackslashReplaceErrors=python35.PyCodec_BackslashReplaceErrors - PyCodec_Decode=python35.PyCodec_Decode - PyCodec_Decoder=python35.PyCodec_Decoder - PyCodec_Encode=python35.PyCodec_Encode - PyCodec_Encoder=python35.PyCodec_Encoder - PyCodec_IgnoreErrors=python35.PyCodec_IgnoreErrors - PyCodec_IncrementalDecoder=python35.PyCodec_IncrementalDecoder - PyCodec_IncrementalEncoder=python35.PyCodec_IncrementalEncoder - PyCodec_KnownEncoding=python35.PyCodec_KnownEncoding - PyCodec_LookupError=python35.PyCodec_LookupError - PyCodec_Register=python35.PyCodec_Register - PyCodec_RegisterError=python35.PyCodec_RegisterError - PyCodec_ReplaceErrors=python35.PyCodec_ReplaceErrors - PyCodec_StreamReader=python35.PyCodec_StreamReader - PyCodec_StreamWriter=python35.PyCodec_StreamWriter - PyCodec_StrictErrors=python35.PyCodec_StrictErrors - PyCodec_XMLCharRefReplaceErrors=python35.PyCodec_XMLCharRefReplaceErrors - PyComplex_FromDoubles=python35.PyComplex_FromDoubles - PyComplex_ImagAsDouble=python35.PyComplex_ImagAsDouble - PyComplex_RealAsDouble=python35.PyComplex_RealAsDouble - PyComplex_Type=python35.PyComplex_Type DATA - PyDescr_NewClassMethod=python35.PyDescr_NewClassMethod - PyDescr_NewGetSet=python35.PyDescr_NewGetSet - PyDescr_NewMember=python35.PyDescr_NewMember - PyDescr_NewMethod=python35.PyDescr_NewMethod - PyDictItems_Type=python35.PyDictItems_Type DATA - PyDictIterItem_Type=python35.PyDictIterItem_Type DATA - PyDictIterKey_Type=python35.PyDictIterKey_Type DATA - PyDictIterValue_Type=python35.PyDictIterValue_Type DATA - PyDictKeys_Type=python35.PyDictKeys_Type DATA - PyDictProxy_New=python35.PyDictProxy_New - PyDictProxy_Type=python35.PyDictProxy_Type DATA - PyDictValues_Type=python35.PyDictValues_Type DATA - PyDict_Clear=python35.PyDict_Clear - PyDict_Contains=python35.PyDict_Contains - PyDict_Copy=python35.PyDict_Copy - PyDict_DelItem=python35.PyDict_DelItem - PyDict_DelItemString=python35.PyDict_DelItemString - PyDict_GetItem=python35.PyDict_GetItem - PyDict_GetItemString=python35.PyDict_GetItemString - PyDict_GetItemWithError=python35.PyDict_GetItemWithError - PyDict_Items=python35.PyDict_Items - PyDict_Keys=python35.PyDict_Keys - PyDict_Merge=python35.PyDict_Merge - PyDict_MergeFromSeq2=python35.PyDict_MergeFromSeq2 - PyDict_New=python35.PyDict_New - PyDict_Next=python35.PyDict_Next - PyDict_SetItem=python35.PyDict_SetItem - PyDict_SetItemString=python35.PyDict_SetItemString - PyDict_Size=python35.PyDict_Size - PyDict_Type=python35.PyDict_Type DATA - PyDict_Update=python35.PyDict_Update - PyDict_Values=python35.PyDict_Values - PyEllipsis_Type=python35.PyEllipsis_Type DATA - PyEnum_Type=python35.PyEnum_Type DATA - PyErr_BadArgument=python35.PyErr_BadArgument - PyErr_BadInternalCall=python35.PyErr_BadInternalCall - PyErr_CheckSignals=python35.PyErr_CheckSignals - PyErr_Clear=python35.PyErr_Clear - PyErr_Display=python35.PyErr_Display - PyErr_ExceptionMatches=python35.PyErr_ExceptionMatches - PyErr_Fetch=python35.PyErr_Fetch - PyErr_Format=python35.PyErr_Format - PyErr_FormatV=python35.PyErr_FormatV - PyErr_GivenExceptionMatches=python35.PyErr_GivenExceptionMatches - PyErr_NewException=python35.PyErr_NewException - PyErr_NewExceptionWithDoc=python35.PyErr_NewExceptionWithDoc - PyErr_NoMemory=python35.PyErr_NoMemory - PyErr_NormalizeException=python35.PyErr_NormalizeException - 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PyArg_VaParseTupleAndKeywords=python36.PyArg_VaParseTupleAndKeywords + PyArg_ValidateKeywordArguments=python36.PyArg_ValidateKeywordArguments + PyBaseObject_Type=python36.PyBaseObject_Type DATA + PyBool_FromLong=python36.PyBool_FromLong + PyBool_Type=python36.PyBool_Type DATA + PyByteArrayIter_Type=python36.PyByteArrayIter_Type DATA + PyByteArray_AsString=python36.PyByteArray_AsString + PyByteArray_Concat=python36.PyByteArray_Concat + PyByteArray_FromObject=python36.PyByteArray_FromObject + PyByteArray_FromStringAndSize=python36.PyByteArray_FromStringAndSize + PyByteArray_Resize=python36.PyByteArray_Resize + PyByteArray_Size=python36.PyByteArray_Size + PyByteArray_Type=python36.PyByteArray_Type DATA + PyBytesIter_Type=python36.PyBytesIter_Type DATA + PyBytes_AsString=python36.PyBytes_AsString + PyBytes_AsStringAndSize=python36.PyBytes_AsStringAndSize + PyBytes_Concat=python36.PyBytes_Concat + PyBytes_ConcatAndDel=python36.PyBytes_ConcatAndDel + PyBytes_DecodeEscape=python36.PyBytes_DecodeEscape + PyBytes_FromFormat=python36.PyBytes_FromFormat + PyBytes_FromFormatV=python36.PyBytes_FromFormatV + PyBytes_FromObject=python36.PyBytes_FromObject + PyBytes_FromString=python36.PyBytes_FromString + PyBytes_FromStringAndSize=python36.PyBytes_FromStringAndSize + PyBytes_Repr=python36.PyBytes_Repr + PyBytes_Size=python36.PyBytes_Size + PyBytes_Type=python36.PyBytes_Type DATA + PyCFunction_Call=python36.PyCFunction_Call + PyCFunction_ClearFreeList=python36.PyCFunction_ClearFreeList + PyCFunction_GetFlags=python36.PyCFunction_GetFlags + PyCFunction_GetFunction=python36.PyCFunction_GetFunction + PyCFunction_GetSelf=python36.PyCFunction_GetSelf + PyCFunction_New=python36.PyCFunction_New + PyCFunction_NewEx=python36.PyCFunction_NewEx + PyCFunction_Type=python36.PyCFunction_Type DATA + PyCallIter_New=python36.PyCallIter_New + PyCallIter_Type=python36.PyCallIter_Type DATA + PyCallable_Check=python36.PyCallable_Check + 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PyCodec_IncrementalDecoder=python36.PyCodec_IncrementalDecoder + PyCodec_IncrementalEncoder=python36.PyCodec_IncrementalEncoder + PyCodec_KnownEncoding=python36.PyCodec_KnownEncoding + PyCodec_LookupError=python36.PyCodec_LookupError + PyCodec_Register=python36.PyCodec_Register + PyCodec_RegisterError=python36.PyCodec_RegisterError + PyCodec_ReplaceErrors=python36.PyCodec_ReplaceErrors + PyCodec_StreamReader=python36.PyCodec_StreamReader + PyCodec_StreamWriter=python36.PyCodec_StreamWriter + PyCodec_StrictErrors=python36.PyCodec_StrictErrors + PyCodec_XMLCharRefReplaceErrors=python36.PyCodec_XMLCharRefReplaceErrors + PyComplex_FromDoubles=python36.PyComplex_FromDoubles + PyComplex_ImagAsDouble=python36.PyComplex_ImagAsDouble + PyComplex_RealAsDouble=python36.PyComplex_RealAsDouble + PyComplex_Type=python36.PyComplex_Type DATA + PyDescr_NewClassMethod=python36.PyDescr_NewClassMethod + PyDescr_NewGetSet=python36.PyDescr_NewGetSet + PyDescr_NewMember=python36.PyDescr_NewMember + PyDescr_NewMethod=python36.PyDescr_NewMethod + PyDictItems_Type=python36.PyDictItems_Type DATA + PyDictIterItem_Type=python36.PyDictIterItem_Type DATA + PyDictIterKey_Type=python36.PyDictIterKey_Type DATA + PyDictIterValue_Type=python36.PyDictIterValue_Type DATA + PyDictKeys_Type=python36.PyDictKeys_Type DATA + PyDictProxy_New=python36.PyDictProxy_New + PyDictProxy_Type=python36.PyDictProxy_Type DATA + PyDictValues_Type=python36.PyDictValues_Type DATA + PyDict_Clear=python36.PyDict_Clear + PyDict_Contains=python36.PyDict_Contains + PyDict_Copy=python36.PyDict_Copy + PyDict_DelItem=python36.PyDict_DelItem + PyDict_DelItemString=python36.PyDict_DelItemString + PyDict_GetItem=python36.PyDict_GetItem + PyDict_GetItemString=python36.PyDict_GetItemString + PyDict_GetItemWithError=python36.PyDict_GetItemWithError + PyDict_Items=python36.PyDict_Items + PyDict_Keys=python36.PyDict_Keys + PyDict_Merge=python36.PyDict_Merge + PyDict_MergeFromSeq2=python36.PyDict_MergeFromSeq2 + PyDict_New=python36.PyDict_New + PyDict_Next=python36.PyDict_Next + PyDict_SetItem=python36.PyDict_SetItem + PyDict_SetItemString=python36.PyDict_SetItemString + PyDict_Size=python36.PyDict_Size + PyDict_Type=python36.PyDict_Type DATA + PyDict_Update=python36.PyDict_Update + PyDict_Values=python36.PyDict_Values + PyEllipsis_Type=python36.PyEllipsis_Type DATA + PyEnum_Type=python36.PyEnum_Type DATA + PyErr_BadArgument=python36.PyErr_BadArgument + PyErr_BadInternalCall=python36.PyErr_BadInternalCall + PyErr_CheckSignals=python36.PyErr_CheckSignals + PyErr_Clear=python36.PyErr_Clear + PyErr_Display=python36.PyErr_Display + PyErr_ExceptionMatches=python36.PyErr_ExceptionMatches + PyErr_Fetch=python36.PyErr_Fetch + PyErr_Format=python36.PyErr_Format + PyErr_FormatV=python36.PyErr_FormatV + PyErr_GivenExceptionMatches=python36.PyErr_GivenExceptionMatches + PyErr_NewException=python36.PyErr_NewException + PyErr_NewExceptionWithDoc=python36.PyErr_NewExceptionWithDoc + PyErr_NoMemory=python36.PyErr_NoMemory + PyErr_NormalizeException=python36.PyErr_NormalizeException + PyErr_Occurred=python36.PyErr_Occurred + PyErr_Print=python36.PyErr_Print + PyErr_PrintEx=python36.PyErr_PrintEx + PyErr_ProgramText=python36.PyErr_ProgramText + PyErr_Restore=python36.PyErr_Restore + PyErr_SetFromErrno=python36.PyErr_SetFromErrno + PyErr_SetFromErrnoWithFilename=python36.PyErr_SetFromErrnoWithFilename + PyErr_SetFromErrnoWithFilenameObject=python36.PyErr_SetFromErrnoWithFilenameObject + PyErr_SetInterrupt=python36.PyErr_SetInterrupt + PyErr_SetNone=python36.PyErr_SetNone + PyErr_SetObject=python36.PyErr_SetObject + PyErr_SetString=python36.PyErr_SetString + PyErr_SyntaxLocation=python36.PyErr_SyntaxLocation + PyErr_WarnEx=python36.PyErr_WarnEx + PyErr_WarnExplicit=python36.PyErr_WarnExplicit + PyErr_WarnFormat=python36.PyErr_WarnFormat + PyErr_WriteUnraisable=python36.PyErr_WriteUnraisable + PyEval_AcquireLock=python36.PyEval_AcquireLock + PyEval_AcquireThread=python36.PyEval_AcquireThread + PyEval_CallFunction=python36.PyEval_CallFunction + PyEval_CallMethod=python36.PyEval_CallMethod + PyEval_CallObjectWithKeywords=python36.PyEval_CallObjectWithKeywords + PyEval_EvalCode=python36.PyEval_EvalCode + PyEval_EvalCodeEx=python36.PyEval_EvalCodeEx + PyEval_EvalFrame=python36.PyEval_EvalFrame + PyEval_EvalFrameEx=python36.PyEval_EvalFrameEx + PyEval_GetBuiltins=python36.PyEval_GetBuiltins + PyEval_GetCallStats=python36.PyEval_GetCallStats + PyEval_GetFrame=python36.PyEval_GetFrame + PyEval_GetFuncDesc=python36.PyEval_GetFuncDesc + PyEval_GetFuncName=python36.PyEval_GetFuncName + PyEval_GetGlobals=python36.PyEval_GetGlobals + PyEval_GetLocals=python36.PyEval_GetLocals + PyEval_InitThreads=python36.PyEval_InitThreads + PyEval_ReInitThreads=python36.PyEval_ReInitThreads + PyEval_ReleaseLock=python36.PyEval_ReleaseLock + PyEval_ReleaseThread=python36.PyEval_ReleaseThread + PyEval_RestoreThread=python36.PyEval_RestoreThread + PyEval_SaveThread=python36.PyEval_SaveThread + PyEval_ThreadsInitialized=python36.PyEval_ThreadsInitialized + PyExc_ArithmeticError=python36.PyExc_ArithmeticError DATA + PyExc_AssertionError=python36.PyExc_AssertionError DATA + PyExc_AttributeError=python36.PyExc_AttributeError DATA + PyExc_BaseException=python36.PyExc_BaseException DATA + PyExc_BufferError=python36.PyExc_BufferError DATA + PyExc_BytesWarning=python36.PyExc_BytesWarning DATA + PyExc_DeprecationWarning=python36.PyExc_DeprecationWarning DATA + PyExc_EOFError=python36.PyExc_EOFError DATA + PyExc_EnvironmentError=python36.PyExc_EnvironmentError DATA + PyExc_Exception=python36.PyExc_Exception DATA + PyExc_FloatingPointError=python36.PyExc_FloatingPointError DATA + PyExc_FutureWarning=python36.PyExc_FutureWarning DATA + PyExc_GeneratorExit=python36.PyExc_GeneratorExit DATA + PyExc_IOError=python36.PyExc_IOError DATA + PyExc_ImportError=python36.PyExc_ImportError DATA + PyExc_ImportWarning=python36.PyExc_ImportWarning DATA + PyExc_IndentationError=python36.PyExc_IndentationError DATA + PyExc_IndexError=python36.PyExc_IndexError DATA + PyExc_KeyError=python36.PyExc_KeyError DATA + PyExc_KeyboardInterrupt=python36.PyExc_KeyboardInterrupt DATA + PyExc_LookupError=python36.PyExc_LookupError DATA + PyExc_MemoryError=python36.PyExc_MemoryError DATA + PyExc_MemoryErrorInst=python36.PyExc_MemoryErrorInst DATA + PyExc_NameError=python36.PyExc_NameError DATA + PyExc_NotImplementedError=python36.PyExc_NotImplementedError DATA + PyExc_OSError=python36.PyExc_OSError DATA + PyExc_OverflowError=python36.PyExc_OverflowError DATA + PyExc_PendingDeprecationWarning=python36.PyExc_PendingDeprecationWarning DATA + PyExc_RecursionErrorInst=python36.PyExc_RecursionErrorInst DATA + PyExc_ReferenceError=python36.PyExc_ReferenceError