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author | Georg Brandl <georg@python.org> | 2007-08-15 14:28:22 (GMT) |
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committer | Georg Brandl <georg@python.org> | 2007-08-15 14:28:22 (GMT) |
commit | 116aa62bf54a39697e25f21d6cf6799f7faa1349 (patch) | |
tree | 8db5729518ed4ca88e26f1e26cc8695151ca3eb3 /Doc/tutorial | |
parent | 739c01d47b9118d04e5722333f0e6b4d0c8bdd9e (diff) | |
download | cpython-116aa62bf54a39697e25f21d6cf6799f7faa1349.zip cpython-116aa62bf54a39697e25f21d6cf6799f7faa1349.tar.gz cpython-116aa62bf54a39697e25f21d6cf6799f7faa1349.tar.bz2 |
Move the 3k reST doc tree in place.
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-rw-r--r-- | Doc/tutorial/appetite.rst | 89 | ||||
-rw-r--r-- | Doc/tutorial/classes.rst | 792 | ||||
-rw-r--r-- | Doc/tutorial/controlflow.rst | 574 | ||||
-rw-r--r-- | Doc/tutorial/datastructures.rst | 586 | ||||
-rw-r--r-- | Doc/tutorial/errors.rst | 418 | ||||
-rw-r--r-- | Doc/tutorial/floatingpoint.rst | 220 | ||||
-rw-r--r-- | Doc/tutorial/glossary.rst | 329 | ||||
-rw-r--r-- | Doc/tutorial/index.rst | 60 | ||||
-rw-r--r-- | Doc/tutorial/inputoutput.rst | 354 | ||||
-rw-r--r-- | Doc/tutorial/interactive.rst | 167 | ||||
-rw-r--r-- | Doc/tutorial/interpreter.rst | 248 | ||||
-rw-r--r-- | Doc/tutorial/introduction.rst | 645 | ||||
-rw-r--r-- | Doc/tutorial/modules.rst | 551 | ||||
-rw-r--r-- | Doc/tutorial/stdlib.rst | 313 | ||||
-rw-r--r-- | Doc/tutorial/stdlib2.rst | 394 | ||||
-rw-r--r-- | Doc/tutorial/whatnow.rst | 68 |
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diff --git a/Doc/tutorial/appetite.rst b/Doc/tutorial/appetite.rst new file mode 100644 index 0000000..f1c80e9 --- /dev/null +++ b/Doc/tutorial/appetite.rst @@ -0,0 +1,89 @@ +.. _tut-intro: + +********************** +Whetting Your Appetite +********************** + +If you do much work on computers, eventually you find that there's some task +you'd like to automate. For example, you may wish to perform a +search-and-replace over a large number of text files, or rename and rearrange a +bunch of photo files in a complicated way. Perhaps you'd like to write a small +custom database, or a specialized GUI application, or a simple game. + +If you're a professional software developer, you may have to work with several +C/C++/Java libraries but find the usual write/compile/test/re-compile cycle is +too slow. Perhaps you're writing a test suite for such a library and find +writing the testing code a tedious task. Or maybe you've written a program that +could use an extension language, and you don't want to design and implement a +whole new language for your application. + +Python is just the language for you. + +You could write a Unix shell script or Windows batch files for some of these +tasks, but shell scripts are best at moving around files and changing text data, +not well-suited for GUI applications or games. You could write a C/C++/Java +program, but it can take a lot of development time to get even a first-draft +program. Python is simpler to use, available on Windows, MacOS X, and Unix +operating systems, and will help you get the job done more quickly. + +Python is simple to use, but it is a real programming language, offering much +more structure and support for large programs than shell scripts or batch files +can offer. On the other hand, Python also offers much more error checking than +C, and, being a *very-high-level language*, it has high-level data types built +in, such as flexible arrays and dictionaries. Because of its more general data +types Python is applicable to a much larger problem domain than Awk or even +Perl, yet many things are at least as easy in Python as in those languages. + +Python allows you to split your program into modules that can be reused in other +Python programs. It comes with a large collection of standard modules that you +can use as the basis of your programs --- or as examples to start learning to +program in Python. Some of these modules provide things like file I/O, system +calls, sockets, and even interfaces to graphical user interface toolkits like +Tk. + +Python is an interpreted language, which can save you considerable time during +program development because no compilation and linking is necessary. The +interpreter can be used interactively, which makes it easy to experiment with +features of the language, to write throw-away programs, or to test functions +during bottom-up program development. It is also a handy desk calculator. + +Python enables programs to be written compactly and readably. Programs written +in Python are typically much shorter than equivalent C, C++, or Java programs, +for several reasons: + +* the high-level data types allow you to express complex operations in a single + statement; + +* statement grouping is done by indentation instead of beginning and ending + brackets; + +* no variable or argument declarations are necessary. + +Python is *extensible*: if you know how to program in C it is easy to add a new +built-in function or module to the interpreter, either to perform critical +operations at maximum speed, or to link Python programs to libraries that may +only be available in binary form (such as a vendor-specific graphics library). +Once you are really hooked, you can link the Python interpreter into an +application written in C and use it as an extension or command language for that +application. + +By the way, the language is named after the BBC show "Monty Python's Flying +Circus" and has nothing to do with nasty reptiles. Making references to Monty +Python skits in documentation is not only allowed, it is encouraged! + +Now that you are all excited about Python, you'll want to examine it in some +more detail. Since the best way to learn a language is to use it, the tutorial +invites you to play with the Python interpreter as you read. + +.. % \section{Where From Here \label{where}} + +In the next chapter, the mechanics of using the interpreter are explained. This +is rather mundane information, but essential for trying out the examples shown +later. + +The rest of the tutorial introduces various features of the Python language and +system through examples, beginning with simple expressions, statements and data +types, through functions and modules, and finally touching upon advanced +concepts like exceptions and user-defined classes. + + diff --git a/Doc/tutorial/classes.rst b/Doc/tutorial/classes.rst new file mode 100644 index 0000000..b733e1e --- /dev/null +++ b/Doc/tutorial/classes.rst @@ -0,0 +1,792 @@ +.. _tut-classes: + +******* +Classes +******* + +Python's class mechanism adds classes to the language with a minimum of new +syntax and semantics. It is a mixture of the class mechanisms found in C++ and +Modula-3. As is true for modules, classes in Python do not put an absolute +barrier between definition and user, but rather rely on the politeness of the +user not to "break into the definition." The most important features of classes +are retained with full power, however: the class inheritance mechanism allows +multiple base classes, a derived class can override any methods of its base +class or classes, and a method can call the method of a base class with the same +name. Objects can contain an arbitrary amount of private data. + +In C++ terminology, all class members (including the data members) are *public*, +and all member functions are *virtual*. There are no special constructors or +destructors. As in Modula-3, there are no shorthands for referencing the +object's members from its methods: the method function is declared with an +explicit first argument representing the object, which is provided implicitly by +the call. As in Smalltalk, classes themselves are objects, albeit in the wider +sense of the word: in Python, all data types are objects. This provides +semantics for importing and renaming. Unlike C++ and Modula-3, built-in types +can be used as base classes for extension by the user. Also, like in C++ but +unlike in Modula-3, most built-in operators with special syntax (arithmetic +operators, subscripting etc.) can be redefined for class instances. + + +.. _tut-terminology: + +A Word About Terminology +======================== + +Lacking universally accepted terminology to talk about classes, I will make +occasional use of Smalltalk and C++ terms. (I would use Modula-3 terms, since +its object-oriented semantics are closer to those of Python than C++, but I +expect that few readers have heard of it.) + +Objects have individuality, and multiple names (in multiple scopes) can be bound +to the same object. This is known as aliasing in other languages. This is +usually not appreciated on a first glance at Python, and can be safely ignored +when dealing with immutable basic types (numbers, strings, tuples). However, +aliasing has an (intended!) effect on the semantics of Python code involving +mutable objects such as lists, dictionaries, and most types representing +entities outside the program (files, windows, etc.). This is usually used to +the benefit of the program, since aliases behave like pointers in some respects. +For example, passing an object is cheap since only a pointer is passed by the +implementation; and if a function modifies an object passed as an argument, the +caller will see the change --- this eliminates the need for two different +argument passing mechanisms as in Pascal. + + +.. _tut-scopes: + +Python Scopes and Name Spaces +============================= + +Before introducing classes, I first have to tell you something about Python's +scope rules. Class definitions play some neat tricks with namespaces, and you +need to know how scopes and namespaces work to fully understand what's going on. +Incidentally, knowledge about this subject is useful for any advanced Python +programmer. + +Let's begin with some definitions. + +A *namespace* is a mapping from names to objects. Most namespaces are currently +implemented as Python dictionaries, but that's normally not noticeable in any +way (except for performance), and it may change in the future. Examples of +namespaces are: the set of built-in names (functions such as :func:`abs`, and +built-in exception names); the global names in a module; and the local names in +a function invocation. In a sense the set of attributes of an object also form +a namespace. The important thing to know about namespaces is that there is +absolutely no relation between names in different namespaces; for instance, two +different modules may both define a function "maximize" without confusion --- +users of the modules must prefix it with the module name. + +By the way, I use the word *attribute* for any name following a dot --- for +example, in the expression ``z.real``, ``real`` is an attribute of the object +``z``. Strictly speaking, references to names in modules are attribute +references: in the expression ``modname.funcname``, ``modname`` is a module +object and ``funcname`` is an attribute of it. In this case there happens to be +a straightforward mapping between the module's attributes and the global names +defined in the module: they share the same namespace! [#]_ + +Attributes may be read-only or writable. In the latter case, assignment to +attributes is possible. Module attributes are writable: you can write +``modname.the_answer = 42``. Writable attributes may also be deleted with the +:keyword:`del` statement. For example, ``del modname.the_answer`` will remove +the attribute :attr:`the_answer` from the object named by ``modname``. + +Name spaces are created at different moments and have different lifetimes. The +namespace containing the built-in names is created when the Python interpreter +starts up, and is never deleted. The global namespace for a module is created +when the module definition is read in; normally, module namespaces also last +until the interpreter quits. The statements executed by the top-level +invocation of the interpreter, either read from a script file or interactively, +are considered part of a module called :mod:`__main__`, so they have their own +global namespace. (The built-in names actually also live in a module; this is +called :mod:`__builtin__`.) + +The local namespace for a function is created when the function is called, and +deleted when the function returns or raises an exception that is not handled +within the function. (Actually, forgetting would be a better way to describe +what actually happens.) Of course, recursive invocations each have their own +local namespace. + +A *scope* is a textual region of a Python program where a namespace is directly +accessible. "Directly accessible" here means that an unqualified reference to a +name attempts to find the name in the namespace. + +Although scopes are determined statically, they are used dynamically. At any +time during execution, there are at least three nested scopes whose namespaces +are directly accessible: the innermost scope, which is searched first, contains +the local names; the namespaces of any enclosing functions, which are searched +starting with the nearest enclosing scope; the middle scope, searched next, +contains the current module's global names; and the outermost scope (searched +last) is the namespace containing built-in names. + +If a name is declared global, then all references and assignments go directly to +the middle scope containing the module's global names. Otherwise, all variables +found outside of the innermost scope are read-only (an attempt to write to such +a variable will simply create a *new* local variable in the innermost scope, +leaving the identically named outer variable unchanged). + +Usually, the local scope references the local names of the (textually) current +function. Outside functions, the local scope references the same namespace as +the global scope: the module's namespace. Class definitions place yet another +namespace in the local scope. + +It is important to realize that scopes are determined textually: the global +scope of a function defined in a module is that module's namespace, no matter +from where or by what alias the function is called. On the other hand, the +actual search for names is done dynamically, at run time --- however, the +language definition is evolving towards static name resolution, at "compile" +time, so don't rely on dynamic name resolution! (In fact, local variables are +already determined statically.) + +A special quirk of Python is that assignments always go into the innermost +scope. Assignments do not copy data --- they just bind names to objects. The +same is true for deletions: the statement ``del x`` removes the binding of ``x`` +from the namespace referenced by the local scope. In fact, all operations that +introduce new names use the local scope: in particular, import statements and +function definitions bind the module or function name in the local scope. (The +:keyword:`global` statement can be used to indicate that particular variables +live in the global scope.) + + +.. _tut-firstclasses: + +A First Look at Classes +======================= + +Classes introduce a little bit of new syntax, three new object types, and some +new semantics. + + +.. _tut-classdefinition: + +Class Definition Syntax +----------------------- + +The simplest form of class definition looks like this:: + + class ClassName: + <statement-1> + . + . + . + <statement-N> + +Class definitions, like function definitions (:keyword:`def` statements) must be +executed before they have any effect. (You could conceivably place a class +definition in a branch of an :keyword:`if` statement, or inside a function.) + +In practice, the statements inside a class definition will usually be function +definitions, but other statements are allowed, and sometimes useful --- we'll +come back to this later. The function definitions inside a class normally have +a peculiar form of argument list, dictated by the calling conventions for +methods --- again, this is explained later. + +When a class definition is entered, a new namespace is created, and used as the +local scope --- thus, all assignments to local variables go into this new +namespace. In particular, function definitions bind the name of the new +function here. + +When a class definition is left normally (via the end), a *class object* is +created. This is basically a wrapper around the contents of the namespace +created by the class definition; we'll learn more about class objects in the +next section. The original local scope (the one in effect just before the class +definition was entered) is reinstated, and the class object is bound here to the +class name given in the class definition header (:class:`ClassName` in the +example). + + +.. _tut-classobjects: + +Class Objects +------------- + +Class objects support two kinds of operations: attribute references and +instantiation. + +*Attribute references* use the standard syntax used for all attribute references +in Python: ``obj.name``. Valid attribute names are all the names that were in +the class's namespace when the class object was created. So, if the class +definition looked like this:: + + class MyClass: + "A simple example class" + i = 12345 + def f(self): + return 'hello world' + +then ``MyClass.i`` and ``MyClass.f`` are valid attribute references, returning +an integer and a function object, respectively. Class attributes can also be +assigned to, so you can change the value of ``MyClass.i`` by assignment. +:attr:`__doc__` is also a valid attribute, returning the docstring belonging to +the class: ``"A simple example class"``. + +Class *instantiation* uses function notation. Just pretend that the class +object is a parameterless function that returns a new instance of the class. +For example (assuming the above class):: + + x = MyClass() + +creates a new *instance* of the class and assigns this object to the local +variable ``x``. + +The instantiation operation ("calling" a class object) creates an empty object. +Many classes like to create objects with instances customized to a specific +initial state. Therefore a class may define a special method named +:meth:`__init__`, like this:: + + def __init__(self): + self.data = [] + +When a class defines an :meth:`__init__` method, class instantiation +automatically invokes :meth:`__init__` for the newly-created class instance. So +in this example, a new, initialized instance can be obtained by:: + + x = MyClass() + +Of course, the :meth:`__init__` method may have arguments for greater +flexibility. In that case, arguments given to the class instantiation operator +are passed on to :meth:`__init__`. For example, :: + + >>> class Complex: + ... def __init__(self, realpart, imagpart): + ... self.r = realpart + ... self.i = imagpart + ... + >>> x = Complex(3.0, -4.5) + >>> x.r, x.i + (3.0, -4.5) + + +.. _tut-instanceobjects: + +Instance Objects +---------------- + +Now what can we do with instance objects? The only operations understood by +instance objects are attribute references. There are two kinds of valid +attribute names, data attributes and methods. + +*data attributes* correspond to "instance variables" in Smalltalk, and to "data +members" in C++. Data attributes need not be declared; like local variables, +they spring into existence when they are first assigned to. For example, if +``x`` is the instance of :class:`MyClass` created above, the following piece of +code will print the value ``16``, without leaving a trace:: + + x.counter = 1 + while x.counter < 10: + x.counter = x.counter * 2 + print x.counter + del x.counter + +The other kind of instance attribute reference is a *method*. A method is a +function that "belongs to" an object. (In Python, the term method is not unique +to class instances: other object types can have methods as well. For example, +list objects have methods called append, insert, remove, sort, and so on. +However, in the following discussion, we'll use the term method exclusively to +mean methods of class instance objects, unless explicitly stated otherwise.) + +.. index:: object: method + +Valid method names of an instance object depend on its class. By definition, +all attributes of a class that are function objects define corresponding +methods of its instances. So in our example, ``x.f`` is a valid method +reference, since ``MyClass.f`` is a function, but ``x.i`` is not, since +``MyClass.i`` is not. But ``x.f`` is not the same thing as ``MyClass.f`` --- it +is a *method object*, not a function object. + + +.. _tut-methodobjects: + +Method Objects +-------------- + +Usually, a method is called right after it is bound:: + + x.f() + +In the :class:`MyClass` example, this will return the string ``'hello world'``. +However, it is not necessary to call a method right away: ``x.f`` is a method +object, and can be stored away and called at a later time. For example:: + + xf = x.f + while True: + print xf() + +will continue to print ``hello world`` until the end of time. + +What exactly happens when a method is called? You may have noticed that +``x.f()`` was called without an argument above, even though the function +definition for :meth:`f` specified an argument. What happened to the argument? +Surely Python raises an exception when a function that requires an argument is +called without any --- even if the argument isn't actually used... + +Actually, you may have guessed the answer: the special thing about methods is +that the object is passed as the first argument of the function. In our +example, the call ``x.f()`` is exactly equivalent to ``MyClass.f(x)``. In +general, calling a method with a list of *n* arguments is equivalent to calling +the corresponding function with an argument list that is created by inserting +the method's object before the first argument. + +If you still don't understand how methods work, a look at the implementation can +perhaps clarify matters. When an instance attribute is referenced that isn't a +data attribute, its class is searched. If the name denotes a valid class +attribute that is a function object, a method object is created by packing +(pointers to) the instance object and the function object just found together in +an abstract object: this is the method object. When the method object is called +with an argument list, it is unpacked again, a new argument list is constructed +from the instance object and the original argument list, and the function object +is called with this new argument list. + + +.. _tut-remarks: + +Random Remarks +============== + +.. % [These should perhaps be placed more carefully...] + +Data attributes override method attributes with the same name; to avoid +accidental name conflicts, which may cause hard-to-find bugs in large programs, +it is wise to use some kind of convention that minimizes the chance of +conflicts. Possible conventions include capitalizing method names, prefixing +data attribute names with a small unique string (perhaps just an underscore), or +using verbs for methods and nouns for data attributes. + +Data attributes may be referenced by methods as well as by ordinary users +("clients") of an object. In other words, classes are not usable to implement +pure abstract data types. In fact, nothing in Python makes it possible to +enforce data hiding --- it is all based upon convention. (On the other hand, +the Python implementation, written in C, can completely hide implementation +details and control access to an object if necessary; this can be used by +extensions to Python written in C.) + +Clients should use data attributes with care --- clients may mess up invariants +maintained by the methods by stamping on their data attributes. Note that +clients may add data attributes of their own to an instance object without +affecting the validity of the methods, as long as name conflicts are avoided --- +again, a naming convention can save a lot of headaches here. + +There is no shorthand for referencing data attributes (or other methods!) from +within methods. I find that this actually increases the readability of methods: +there is no chance of confusing local variables and instance variables when +glancing through a method. + +Often, the first argument of a method is called ``self``. This is nothing more +than a convention: the name ``self`` has absolutely no special meaning to +Python. (Note, however, that by not following the convention your code may be +less readable to other Python programmers, and it is also conceivable that a +*class browser* program might be written that relies upon such a convention.) + +Any function object that is a class attribute defines a method for instances of +that class. It is not necessary that the function definition is textually +enclosed in the class definition: assigning a function object to a local +variable in the class is also ok. For example:: + + # Function defined outside the class + def f1(self, x, y): + return min(x, x+y) + + class C: + f = f1 + def g(self): + return 'hello world' + h = g + +Now ``f``, ``g`` and ``h`` are all attributes of class :class:`C` that refer to +function objects, and consequently they are all methods of instances of +:class:`C` --- ``h`` being exactly equivalent to ``g``. Note that this practice +usually only serves to confuse the reader of a program. + +Methods may call other methods by using method attributes of the ``self`` +argument:: + + class Bag: + def __init__(self): + self.data = [] + def add(self, x): + self.data.append(x) + def addtwice(self, x): + self.add(x) + self.add(x) + +Methods may reference global names in the same way as ordinary functions. The +global scope associated with a method is the module containing the class +definition. (The class itself is never used as a global scope!) While one +rarely encounters a good reason for using global data in a method, there are +many legitimate uses of the global scope: for one thing, functions and modules +imported into the global scope can be used by methods, as well as functions and +classes defined in it. Usually, the class containing the method is itself +defined in this global scope, and in the next section we'll find some good +reasons why a method would want to reference its own class! + + +.. _tut-inheritance: + +Inheritance +=========== + +Of course, a language feature would not be worthy of the name "class" without +supporting inheritance. The syntax for a derived class definition looks like +this:: + + class DerivedClassName(BaseClassName): + <statement-1> + . + . + . + <statement-N> + +The name :class:`BaseClassName` must be defined in a scope containing the +derived class definition. In place of a base class name, other arbitrary +expressions are also allowed. This can be useful, for example, when the base +class is defined in another module:: + + class DerivedClassName(modname.BaseClassName): + +Execution of a derived class definition proceeds the same as for a base class. +When the class object is constructed, the base class is remembered. This is +used for resolving attribute references: if a requested attribute is not found +in the class, the search proceeds to look in the base class. This rule is +applied recursively if the base class itself is derived from some other class. + +There's nothing special about instantiation of derived classes: +``DerivedClassName()`` creates a new instance of the class. Method references +are resolved as follows: the corresponding class attribute is searched, +descending down the chain of base classes if necessary, and the method reference +is valid if this yields a function object. + +Derived classes may override methods of their base classes. Because methods +have no special privileges when calling other methods of the same object, a +method of a base class that calls another method defined in the same base class +may end up calling a method of a derived class that overrides it. (For C++ +programmers: all methods in Python are effectively :keyword:`virtual`.) + +An overriding method in a derived class may in fact want to extend rather than +simply replace the base class method of the same name. There is a simple way to +call the base class method directly: just call ``BaseClassName.methodname(self, +arguments)``. This is occasionally useful to clients as well. (Note that this +only works if the base class is defined or imported directly in the global +scope.) + + +.. _tut-multiple: + +Multiple Inheritance +-------------------- + +Python supports a limited form of multiple inheritance as well. A class +definition with multiple base classes looks like this:: + + class DerivedClassName(Base1, Base2, Base3): + <statement-1> + . + . + . + <statement-N> + +For old-style classes, the only rule is depth-first, left-to-right. Thus, if an +attribute is not found in :class:`DerivedClassName`, it is searched in +:class:`Base1`, then (recursively) in the base classes of :class:`Base1`, and +only if it is not found there, it is searched in :class:`Base2`, and so on. + +(To some people breadth first --- searching :class:`Base2` and :class:`Base3` +before the base classes of :class:`Base1` --- looks more natural. However, this +would require you to know whether a particular attribute of :class:`Base1` is +actually defined in :class:`Base1` or in one of its base classes before you can +figure out the consequences of a name conflict with an attribute of +:class:`Base2`. The depth-first rule makes no differences between direct and +inherited attributes of :class:`Base1`.) + +For new-style classes, the method resolution order changes dynamically to +support cooperative calls to :func:`super`. This approach is known in some +other multiple-inheritance languages as call-next-method and is more powerful +than the super call found in single-inheritance languages. + +With new-style classes, dynamic ordering is necessary because all cases of +multiple inheritance exhibit one or more diamond relationships (where one at +least one of the parent classes can be accessed through multiple paths from the +bottommost class). For example, all new-style classes inherit from +:class:`object`, so any case of multiple inheritance provides more than one path +to reach :class:`object`. To keep the base classes from being accessed more +than once, the dynamic algorithm linearizes the search order in a way that +preserves the left-to-right ordering specified in each class, that calls each +parent only once, and that is monotonic (meaning that a class can be subclassed +without affecting the precedence order of its parents). Taken together, these +properties make it possible to design reliable and extensible classes with +multiple inheritance. For more detail, see +http://www.python.org/download/releases/2.3/mro/. + + +.. _tut-private: + +Private Variables +================= + +There is limited support for class-private identifiers. Any identifier of the +form ``__spam`` (at least two leading underscores, at most one trailing +underscore) is textually replaced with ``_classname__spam``, where ``classname`` +is the current class name with leading underscore(s) stripped. This mangling is +done without regard to the syntactic position of the identifier, so it can be +used to define class-private instance and class variables, methods, variables +stored in globals, and even variables stored in instances. private to this class +on instances of *other* classes. Truncation may occur when the mangled name +would be longer than 255 characters. Outside classes, or when the class name +consists of only underscores, no mangling occurs. + +Name mangling is intended to give classes an easy way to define "private" +instance variables and methods, without having to worry about instance variables +defined by derived classes, or mucking with instance variables by code outside +the class. Note that the mangling rules are designed mostly to avoid accidents; +it still is possible for a determined soul to access or modify a variable that +is considered private. This can even be useful in special circumstances, such +as in the debugger, and that's one reason why this loophole is not closed. +(Buglet: derivation of a class with the same name as the base class makes use of +private variables of the base class possible.) + +Notice that code passed to ``exec()`` or ``eval()`` does not +consider the classname of the invoking class to be the current class; this is +similar to the effect of the ``global`` statement, the effect of which is +likewise restricted to code that is byte-compiled together. The same +restriction applies to ``getattr()``, ``setattr()`` and ``delattr()``, as well +as when referencing ``__dict__`` directly. + + +.. _tut-odds: + +Odds and Ends +============= + +Sometimes it is useful to have a data type similar to the Pascal "record" or C +"struct", bundling together a few named data items. An empty class definition +will do nicely:: + + class Employee: + pass + + john = Employee() # Create an empty employee record + + # Fill the fields of the record + john.name = 'John Doe' + john.dept = 'computer lab' + john.salary = 1000 + +A piece of Python code that expects a particular abstract data type can often be +passed a class that emulates the methods of that data type instead. For +instance, if you have a function that formats some data from a file object, you +can define a class with methods :meth:`read` and :meth:`readline` that get the +data from a string buffer instead, and pass it as an argument. + +.. % (Unfortunately, this +.. % technique has its limitations: a class can't define operations that +.. % are accessed by special syntax such as sequence subscripting or +.. % arithmetic operators, and assigning such a ``pseudo-file'' to +.. % \code{sys.stdin} will not cause the interpreter to read further input +.. % from it.) + +Instance method objects have attributes, too: ``m.im_self`` is the instance +object with the method :meth:`m`, and ``m.im_func`` is the function object +corresponding to the method. + + +.. _tut-exceptionclasses: + +Exceptions Are Classes Too +========================== + +User-defined exceptions are identified by classes as well. Using this mechanism +it is possible to create extensible hierarchies of exceptions. + +There are two new valid (semantic) forms for the raise statement:: + + raise Class, instance + + raise instance + +In the first form, ``instance`` must be an instance of :class:`Class` or of a +class derived from it. The second form is a shorthand for:: + + raise instance.__class__, instance + +A class in an except clause is compatible with an exception if it is the same +class or a base class thereof (but not the other way around --- an except clause +listing a derived class is not compatible with a base class). For example, the +following code will print B, C, D in that order:: + + class B: + pass + class C(B): + pass + class D(C): + pass + + for c in [B, C, D]: + try: + raise c() + except D: + print "D" + except C: + print "C" + except B: + print "B" + +Note that if the except clauses were reversed (with ``except B`` first), it +would have printed B, B, B --- the first matching except clause is triggered. + +When an error message is printed for an unhandled exception, the exception's +class name is printed, then a colon and a space, and finally the instance +converted to a string using the built-in function :func:`str`. + + +.. _tut-iterators: + +Iterators +========= + +By now you have probably noticed that most container objects can be looped over +using a :keyword:`for` statement:: + + for element in [1, 2, 3]: + print element + for element in (1, 2, 3): + print element + for key in {'one':1, 'two':2}: + print key + for char in "123": + print char + for line in open("myfile.txt"): + print line + +This style of access is clear, concise, and convenient. The use of iterators +pervades and unifies Python. Behind the scenes, the :keyword:`for` statement +calls :func:`iter` on the container object. The function returns an iterator +object that defines the method :meth:`__next__` which accesses elements in the +container one at a time. When there are no more elements, :meth:`__next__` +raises a :exc:`StopIteration` exception which tells the :keyword:`for` loop to +terminate. You can call the :meth:`__next__` method using the :func:`next` +builtin; this example shows how it all works:: + + >>> s = 'abc' + >>> it = iter(s) + >>> it + <iterator object at 0x00A1DB50> + >>> next(it) + 'a' + >>> next(it) + 'b' + >>> next(it) + 'c' + >>> next(it) + + Traceback (most recent call last): + File "<stdin>", line 1, in ? + next(it) + StopIteration + +Having seen the mechanics behind the iterator protocol, it is easy to add +iterator behavior to your classes. Define a :meth:`__iter__` method which +returns an object with a :meth:`__next__` method. If the class defines +:meth:`__next__`, then :meth:`__iter__` can just return ``self``:: + + class Reverse: + "Iterator for looping over a sequence backwards" + def __init__(self, data): + self.data = data + self.index = len(data) + def __iter__(self): + return self + def __next__(self): + if self.index == 0: + raise StopIteration + self.index = self.index - 1 + return self.data[self.index] + + >>> for char in Reverse('spam'): + ... print char + ... + m + a + p + s + + +.. _tut-generators: + +Generators +========== + +Generators are a simple and powerful tool for creating iterators. They are +written like regular functions but use the :keyword:`yield` statement whenever +they want to return data. Each time :func:`next` is called on it, the generator +resumes where it left-off (it remembers all the data values and which statement +was last executed). An example shows that generators can be trivially easy to +create:: + + def reverse(data): + for index in