DATA + PyExc_RuntimeError=python36.PyExc_RuntimeError DATA + PyExc_RuntimeWarning=python36.PyExc_RuntimeWarning DATA + PyExc_StopIteration=python36.PyExc_StopIteration DATA + PyExc_SyntaxError=python36.PyExc_SyntaxError DATA + PyExc_SyntaxWarning=python36.PyExc_SyntaxWarning DATA + PyExc_SystemError=python36.PyExc_SystemError DATA + PyExc_SystemExit=python36.PyExc_SystemExit DATA + PyExc_TabError=python36.PyExc_TabError DATA + PyExc_TypeError=python36.PyExc_TypeError DATA + PyExc_UnboundLocalError=python36.PyExc_UnboundLocalError DATA + PyExc_UnicodeDecodeError=python36.PyExc_UnicodeDecodeError DATA + PyExc_UnicodeEncodeError=python36.PyExc_UnicodeEncodeError DATA + PyExc_UnicodeError=python36.PyExc_UnicodeError DATA + PyExc_UnicodeTranslateError=python36.PyExc_UnicodeTranslateError DATA + PyExc_UnicodeWarning=python36.PyExc_UnicodeWarning DATA + PyExc_UserWarning=python36.PyExc_UserWarning DATA + PyExc_ValueError=python36.PyExc_ValueError DATA + PyExc_Warning=python36.PyExc_Warning DATA + PyExc_ZeroDivisionError=python36.PyExc_ZeroDivisionError DATA + PyException_GetCause=python36.PyException_GetCause + PyException_GetContext=python36.PyException_GetContext + PyException_GetTraceback=python36.PyException_GetTraceback + PyException_SetCause=python36.PyException_SetCause + PyException_SetContext=python36.PyException_SetContext + PyException_SetTraceback=python36.PyException_SetTraceback + PyFile_FromFd=python36.PyFile_FromFd + PyFile_GetLine=python36.PyFile_GetLine + PyFile_WriteObject=python36.PyFile_WriteObject + PyFile_WriteString=python36.PyFile_WriteString + PyFilter_Type=python36.PyFilter_Type DATA + PyFloat_AsDouble=python36.PyFloat_AsDouble + PyFloat_FromDouble=python36.PyFloat_FromDouble + PyFloat_FromString=python36.PyFloat_FromString + PyFloat_GetInfo=python36.PyFloat_GetInfo + PyFloat_GetMax=python36.PyFloat_GetMax + PyFloat_GetMin=python36.PyFloat_GetMin + PyFloat_Type=python36.PyFloat_Type DATA + PyFrozenSet_New=python36.PyFrozenSet_New + PyFrozenSet_Type=python36.PyFrozenSet_Type DATA + PyGC_Collect=python36.PyGC_Collect + PyGILState_Ensure=python36.PyGILState_Ensure + PyGILState_GetThisThreadState=python36.PyGILState_GetThisThreadState + PyGILState_Release=python36.PyGILState_Release + PyGetSetDescr_Type=python36.PyGetSetDescr_Type DATA + PyImport_AddModule=python36.PyImport_AddModule + PyImport_AppendInittab=python36.PyImport_AppendInittab + PyImport_Cleanup=python36.PyImport_Cleanup + PyImport_ExecCodeModule=python36.PyImport_ExecCodeModule + PyImport_ExecCodeModuleEx=python36.PyImport_ExecCodeModuleEx + PyImport_ExecCodeModuleWithPathnames=python36.PyImport_ExecCodeModuleWithPathnames + PyImport_GetImporter=python36.PyImport_GetImporter + PyImport_GetMagicNumber=python36.PyImport_GetMagicNumber + PyImport_GetMagicTag=python36.PyImport_GetMagicTag + PyImport_GetModuleDict=python36.PyImport_GetModuleDict + PyImport_Import=python36.PyImport_Import + PyImport_ImportFrozenModule=python36.PyImport_ImportFrozenModule + PyImport_ImportModule=python36.PyImport_ImportModule + PyImport_ImportModuleLevel=python36.PyImport_ImportModuleLevel + PyImport_ImportModuleNoBlock=python36.PyImport_ImportModuleNoBlock + PyImport_ReloadModule=python36.PyImport_ReloadModule + PyInterpreterState_Clear=python36.PyInterpreterState_Clear + PyInterpreterState_Delete=python36.PyInterpreterState_Delete + PyInterpreterState_New=python36.PyInterpreterState_New + PyIter_Next=python36.PyIter_Next + PyListIter_Type=python36.PyListIter_Type DATA + PyListRevIter_Type=python36.PyListRevIter_Type DATA + PyList_Append=python36.PyList_Append + PyList_AsTuple=python36.PyList_AsTuple + PyList_GetItem=python36.PyList_GetItem + PyList_GetSlice=python36.PyList_GetSlice + PyList_Insert=python36.PyList_Insert + PyList_New=python36.PyList_New + PyList_Reverse=python36.PyList_Reverse + PyList_SetItem=python36.PyList_SetItem + PyList_SetSlice=python36.PyList_SetSlice + PyList_Size=python36.PyList_Size + PyList_Sort=python36.PyList_Sort + PyList_Type=python36.PyList_Type DATA + PyLongRangeIter_Type=python36.PyLongRangeIter_Type DATA + PyLong_AsDouble=python36.PyLong_AsDouble + PyLong_AsLong=python36.PyLong_AsLong + PyLong_AsLongAndOverflow=python36.PyLong_AsLongAndOverflow + PyLong_AsLongLong=python36.PyLong_AsLongLong + PyLong_AsLongLongAndOverflow=python36.PyLong_AsLongLongAndOverflow + PyLong_AsSize_t=python36.PyLong_AsSize_t + PyLong_AsSsize_t=python36.PyLong_AsSsize_t + PyLong_AsUnsignedLong=python36.PyLong_AsUnsignedLong + PyLong_AsUnsignedLongLong=python36.PyLong_AsUnsignedLongLong + PyLong_AsUnsignedLongLongMask=python36.PyLong_AsUnsignedLongLongMask + PyLong_AsUnsignedLongMask=python36.PyLong_AsUnsignedLongMask + PyLong_AsVoidPtr=python36.PyLong_AsVoidPtr + PyLong_FromDouble=python36.PyLong_FromDouble + PyLong_FromLong=python36.PyLong_FromLong + PyLong_FromLongLong=python36.PyLong_FromLongLong + PyLong_FromSize_t=python36.PyLong_FromSize_t + PyLong_FromSsize_t=python36.PyLong_FromSsize_t + PyLong_FromString=python36.PyLong_FromString + PyLong_FromUnsignedLong=python36.PyLong_FromUnsignedLong + PyLong_FromUnsignedLongLong=python36.PyLong_FromUnsignedLongLong + PyLong_FromVoidPtr=python36.PyLong_FromVoidPtr + PyLong_GetInfo=python36.PyLong_GetInfo + PyLong_Type=python36.PyLong_Type DATA + PyMap_Type=python36.PyMap_Type DATA + PyMapping_Check=python36.PyMapping_Check + PyMapping_GetItemString=python36.PyMapping_GetItemString + PyMapping_HasKey=python36.PyMapping_HasKey + PyMapping_HasKeyString=python36.PyMapping_HasKeyString + PyMapping_Items=python36.PyMapping_Items + PyMapping_Keys=python36.PyMapping_Keys + PyMapping_Length=python36.PyMapping_Length + PyMapping_SetItemString=python36.PyMapping_SetItemString + PyMapping_Size=python36.PyMapping_Size + PyMapping_Values=python36.PyMapping_Values + PyMem_Free=python36.PyMem_Free + PyMem_Malloc=python36.PyMem_Malloc + PyMem_Realloc=python36.PyMem_Realloc + PyMemberDescr_Type=python36.PyMemberDescr_Type DATA + PyMemoryView_FromObject=python36.PyMemoryView_FromObject + PyMemoryView_GetContiguous=python36.PyMemoryView_GetContiguous + PyMemoryView_Type=python36.PyMemoryView_Type DATA + PyMethodDescr_Type=python36.PyMethodDescr_Type DATA + PyModule_AddIntConstant=python36.PyModule_AddIntConstant + PyModule_AddObject=python36.PyModule_AddObject + PyModule_AddStringConstant=python36.PyModule_AddStringConstant + PyModule_Create2=python36.PyModule_Create2 + PyModule_GetDef=python36.PyModule_GetDef + PyModule_GetDict=python36.PyModule_GetDict + PyModule_GetFilename=python36.PyModule_GetFilename + PyModule_GetFilenameObject=python36.PyModule_GetFilenameObject + PyModule_GetName=python36.PyModule_GetName + PyModule_GetState=python36.PyModule_GetState + PyModule_New=python36.PyModule_New + PyModule_Type=python36.PyModule_Type DATA + PyModuleDef_Init=python36.PyModuleDef_Init + PyModuleDef_Type=python36.PyModuleDef_Type DATA + PyNullImporter_Type=python36.PyNullImporter_Type DATA + PyNumber_Absolute=python36.PyNumber_Absolute + PyNumber_Add=python36.PyNumber_Add + PyNumber_And=python36.PyNumber_And + PyNumber_AsSsize_t=python36.PyNumber_AsSsize_t + PyNumber_Check=python36.PyNumber_Check + PyNumber_Divmod=python36.PyNumber_Divmod + PyNumber_Float=python36.PyNumber_Float + PyNumber_FloorDivide=python36.PyNumber_FloorDivide + PyNumber_InPlaceAdd=python36.PyNumber_InPlaceAdd + PyNumber_InPlaceAnd=python36.PyNumber_InPlaceAnd + PyNumber_InPlaceFloorDivide=python36.PyNumber_InPlaceFloorDivide + PyNumber_InPlaceLshift=python36.PyNumber_InPlaceLshift + PyNumber_InPlaceMultiply=python36.PyNumber_InPlaceMultiply + PyNumber_InPlaceOr=python36.PyNumber_InPlaceOr + PyNumber_InPlacePower=python36.PyNumber_InPlacePower + PyNumber_InPlaceRemainder=python36.PyNumber_InPlaceRemainder + PyNumber_InPlaceRshift=python36.PyNumber_InPlaceRshift + PyNumber_InPlaceSubtract=python36.PyNumber_InPlaceSubtract + PyNumber_InPlaceTrueDivide=python36.PyNumber_InPlaceTrueDivide + PyNumber_InPlaceXor=python36.PyNumber_InPlaceXor + PyNumber_Index=python36.PyNumber_Index + PyNumber_Invert=python36.PyNumber_Invert + PyNumber_Long=python36.PyNumber_Long + PyNumber_Lshift=python36.PyNumber_Lshift + PyNumber_Multiply=python36.PyNumber_Multiply + PyNumber_Negative=python36.PyNumber_Negative + PyNumber_Or=python36.PyNumber_Or + PyNumber_Positive=python36.PyNumber_Positive + PyNumber_Power=python36.PyNumber_Power + PyNumber_Remainder=python36.PyNumber_Remainder + PyNumber_Rshift=python36.PyNumber_Rshift + PyNumber_Subtract=python36.PyNumber_Subtract + PyNumber_ToBase=python36.PyNumber_ToBase + PyNumber_TrueDivide=python36.PyNumber_TrueDivide + PyNumber_Xor=python36.PyNumber_Xor + PyOS_AfterFork=python36.PyOS_AfterFork + PyOS_InitInterrupts=python36.PyOS_InitInterrupts + PyOS_InputHook=python36.PyOS_InputHook DATA + PyOS_InterruptOccurred=python36.PyOS_InterruptOccurred + PyOS_ReadlineFunctionPointer=python36.PyOS_ReadlineFunctionPointer DATA + PyOS_double_to_string=python36.PyOS_double_to_string + PyOS_getsig=python36.PyOS_getsig + PyOS_mystricmp=python36.PyOS_mystricmp + PyOS_mystrnicmp=python36.PyOS_mystrnicmp + PyOS_setsig=python36.PyOS_setsig + PyOS_snprintf=python36.PyOS_snprintf + PyOS_string_to_double=python36.PyOS_string_to_double + PyOS_strtol=python36.PyOS_strtol + PyOS_strtoul=python36.PyOS_strtoul + PyOS_vsnprintf=python36.PyOS_vsnprintf + PyObject_ASCII=python36.PyObject_ASCII + PyObject_AsCharBuffer=python36.PyObject_AsCharBuffer + PyObject_AsFileDescriptor=python36.PyObject_AsFileDescriptor + PyObject_AsReadBuffer=python36.PyObject_AsReadBuffer + PyObject_AsWriteBuffer=python36.PyObject_AsWriteBuffer + PyObject_Bytes=python36.PyObject_Bytes + PyObject_Call=python36.PyObject_Call + PyObject_CallFunction=python36.PyObject_CallFunction + PyObject_CallFunctionObjArgs=python36.PyObject_CallFunctionObjArgs + PyObject_CallMethod=python36.PyObject_CallMethod + PyObject_CallMethodObjArgs=python36.PyObject_CallMethodObjArgs + PyObject_CallObject=python36.PyObject_CallObject + PyObject_CheckReadBuffer=python36.PyObject_CheckReadBuffer + PyObject_ClearWeakRefs=python36.PyObject_ClearWeakRefs + PyObject_DelItem=python36.PyObject_DelItem + PyObject_DelItemString=python36.PyObject_DelItemString + PyObject_Dir=python36.PyObject_Dir + PyObject_Format=python36.PyObject_Format + PyObject_Free=python36.PyObject_Free + PyObject_GC_Del=python36.PyObject_GC_Del + PyObject_GC_Track=python36.PyObject_GC_Track + PyObject_GC_UnTrack=python36.PyObject_GC_UnTrack + PyObject_GenericGetAttr=python36.PyObject_GenericGetAttr + PyObject_GenericSetAttr=python36.PyObject_GenericSetAttr + PyObject_GetAttr=python36.PyObject_GetAttr + PyObject_GetAttrString=python36.PyObject_GetAttrString + PyObject_GetItem=python36.PyObject_GetItem + PyObject_GetIter=python36.PyObject_GetIter + PyObject_HasAttr=python36.PyObject_HasAttr + PyObject_HasAttrString=python36.PyObject_HasAttrString + PyObject_Hash=python36.PyObject_Hash + PyObject_HashNotImplemented=python36.PyObject_HashNotImplemented + PyObject_Init=python36.PyObject_Init + PyObject_InitVar=python36.PyObject_InitVar + PyObject_IsInstance=python36.PyObject_IsInstance + PyObject_IsSubclass=python36.PyObject_IsSubclass + PyObject_IsTrue=python36.PyObject_IsTrue + PyObject_Length=python36.PyObject_Length + PyObject_Malloc=python36.PyObject_Malloc + PyObject_Not=python36.PyObject_Not + PyObject_Realloc=python36.PyObject_Realloc + PyObject_Repr=python36.PyObject_Repr + PyObject_RichCompare=python36.PyObject_RichCompare + PyObject_RichCompareBool=python36.PyObject_RichCompareBool + PyObject_SelfIter=python36.PyObject_SelfIter + PyObject_SetAttr=python36.PyObject_SetAttr + PyObject_SetAttrString=python36.PyObject_SetAttrString + PyObject_SetItem=python36.PyObject_SetItem + PyObject_Size=python36.PyObject_Size + PyObject_Str=python36.PyObject_Str + PyObject_Type=python36.PyObject_Type DATA + PyODict_DelItem=python36.PyODict_DelItem + PyODict_New=python36.PyODict_New + PyODict_SetItem=python36.PyODict_SetItem + PyODict_Type=python36.PyODict_Type DATA + PyODictItems_Type=python36.PyODictItems_Type DATA + PyODictIter_Type=python36.PyODictIter_Type