range(len(data)-1, -1, -1): + yield data[index] + + >>> for char in reverse('golf'): + ... print char + ... + f + l + o + g + +Anything that can be done with generators can also be done with class based +iterators as described in the previous section. What makes generators so +compact is that the :meth:`__iter__` and :meth:`__next__` methods are created +automatically. + +Another key feature is that the local variables and execution state are +automatically saved between calls. This made the function easier to write and +much more clear than an approach using instance variables like ``self.index`` +and ``self.data``. + +In addition to automatic method creation and saving program state, when +generators terminate, they automatically raise :exc:`StopIteration`. In +combination, these features make it easy to create iterators with no more effort +than writing a regular function. + + +.. _tut-genexps: + +Generator Expressions +===================== + +Some simple generators can be coded succinctly as expressions using a syntax +similar to list comprehensions but with parentheses instead of brackets. These +expressions are designed for situations where the generator is used right away +by an enclosing function. Generator expressions are more compact but less +versatile than full generator definitions and tend to be more memory friendly +than equivalent list comprehensions. + +Examples:: + + >>> sum(i*i for i in range(10)) # sum of squares + 285 + + >>> xvec = [10, 20, 30] + >>> yvec = [7, 5, 3] + >>> sum(x*y for x,y in zip(xvec, yvec)) # dot product + 260 + + >>> from math import pi, sin + >>> sine_table = dict((x, sin(x*pi/180)) for x in range(0, 91)) + + >>> unique_words = set(word for line in page for word in line.split()) + + >>> valedictorian = max((student.gpa, student.name) for student in graduates) + + >>> data = 'golf' + >>> list(data[i] for i in range(len(data)-1,-1,-1)) + ['f', 'l', 'o', 'g'] + + + +.. rubric:: Footnotes + +.. [#] Except for one thing. Module objects have a secret read-only attribute called + :attr:`__dict__` which returns the dictionary used to implement the module's + namespace; the name :attr:`__dict__` is an attribute but not a global name. + Obviously, using this violates the abstraction of namespace implementation, and + should be restricted to things like post-mortem debuggers. + diff --git a/Doc/tutorial/controlflow.rst b/Doc/tutorial/controlflow.rst new file mode 100644 index 0000000..f6f41b3 --- /dev/null +++ b/Doc/tutorial/controlflow.rst @@ -0,0 +1,574 @@ +.. _tut-morecontrol: + +*********************** +More Control Flow Tools +*********************** + +Besides the :keyword:`while` statement just introduced, Python knows the usual +control flow statements known from other languages, with some twists. + + +.. _tut-if: + +:keyword:`if` Statements +======================== + +Perhaps the most well-known statement type is the :keyword:`if` statement. For +example:: + + >>> def raw_input(prompt): + ... import sys + ... sys.stdout.write(prompt) + ... sys.stdout.flush() + ... return sys.stdin.readline() + ... + >>> x = int(raw_input("Please enter an integer: ")) + >>> if x < 0: + ... x = 0 + ... print 'Negative changed to zero' + ... elif x == 0: + ... print 'Zero' + ... elif x == 1: + ... print 'Single' + ... else: + ... print 'More' + ... + +There can be zero or more :keyword:`elif` parts, and the :keyword:`else` part is +optional. The keyword ':keyword:`elif`' is short for 'else if', and is useful +to avoid excessive indentation. An :keyword:`if` ... :keyword:`elif` ... +:keyword:`elif` ... sequence is a substitute for the :keyword:`switch` or +:keyword:`case` statements found in other languages. + +.. % Weird spacings happen here if the wrapping of the source text +.. % gets changed in the wrong way. + + +.. _tut-for: + +:keyword:`for` Statements +========================= + +.. index:: + statement: for + statement: for + +The :keyword:`for` statement in Python differs a bit from what you may be used +to in C or Pascal. Rather than always iterating over an arithmetic progression +of numbers (like in Pascal), or giving the user the ability to define both the +iteration step and halting condition (as C), Python's :keyword:`for` statement +iterates over the items of any sequence (a list or a string), in the order that +they appear in the sequence. For example (no pun intended): + +.. % One suggestion was to give a real C example here, but that may only +.. % serve to confuse non-C programmers. + +:: + + >>> # Measure some strings: + ... a = ['cat', 'window', 'defenestrate'] + >>> for x in a: + ... print x, len(x) + ... + cat 3 + window 6 + defenestrate 12 + +It is not safe to modify the sequence being iterated over in the loop (this can +only happen for mutable sequence types, such as lists). If you need to modify +the list you are iterating over (for example, to duplicate selected items) you +must iterate over a copy. The slice notation makes this particularly +convenient:: + + >>> for x in a[:]: # make a slice copy of the entire list + ... if len(x) > 6: a.insert(0, x) + ... + >>> a + ['defenestrate', 'cat', 'window', 'defenestrate'] + + +.. _tut-range: + +The :func:`range` Function +========================== + +If you do need to iterate over a sequence of numbers, the built-in function +:func:`range` comes in handy. It generates lists containing arithmetic +progressions:: + + >>> range(10) + [0, 1, 2, 3, 4, 5, 6, 7, 8, 9] + +The given end point is never part of the generated list; ``range(10)`` generates +a list of 10 values, the legal indices for items of a sequence of length 10. It +is possible to let the range start at another number, or to specify a different +increment (even negative; sometimes this is called the 'step'):: + + >>> range(5, 10) + [5, 6, 7, 8, 9] + >>> range(0, 10, 3) + [0, 3, 6, 9] + >>> range(-10, -100, -30) + [-10, -40, -70] + +To iterate over the indices of a sequence, combine :func:`range` and :func:`len` +as follows:: + + >>> a = ['Mary', 'had', 'a', 'little', 'lamb'] + >>> for i in range(len(a)): + ... print i, a[i] + ... + 0 Mary + 1 had + 2 a + 3 little + 4 lamb + + +.. _tut-break: + +:keyword:`break` and :keyword:`continue` Statements, and :keyword:`else` Clauses on Loops +========================================================================================= + +The :keyword:`break` statement, like in C, breaks out of the smallest enclosing +:keyword:`for` or :keyword:`while` loop. + +The :keyword:`continue` statement, also borrowed from C, continues with the next +iteration of the loop. + +Loop statements may have an ``else`` clause; it is executed when the loop +terminates through exhaustion of the list (with :keyword:`for`) or when the +condition becomes false (with :keyword:`while`), but not when the loop is +terminated by a :keyword:`break` statement. This is exemplified by the +following loop, which searches for prime numbers:: + + >>> for n in range(2, 10): + ... for x in range(2, n): + ... if n % x == 0: + ... print n, 'equals', x, '*', n/x + ... break + ... else: + ... # loop fell through without finding a factor + ... print n, 'is a prime number' + ... + 2 is a prime number + 3 is a prime number + 4 equals 2 * 2 + 5 is a prime number + 6 equals 2 * 3 + 7 is a prime number + 8 equals 2 * 4 + 9 equals 3 * 3 + + +.. _tut-pass: + +:keyword:`pass` Statements +========================== + +The :keyword:`pass` statement does nothing. It can be used when a statement is +required syntactically but the program requires no action. For example:: + + >>> while True: + ... pass # Busy-wait for keyboard interrupt + ... + + +.. _tut-functions: + +Defining Functions +================== + +We can create a function that writes the Fibonacci series to an arbitrary +boundary:: + + >>> def fib(n): # write Fibonacci series up to n + ... """Print a Fibonacci series up to n.""" + ... a, b = 0, 1 + ... while b < n: + ... print b, + ... a, b = b, a+b + ... + >>> # Now call the function we just defined: + ... fib(2000) + 1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987 1597 + +.. index:: + single: documentation strings + single: docstrings + single: strings, documentation + +The keyword :keyword:`def` introduces a function *definition*. It must be +followed by the function name and the parenthesized list of formal parameters. +The statements that form the body of the function start at the next line, and +must be indented. The first statement of the function body can optionally be a +string literal; this string literal is the function's documentation string, or +:dfn:`docstring`. + +There are tools which use docstrings to automatically produce online or printed +documentation, or to let the user interactively browse through code; it's good +practice to include docstrings in code that you write, so try to make a habit of +it. + +The *execution* of a function introduces a new symbol table used for the local +variables of the function. More precisely, all variable assignments in a +function store the value in the local symbol table; whereas variable references +first look in the local symbol table, then in the global symbol table, and then +in the table of built-in names. Thus, global variables cannot be directly +assigned a value within a function (unless named in a :keyword:`global` +statement), although they may be referenced. + +The actual parameters (arguments) to a function call are introduced in the local +symbol table of the called function when it is called; thus, arguments are +passed using *call by value* (where the *value* is always an object *reference*, +not the value of the object). [#]_ When a function calls another function, a new +local symbol table is created for that call. + +A function definition introduces the function name in the current symbol table. +The value of the function name has a type that is recognized by the interpreter +as a user-defined function. This value can be assigned to another name which +can then also be used as a function. This serves as a general renaming +mechanism:: + + >>> fib + <function fib at 10042ed0> + >>> f = fib + >>> f(100) + 1 1 2 3 5 8 13 21 34 55 89 + +You might object that ``fib`` is not a function but a procedure. In Python, +like in C, procedures are just functions that don't return a value. In fact, +technically speaking, procedures do return a value, albeit a rather boring one. +This value is called ``None`` (it's a built-in name). Writing the value +``None`` is normally suppressed by the interpreter if it would be the only value +written. You can see it if you really want to:: + + >>> print fib(0) + None + +It is simple to write a function that returns a list of the numbers of the +Fibonacci series, instead of printing it:: + + >>> def fib2(n): # return Fibonacci series up to n + ... """Return a list containing the Fibonacci series up to n.""" + ... result = [] + ... a, b = 0, 1 + ... while b < n: + ... result.append(b) # see below + ... a, b = b, a+b + ... return result + ... + >>> f100 = fib2(100) # call it + >>> f100 # write the result + [1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89] + +This example, as usual, demonstrates some new Python features: + +* The :keyword:`return` statement returns with a value from a function. + :keyword:`return` without an expression argument returns ``None``. Falling off + the end of a procedure also returns ``None``. + +* The statement ``result.append(b)`` calls a *method* of the list object + ``result``. A method is a function that 'belongs' to an object and is named + ``obj.methodname``, where ``obj`` is some object (this may be an expression), + and ``methodname`` is the name of a method that is defined by the object's type. + Different types define different methods. Methods of different types may have + the same name without causing ambiguity. (It is possible to define your own + object types and methods, using *classes*, as discussed later in this tutorial.) + The method :meth:`append` shown in the example is defined for list objects; it + adds a new element at the end of the list. In this example it is equivalent to + ``result = result + [b]``, but more efficient. + + +.. _tut-defining: + +More on Defining Functions +========================== + +It is also possible to define functions with a variable number of arguments. +There are three forms, which can be combined. + + +.. _tut-defaultargs: + +Default Argument Values +----------------------- + +The most useful form is to specify a default value for one or more arguments. +This creates a function that can be called with fewer arguments than it is +defined to allow. For example:: + + def raw_input(prompt): + import sys + sys.stdout.write(prompt) + sys.stdout.flush() + return sys.stdin.readline() + + def ask_ok(prompt, retries=4, complaint='Yes or no, please!'): + while True: + ok = raw_input(prompt) + if ok in ('y', 'ye', 'yes'): return True + if ok in ('n', 'no', 'nop', 'nope'): return False + retries = retries - 1 + if retries < 0: raise IOError, 'refusenik user' + print complaint + +This function can be called either like this: ``ask_ok('Do you really want to +quit?')`` or like this: ``ask_ok('OK to overwrite the file?', 2)``. + +This example also introduces the :keyword:`in` keyword. This tests whether or +not a sequence contains a certain value. + +The default values are evaluated at the point of function definition in the +*defining* scope, so that :: + + i = 5 + + def f(arg=i): + print arg + + i = 6 + f() + +will print ``5``. + +**Important warning:** The default value is evaluated only once. This makes a +difference when the default is a mutable object such as a list, dictionary, or +instances of most classes. For example, the following function accumulates the +arguments passed to it on subsequent calls:: + + def f(a, L=[]): + L.append(a) + return L + + print f(1) + print f(2) + print f(3) + +This will print :: + + [1] + [1, 2] + [1, 2, 3] + +If you don't want the default to be shared between subsequent calls, you can +write the function like this instead:: + + def f(a, L=None): + if L is None: + L = [] + L.append(a) + return L + + +.. _tut-keywordargs: + +Keyword Arguments +----------------- + +Functions can also be called using keyword arguments of the form ``keyword = +value``. For instance, the following function:: + + def parrot(voltage, state='a stiff', action='voom', type='Norwegian Blue'): + print "-- This parrot wouldn't", action, + print "if you put", voltage, "volts through it." + print "-- Lovely plumage, the", type + print "-- It's", state, "!" + +could be called in any of the following ways:: + + parrot(1000) + parrot(action = 'VOOOOOM', voltage = 1000000) + parrot('a thousand', state = 'pushing up the daisies') + parrot('a million', 'bereft of life', 'jump') + +but the following calls would all be invalid:: + + parrot() # required argument missing + parrot(voltage=5.0, 'dead') # non-keyword argument following keyword + parrot(110, voltage=220) # duplicate value for argument + parrot(actor='John Cleese') # unknown keyword + +In general, an argument list must have any positional arguments followed by any +keyword arguments, where the keywords must be chosen from the formal parameter +names. It's not important whether a formal parameter has a default value or +not. No argument may receive a value more than once --- formal parameter names +corresponding to positional arguments cannot be used as keywords in the same +calls. Here's an example that fails due to this restriction:: + + >>> def function(a): + ... pass + ... + >>> function(0, a=0) + Traceback (most recent call last): + File "<stdin>", line 1, in ? + TypeError: function() got multiple values for keyword argument 'a' + +When a final formal parameter of the form ``**name`` is present, it receives a +dictionary (see :ref:`typesmapping`) containing all keyword arguments except for +those corresponding to a formal parameter. This may be combined with a formal +parameter of the form ``*name`` (described in the next subsection) which +receives a tuple containing the positional arguments beyond the formal parameter +list. (``*name`` must occur before ``**name``.) For example, if we define a +function like this:: + + def cheeseshop(kind, *arguments, **keywords): + print "-- Do you have any", kind, '?' + print "-- I'm sorry, we're all out of", kind + for arg in arguments: print arg + print '-'*40 + keys = keywords.keys() + keys.sort() + for kw in keys: print kw, ':', keywords[kw] + +It could be called like this:: + + cheeseshop('Limburger', "It's very runny, sir.", + "It's really very, VERY runny, sir.", + client='John Cleese', + shopkeeper='Michael Palin', + sketch='Cheese Shop Sketch') + +and of course it would print:: + + -- Do you have any Limburger ? + -- I'm sorry, we're all out of Limburger + It's very runny, sir. + It's really very, VERY runny, sir. + ---------------------------------------- + client : John Cleese + shopkeeper : Michael Palin + sketch : Cheese Shop Sketch + +Note that the :meth:`sort` method of the list of keyword argument names is +called before printing the contents of the ``keywords`` dictionary; if this is +not done, the order in which the arguments are printed is undefined. + + +.. _tut-arbitraryargs: + +Arbitrary Argument Lists +------------------------ + +Finally, the least frequently used option is to specify that a function can be +called with an arbitrary number of arguments. These arguments will be wrapped +up in a tuple. Before the variable number of arguments, zero or more normal +arguments may occur. :: + + def fprintf(file, format, *args): + file.write(format % args) + + +.. _tut-unpacking-arguments: + +Unpacking Argument Lists +------------------------ + +The reverse situation occurs when the arguments are already in a list or tuple +but need to be unpacked for a function call requiring separate positional +arguments. For instance, the built-in :func:`range` function expects separate +*start* and *stop* arguments. If they are not available separately, write the +function call with the ``*``\ -operator to unpack the arguments out of a list +or tuple:: + + >>> range(3, 6) # normal call with separate arguments + [3, 4, 5] + >>> args = [3, 6] + >>> range(*args) # call with arguments unpacked from a list + [3, 4, 5] + +In the same fashion, dictionaries can deliver keyword arguments with the ``**``\ +-operator:: + + >>> def parrot(voltage, state='a stiff', action='voom'): + ... print "-- This parrot wouldn't", action, + ... print "if you put", voltage, "volts through it.", + ... print "E's", state, "!" + ... + >>> d = {"voltage": "four million", "state": "bleedin' demised", "action": "VOOM"} + >>> parrot(**d) + -- This parrot wouldn't VOOM if you put four million volts through it. E's bleedin' demised ! + + +.. _tut-lambda: + +Lambda Forms +------------ + +By popular demand, a few features commonly found in functional programming +languages like Lisp have been added to Python. With the :keyword:`lambda` +keyword, small anonymous functions can be created. Here's a function that +returns the sum of its two arguments: ``lambda a, b: a+b``. Lambda forms can be +used wherever function objects are required. They are syntactically restricted +to a single expression. Semantically, they are just syntactic sugar for a +normal function definition. Like nested function definitions, lambda forms can +reference variables from the containing scope:: + + >>> def make_incrementor(n): + ... return lambda x: x + n + ... + >>> f = make_incrementor(42) + >>> f(0) + 42 + >>> f(1) + 43 + + +.. _tut-docstrings: + +Documentation Strings +--------------------- + +.. index:: + single: docstrings + single: documentation strings + single: strings, documentation + +There are emerging conventions about the content and formatting of documentation +strings. + +The first line should always be a short, concise summary of the object's +purpose. For brevity, it should not explicitly state the object's name or type, +since these are available by other means (except if the name happens to be a +verb describing a function's operation). This line should begin with a capital +letter and end with a period. + +If there are more lines in the documentation string, the second line should be +blank, visually separating the summary from the rest of the description. The +following lines should be one or more paragraphs describing the object's calling +conventions, its side effects, etc. + +The Python parser does not strip indentation from multi-line string literals in +Python, so tools that process documentation have to strip indentation if +desired. This is done using the following convention. The first non-blank line +*after* the first line of the string determines the amount of indentation for +the entire documentation string. (We can't use the first line since it is +generally adjacent to the string's opening quotes so its indentation is not +apparent in the string literal.) Whitespace "equivalent" to this indentation is +then stripped from the start of all lines of the string. Lines that are +indented less should not occur, but if they occur all their leading whitespace +should be stripped. Equivalence of whitespace should be tested after expansion +of tabs (to 8 spaces, normally). + +Here is an example of a multi-line docstring:: + + >>> def my_function(): + ... """Do nothing, but document it. + ... + ... No, really, it doesn't do anything. + ... """ + ... pass + ... + >>> print my_function.__doc__ + Do nothing, but document it. + + No, really, it doesn't do anything. + + + +.. rubric:: Footnotes + +.. [#] Actually, *call by object reference* would be a better description, since if a + mutable object is passed, the caller will see any changes the callee makes to it + (items inserted into a list). + diff --git a/Doc/tutorial/datastructures.rst b/Doc/tutorial/datastructures.rst new file mode 100644 index 0000000..d65e55b --- /dev/null +++ b/Doc/tutorial/datastructures.rst @@ -0,0 +1,586 @@ +.. _tut-structures: + +*************** +Data Structures +*************** + +This chapter describes some things you've learned about already in more detail, +and adds some new things as well. + + +.. _tut-morelists: + +More on Lists +============= + +The list data type has some more methods. Here are all of the methods of list +objects: + + +.. method:: list.append(x) + + Add an item to the end of the list; equivalent to ``a[len(a):] = [x]``. + + +.. method:: list.extend(L) + + Extend the list by appending all the items in the given list; equivalent to + ``a[len(a):] = L``. + + +.. method:: list.insert(i, x) + + Insert an item at a given position. The first argument is the index of the + element before which to insert, so ``a.insert(0, x)`` inserts at the front of + the list, and ``a.insert(len(a), x)`` is equivalent to ``a.append(x)``. + + +.. method:: list.remove(x) + + Remove the first item from the list whose value is *x*. It is an error if there + is no such item. + + +.. method:: list.pop([i]) + + Remove the item at the given position in the list, and return it. If no index + is specified, ``a.pop()`` removes and returns the last item in the list. (The + square brackets around the *i* in the method signature denote that the parameter + is optional, not that you should type square brackets at that position. You + will see this notation frequently in the Python Library Reference.) + + +.. method:: list.index(x) + + Return the index in the list of the first item whose value is *x*. It is an + error if there is no such item. + + +.. method:: list.count(x) + + Return the number of times *x* appears in the list. + + +.. method:: list.sort() + + Sort the items of the list, in place. + + +.. method:: list.reverse() + + Reverse the elements of the list, in place. + +An example that uses most of the list methods:: + + >>> a = [66.25, 333, 333, 1, 1234.5] + >>> print a.count(333), a.count(66.25), a.count('x') + 2 1 0 + >>> a.insert(2, -1) + >>> a.append(333) + >>> a + [66.25, 333, -1, 333, 1, 1234.5, 333] + >>> a.index(333) + 1 + >>> a.remove(333) + >>> a + [66.25, -1, 333, 1, 1234.5, 333] + >>> a.reverse() + >>> a + [333, 1234.5, 1, 333, -1, 66.25] + >>> a.sort() + >>> a + [-1, 1, 66.25, 333, 333, 1234.5] + + +.. _tut-lists-as-stacks: + +Using Lists as Stacks +--------------------- + +.. sectionauthor:: Ka-Ping Yee <ping@lfw.org> + + +The list methods make it very easy to use a list as a stack, where the last +element added is the first element retrieved ("last-in, first-out"). To add an +item to the top of the stack, use :meth:`append`. To retrieve an item from the +top of the stack, use :meth:`pop` without an explicit index. For example:: + + >>> stack = [3, 4, 5] + >>> stack.append(6) + >>> stack.append(7) + >>> stack + [3, 4, 5, 6, 7] + >>> stack.pop() + 7 + >>> stack + [3, 4, 5, 6] + >>> stack.pop() + 6 + >>> stack.pop() + 5 + >>> stack + [3, 4] + + +.. _tut-lists-as-queues: + +Using Lists as Queues +--------------------- + +.. sectionauthor:: Ka-Ping Yee <ping@lfw.org> + + +You can also use a list conveniently as a queue, where the first element added +is the first element retrieved ("first-in, first-out"). To add an item to the +back of the queue, use :meth:`append`. To retrieve an item from the front of +the queue, use :meth:`pop` with ``0`` as the index. For example:: + + >>> queue = ["Eric", "John", "Michael"] + >>> queue.append("Terry") # Terry arrives + >>> queue.append("Graham") # Graham arrives + >>> queue.pop(0) + 'Eric' + >>> queue.pop(0) + 'John' + >>> queue + ['Michael', 'Terry', 'Graham'] + + +.. _tut-functional: + +Functional Programming Tools +---------------------------- + +There are two built-in functions that are very useful when used with lists: +:func:`filter` and :func:`map`. + +``filter(function, sequence)`` returns a sequence consisting of those items from +the sequence for which ``function(item)`` is true. If *sequence* is a +:class:`string` or :class:`tuple`, the result will be of the same type; +otherwise, it is always a :class:`list`. For example, to compute some primes:: + + >>> def f(x): return x % 2 != 0 and x % 3 != 0 + ... + >>> filter(f, range(2, 25)) + [5, 7, 11, 13, 17, 19, 23] + +``map(function, sequence)`` calls ``function(item)`` for each of the sequence's +items and returns a list of the return values. For example, to compute some +cubes:: + + >>> def cube(x): return x*x*x + ... + >>> map(cube, range(1, 11)) + [1, 8, 27, 64, 125, 216, 343, 512, 729, 1000] + +More than one sequence may be passed; the function must then have as many +arguments as there are sequences and is called with the corresponding item from +each sequence (or ``None`` if some sequence is shorter than another). For +example:: + + >>> seq = range(8) + >>> def add(x, y): return x+y + ... + >>> map(add, seq, seq) + [0, 2, 4, 6, 8, 10, 12, 14] + +.. versionadded:: 2.3 + + +List Comprehensions +------------------- + +List comprehensions provide a concise way to create lists without resorting to +use of :func:`map`, :func:`filter` and/or :keyword:`lambda`. The resulting list +definition tends often to be clearer than lists built using those constructs. +Each list comprehension consists of an expression followed by a :keyword:`for` +clause, then zero or more :keyword:`for` or :keyword:`if` clauses. The result +will be a list resulting from evaluating the expression in the context of the +:keyword:`for` and :keyword:`if` clauses which follow it. If the expression +would evaluate to a tuple, it must be parenthesized. :: + + >>> freshfruit = [' banana', ' loganberry ', 'passion fruit '] + >>> [weapon.strip() for weapon in freshfruit] + ['banana', 'loganberry', 'passion fruit'] + >>> vec = [2, 4, 6] + >>> [3*x for x in vec] + [6, 12, 18] + >>> [3*x for x in vec if x > 3] + [12, 18] + >>> [3*x for x in vec if x < 2] + [] + >>> [[x,x**2] for x in vec] + [[2, 4], [4, 16], [6, 36]] + >>> [x, x**2 for x in vec] # error - parens required for tuples + File "<stdin>", line 1, in ? + [x, x**2 for x in vec] + ^ + SyntaxError: invalid syntax + >>> [(x, x**2) for x in vec] + [(2, 4), (4, 16), (6, 36)] + >>> vec1 = [2, 4, 6] + >>> vec2 = [4, 3, -9] + >>> [x*y for x in vec1 for y in vec2] + [8, 6, -18, 16, 12, -36, 24, 18, -54] + >>> [x+y for x in vec1 for y in vec2] + [6, 5, -7, 8, 7, -5, 10, 9, -3] + >>> [vec1[i]*vec2[i] for i in range(len(vec1))] + [8, 12, -54] + +List comprehensions are much more flexible than :func:`map` and can be applied +to complex expressions and nested functions:: + + >>> [str(round(355/113.0, i)) for i in range(1,6)] + ['3.1', '3.14', '3.142', '3.1416', '3.14159'] + + +.. _tut-del: + +The :keyword:`del` statement +============================ + +There is a way to remove an item from a list given its index instead of its +value: the :keyword:`del` statement. This differs from the :meth:`pop` method +which returns a value. The :keyword:`del` statement can also be used to remove +slices from a list or clear the entire list (which we did earlier by assignment +of an empty list to the slice). For example:: + + >>> a = [-1, 1, 66.25, 333, 333, 1234.5] + >>> del a[0] + >>> a + [1, 66.25, 333, 333, 1234.5] + >>> del a[2:4] + >>> a + [1, 66.25, 1234.5] + >>> del a[:] + >>> a + [] + +:keyword:`del` can also be used to delete entire variables:: + + >>> del a + +Referencing the name ``a`` hereafter is an error (at least until another value +is assigned to it). We'll find other uses for :keyword:`del` later. + + +.. _tut-tuples: + +Tuples and Sequences +==================== + +We saw that lists and strings have many common properties, such as indexing and +slicing operations. They are two examples of *sequence* data types (see +:ref:`typesseq`). Since Python is an evolving language, other sequence data +types may be added. There is also another standard sequence data type: the +*tuple*. + +A tuple consists of a number of values separated by commas, for instance:: + + >>> t = 12345, 54321, 'hello!' + >>> t[0] + 12345 + >>> t + (12345, 54321, 'hello!') + >>> # Tuples may be nested: + ... u = t, (1, 2, 3, 4, 5) + >>> u + ((12345, 54321, 'hello!'), (1, 2, 3, 4, 5)) + +As you see, on output tuples are always enclosed in parentheses, so that nested +tuples are interpreted correctly; they may be input with or without surrounding +parentheses, although often parentheses are necessary anyway (if the tuple is +part of a larger expression). + +Tuples have many uses. For example: (x, y) coordinate pairs, employee records +from a database, etc. Tuples, like strings, are immutable: it is not possible +to assign to the individual items of a tuple (you can simulate much of the same +effect with slicing and concatenation, though). It is also possible to create +tuples which contain mutable objects, such as lists. + +A special problem is the construction of tuples containing 0 or 1 items: the +syntax has some extra quirks to accommodate these. Empty tuples are constructed +by an empty pair of parentheses; a tuple with one item is constructed by +following a value with a comma (it is not sufficient to enclose a single value +in parentheses). Ugly, but effective. For example:: + + >>> empty = () + >>> singleton = 'hello', # <-- note trailing comma + >>> len(empty) + 0 + >>> len(singleton) + 1 + >>> singleton + ('hello',) + +The statement ``t = 12345, 54321, 'hello!'`` is an example of *tuple packing*: +the values ``12345``, ``54321`` and ``'hello!'`` are packed together in a tuple. +The reverse operation is also possible:: + + >>> x, y, z = t + +This is called, appropriately enough, *sequence unpacking*. Sequence unpacking +requires the list of variables on the left to have the same number of elements +as the length of the sequence. Note that multiple assignment is really just a +combination of tuple packing and sequence unpacking! + +There is a small bit of asymmetry here: packing multiple values always creates +a tuple, and unpacking works for any sequence. + +.. % XXX Add a bit on the difference between tuples and lists. + + +.. _tut-sets: + +Sets +==== + +Python also includes a data type for *sets*. A set is an unordered collection +with no duplicate elements. Basic uses include membership testing and +eliminating duplicate entries. Set objects also support mathematical operations +like union, intersection, difference, and symmetric difference. + +Here is a brief demonstration:: + + >>> basket = ['apple', 'orange', 'apple', 'pear', 'orange', 'banana'] + >>> fruit = set(basket) # create a set without duplicates + >>> fruit + set(['orange', 'pear', 'apple', 'banana']) + >>> 'orange' in fruit # fast membership testing + True + >>> 'crabgrass' in fruit + False + + >>> # Demonstrate set operations on unique letters from two words + ... + >>> a = set('abracadabra') + >>> b = set('alacazam') + >>> a # unique letters in a + set(['a', 'r', 'b', 'c', 'd']) + >>> a - b # letters in a but not in b + set(['r', 'd', 'b']) + >>> a | b # letters in either a or b + set(['a', 'c', 'r', 'd', 'b', 'm', 'z', 'l']) + >>> a & b # letters in both a and b + set(['a', 'c']) + >>> a ^ b # letters in a or b but not both + set(['r', 'd', 'b', 'm', 'z', 'l']) + + +.. _tut-dictionaries: + +Dictionaries +============ + +Another useful data type built into Python is the *dictionary* (see +:ref:`typesmapping`). Dictionaries are sometimes found in other languages as +"associative memories" or "associative arrays". Unlike sequences, which are +indexed by a range of numbers, dictionaries are indexed by *keys*, which can be +any immutable type; strings and numbers can always be keys. Tuples can be used +as keys if they contain only strings, numbers, or tuples; if a tuple contains +any mutable object either directly or indirectly, it cannot be used as a key. +You can't use lists as keys, since lists can be modified in place using index +assignments, slice assignments, or methods like :meth:`append` and +:meth:`extend`. + +It is best to think of a dictionary as an unordered set of *key: value* pairs, +with the requirement that the keys are unique (within one dictionary). A pair of +braces creates an empty dictionary: ``{}``. Placing a comma-separated list of +key:value pairs within the braces adds initial key:value pairs to the +dictionary; this is also the way dictionaries are written on output. + +The main operations on a dictionary are storing a value with some key and +extracting the value given the key. It is also possible to delete a key:value +pair with ``del``. If you store using a key that is already in use, the old +value associated with that key is forgotten. It is an error to extract a value +using a non-existent key. + +The :meth:`keys` method of a dictionary object returns a list of all the keys +used in the dictionary, in arbitrary order (if you want it sorted, just apply +the :meth:`sort` method to the list of keys). To check whether a single key is +in the dictionary, either use the dictionary's :meth:`has_key` method or the +:keyword:`in` keyword. + +Here is a small example using a dictionary:: + + >>> tel = {'jack': 4098, 'sape': 4139} + >>> tel['guido'] = 4127 + >>> tel + {'sape': 4139, 'guido': 4127, 'jack': 4098} + >>> tel['jack'] + 4098 + >>> del tel['sape'] + >>> tel['irv'] = 4127 + >>> tel + {'guido': 4127, 'irv': 4127, 'jack': 4098} + >>> tel.keys() + ['guido', 'irv', 'jack'] + >>> tel.has_key('guido') + True + >>> 'guido' in tel + True + +The :func:`dict` constructor builds dictionaries directly from lists of +key-value pairs stored as tuples. When the pairs form a pattern, list +comprehensions can compactly specify the key-value list. :: + + >>> dict([('sape', 4139), ('guido', 4127), ('jack', 4098)]) + {'sape': 4139, 'jack': 4098, 'guido': 4127} + >>> dict([(x, x**2) for x in (2, 4, 6)]) # use a list comprehension + {2: 4, 4: 16, 6: 36} + +Later in the tutorial, we will learn about Generator Expressions which are even +better suited for the task of supplying key-values pairs to the :func:`dict` +constructor. + +When the keys are simple strings, it is sometimes easier to specify pairs using +keyword arguments:: + + >>> dict(sape=4139, guido=4127, jack=4098) + {'sape': 4139, 'jack': 4098, 'guido': 4127} + + +.. _tut-loopidioms: + +Looping Techniques +================== + +When looping through dictionaries, the key and corresponding value can be +retrieved at the same time using the :meth:`iteritems` method. :: + + >>> knights = {'gallahad': 'the pure', 'robin': 'the brave'} + >>> for k, v in knights.iteritems(): + ... print k, v + ... + gallahad the pure + robin the brave + +When looping through a sequence, the position index and corresponding value can +be retrieved at the same time using the :func:`enumerate` function. :: + + >>> for i, v in enumerate(['tic', 'tac', 'toe']): + ... print i, v + ... + 0 tic + 1 tac + 2 toe + +To loop over two or more sequences at the same time, the entries can be paired +with the :func:`zip` function. :: + + >>> questions = ['name', 'quest', 'favorite color'] + >>> answers = ['lancelot', 'the holy grail', 'blue'] + >>> for q, a in zip(questions, answers): + ... print 'What is your %s? It is %s.' % (q, a) + ... + What is your name? It is lancelot. + What is your quest? It is the holy grail. + What is your favorite color? It is blue. + +To loop over a sequence in reverse, first specify the sequence in a forward +direction and then call the :func:`reversed` function. :: + + >>> for i in reversed(range(1,10,2)): + ... print i + ... + 9 + 7 + 5 + 3 + 1 + +To loop over a sequence in sorted order, use the :func:`sorted` function which +returns a new sorted list while leaving the source unaltered. :: + + >>> basket = ['apple', 'orange', 'apple', 'pear', 'orange', 'banana'] + >>> for f in sorted(set(basket)): + ... print f + ... + apple + banana + orange + pear + + +.. _tut-conditions: + +More on Conditions +================== + +The