DATA + PyODictKeys_Type=python36.PyODictKeys_Type DATA + PyODictValues_Type=python36.PyODictValues_Type DATA + PyParser_SimpleParseFileFlags=python36.PyParser_SimpleParseFileFlags + PyParser_SimpleParseStringFlags=python36.PyParser_SimpleParseStringFlags + PyProperty_Type=python36.PyProperty_Type DATA + PyRangeIter_Type=python36.PyRangeIter_Type DATA + PyRange_Type=python36.PyRange_Type DATA + PyReversed_Type=python36.PyReversed_Type DATA + PySeqIter_New=python36.PySeqIter_New + PySeqIter_Type=python36.PySeqIter_Type DATA + PySequence_Check=python36.PySequence_Check + PySequence_Concat=python36.PySequence_Concat + PySequence_Contains=python36.PySequence_Contains + PySequence_Count=python36.PySequence_Count + PySequence_DelItem=python36.PySequence_DelItem + PySequence_DelSlice=python36.PySequence_DelSlice + PySequence_Fast=python36.PySequence_Fast + PySequence_GetItem=python36.PySequence_GetItem + PySequence_GetSlice=python36.PySequence_GetSlice + PySequence_In=python36.PySequence_In + PySequence_InPlaceConcat=python36.PySequence_InPlaceConcat + PySequence_InPlaceRepeat=python36.PySequence_InPlaceRepeat + PySequence_Index=python36.PySequence_Index + PySequence_Length=python36.PySequence_Length + PySequence_List=python36.PySequence_List + PySequence_Repeat=python36.PySequence_Repeat + PySequence_SetItem=python36.PySequence_SetItem + PySequence_SetSlice=python36.PySequence_SetSlice + PySequence_Size=python36.PySequence_Size + PySequence_Tuple=python36.PySequence_Tuple + PySetIter_Type=python36.PySetIter_Type DATA + PySet_Add=python36.PySet_Add + PySet_Clear=python36.PySet_Clear + PySet_Contains=python36.PySet_Contains + PySet_Discard=python36.PySet_Discard + PySet_New=python36.PySet_New + PySet_Pop=python36.PySet_Pop + PySet_Size=python36.PySet_Size + PySet_Type=python36.PySet_Type DATA + PySlice_GetIndices=python36.PySlice_GetIndices + PySlice_GetIndicesEx=python36.PySlice_GetIndicesEx + PySlice_New=python36.PySlice_New + PySlice_Type=python36.PySlice_Type DATA + PySortWrapper_Type=python36.PySortWrapper_Type DATA + PyState_FindModule=python36.PyState_FindModule + PyState_AddModule=python36.PyState_AddModule + PyState_RemoveModule=python36.PyState_RemoveModule + PyStructSequence_GetItem=python36.PyStructSequence_GetItem + PyStructSequence_New=python36.PyStructSequence_New + PyStructSequence_NewType=python36.PyStructSequence_NewType + PyStructSequence_SetItem=python36.PyStructSequence_SetItem + PySuper_Type=python36.PySuper_Type DATA + PySys_AddWarnOption=python36.PySys_AddWarnOption + PySys_AddWarnOptionUnicode=python36.PySys_AddWarnOptionUnicode + PySys_FormatStderr=python36.PySys_FormatStderr + PySys_FormatStdout=python36.PySys_FormatStdout + PySys_GetObject=python36.PySys_GetObject + PySys_HasWarnOptions=python36.PySys_HasWarnOptions + PySys_ResetWarnOptions=python36.PySys_ResetWarnOptions + PySys_SetArgv=python36.PySys_SetArgv + PySys_SetArgvEx=python36.PySys_SetArgvEx + PySys_SetObject=python36.PySys_SetObject + PySys_SetPath=python36.PySys_SetPath + PySys_WriteStderr=python36.PySys_WriteStderr + PySys_WriteStdout=python36.PySys_WriteStdout + PyThreadState_Clear=python36.PyThreadState_Clear + PyThreadState_Delete=python36.PyThreadState_Delete + PyThreadState_DeleteCurrent=python36.PyThreadState_DeleteCurrent + PyThreadState_Get=python36.PyThreadState_Get + PyThreadState_GetDict=python36.PyThreadState_GetDict + PyThreadState_New=python36.PyThreadState_New + PyThreadState_SetAsyncExc=python36.PyThreadState_SetAsyncExc + PyThreadState_Swap=python36.PyThreadState_Swap + PyTraceBack_Here=python36.PyTraceBack_Here + PyTraceBack_Print=python36.PyTraceBack_Print + PyTraceBack_Type=python36.PyTraceBack_Type DATA + PyTupleIter_Type=python36.PyTupleIter_Type DATA + PyTuple_ClearFreeList=python36.PyTuple_ClearFreeList + PyTuple_GetItem=python36.PyTuple_GetItem + PyTuple_GetSlice=python36.PyTuple_GetSlice + PyTuple_New=python36.PyTuple_New + PyTuple_Pack=python36.PyTuple_Pack + PyTuple_SetItem=python36.PyTuple_SetItem + PyTuple_Size=python36.PyTuple_Size + PyTuple_Type=python36.PyTuple_Type DATA + PyType_ClearCache=python36.PyType_ClearCache + PyType_FromSpec=python36.PyType_FromSpec + PyType_FromSpecWithBases=python36.PyType_FromSpecWithBases + PyType_GenericAlloc=python36.PyType_GenericAlloc + PyType_GenericNew=python36.PyType_GenericNew + PyType_GetFlags=python36.PyType_GetFlags + PyType_GetSlot=python36.PyType_GetSlot + PyType_IsSubtype=python36.PyType_IsSubtype + PyType_Modified=python36.PyType_Modified + PyType_Ready=python36.PyType_Ready + PyType_Type=python36.PyType_Type DATA + PyUnicodeDecodeError_Create=python36.PyUnicodeDecodeError_Create + PyUnicodeDecodeError_GetEncoding=python36.PyUnicodeDecodeError_GetEncoding + PyUnicodeDecodeError_GetEnd=python36.PyUnicodeDecodeError_GetEnd + PyUnicodeDecodeError_GetObject=python36.PyUnicodeDecodeError_GetObject + PyUnicodeDecodeError_GetReason=python36.PyUnicodeDecodeError_GetReason + PyUnicodeDecodeError_GetStart=python36.PyUnicodeDecodeError_GetStart + PyUnicodeDecodeError_SetEnd=python36.PyUnicodeDecodeError_SetEnd + PyUnicodeDecodeError_SetReason=python36.PyUnicodeDecodeError_SetReason + PyUnicodeDecodeError_SetStart=python36.PyUnicodeDecodeError_SetStart + PyUnicodeEncodeError_GetEncoding=python36.PyUnicodeEncodeError_GetEncoding + PyUnicodeEncodeError_GetEnd=python36.PyUnicodeEncodeError_GetEnd + PyUnicodeEncodeError_GetObject=python36.PyUnicodeEncodeError_GetObject + PyUnicodeEncodeError_GetReason=python36.PyUnicodeEncodeError_GetReason + PyUnicodeEncodeError_GetStart=python36.PyUnicodeEncodeError_GetStart + PyUnicodeEncodeError_SetEnd=python36.PyUnicodeEncodeError_SetEnd + PyUnicodeEncodeError_SetReason=python36.PyUnicodeEncodeError_SetReason + PyUnicodeEncodeError_SetStart=python36.PyUnicodeEncodeError_SetStart + PyUnicodeIter_Type=python36.PyUnicodeIter_Type DATA + PyUnicodeTranslateError_GetEnd=python36.PyUnicodeTranslateError_GetEnd + PyUnicodeTranslateError_GetObject=python36.PyUnicodeTranslateError_GetObject + PyUnicodeTranslateError_GetReason=python36.PyUnicodeTranslateError_GetReason + PyUnicodeTranslateError_GetStart=python36.PyUnicodeTranslateError_GetStart + PyUnicodeTranslateError_SetEnd=python36.PyUnicodeTranslateError_SetEnd + PyUnicodeTranslateError_SetReason=python36.PyUnicodeTranslateError_SetReason + PyUnicodeTranslateError_SetStart=python36.PyUnicodeTranslateError_SetStart + PyUnicode_Append=python36.PyUnicode_Append + PyUnicode_AppendAndDel=python36.PyUnicode_AppendAndDel + PyUnicode_AsASCIIString=python36.PyUnicode_AsASCIIString + PyUnicode_AsCharmapString=python36.PyUnicode_AsCharmapString + PyUnicode_AsDecodedObject=python36.PyUnicode_AsDecodedObject + PyUnicode_AsDecodedUnicode=python36.PyUnicode_AsDecodedUnicode + PyUnicode_AsEncodedObject=python36.PyUnicode_AsEncodedObject + PyUnicode_AsEncodedString=python36.PyUnicode_AsEncodedString + PyUnicode_AsEncodedUnicode=python36.PyUnicode_AsEncodedUnicode + PyUnicode_AsLatin1String=python36.PyUnicode_AsLatin1String + PyUnicode_AsRawUnicodeEscapeString=python36.PyUnicode_AsRawUnicodeEscapeString + PyUnicode_AsUTF16String=python36.PyUnicode_AsUTF16String + PyUnicode_AsUTF32String=python36.PyUnicode_AsUTF32String + PyUnicode_AsUTF8String=python36.PyUnicode_AsUTF8String + PyUnicode_AsUnicodeEscapeString=python36.PyUnicode_AsUnicodeEscapeString + PyUnicode_AsWideChar=python36.PyUnicode_AsWideChar + PyUnicode_ClearFreelist=python36.PyUnicode_ClearFreelist + PyUnicode_Compare=python36.PyUnicode_Compare + PyUnicode_Concat=python36.PyUnicode_Concat + PyUnicode_Contains=python36.PyUnicode_Contains + PyUnicode_Count=python36.PyUnicode_Count + PyUnicode_Decode=python36.PyUnicode_Decode + PyUnicode_DecodeASCII=python36.PyUnicode_DecodeASCII + PyUnicode_DecodeCharmap=python36.PyUnicode_DecodeCharmap + PyUnicode_DecodeFSDefault=python36.PyUnicode_DecodeFSDefault + PyUnicode_DecodeFSDefaultAndSize=python36.PyUnicode_DecodeFSDefaultAndSize + PyUnicode_DecodeLatin1=python36.PyUnicode_DecodeLatin1 + PyUnicode_DecodeRawUnicodeEscape=python36.PyUnicode_DecodeRawUnicodeEscape + PyUnicode_DecodeUTF16=python36.PyUnicode_DecodeUTF16 + PyUnicode_DecodeUTF16Stateful=python36.PyUnicode_DecodeUTF16Stateful + PyUnicode_DecodeUTF32=python36.PyUnicode_DecodeUTF32 + PyUnicode_DecodeUTF32Stateful=python36.PyUnicode_DecodeUTF32Stateful + PyUnicode_DecodeUTF8=python36.PyUnicode_DecodeUTF8 + PyUnicode_DecodeUTF8Stateful=python36.PyUnicode_DecodeUTF8Stateful + PyUnicode_DecodeUnicodeEscape=python36.PyUnicode_DecodeUnicodeEscape + PyUnicode_FSConverter=python36.PyUnicode_FSConverter + PyUnicode_FSDecoder=python36.PyUnicode_FSDecoder + PyUnicode_Find=python36.PyUnicode_Find + PyUnicode_Format=python36.PyUnicode_Format + PyUnicode_FromEncodedObject=python36.PyUnicode_FromEncodedObject + PyUnicode_FromFormat=python36.PyUnicode_FromFormat + PyUnicode_FromFormatV=python36.PyUnicode_FromFormatV + PyUnicode_FromObject=python36.PyUnicode_FromObject + PyUnicode_FromOrdinal=python36.PyUnicode_FromOrdinal + PyUnicode_FromString=python36.PyUnicode_FromString + PyUnicode_FromStringAndSize=python36.PyUnicode_FromStringAndSize + PyUnicode_FromWideChar=python36.PyUnicode_FromWideChar + PyUnicode_GetDefaultEncoding=python36.PyUnicode_GetDefaultEncoding + PyUnicode_GetSize=python36.PyUnicode_GetSize + PyUnicode_IsIdentifier=python36.PyUnicode_IsIdentifier + PyUnicode_Join=python36.PyUnicode_Join + PyUnicode_Partition=python36.PyUnicode_Partition + PyUnicode_RPartition=python36.PyUnicode_RPartition + PyUnicode_RSplit=python36.PyUnicode_RSplit + PyUnicode_Replace=python36.PyUnicode_Replace + PyUnicode_Resize=python36.PyUnicode_Resize + PyUnicode_RichCompare=python36.PyUnicode_RichCompare + PyUnicode_SetDefaultEncoding=python36.PyUnicode_SetDefaultEncoding + PyUnicode_Split=python36.PyUnicode_Split + PyUnicode_Splitlines=python36.PyUnicode_Splitlines + PyUnicode_Tailmatch=python36.PyUnicode_Tailmatch + PyUnicode_Translate=python36.PyUnicode_Translate + PyUnicode_BuildEncodingMap=python36.PyUnicode_BuildEncodingMap + PyUnicode_CompareWithASCIIString=python36.PyUnicode_CompareWithASCIIString + PyUnicode_DecodeUTF7=python36.PyUnicode_DecodeUTF7 + PyUnicode_DecodeUTF7Stateful=python36.PyUnicode_DecodeUTF7Stateful + PyUnicode_EncodeFSDefault=python36.PyUnicode_EncodeFSDefault + PyUnicode_InternFromString=python36.PyUnicode_InternFromString + PyUnicode_InternImmortal=python36.PyUnicode_InternImmortal + PyUnicode_InternInPlace=python36.PyUnicode_InternInPlace + PyUnicode_Type=python36.PyUnicode_Type DATA + PyWeakref_GetObject=python36.PyWeakref_GetObject DATA + PyWeakref_NewProxy=python36.PyWeakref_NewProxy + PyWeakref_NewRef=python36.PyWeakref_NewRef + PyWrapperDescr_Type=python36.PyWrapperDescr_Type DATA + PyWrapper_New=python36.PyWrapper_New + PyZip_Type=python36.PyZip_Type DATA + Py_AddPendingCall=python36.Py_AddPendingCall + Py_AtExit=python36.Py_AtExit + Py_BuildValue=python36.Py_BuildValue + Py_CompileString=python36.Py_CompileString + Py_DecRef=python36.Py_DecRef + Py_EndInterpreter=python36.Py_EndInterpreter + Py_Exit=python36.Py_Exit + Py_FatalError=python36.Py_FatalError + Py_FileSystemDefaultEncoding=python36.Py_FileSystemDefaultEncoding DATA + Py_Finalize=python36.Py_Finalize + Py_GetBuildInfo=python36.Py_GetBuildInfo + Py_GetCompiler=python36.Py_GetCompiler + Py_GetCopyright=python36.Py_GetCopyright + Py_GetExecPrefix=python36.Py_GetExecPrefix + Py_GetPath=python36.Py_GetPath + Py_GetPlatform=python36.Py_GetPlatform + Py_GetPrefix=python36.Py_GetPrefix + Py_GetProgramFullPath=python36.Py_GetProgramFullPath + Py_GetProgramName=python36.Py_GetProgramName + Py_GetPythonHome=python36.Py_GetPythonHome + Py_GetRecursionLimit=python36.Py_GetRecursionLimit + Py_GetVersion=python36.Py_GetVersion + Py_HasFileSystemDefaultEncoding=python36.Py_HasFileSystemDefaultEncoding DATA + Py_IncRef=python36.Py_IncRef + Py_Initialize=python36.Py_Initialize + Py_InitializeEx=python36.Py_InitializeEx + Py_IsInitialized=python36.Py_IsInitialized + Py_Main=python36.Py_Main + Py_MakePendingCalls=python36.Py_MakePendingCalls + Py_NewInterpreter=python36.Py_NewInterpreter + Py_ReprEnter=python36.Py_ReprEnter + Py_ReprLeave=python36.Py_ReprLeave + Py_SetProgramName=python36.Py_SetProgramName + Py_SetPythonHome=python36.Py_SetPythonHome + Py_SetRecursionLimit=python36.Py_SetRecursionLimit + Py_SymtableString=python36.Py_SymtableString + Py_VaBuildValue=python36.Py_VaBuildValue + _PyErr_BadInternalCall=python36._PyErr_BadInternalCall + _PyObject_CallFunction_SizeT=python36._PyObject_CallFunction_SizeT + _PyObject_CallMethod_SizeT=python36._PyObject_CallMethod_SizeT + _PyObject_GC_Malloc=python36._PyObject_GC_Malloc + _PyObject_GC_New=python36._PyObject_GC_New + _PyObject_GC_NewVar=python36._PyObject_GC_NewVar + _PyObject_GC_Resize=python36._PyObject_GC_Resize + _PyObject_New=python36._PyObject_New + _PyObject_NewVar=python36._PyObject_NewVar + _PyState_AddModule=python36._PyState_AddModule + _PyThreadState_Init=python36._PyThreadState_Init + _PyThreadState_Prealloc=python36._PyThreadState_Prealloc + _PyTrash_delete_later=python36._PyTrash_delete_later DATA + _PyTrash_delete_nesting=python36._PyTrash_delete_nesting DATA + _PyTrash_deposit_object=python36._PyTrash_deposit_object + _PyTrash_destroy_chain=python36._PyTrash_destroy_chain + _PyWeakref_CallableProxyType=python36._PyWeakref_CallableProxyType DATA + _PyWeakref_ProxyType=python36._PyWeakref_ProxyType DATA + _PyWeakref_RefType=python36._PyWeakref_RefType DATA + _Py_BuildValue_SizeT=python36._Py_BuildValue_SizeT + _Py_CheckRecursionLimit=python36._Py_CheckRecursionLimit DATA + _Py_CheckRecursiveCall=python36._Py_CheckRecursiveCall + _Py_Dealloc=python36._Py_Dealloc + _Py_EllipsisObject=python36._Py_EllipsisObject DATA + _Py_FalseStruct=python36._Py_FalseStruct DATA + _Py_NoneStruct=python36._Py_NoneStruct DATA + _Py_NotImplementedStruct=python36._Py_NotImplementedStruct DATA + _Py_SwappedOp=python36._Py_SwappedOp DATA + _Py_TrueStruct=python36._Py_TrueStruct DATA + _Py_VaBuildValue_SizeT=python36._Py_VaBuildValue_SizeT + _PyArg_Parse_SizeT=python36._PyArg_Parse_SizeT + _PyArg_ParseTuple_SizeT=python36._PyArg_ParseTuple_SizeT + _PyArg_ParseTupleAndKeywords_SizeT=python36._PyArg_ParseTupleAndKeywords_SizeT + _PyArg_VaParse_SizeT=python36._PyArg_VaParse_SizeT + _PyArg_VaParseTupleAndKeywords_SizeT=python36._PyArg_VaParseTupleAndKeywords_SizeT + _Py_BuildValue_SizeT=python36._Py_BuildValue_SizeT diff --git a/PCbuild/prepare_ssl.bat b/PCbuild/prepare_ssl.bat index c08a9f3..3153615 100644 --- a/PCbuild/prepare_ssl.bat +++ b/PCbuild/prepare_ssl.bat @@ -3,10 +3,10 @@ if not defined HOST_PYTHON ( if %1 EQU Debug (
shift
set HOST_PYTHON=python_d.exe
- if not exist python35_d.dll exit 1
+ if not exist python36_d.dll exit 1
) ELSE (
set HOST_PYTHON=python.exe
- if not exist python35.dll exit 1
+ if not exist python36.dll exit 1
)
)
%HOST_PYTHON% prepare_ssl.py %1
diff --git a/PCbuild/xxlimited.vcxproj b/PCbuild/xxlimited.vcxproj index 0144fa9..9dbdc77 100644 --- a/PCbuild/xxlimited.vcxproj +++ b/PCbuild/xxlimited.vcxproj @@ -62,7 +62,7 @@ </PropertyGroup> <ItemDefinitionGroup> <ClCompile> - <PreprocessorDefinitions>%(PreprocessorDefinitions);Py_LIMITED_API=0x03050000</PreprocessorDefinitions> + <PreprocessorDefinitions>%(PreprocessorDefinitions);Py_LIMITED_API=0x03060000</PreprocessorDefinitions> </ClCompile> <Link> <AdditionalDependencies>wsock32.lib;%(AdditionalDependencies)</AdditionalDependencies> diff --git a/Python/compile.c b/Python/compile.c index cfeab0f..b246c3b 100644 --- a/Python/compile.c +++ b/Python/compile.c @@ -3628,9 +3628,9 @@ expr_constant(struct compiler *c, expr_ty e) BLOCK finally: if an exception was raised: - exc = copy of (exception, instance, traceback) + exc = copy of (exception, instance, traceback) else: - exc = (None, None, None) + exc = (None, None, None) if not (await exit(*exc)): raise */ @@ -1,5 +1,5 @@ -This is Python version 3.5.0 beta 4 -=================================== +This is Python version 3.6.0 alpha 1 +==================================== Copyright (c) 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014, 2015 Python Software Foundation. All rights reserved. @@ -50,9 +50,9 @@ What's New ---------- We try to have a comprehensive overview of the changes in the "What's New in -Python 3.5" document, found at +Python 3.6" document, found at - http://docs.python.org/3.5/whatsnew/3.5.html + http://docs.python.org/3.6/whatsnew/3.6.html For a more detailed change log, read Misc/NEWS (though this file, too, is incomplete, and also doesn't list anything merged in from the 2.7 release under @@ -65,9 +65,9 @@ entitled "Installing multiple versions". Documentation ------------- -Documentation for Python 3.5 is online, updated daily: +Documentation for Python 3.6 is online, updated daily: - http://docs.python.org/3.5/ + http://docs.python.org/3.6/ It can also be downloaded in many formats for faster access. The documentation is downloadable in HTML, PDF, and reStructuredText formats; the latter version @@ -92,7 +92,7 @@ backported versions of certain key Python 3.x features. A source-to-source translation tool, "2to3", can take care of the mundane task of converting large amounts of source code. It is not a complete solution but is complemented by the deprecation warnings in 2.6. See -http://docs.python.org/3.5/library/2to3.html for more information. +http://docs.python.org/3.6/library/2to3.html for more information. Testing @@ -130,7 +130,7 @@ same prefix you must decide which version (if any) is your "primary" version. Install that version using "make install". Install all other versions using "make altinstall". -For example, if you want to install Python 2.6, 2.7 and 3.5 with 2.7 being the +For example, if you want to install Python 2.6, 2.7 and 3.6 with 2.7 being the primary version, you would execute "make install" in your 2.7 build directory and "make altinstall" in the others. diff --git a/Tools/buildbot/build-amd64.bat b/Tools/buildbot/build-amd64.bat deleted file mode 100644 index f77407b..0000000 --- a/Tools/buildbot/build-amd64.bat +++ /dev/null @@ -1,5 +0,0 @@ -@rem Formerly used by the buildbot "compile" step.