conditions used in ``while`` and ``if`` statements can contain any +operators, not just comparisons. + +The comparison operators ``in`` and ``not in`` check whether a value occurs +(does not occur) in a sequence. The operators ``is`` and ``is not`` compare +whether two objects are really the same object; this only matters for mutable +objects like lists. All comparison operators have the same priority, which is +lower than that of all numerical operators. + +Comparisons can be chained. For example, ``a < b == c`` tests whether ``a`` is +less than ``b`` and moreover ``b`` equals ``c``. + +Comparisons may be combined using the Boolean operators ``and`` and ``or``, and +the outcome of a comparison (or of any other Boolean expression) may be negated +with ``not``. These have lower priorities than comparison operators; between +them, ``not`` has the highest priority and ``or`` the lowest, so that ``A and +not B or C`` is equivalent to ``(A and (not B)) or C``. As always, parentheses +can be used to express the desired composition. + +The Boolean operators ``and`` and ``or`` are so-called *short-circuit* +operators: their arguments are evaluated from left to right, and evaluation +stops as soon as the outcome is determined. For example, if ``A`` and ``C`` are +true but ``B`` is false, ``A and B and C`` does not evaluate the expression +``C``. When used as a general value and not as a Boolean, the return value of a +short-circuit operator is the last evaluated argument. + +It is possible to assign the result of a comparison or other Boolean expression +to a variable. For example, :: + + >>> string1, string2, string3 = '', 'Trondheim', 'Hammer Dance' + >>> non_null = string1 or string2 or string3 + >>> non_null + 'Trondheim' + +Note that in Python, unlike C, assignment cannot occur inside expressions. C +programmers may grumble about this, but it avoids a common class of problems +encountered in C programs: typing ``=`` in an expression when ``==`` was +intended. + + +.. _tut-comparing: + +Comparing Sequences and Other Types +=================================== + +Sequence objects may be compared to other objects with the same sequence type. +The comparison uses *lexicographical* ordering: first the first two items are +compared, and if they differ this determines the outcome of the comparison; if +they are equal, the next two items are compared, and so on, until either +sequence is exhausted. If two items to be compared are themselves sequences of +the same type, the lexicographical comparison is carried out recursively. If +all items of two sequences compare equal, the sequences are considered equal. +If one sequence is an initial sub-sequence of the other, the shorter sequence is +the smaller (lesser) one. Lexicographical ordering for strings uses the ASCII +ordering for individual characters. Some examples of comparisons between +sequences of the same type:: + + (1, 2, 3) < (1, 2, 4) + [1, 2, 3] < [1, 2, 4] + 'ABC' < 'C' < 'Pascal' < 'Python' + (1, 2, 3, 4) < (1, 2, 4) + (1, 2) < (1, 2, -1) + (1, 2, 3) == (1.0, 2.0, 3.0) + (1, 2, ('aa', 'ab')) < (1, 2, ('abc', 'a'), 4) + +Note that comparing objects of different types is legal. The outcome is +deterministic but arbitrary: the types are ordered by their name. Thus, a list +is always smaller than a string, a string is always smaller than a tuple, etc. +[#]_ Mixed numeric types are compared according to their numeric value, so 0 +equals 0.0, etc. + + +.. rubric:: Footnotes + +.. [#] The rules for comparing objects of different types should not be relied upon; + they may change in a future version of the language. + diff --git a/Doc/tutorial/errors.rst b/Doc/tutorial/errors.rst new file mode 100644 index 0000000..99af9c7 --- /dev/null +++ b/Doc/tutorial/errors.rst @@ -0,0 +1,418 @@ +.. _tut-errors: + +********************* +Errors and Exceptions +********************* + +Until now error messages haven't been more than mentioned, but if you have tried +out the examples you have probably seen some. There are (at least) two +distinguishable kinds of errors: *syntax errors* and *exceptions*. + + +.. _tut-syntaxerrors: + +Syntax Errors +============= + +Syntax errors, also known as parsing errors, are perhaps the most common kind of +complaint you get while you are still learning Python:: + + >>> while True print 'Hello world' + File "<stdin>", line 1, in ? + while True print 'Hello world' + ^ + SyntaxError: invalid syntax + +The parser repeats the offending line and displays a little 'arrow' pointing at +the earliest point in the line where the error was detected. The error is +caused by (or at least detected at) the token *preceding* the arrow: in the +example, the error is detected at the keyword :keyword:`print`, since a colon +(``':'``) is missing before it. File name and line number are printed so you +know where to look in case the input came from a script. + + +.. _tut-exceptions: + +Exceptions +========== + +Even if a statement or expression is syntactically correct, it may cause an +error when an attempt is made to execute it. Errors detected during execution +are called *exceptions* and are not unconditionally fatal: you will soon learn +how to handle them in Python programs. Most exceptions are not handled by +programs, however, and result in error messages as shown here:: + + >>> 10 * (1/0) + Traceback (most recent call last): + File "<stdin>", line 1, in ? + ZeroDivisionError: integer division or modulo by zero + >>> 4 + spam*3 + Traceback (most recent call last): + File "<stdin>", line 1, in ? + NameError: name 'spam' is not defined + >>> '2' + 2 + Traceback (most recent call last): + File "<stdin>", line 1, in ? + TypeError: cannot concatenate 'str' and 'int' objects + +The last line of the error message indicates what happened. Exceptions come in +different types, and the type is printed as part of the message: the types in +the example are :exc:`ZeroDivisionError`, :exc:`NameError` and :exc:`TypeError`. +The string printed as the exception type is the name of the built-in exception +that occurred. This is true for all built-in exceptions, but need not be true +for user-defined exceptions (although it is a useful convention). Standard +exception names are built-in identifiers (not reserved keywords). + +The rest of the line provides detail based on the type of exception and what +caused it. + +The preceding part of the error message shows the context where the exception +happened, in the form of a stack traceback. In general it contains a stack +traceback listing source lines; however, it will not display lines read from +standard input. + +:ref:`bltin-exceptions` lists the built-in exceptions and their meanings. + + +.. _tut-handling: + +Handling Exceptions +=================== + +It is possible to write programs that handle selected exceptions. Look at the +following example, which asks the user for input until a valid integer has been +entered, but allows the user to interrupt the program (using :kbd:`Control-C` or +whatever the operating system supports); note that a user-generated interruption +is signalled by raising the :exc:`KeyboardInterrupt` exception. :: + + >>> def raw_input(prompt): + ... import sys + ... sys.stdout.write(prompt) + ... sys.stdout.flush() + ... return sys.stdin.readline() + ... + >>> while True: + ... try: + ... x = int(raw_input("Please enter a number: ")) + ... break + ... except ValueError: + ... print "Oops! That was no valid number. Try again..." + ... + +The :keyword:`try` statement works as follows. + +* First, the *try clause* (the statement(s) between the :keyword:`try` and + :keyword:`except` keywords) is executed. + +* If no exception occurs, the *except clause* is skipped and execution of the + :keyword:`try` statement is finished. + +* If an exception occurs during execution of the try clause, the rest of the + clause is skipped. Then if its type matches the exception named after the + :keyword:`except` keyword, the except clause is executed, and then execution + continues after the :keyword:`try` statement. + +* If an exception occurs which does not match the exception named in the except + clause, it is passed on to outer :keyword:`try` statements; if no handler is + found, it is an *unhandled exception* and execution stops with a message as + shown above. + +A :keyword:`try` statement may have more than one except clause, to specify +handlers for different exceptions. At most one handler will be executed. +Handlers only handle exceptions that occur in the corresponding try clause, not +in other handlers of the same :keyword:`try` statement. An except clause may +name multiple exceptions as a parenthesized tuple, for example:: + + ... except (RuntimeError, TypeError, NameError): + ... pass + +The last except clause may omit the exception name(s), to serve as a wildcard. +Use this with extreme caution, since it is easy to mask a real programming error +in this way! It can also be used to print an error message and then re-raise +the exception (allowing a caller to handle the exception as well):: + + import sys + + try: + f = open('myfile.txt') + s = f.readline() + i = int(s.strip()) + except IOError as e: + (errno, strerror) = e + print "I/O error(%s): %s" % (e.errno, e.strerror) + except ValueError: + print "Could not convert data to an integer." + except: + print "Unexpected error:", sys.exc_info()[0] + raise + +The :keyword:`try` ... :keyword:`except` statement has an optional *else +clause*, which, when present, must follow all except clauses. It is useful for +code that must be executed if the try clause does not raise an exception. For +example:: + + for arg in sys.argv[1:]: + try: + f = open(arg, 'r') + except IOError: + print 'cannot open', arg + else: + print arg, 'has', len(f.readlines()), 'lines' + f.close() + +The use of the :keyword:`else` clause is better than adding additional code to +the :keyword:`try` clause because it avoids accidentally catching an exception +that wasn't raised by the code being protected by the :keyword:`try` ... +:keyword:`except` statement. + +When an exception occurs, it may have an associated value, also known as the +exception's *argument*. The presence and type of the argument depend on the +exception type. + +The except clause may specify a variable after the exception name (or tuple). +The variable is bound to an exception instance with the arguments stored in +``instance.args``. For convenience, the exception instance defines +:meth:`__getitem__` and :meth:`__str__` so the arguments can be accessed or +printed directly without having to reference ``.args``. + +But use of ``.args`` is discouraged. Instead, the preferred use is to pass a +single argument to an exception (which can be a tuple if multiple arguments are +needed) and have it bound to the ``message`` attribute. One may also +instantiate an exception first before raising it and add any attributes to it as +desired. :: + + >>> try: + ... raise Exception('spam', 'eggs') + ... except Exception as inst: + ... print type(inst) # the exception instance + ... print inst.args # arguments stored in .args + ... print inst # __str__ allows args to printed directly + ... x, y = inst # __getitem__ allows args to be unpacked directly + ... print 'x =', x + ... print 'y =', y + ... + <type 'Exception'> + ('spam', 'eggs') + ('spam', 'eggs') + x = spam + y = eggs + +If an exception has an argument, it is printed as the last part ('detail') of +the message for unhandled exceptions. + +Exception handlers don't just handle exceptions if they occur immediately in the +try clause, but also if they occur inside functions that are called (even +indirectly) in the try clause. For example:: + + >>> def this_fails(): + ... x = 1/0 + ... + >>> try: + ... this_fails() + ... except ZeroDivisionError as detail: + ... print 'Handling run-time error:', detail + ... + Handling run-time error: integer division or modulo by zero + + +.. _tut-raising: + +Raising Exceptions +================== + +The :keyword:`raise` statement allows the programmer to force a specified +exception to occur. For example:: + + >>> raise NameError, 'HiThere' + Traceback (most recent call last): + File "<stdin>", line 1, in ? + NameError: HiThere + +The first argument to :keyword:`raise` names the exception to be raised. The +optional second argument specifies the exception's argument. Alternatively, the +above could be written as ``raise NameError('HiThere')``. Either form works +fine, but there seems to be a growing stylistic preference for the latter. + +If you need to determine whether an exception was raised but don't intend to +handle it, a simpler form of the :keyword:`raise` statement allows you to +re-raise the exception:: + + >>> try: + ... raise NameError, 'HiThere' + ... except NameError: + ... print 'An exception flew by!' + ... raise + ... + An exception flew by! + Traceback (most recent call last): + File "<stdin>", line 2, in ? + NameError: HiThere + + +.. _tut-userexceptions: + +User-defined Exceptions +======================= + +Programs may name their own exceptions by creating a new exception class. +Exceptions should typically be derived from the :exc:`Exception` class, either +directly or indirectly. For example:: + + >>> class MyError(Exception): + ... def __init__(self, value): + ... self.value = value + ... def __str__(self): + ... return repr(self.value) + ... + >>> try: + ... raise MyError(2*2) + ... except MyError as e: + ... print 'My exception occurred, value:', e.value + ... + My exception occurred, value: 4 + >>> raise MyError, 'oops!' + Traceback (most recent call last): + File "<stdin>", line 1, in ? + __main__.MyError: 'oops!' + +In this example, the default :meth:`__init__` of :class:`Exception` has been +overridden. The new behavior simply creates the *value* attribute. This +replaces the default behavior of creating the *args* attribute. + +Exception classes can be defined which do anything any other class can do, but +are usually kept simple, often only offering a number of attributes that allow +information about the error to be extracted by handlers for the exception. When +creating a module that can raise several distinct errors, a common practice is +to create a base class for exceptions defined by that module, and subclass that +to create specific exception classes for different error conditions:: + + class Error(Exception): + """Base class for exceptions in this module.""" + pass + + class InputError(Error): + """Exception raised for errors in the input. + + Attributes: + expression -- input expression in which the error occurred + message -- explanation of the error + """ + + def __init__(self, expression, message): + self.expression = expression + self.message = message + + class TransitionError(Error): + """Raised when an operation attempts a state transition that's not + allowed. + + Attributes: + previous -- state at beginning of transition + next -- attempted new state + message -- explanation of why the specific transition is not allowed + """ + + def __init__(self, previous, next, message): + self.previous = previous + self.next = next + self.message = message + +Most exceptions are defined with names that end in "Error," similar to the +naming of the standard exceptions. + +Many standard modules define their own exceptions to report errors that may +occur in functions they define. More information on classes is presented in +chapter :ref:`tut-classes`. + + +.. _tut-cleanup: + +Defining Clean-up Actions +========================= + +The :keyword:`try` statement has another optional clause which is intended to +define clean-up actions that must be executed under all circumstances. For +example:: + + >>> try: + ... raise KeyboardInterrupt + ... finally: + ... print 'Goodbye, world!' + ... + Goodbye, world! + Traceback (most recent call last): + File "<stdin>", line 2, in ? + KeyboardInterrupt + +A *finally clause* is always executed before leaving the :keyword:`try` +statement, whether an exception has occurred or not. When an exception has +occurred in the :keyword:`try` clause and has not been handled by an +:keyword:`except` clause (or it has occurred in a :keyword:`except` or +:keyword:`else` clause), it is re-raised after the :keyword:`finally` clause has +been executed. The :keyword:`finally` clause is also executed "on the way out" +when any other clause of the :keyword:`try` statement is left via a +:keyword:`break`, :keyword:`continue` or :keyword:`return` statement. A more +complicated example (having :keyword:`except` and :keyword:`finally` clauses in +the same :keyword:`try` statement works as of Python 2.5):: + + >>> def divide(x, y): + ... try: + ... result = x / y + ... except ZeroDivisionError: + ... print "division by zero!" + ... else: + ... print "result is", result + ... finally: + ... print "executing finally clause" + ... + >>> divide(2, 1) + result is 2 + executing finally clause + >>> divide(2, 0) + division by zero! + executing finally clause + >>> divide("2", "1") + executing finally clause + Traceback (most recent call last): + File "<stdin>", line 1, in ? + File "<stdin>", line 3, in divide + TypeError: unsupported operand type(s) for /: 'str' and 'str' + +As you can see, the :keyword:`finally` clause is executed in any event. The +:exc:`TypeError` raised by dividing two strings is not handled by the +:keyword:`except` clause and therefore re-raised after the :keyword:`finally` +clauses has been executed. + +In real world applications, the :keyword:`finally` clause is useful for +releasing external resources (such as files or network connections), regardless +of whether the use of the resource was successful. + + +.. _tut-cleanup-with: + +Predefined Clean-up Actions +=========================== + +Some objects define standard clean-up actions to be undertaken when the object +is no longer needed, regardless of whether or not the operation using the object +succeeded or failed. Look at the following example, which tries to open a file +and print its contents to the screen. :: + + for line in open("myfile.txt"): + print line + +The problem with this code is that it leaves the file open for an indeterminate +amount of time after the code has finished executing. This is not an issue in +simple scripts, but can be a problem for larger applications. The +:keyword:`with` statement allows objects like files to be used in a way that +ensures they are always cleaned up promptly and correctly. :: + + with open("myfile.txt") as f: + for line in f: + print line + +After the statement is executed, the file *f* is always closed, even if a +problem was encountered while processing the lines. Other objects which provide +predefined clean-up actions will indicate this in their documentation. + + diff --git a/Doc/tutorial/floatingpoint.rst b/Doc/tutorial/floatingpoint.rst new file mode 100644 index 0000000..cbf7008 --- /dev/null +++ b/Doc/tutorial/floatingpoint.rst @@ -0,0 +1,220 @@ +.. _tut-fp-issues: + +************************************************** +Floating Point Arithmetic: Issues and Limitations +************************************************** + +.. sectionauthor:: Tim Peters <tim_one@users.sourceforge.net> + + +Floating-point numbers are represented in computer hardware as base 2 (binary) +fractions. For example, the decimal fraction :: + + 0.125 + +has value 1/10 + 2/100 + 5/1000, and in the same way the binary fraction :: + + 0.001 + +has value 0/2 + 0/4 + 1/8. These two fractions have identical values, the only +real difference being that the first is written in base 10 fractional notation, +and the second in base 2. + +Unfortunately, most decimal fractions cannot be represented exactly as binary +fractions. A consequence is that, in general, the decimal floating-point +numbers you enter are only approximated by the binary floating-point numbers +actually stored in the machine. + +The problem is easier to understand at first in base 10. Consider the fraction +1/3. You can approximate that as a base 10 fraction:: + + 0.3 + +or, better, :: + + 0.33 + +or, better, :: + + 0.333 + +and so on. No matter how many digits you're willing to write down, the result +will never be exactly 1/3, but will be an increasingly better approximation of +1/3. + +In the same way, no matter how many base 2 digits you're willing to use, the +decimal value 0.1 cannot be represented exactly as a base 2 fraction. In base +2, 1/10 is the infinitely repeating fraction :: + + 0.0001100110011001100110011001100110011001100110011... + +Stop at any finite number of bits, and you get an approximation. This is why +you see things like:: + + >>> 0.1 + 0.10000000000000001 + +On most machines today, that is what you'll see if you enter 0.1 at a Python +prompt. You may not, though, because the number of bits used by the hardware to +store floating-point values can vary across machines, and Python only prints a +decimal approximation to the true decimal value of the binary approximation +stored by the machine. On most machines, if Python were to print the true +decimal value of the binary approximation stored for 0.1, it would have to +display :: + + >>> 0.1 + 0.1000000000000000055511151231257827021181583404541015625 + +instead! The Python prompt uses the builtin :func:`repr` function to obtain a +string version of everything it displays. For floats, ``repr(float)`` rounds +the true decimal value to 17 significant digits, giving :: + + 0.10000000000000001 + +``repr(float)`` produces 17 significant digits because it turns out that's +enough (on most machines) so that ``eval(repr(x)) == x`` exactly for all finite +floats *x*, but rounding to 16 digits is not enough to make that true. + +Note that this is in the very nature of binary floating-point: this is not a bug +in Python, and it is not a bug in your code either. You'll see the same kind of +thing in all languages that support your hardware's floating-point arithmetic +(although some languages may not *display* the difference by default, or in all +output modes). + +Python's builtin :func:`str` function produces only 12 significant digits, and +you may wish to use that instead. It's unusual for ``eval(str(x))`` to +reproduce *x*, but the output may be more pleasant to look at:: + + >>> print str(0.1) + 0.1 + +It's important to realize that this is, in a real sense, an illusion: the value +in the machine is not exactly 1/10, you're simply rounding the *display* of the +true machine value. + +Other surprises follow from this one. For example, after seeing :: + + >>> 0.1 + 0.10000000000000001 + +you may be tempted to use the :func:`round` function to chop it back to the +single digit you expect. But that makes no difference:: + + >>> round(0.1, 1) + 0.10000000000000001 + +The problem is that the binary floating-point value stored for "0.1" was already +the best possible binary approximation to 1/10, so trying to round it again +can't make it better: it was already as good as it gets. + +Another consequence is that since 0.1 is not exactly 1/10, summing ten values of +0.1 may not yield exactly 1.0, either:: + + >>> sum = 0.0 + >>> for i in range(10): + ... sum += 0.1 + ... + >>> sum + 0.99999999999999989 + +Binary floating-point arithmetic holds many surprises like this. The problem +with "0.1" is explained in precise detail below, in the "Representation Error" +section. See `The Perils of Floating Point <http://www.lahey.com/float.htm>`_ +for a more complete account of other common surprises. + +As that says near the end, "there are no easy answers." Still, don't be unduly +wary of floating-point! The errors in Python float operations are inherited +from the floating-point hardware, and on most machines are on the order of no +more than 1 part in 2\*\*53 per operation. That's more than adequate for most +tasks, but you do need to keep in mind that it's not decimal arithmetic, and +that every float operation can suffer a new rounding error. + +While pathological cases do exist, for most casual use of floating-point +arithmetic you'll see the result you expect in the end if you simply round the +display of your final results to the number of decimal digits you expect. +:func:`str` usually suffices, and for finer control see the discussion of +Python's ``%`` format operator: the ``%g``, ``%f`` and ``%e`` format codes +supply flexible and easy ways to round float results for display. + + +.. _tut-fp-error: + +Representation Error +==================== + +This section explains the "0.1" example in detail, and shows how you can perform +an exact analysis of cases like this yourself. Basic familiarity with binary +floating-point representation is assumed. + +:dfn:`Representation error` refers to the fact that some (most, actually) +decimal fractions cannot be represented exactly as binary (base 2) fractions. +This is the chief reason why Python (or Perl, C, C++, Java, Fortran, and many +others) often won't display the exact decimal number you expect:: + + >>> 0.1 + 0.10000000000000001 + +Why is that? 1/10 is not exactly representable as a binary fraction. Almost all +machines today (November 2000) use IEEE-754 floating point arithmetic, and +almost all platforms map Python floats to IEEE-754 "double precision". 754 +doubles contain 53 bits of precision, so on input the computer strives to +convert 0.1 to the closest fraction it can of the form *J*/2\*\**N* where *J* is +an integer containing exactly 53 bits. Rewriting :: + + 1 / 10 ~= J / (2**N) + +as :: + + J ~= 2**N / 10 + +and recalling that *J* has exactly 53 bits (is ``>= 2**52`` but ``< 2**53``), +the best value for *N* is 56:: + + >>> 2**52 + 4503599627370496L + >>> 2**53 + 9007199254740992L + >>> 2**56/10 + 7205759403792793L + +That is, 56 is the only value for *N* that leaves *J* with exactly 53 bits. The +best possible value for *J* is then that quotient rounded:: + + >>> q, r = divmod(2**56, 10) + >>> r + 6L + +Since the remainder is more than half of 10, the best approximation is obtained +by rounding up:: + + >>> q+1 + 7205759403792794L + +Therefore the best possible approximation to 1/10 in 754 double precision is +that over 2\*\*56, or :: + + 7205759403792794 / 72057594037927936 + +Note that since we rounded up, this is actually a little bit larger than 1/10; +if we had not rounded up, the quotient would have been a little bit smaller than +1/10. But in no case can it be *exactly* 1/10! + +So the computer never "sees" 1/10: what it sees is the exact fraction given +above, the best 754 double approximation it can get:: + + >>> .1 * 2**56 + 7205759403792794.0 + +If we multiply that fraction by 10\*\*30, we can see the (truncated) value of +its 30 most significant decimal digits:: + + >>> 7205759403792794 * 10**30 / 2**56 + 100000000000000005551115123125L + +meaning that the exact number stored in the computer is approximately equal to +the decimal value 0.100000000000000005551115123125. Rounding that to 17 +significant digits gives the 0.10000000000000001 that Python displays (well, +will display on any 754-conforming platform that does best-possible input and +output conversions in its C library --- yours may not!). + + diff --git a/Doc/tutorial/glossary.rst b/Doc/tutorial/glossary.rst new file mode 100644 index 0000000..c05d68d --- /dev/null +++ b/Doc/tutorial/glossary.rst @@ -0,0 +1,329 @@ + +.. _tut-glossary: + +******** +Glossary +******** + +.. % %% keep the entries sorted and include at least one \index{} item for each +.. % %% cross-references are marked with \emph{entry} + +``>>>`` + The typical Python prompt of the interactive shell. Often seen for code + examples that can be tried right away in the interpreter. + + .. index:: single: ... + +``...`` + The typical Python prompt of the interactive shell when entering code for an + indented code block. + + .. index:: single: BDFL + +BDFL + Benevolent Dictator For Life, a.k.a. `Guido van Rossum + <http://www.python.org/~guido/>`_, Python's creator. + + .. index:: single: byte code + +byte code + The internal representation of a Python program in the interpreter. The byte + code is also cached in ``.pyc`` and ``.pyo`` files so that executing the same + file is faster the second time (recompilation from source to byte code can be + avoided). This "intermediate language" is said to run on a "virtual machine" + that calls the subroutines corresponding to each bytecode. + + .. index:: single: classic class + +classic class + Any class which does not inherit from :class:`object`. See *new-style class*. + + .. index:: single: complex number + +complex number + An extension of the familiar real number system in which all numbers are + expressed as a sum of a real part and an imaginary part. Imaginary numbers are + real multiples of the imaginary unit (the square root of ``-1``), often written + ``i`` in mathematics or ``j`` in engineering. Python has builtin support for + complex numbers, which are written with this latter notation; the imaginary part + is written with a ``j`` suffix, e.g., ``3+1j``. To get access to complex + equivalents of the :mod:`math` module, use :mod:`cmath`. Use of complex numbers + is a fairly advanced mathematical feature. If you're not aware of a need for + them, it's almost certain you can safely ignore them. + + .. index:: single: descriptor + +descriptor + Any *new-style* object that defines the methods :meth:`__get__`, + :meth:`__set__`, or :meth:`__delete__`. When a class attribute is a descriptor, + its special binding behavior is triggered upon attribute lookup. Normally, + writing *a.b* looks up the object *b* in the class dictionary for *a*, but if + *b* is a descriptor, the defined method gets called. Understanding descriptors + is a key to a deep understanding of Python because they are the basis for many + features including functions, methods, properties, class methods, static + methods, and reference to super classes. + + .. index:: single: dictionary + +dictionary + An associative array, where arbitrary keys are mapped to values. The use of + :class:`dict` much resembles that for :class:`list`, but the keys can be any + object with a :meth:`__hash__` function, not just integers starting from zero. + Called a hash in Perl. + + .. index:: single: duck-typing + +duck-typing + Pythonic programming style that determines an object's type by inspection of its + method or attribute signature rather than by explicit relationship to some type + object ("If it looks like a duck and quacks like a duck, it must be a duck.") + By emphasizing interfaces rather than specific types, well-designed code + improves its flexibility by allowing polymorphic substitution. Duck-typing + avoids tests using :func:`type` or :func:`isinstance`. Instead, it typically + employs :func:`hasattr` tests or *EAFP* programming. + + .. index:: single: EAFP + +EAFP + Easier to ask for forgiveness than permission. This common Python coding style + assumes the existence of valid keys or attributes and catches exceptions if the + assumption proves false. This clean and fast style is characterized by the + presence of many :keyword:`try` and :keyword:`except` statements. The technique + contrasts with the *LBYL* style that is common in many other languages such as + C. + + .. index:: single: __future__ + +__future__ + A pseudo module which programmers can use to enable new language features which + are not compatible with the current interpreter. To enable ``new_feature`` :: + + from __future__ import new_feature + + By importing the :mod:`__future__` module and evaluating its variables, you + can see when a new feature was first added to the language and when it will + become the default:: + + >>> import __future__ + >>> __future__.division + _Feature((2, 2, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0), 8192) + + .. index:: single: generator + +generator + A function that returns an iterator. It looks like a normal function except + that values are returned to the caller using a :keyword:`yield` statement + instead of a :keyword:`return` statement. Generator functions often contain one + or more :keyword:`for` or :keyword:`while` loops that :keyword:`yield` elements + back to the caller. The function execution is stopped at the :keyword:`yield` + keyword (returning the result) and is resumed there when the next element is + requested by calling the :meth:`__next__` method of the returned iterator. + + .. index:: single: generator expression + +generator expression + An expression that returns a generator. It looks like a normal expression + followed by a :keyword:`for` expression defining a loop variable, range, and an + optional :keyword:`if` expression. The combined expression generates values for + an enclosing function:: + + >>> sum(i*i for i in range(10)) # sum of squares 0, 1, 4, ... 81 + 285 + + .. index:: single: GIL + +GIL + See *global interpreter lock*. + + .. index:: single: global interpreter lock + +global interpreter lock + The lock used by Python threads to assure that only one thread can be run at + a time. This simplifies Python by assuring that no two processes can access + the same memory at the same time. Locking the entire interpreter makes it + easier for the interpreter to be multi-threaded, at the expense of some + parallelism on multi-processor machines. Efforts have been made in the past + to create a "free-threaded" interpreter (one which locks shared data at a + much finer granularity), but performance suffered in the common + single-processor case. + + .. index:: single: IDLE + +IDLE + An Integrated Development Environment for Python. IDLE is a basic editor and + interpreter environment that ships with the standard distribution of Python. + Good for beginners, it also serves as clear example code for those wanting to + implement a moderately sophisticated, multi-platform GUI application. + + .. index:: single: immutable + +immutable + An object with fixed value. Immutable objects are numbers, strings or tuples + (and more). Such an object cannot be altered. A new object has to be created + if a different value has to be stored. They play an important role in places + where a constant hash value is needed, for example as a key in a dictionary. + + .. index:: single: integer division + +integer division + Mathematical division including any remainder. The result will always be a + float. For example, the expression ``11/4`` evaluates to ``2.75``. Integer + division can be forced by using the ``//`` operator instead of the ``/`` + operator. + + .. index:: single: interactive + +interactive + Python has an interactive interpreter which means that you can try out things + and immediately see their results. Just launch ``python`` with no arguments + (possibly by selecting it from your computer's main menu). It is a very powerful + way to test out new ideas or inspect modules and packages (remember + ``help(x)``). + + .. index:: single: interpreted + +interpreted + Python is an interpreted language, as opposed to a compiled one. This means + that the source files can be run directly without first creating an executable + which is then run. Interpreted languages typically have a shorter + development/debug cycle than compiled ones, though their programs generally also + run more slowly. See also *interactive*. + + .. index:: single: iterable + +iterable + A container object capable of returning its members one at a time. Examples of + iterables include all sequence types (such as :class:`list`, :class:`str`, and + :class:`tuple`) and some non-sequence types like :class:`dict` and :class:`file` + and objects of any classes you define with an :meth:`__iter__` or + :meth:`__getitem__` method. Iterables can be used in a :keyword:`for` loop and + in many other places where a sequence is needed (:func:`zip`, :func:`map`, ...). + When an iterable object is passed as an argument to the builtin function + :func:`iter`, it returns an iterator for the object. This iterator is good for + one pass over the set of values. When using iterables, it is usually not + necessary to call :func:`iter` or deal with iterator objects yourself. The + ``for`` statement does that automatically for you, creating a temporary unnamed + variable to hold the iterator for the duration of the loop. See also + *iterator*, *sequence*, and *generator*. + + .. index:: single: iterator + +iterator + An object representing a stream of data. Repeated calls to the iterator's + :meth:`__next__` method return successive items in the stream. When no more + data is available a :exc:`StopIteration` exception is raised instead. At this + point, the iterator object is exhausted and any further calls to its + :meth:`__next__` method just raise :exc:`StopIteration` again. Iterators are + required to have an :meth:`__iter__` method that returns the iterator object + itself so every iterator is also iterable and may be used in most places where + other iterables are accepted. One notable exception is code that attempts + multiple iteration passes. A container object (such as a :class:`list`) + produces a fresh new iterator each time you pass it to the :func:`iter` function + or use it in a :keyword:`for` loop. Attempting this with an iterator will just + return the same exhausted iterator object used in the previous iteration pass, + making it appear like an empty container. + + .. index:: single: LBYL + +LBYL + Look before you leap. This coding style explicitly tests for pre-conditions + before making calls or lookups. This style contrasts with the *EAFP* approach + and is characterized by the presence of many :keyword:`if` statements. + + .. index:: single: list comprehension + +list comprehension + A compact way to process all or a subset of elements in a sequence and return a + list with the results. ``result = ["0x%02x" % x for x in range(256) if