-@echo This script is no longer used and may be removed in the future.
-@echo To get the same effect as this script, use
-@echo PCbuild\build.bat -d -e -k -p x64
-call "%~dp0build.bat" -p x64 %*
diff --git a/Tools/buildbot/clean-amd64.bat b/Tools/buildbot/clean-amd64.bat deleted file mode 100644 index b53c7c1..0000000 --- a/Tools/buildbot/clean-amd64.bat +++ /dev/null @@ -1,5 +0,0 @@ -@rem Formerly used by the buildbot "clean" step.
-@echo This script is no longer used and may be removed in the future.
-@echo To get the same effect as this script, use `clean.bat` from this
-@echo directory and pass `-p x64` as two arguments.
-call "%~dp0clean.bat" -p x64 %*
diff --git a/Tools/buildbot/external-amd64.bat b/Tools/buildbot/external-amd64.bat deleted file mode 100644 index bfaef05..0000000 --- a/Tools/buildbot/external-amd64.bat +++ /dev/null @@ -1,3 +0,0 @@ -@echo This script is no longer used and may be removed in the future.
-@echo Please use PCbuild\get_externals.bat instead.
-@"%~dp0..\..\PCbuild\get_externals.bat" %*
diff --git a/Tools/buildbot/external.bat b/Tools/buildbot/external.bat deleted file mode 100644 index bfaef05..0000000 --- a/Tools/buildbot/external.bat +++ /dev/null @@ -1,3 +0,0 @@ -@echo This script is no longer used and may be removed in the future.
-@echo Please use PCbuild\get_externals.bat instead.
-@"%~dp0..\..\PCbuild\get_externals.bat" %*
diff --git a/Tools/buildbot/test-amd64.bat b/Tools/buildbot/test-amd64.bat deleted file mode 100644 index e48329c..0000000 --- a/Tools/buildbot/test-amd64.bat +++ /dev/null @@ -1,6 +0,0 @@ -@rem Formerly used by the buildbot "test" step.
-@echo This script is no longer used and may be removed in the future.
-@echo To get the same effect as this script, use
-@echo PCbuild\rt.bat -q -d -x64 -uall -rwW
-@echo or use `test.bat` in this directory and pass `-x64` as an argument.
-call "%~dp0test.bat" -x64 %*
@@ -1,6 +1,6 @@ #! /bin/sh # Guess values for system-dependent variables and create Makefiles. -# Generated by GNU Autoconf 2.69 for python 3.5. +# Generated by GNU Autoconf 2.69 for python 3.6. # # Report bugs to <http://bugs.python.org/>. # @@ -580,8 +580,8 @@ MAKEFLAGS= # Identity of this package. PACKAGE_NAME='python' PACKAGE_TARNAME='python' -PACKAGE_VERSION='3.5' -PACKAGE_STRING='python 3.5' +PACKAGE_VERSION='3.6' +PACKAGE_STRING='python 3.6' PACKAGE_BUGREPORT='http://bugs.python.org/' PACKAGE_URL='' @@ -1378,7 +1378,7 @@ if test "$ac_init_help" = "long"; then # Omit some internal or obsolete options to make the list less imposing. # This message is too long to be a string in the A/UX 3.1 sh. cat <<_ACEOF -\`configure' configures python 3.5 to adapt to many kinds of systems. +\`configure' configures python 3.6 to adapt to many kinds of systems. Usage: $0 [OPTION]... [VAR=VALUE]... @@ -1443,7 +1443,7 @@ fi if test -n "$ac_init_help"; then case $ac_init_help in - short | recursive ) echo "Configuration of python 3.5:";; + short | recursive ) echo "Configuration of python 3.6:";; esac cat <<\_ACEOF @@ -1597,7 +1597,7 @@ fi test -n "$ac_init_help" && exit $ac_status if $ac_init_version; then cat <<\_ACEOF -python configure 3.5 +python configure 3.6 generated by GNU Autoconf 2.69 Copyright (C) 2012 Free Software Foundation, Inc. @@ -2436,7 +2436,7 @@ cat >config.log <<_ACEOF This file contains any messages produced by compilers while running configure, to aid debugging if configure makes a mistake. -It was created by python $as_me 3.5, which was +It was created by python $as_me 3.6, which was generated by GNU Autoconf 2.69. Invocation command line was $ $0 $@ @@ -3009,7 +3009,7 @@ rm confdefs.h mv confdefs.h.new confdefs.h -VERSION=3.5 +VERSION=3.6 # Version number of Python's own shared library file. @@ -16543,7 +16543,7 @@ cat >>$CONFIG_STATUS <<\_ACEOF || ac_write_fail=1 # report actual input values of CONFIG_FILES etc. instead of their # values after options handling. ac_log=" -This file was extended by python $as_me 3.5, which was +This file was extended by python $as_me 3.6, which was generated by GNU Autoconf 2.69. Invocation command line was CONFIG_FILES = $CONFIG_FILES @@ -16605,7 +16605,7 @@ _ACEOF cat >>$CONFIG_STATUS <<_ACEOF || ac_write_fail=1 ac_cs_config="`$as_echo "$ac_configure_args" | sed 's/^ //; s/[\\""\`\$]/\\\\&/g'`" ac_cs_version="\\ -python config.status 3.5 +python config.status 3.6 configured by $0, generated by GNU Autoconf 2.69, with options \\"\$ac_cs_config\\" diff --git a/configure.ac b/configure.ac index 56a73df..668234d 100644 --- a/configure.ac +++ b/configure.ac @@ -3,7 +3,7 @@ dnl * Please run autoreconf to test your changes! * dnl *********************************************** # Set VERSION so we only need to edit in one place (i.e., here) -m4_define(PYTHON_VERSION, 3.5) +m4_define(PYTHON_VERSION, 3.6) AC_PREREQ(2.65) |