x % 2 == + 0]`` generates a list of strings containing hex numbers (0x..) that are even and + in the range from 0 to 255. The :keyword:`if` clause is optional. If omitted, + all elements in ``range(256)`` are processed. + + .. index:: single: mapping + +mapping + A container object (such as :class:`dict`) that supports arbitrary key lookups + using the special method :meth:`__getitem__`. + + .. index:: single: metaclass + +metaclass + The class of a class. Class definitions create a class name, a class + dictionary, and a list of base classes. The metaclass is responsible for taking + those three arguments and creating the class. Most object oriented programming + languages provide a default implementation. What makes Python special is that + it is possible to create custom metaclasses. Most users never need this tool, + but when the need arises, metaclasses can provide powerful, elegant solutions. + They have been used for logging attribute access, adding thread-safety, tracking + object creation, implementing singletons, and many other tasks. + + .. index:: single: mutable + +mutable + Mutable objects can change their value but keep their :func:`id`. See also + *immutable*. + + .. index:: single: namespace + +namespace + The place where a variable is stored. Namespaces are implemented as + dictionaries. There are the local, global and builtin namespaces as well as + nested namespaces in objects (in methods). Namespaces support modularity by + preventing naming conflicts. For instance, the functions + :func:`__builtin__.open` and :func:`os.open` are distinguished by their + namespaces. Namespaces also aid readability and maintainability by making it + clear which module implements a function. For instance, writing + :func:`random.seed` or :func:`itertools.izip` makes it clear that those + functions are implemented by the :mod:`random` and :mod:`itertools` modules + respectively. + + .. index:: single: nested scope + +nested scope + The ability to refer to a variable in an enclosing definition. For instance, a + function defined inside another function can refer to variables in the outer + function. Note that nested scopes work only for reference and not for + assignment which will always write to the innermost scope. In contrast, local + variables both read and write in the innermost scope. Likewise, global + variables read and write to the global namespace. + + .. index:: single: new-style class + +new-style class + Any class that inherits from :class:`object`. This includes all built-in types + like :class:`list` and :class:`dict`. Only new-style classes can use Python's + newer, versatile features like :meth:`__slots__`, descriptors, properties, + :meth:`__getattribute__`, class methods, and static methods. + + .. index:: single: Python3000 + +Python3000 + A mythical python release, not required to be backward compatible, with + telepathic interface. + + .. index:: single: __slots__ + +__slots__ + A declaration inside a *new-style class* that saves memory by pre-declaring + space for instance attributes and eliminating instance dictionaries. Though + popular, the technique is somewhat tricky to get right and is best reserved for + rare cases where there are large numbers of instances in a memory-critical + application. + + .. index:: single: sequence + +sequence + An *iterable* which supports efficient element access using integer indices via + the :meth:`__getitem__` and :meth:`__len__` special methods. Some built-in + sequence types are :class:`list`, :class:`str`, :class:`tuple`, and + :class:`unicode`. Note that :class:`dict` also supports :meth:`__getitem__` and + :meth:`__len__`, but is considered a mapping rather than a sequence because the + lookups use arbitrary *immutable* keys rather than integers. + + .. index:: single: Zen of Python + +Zen of Python + Listing of Python design principles and philosophies that are helpful in + understanding and using the language. The listing can be found by typing + "``import this``" at the interactive prompt. + diff --git a/Doc/tutorial/index.rst b/Doc/tutorial/index.rst new file mode 100644 index 0000000..7309b7c --- /dev/null +++ b/Doc/tutorial/index.rst @@ -0,0 +1,60 @@ +.. _tutorial-index: + +###################### + The Python tutorial +###################### + +:Release: |version| +:Date: |today| + +Python is an easy to learn, powerful programming language. It has efficient +high-level data structures and a simple but effective approach to +object-oriented programming. Python's elegant syntax and dynamic typing, +together with its interpreted nature, make it an ideal language for scripting +and rapid application development in many areas on most platforms. + +The Python interpreter and the extensive standard library are freely available +in source or binary form for all major platforms from the Python Web site, +http://www.python.org/, and may be freely distributed. The same site also +contains distributions of and pointers to many free third party Python modules, +programs and tools, and additional documentation. + +The Python interpreter is easily extended with new functions and data types +implemented in C or C++ (or other languages callable from C). Python is also +suitable as an extension language for customizable applications. + +This tutorial introduces the reader informally to the basic concepts and +features of the Python language and system. It helps to have a Python +interpreter handy for hands-on experience, but all examples are self-contained, +so the tutorial can be read off-line as well. + +For a description of standard objects and modules, see the Python Library +Reference document. The Python Reference Manual gives a more formal definition +of the language. To write extensions in C or C++, read Extending and Embedding +the Python Interpreter and Python/C API Reference. There are also several books +covering Python in depth. + +This tutorial does not attempt to be comprehensive and cover every single +feature, or even every commonly used feature. Instead, it introduces many of +Python's most noteworthy features, and will give you a good idea of the +language's flavor and style. After reading it, you will be able to read and +write Python modules and programs, and you will be ready to learn more about the +various Python library modules described in the Python Library Reference. + +.. toctree:: + + appetite.rst + interpreter.rst + introduction.rst + controlflow.rst + datastructures.rst + modules.rst + inputoutput.rst + errors.rst + classes.rst + stdlib.rst + stdlib2.rst + whatnow.rst + interactive.rst + floatingpoint.rst + glossary.rst diff --git a/Doc/tutorial/inputoutput.rst b/Doc/tutorial/inputoutput.rst new file mode 100644 index 0000000..9c302af --- /dev/null +++ b/Doc/tutorial/inputoutput.rst @@ -0,0 +1,354 @@ +.. _tut-io: + +**************** +Input and Output +**************** + +There are several ways to present the output of a program; data can be printed +in a human-readable form, or written to a file for future use. This chapter will +discuss some of the possibilities. + + +.. _tut-formatting: + +Fancier Output Formatting +========================= + +So far we've encountered two ways of writing values: *expression statements* and +the :keyword:`print` statement. (A third way is using the :meth:`write` method +of file objects; the standard output file can be referenced as ``sys.stdout``. +See the Library Reference for more information on this.) + +.. index:: module: string + +Often you'll want more control over the formatting of your output than simply +printing space-separated values. There are two ways to format your output; the +first way is to do all the string handling yourself; using string slicing and +concatenation operations you can create any layout you can imagine. The +standard module :mod:`string` contains some useful operations for padding +strings to a given column width; these will be discussed shortly. The second +way is to use the ``%`` operator with a string as the left argument. The ``%`` +operator interprets the left argument much like a :cfunc:`sprintf`\ -style +format string to be applied to the right argument, and returns the string +resulting from this formatting operation. + +One question remains, of course: how do you convert values to strings? Luckily, +Python has ways to convert any value to a string: pass it to the :func:`repr` +or :func:`str` functions. Reverse quotes (``````) are equivalent to +:func:`repr`, but they are no longer used in modern Python code and will likely +not be in future versions of the language. + +The :func:`str` function is meant to return representations of values which are +fairly human-readable, while :func:`repr` is meant to generate representations +which can be read by the interpreter (or will force a :exc:`SyntaxError` if +there is not equivalent syntax). For objects which don't have a particular +representation for human consumption, :func:`str` will return the same value as +:func:`repr`. Many values, such as numbers or structures like lists and +dictionaries, have the same representation using either function. Strings and +floating point numbers, in particular, have two distinct representations. + +Some examples:: + + >>> s = 'Hello, world.' + >>> str(s) + 'Hello, world.' + >>> repr(s) + "'Hello, world.'" + >>> str(0.1) + '0.1' + >>> repr(0.1) + '0.10000000000000001' + >>> x = 10 * 3.25 + >>> y = 200 * 200 + >>> s = 'The value of x is ' + repr(x) + ', and y is ' + repr(y) + '...' + >>> print s + The value of x is 32.5, and y is 40000... + >>> # The repr() of a string adds string quotes and backslashes: + ... hello = 'hello, world\n' + >>> hellos = repr(hello) + >>> print hellos + 'hello, world\n' + >>> # The argument to repr() may be any Python object: + ... repr((x, y, ('spam', 'eggs'))) + "(32.5, 40000, ('spam', 'eggs'))" + >>> # reverse quotes are convenient in interactive sessions: + ... `x, y, ('spam', 'eggs')` + "(32.5, 40000, ('spam', 'eggs'))" + +Here are two ways to write a table of squares and cubes:: + + >>> for x in range(1, 11): + ... print repr(x).rjust(2), repr(x*x).rjust(3), + ... # Note trailing comma on previous line + ... print repr(x*x*x).rjust(4) + ... + 1 1 1 + 2 4 8 + 3 9 27 + 4 16 64 + 5 25 125 + 6 36 216 + 7 49 343 + 8 64 512 + 9 81 729 + 10 100 1000 + + >>> for x in range(1,11): + ... print '%2d %3d %4d' % (x, x*x, x*x*x) + ... + 1 1 1 + 2 4 8 + 3 9 27 + 4 16 64 + 5 25 125 + 6 36 216 + 7 49 343 + 8 64 512 + 9 81 729 + 10 100 1000 + +(Note that in the first example, one space between each column was added by the +way :keyword:`print` works: it always adds spaces between its arguments.) + +This example demonstrates the :meth:`rjust` method of string objects, which +right-justifies a string in a field of a given width by padding it with spaces +on the left. There are similar methods :meth:`ljust` and :meth:`center`. These +methods do not write anything, they just return a new string. If the input +string is too long, they don't truncate it, but return it unchanged; this will +mess up your column lay-out but that's usually better than the alternative, +which would be lying about a value. (If you really want truncation you can +always add a slice operation, as in ``x.ljust(n)[:n]``.) + +There is another method, :meth:`zfill`, which pads a numeric string on the left +with zeros. It understands about plus and minus signs:: + + >>> '12'.zfill(5) + '00012' + >>> '-3.14'.zfill(7) + '-003.14' + >>> '3.14159265359'.zfill(5) + '3.14159265359' + +Using the ``%`` operator looks like this:: + + >>> import math + >>> print 'The value of PI is approximately %5.3f.' % math.pi + The value of PI is approximately 3.142. + +If there is more than one format in the string, you need to pass a tuple as +right operand, as in this example:: + + >>> table = {'Sjoerd': 4127, 'Jack': 4098, 'Dcab': 7678} + >>> for name, phone in table.items(): + ... print '%-10s ==> %10d' % (name, phone) + ... + Jack ==> 4098 + Dcab ==> 7678 + Sjoerd ==> 4127 + +Most formats work exactly as in C and require that you pass the proper type; +however, if you don't you get an exception, not a core dump. The ``%s`` format +is more relaxed: if the corresponding argument is not a string object, it is +converted to string using the :func:`str` built-in function. Using ``*`` to +pass the width or precision in as a separate (integer) argument is supported. +The C formats ``%n`` and ``%p`` are not supported. + +If you have a really long format string that you don't want to split up, it +would be nice if you could reference the variables to be formatted by name +instead of by position. This can be done by using form ``%(name)format``, as +shown here:: + + >>> table = {'Sjoerd': 4127, 'Jack': 4098, 'Dcab': 8637678} + >>> print 'Jack: %(Jack)d; Sjoerd: %(Sjoerd)d; Dcab: %(Dcab)d' % table + Jack: 4098; Sjoerd: 4127; Dcab: 8637678 + +This is particularly useful in combination with the new built-in :func:`vars` +function, which returns a dictionary containing all local variables. + + +.. _tut-files: + +Reading and Writing Files +========================= + +.. index:: + builtin: open + object: file + +:func:`open` returns a file object, and is most commonly used with two +arguments: ``open(filename, mode)``. + +.. % Opening files + +:: + + >>> f=open('/tmp/workfile', 'w') + >>> print f + <open file '/tmp/workfile', mode 'w' at 80a0960> + +The first argument is a string containing the filename. The second argument is +another string containing a few characters describing the way in which the file +will be used. *mode* can be ``'r'`` when the file will only be read, ``'w'`` +for only writing (an existing file with the same name will be erased), and +``'a'`` opens the file for appending; any data written to the file is +automatically added to the end. ``'r+'`` opens the file for both reading and +writing. The *mode* argument is optional; ``'r'`` will be assumed if it's +omitted. + +On Windows and the Macintosh, ``'b'`` appended to the mode opens the file in +binary mode, so there are also modes like ``'rb'``, ``'wb'``, and ``'r+b'``. +Windows makes a distinction between text and binary files; the end-of-line +characters in text files are automatically altered slightly when data is read or +written. This behind-the-scenes modification to file data is fine for ASCII +text files, but it'll corrupt binary data like that in :file:`JPEG` or +:file:`EXE` files. Be very careful to use binary mode when reading and writing +such files. + + +.. _tut-filemethods: + +Methods of File Objects +----------------------- + +The rest of the examples in this section will assume that a file object called +``f`` has already been created. + +To read a file's contents, call ``f.read(size)``, which reads some quantity of +data and returns it as a string. *size* is an optional numeric argument. When +*size* is omitted or negative, the entire contents of the file will be read and +returned; it's your problem if the file is twice as large as your machine's +memory. Otherwise, at most *size* bytes are read and returned. If the end of +the file has been reached, ``f.read()`` will return an empty string (``""``). +:: + + >>> f.read() + 'This is the entire file.\n' + >>> f.read() + '' + +``f.readline()`` reads a single line from the file; a newline character (``\n``) +is left at the end of the string, and is only omitted on the last line of the +file if the file doesn't end in a newline. This makes the return value +unambiguous; if ``f.readline()`` returns an empty string, the end of the file +has been reached, while a blank line is represented by ``'\n'``, a string +containing only a single newline. :: + + >>> f.readline() + 'This is the first line of the file.\n' + >>> f.readline() + 'Second line of the file\n' + >>> f.readline() + '' + +``f.readlines()`` returns a list containing all the lines of data in the file. +If given an optional parameter *sizehint*, it reads that many bytes from the +file and enough more to complete a line, and returns the lines from that. This +is often used to allow efficient reading of a large file by lines, but without +having to load the entire file in memory. Only complete lines will be returned. +:: + + >>> f.readlines() + ['This is the first line of the file.\n', 'Second line of the file\n'] + +An alternate approach to reading lines is to loop over the file object. This is +memory efficient, fast, and leads to simpler code:: + + >>> for line in f: + print line, + + This is the first line of the file. + Second line of the file + +The alternative approach is simpler but does not provide as fine-grained +control. Since the two approaches manage line buffering differently, they +should not be mixed. + +``f.write(string)`` writes the contents of *string* to the file, returning +``None``. :: + + >>> f.write('This is a test\n') + +To write something other than a string, it needs to be converted to a string +first:: + + >>> value = ('the answer', 42) + >>> s = str(value) + >>> f.write(s) + +``f.tell()`` returns an integer giving the file object's current position in the +file, measured in bytes from the beginning of the file. To change the file +object's position, use ``f.seek(offset, from_what)``. The position is computed +from adding *offset* to a reference point; the reference point is selected by +the *from_what* argument. A *from_what* value of 0 measures from the beginning +of the file, 1 uses the current file position, and 2 uses the end of the file as +the reference point. *from_what* can be omitted and defaults to 0, using the +beginning of the file as the reference point. :: + + >>> f = open('/tmp/workfile', 'r+') + >>> f.write('0123456789abcdef') + >>> f.seek(5) # Go to the 6th byte in the file + >>> f.read(1) + '5' + >>> f.seek(-3, 2) # Go to the 3rd byte before the end + >>> f.read(1) + 'd' + +When you're done with a file, call ``f.close()`` to close it and free up any +system resources taken up by the open file. After calling ``f.close()``, +attempts to use the file object will automatically fail. :: + + >>> f.close() + >>> f.read() + Traceback (most recent call last): + File "<stdin>", line 1, in ? + ValueError: I/O operation on closed file + +File objects have some additional methods, such as :meth:`isatty` and +:meth:`truncate` which are less frequently used; consult the Library Reference +for a complete guide to file objects. + + +.. _tut-pickle: + +The :mod:`pickle` Module +------------------------ + +.. index:: module: pickle + +Strings can easily be written to and read from a file. Numbers take a bit more +effort, since the :meth:`read` method only returns strings, which will have to +be passed to a function like :func:`int`, which takes a string like ``'123'`` +and returns its numeric value 123. However, when you want to save more complex +data types like lists, dictionaries, or class instances, things get a lot more +complicated. + +Rather than have users be constantly writing and debugging code to save +complicated data types, Python provides a standard module called :mod:`pickle`. +This is an amazing module that can take almost any Python object (even some +forms of Python code!), and convert it to a string representation; this process +is called :dfn:`pickling`. Reconstructing the object from the string +representation is called :dfn:`unpickling`. Between pickling and unpickling, +the string representing the object may have been stored in a file or data, or +sent over a network connection to some distant machine. + +If you have an object ``x``, and a file object ``f`` that's been opened for +writing, the simplest way to pickle the object takes only one line of code:: + + pickle.dump(x, f) + +To unpickle the object again, if ``f`` is a file object which has been opened +for reading:: + + x = pickle.load(f) + +(There are other variants of this, used when pickling many objects or when you +don't want to write the pickled data to a file; consult the complete +documentation for :mod:`pickle` in the Python Library Reference.) + +:mod:`pickle` is the standard way to make Python objects which can be stored and +reused by other programs or by a future invocation of the same program; the +technical term for this is a :dfn:`persistent` object. Because :mod:`pickle` is +so widely used, many authors who write Python extensions take care to ensure +that new data types such as matrices can be properly pickled and unpickled. + + diff --git a/Doc/tutorial/interactive.rst b/Doc/tutorial/interactive.rst new file mode 100644 index 0000000..8eeca2a --- /dev/null +++ b/Doc/tutorial/interactive.rst @@ -0,0 +1,167 @@ +.. _tut-interacting: + +************************************************** +Interactive Input Editing and History Substitution +************************************************** + +Some versions of the Python interpreter support editing of the current input +line and history substitution, similar to facilities found in the Korn shell and +the GNU Bash shell. This is implemented using the *GNU Readline* library, which +supports Emacs-style and vi-style editing. This library has its own +documentation which I won't duplicate here; however, the basics are easily +explained. The interactive editing and history described here are optionally +available in the Unix and Cygwin versions of the interpreter. + +This chapter does *not* document the editing facilities of Mark Hammond's +PythonWin package or the Tk-based environment, IDLE, distributed with Python. +The command line history recall which operates within DOS boxes on NT and some +other DOS and Windows flavors is yet another beast. + + +.. _tut-lineediting: + +Line Editing +============ + +If supported, input line editing is active whenever the interpreter prints a +primary or secondary prompt. The current line can be edited using the +conventional Emacs control characters. The most important of these are: +:kbd:`C-A` (Control-A) moves the cursor to the beginning of the line, :kbd:`C-E` +to the end, :kbd:`C-B` moves it one position to the left, :kbd:`C-F` to the +right. Backspace erases the character to the left of the cursor, :kbd:`C-D` the +character to its right. :kbd:`C-K` kills (erases) the rest of the line to the +right of the cursor, :kbd:`C-Y` yanks back the last killed string. +:kbd:`C-underscore` undoes the last change you made; it can be repeated for +cumulative effect. + + +.. _tut-history: + +History Substitution +==================== + +History substitution works as follows. All non-empty input lines issued are +saved in a history buffer, and when a new prompt is given you are positioned on +a new line at the bottom of this buffer. :kbd:`C-P` moves one line up (back) in +the history buffer, :kbd:`C-N` moves one down. Any line in the history buffer +can be edited; an asterisk appears in front of the prompt to mark a line as +modified. Pressing the :kbd:`Return` key passes the current line to the +interpreter. :kbd:`C-R` starts an incremental reverse search; :kbd:`C-S` starts +a forward search. + + +.. _tut-keybindings: + +Key Bindings +============ + +The key bindings and some other parameters of the Readline library can be +customized by placing commands in an initialization file called +:file:`~/.inputrc`. Key bindings have the form :: + + key-name: function-name + +or :: + + "string": function-name + +and options can be set with :: + + set option-name value + +For example:: + + # I prefer vi-style editing: + set editing-mode vi + + # Edit using a single line: + set horizontal-scroll-mode On + + # Rebind some keys: + Meta-h: backward-kill-word + "\C-u": universal-argument + "\C-x\C-r": re-read-init-file + +Note that the default binding for :kbd:`Tab` in Python is to insert a :kbd:`Tab` +character instead of Readline's default filename completion function. If you +insist, you can override this by putting :: + + Tab: complete + +in your :file:`~/.inputrc`. (Of course, this makes it harder to type indented +continuation lines if you're accustomed to using :kbd:`Tab` for that purpose.) + +.. index:: + module: rlcompleter + module: readline + +Automatic completion of variable and module names is optionally available. To +enable it in the interpreter's interactive mode, add the following to your +startup file: [#]_ :: + + import rlcompleter, readline + readline.parse_and_bind('tab: complete') + +This binds the :kbd:`Tab` key to the completion function, so hitting the +:kbd:`Tab` key twice suggests completions; it looks at Python statement names, +the current local variables, and the available module names. For dotted +expressions such as ``string.a``, it will evaluate the expression up to the +final ``'.'`` and then suggest completions from the attributes of the resulting +object. Note that this may execute application-defined code if an object with a +:meth:`__getattr__` method is part of the expression. + +A more capable startup file might look like this example. Note that this +deletes the names it creates once they are no longer needed; this is done since +the startup file is executed in the same namespace as the interactive commands, +and removing the names avoids creating side effects in the interactive +environment. You may find it convenient to keep some of the imported modules, +such as :mod:`os`, which turn out to be needed in most sessions with the +interpreter. :: + + # Add auto-completion and a stored history file of commands to your Python + # interactive interpreter. Requires Python 2.0+, readline. Autocomplete is + # bound to the Esc key by default (you can change it - see readline docs). + # + # Store the file in ~/.pystartup, and set an environment variable to point + # to it: "export PYTHONSTARTUP=/max/home/itamar/.pystartup" in bash. + # + # Note that PYTHONSTARTUP does *not* expand "~", so you have to put in the + # full path to your home directory. + + import atexit + import os + import readline + import rlcompleter + + historyPath = os.path.expanduser("~/.pyhistory") + + def save_history(historyPath=historyPath): + import readline + readline.write_history_file(historyPath) + + if os.path.exists(historyPath): + readline.read_history_file(historyPath) + + atexit.register(save_history) + del os, atexit, readline, rlcompleter, save_history, historyPath + + +.. _tut-commentary: + +Commentary +========== + +This facility is an enormous step forward compared to earlier versions of the +interpreter; however, some wishes are left: It would be nice if the proper +indentation were suggested on continuation lines (the parser knows if an indent +token is required next). The completion mechanism might use the interpreter's +symbol table. A command to check (or even suggest) matching parentheses, +quotes, etc., would also be useful. + + +.. rubric:: Footnotes + +.. [#] Python will execute the contents of a file identified by the + :envvar:`PYTHONSTARTUP` environment variable when you start an interactive + interpreter. + diff --git a/Doc/tutorial/interpreter.rst b/Doc/tutorial/interpreter.rst new file mode 100644 index 0000000..8b42090 --- /dev/null +++ b/Doc/tutorial/interpreter.rst @@ -0,0 +1,248 @@ +.. _tut-using: + +**************************** +Using the Python Interpreter +**************************** + + +.. _tut-invoking: + +Invoking the Interpreter +======================== + +The Python interpreter is usually installed as :file:`/usr/local/bin/python` 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 :: + + python + +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 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:\Python30`, 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:\python30 + +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 +status. If that doesn't work, you can exit the interpreter by typing the +following commands: ``import sys; sys.exit()``. + +The interpreter's line-editing features usually aren't very sophisticated. On +Unix, whoever installed the interpreter may have enabled support for the GNU +readline library, which adds more elaborate interactive editing and history +features. Perhaps the quickest check to see whether command line editing is +supported is typing Control-P to the first Python prompt you get. If it beeps, +you have command line editing; see Appendix :ref:`tut-interacting` for an +introduction to the keys. If nothing appears to happen, or if ``^P`` is echoed, +command line editing isn't available; you'll only be able to use backspace to +remove characters from the current line. + +The interpreter operates somewhat like the Unix shell: when called with standard +input connected to a tty device, it reads and executes commands interactively; +when called with a file name argument or with a file as standard input, it reads +and executes a *script* from that file. + +A second way of starting the interpreter is ``python -c command [arg] ...``, +which executes the statement(s) in *command*, analogous to the shell's +:option:`-c` option. Since Python statements often contain spaces or other +characters that are special to the shell, it is best to quote *command* in its +entirety with double quotes. + +Some Python modules are also useful as scripts. These can be invoked using +``python -m module [arg] ...``, which executes the source file for *module* as +if you had spelled out its full name on the command line. + +Note that there is a difference between ``python file`` and ``python <file``. +In the latter case, input requests from the program, such as calling +``sys.stdin.read()``, are satisfied from *file*. Since this file has already +been read until the end by the parser before the program starts executing, the +program will encounter end-of-file immediately. In the former case (which is +usually what you want) they are satisfied from whatever file or device is +connected to standard input of the Python interpreter. + +When a script file is used, it is sometimes useful to be able to run the script +and enter interactive mode afterwards. This can be done by passing :option:`-i` +before the script. (This does not work if the script is read from standard +input, for the same reason as explained in the previous paragraph.) + + +.. _tut-argpassing: + +Argument Passing +---------------- + +When known to the interpreter, the script name and additional arguments +thereafter are passed to the script in the variable ``sys.argv``, which is a +list of strings. Its length is at least one; when no script and no arguments +are given, ``sys.argv[0]`` is an empty string. When the script name is given as +``'-'`` (meaning standard input), ``sys.argv[0]`` is set to ``'-'``. When +:option:`-c` *command* is used, ``sys.argv[0]`` is set to ``'-c'``. When +:option:`-m` *module* is used, ``sys.argv[0]`` is set to the full name of the +located module. Options found after :option:`-c` *command* or :option:`-m` +*module* are not consumed by the Python interpreter's option processing but +left in ``sys.argv`` for the command or module to handle. + + +.. _tut-interactive: + +Interactive Mode +---------------- + +When commands are read from a tty, the interpreter is said to be in *interactive +mode*. In this mode it prompts for the next command with the *primary prompt*, +usually three greater-than signs (``>>>``); for continuation lines it prompts +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:: + + python + Python 1.5.2b2 (#1, Feb 28 1999, 00:02:06) [GCC 2.8.1] on sunos5 + Copyright 1991-1995 Stichting Mathematisch Centrum, Amsterdam + >>> + +Continuation lines are needed when entering a multi-line construct. As an +example, take a look at this :keyword:`if` statement:: + + >>> the_world_is_flat = 1 + >>> if the_world_is_flat: + ... print "Be careful not to fall off!" + ... + Be careful not to fall off! + + +.. _tut-interp: + +The Interpreter and Its Environment +=================================== + + +.. _tut-error: + +Error Handling +-------------- + +When an error occurs, the interpreter prints an error message and a stack trace. +In interactive mode, it then returns to the primary prompt; when input came from +a file, it exits with a nonzero exit status after printing the stack trace. +(Exceptions handled by an :keyword:`except` clause in a :keyword:`try` statement +are not errors in this context.) Some errors are unconditionally fatal and +cause an exit with a nonzero exit; this applies to internal inconsistencies and +some cases of running out of memory. All error messages are written to the +standard error stream; normal output from executed commands is written to +standard output. + +Typing the interrupt character (usually Control-C or DEL) to the primary or +secondary prompt cancels the input and returns to the primary prompt. [#]_ +Typing an interrupt while a command is executing raises the +:exc:`KeyboardInterrupt` exception, which may be handled by a :keyword:`try` +statement. + + +.. _tut-scripts: + +Executable Python Scripts +------------------------- + +On BSD'ish Unix systems, Python scripts can be made directly executable, like +shell scripts, by putting the line :: + + #! /usr/bin/env python + +(assuming that the interpreter is on the user's :envvar:`PATH`) at the beginning +of the script and giving the file an executable mode. The ``#!`` must be the +first two characters of the file. On some platforms, this first line must end +with a Unix-style line ending (``'\n'``), not a Mac OS (``'\r'``) or Windows +(``'\r\n'``) line ending. Note that the hash, or pound, character, ``'#'``, is +used to start a comment in Python. + +The script can be given an executable mode, or permission, using the +:program:`chmod` command:: + + $ chmod +x myscript.py + + +Source Code Encoding +-------------------- + +It is possible to use encodings different than ASCII in Python source files. The +best way to do it is to put one more special comment line right after the ``#!`` +line to define the source file encoding:: + + # -*- coding: encoding -*- + + +With that declaration, all characters in the source file will be treated as +having the encoding *encoding*, and it will be possible to directly write +Unicode string literals in the selected encoding. The list of possible +encodings can be found in the Python Library Reference, in the section on +:mod:`codecs`. + +For example, to write Unicode literals including the Euro currency symbol, the +ISO-8859-15 encoding can be used, with the Euro symbol having the ordinal value +164. This script will print the value 8364 (the Unicode codepoint corresponding +to the Euro symbol) and then exit:: + + # -*- coding: iso-8859-15 -*- + + currency = u"€" + print ord(currency) + +If your editor supports saving files as ``UTF-8`` with a UTF-8 *byte order mark* +(aka BOM), you can use that instead of an encoding declaration. IDLE supports +this capability if ``Options/General/Default Source Encoding/UTF-8`` is set. +Notice that this signature is not understood in older Python releases (2.2 and +earlier), and also not understood by the operating system for script files with +``#!`` lines (only used on Unix systems). + +By using UTF-8 (either through the signature or an encoding declaration), +characters of most languages in the world can be used simultaneously in string +literals and comments. Using non-ASCII characters in identifiers is not +supported. To display all these characters properly, your editor must recognize +that the file is UTF-8, and it must use a font that supports all the characters +in the file. + + +.. _tut-startup: + +The Interactive Startup File +---------------------------- + +When you use Python interactively, it is frequently handy to have some standard +commands executed every time the interpreter is started. You can do this by +setting an environment variable named :envvar:`PYTHONSTARTUP` to the name of a +file containing your start-up commands. This is similar to the :file:`.profile` +feature of the Unix shells. + +.. % XXX This should probably be dumped in an appendix, since most people +.. % don't use Python interactively in non-trivial ways. + +This file is only read in interactive sessions, not when Python reads commands +from a script, and not when :file:`/dev/tty` is given as the explicit source of +commands (which otherwise behaves like an interactive session). It is executed +in the same namespace where interactive commands are executed, so that objects +that it defines or imports can be used without qualification in the interactive +session. You can also change the prompts ``sys.ps1`` and ``sys.ps2`` in this +file. + +If you want to read an additional start-up file from the current directory, you +can program this in the global start-up file using code like ``if +os.path.isfile('.pythonrc.py'): exec(open('.pythonrc.py').read())``. +If you want to use the startup file in a script, you must do this explicitly +in the script:: + + import os + filename = os.environ.get('PYTHONSTARTUP') + if filename and os.path.isfile(filename): + exec(open(filename).read()) + + +.. rubric:: Footnotes + +.. [#] A problem with the GNU Readline package may prevent this. + diff --git a/Doc/tutorial/introduction.rst b/Doc/tutorial/introduction.rst new file mode 100644 index 0000000..e209bfc --- /dev/null +++ b/Doc/tutorial/introduction.rst @@ -0,0 +1,645 @@ +.. _tut-informal: + +********************************** +An Informal Introduction to Python +********************************** + +In the following examples, input and output are distinguished by the presence or +absence of prompts (``>>>`` and ``...``): to repeat the example, you must type +everything after the prompt, when the prompt appears; lines that do not begin +with a prompt are output from the interpreter. Note that a secondary prompt on a +line by itself in an example means you must type a blank line; this is used to +end a multi-line command. + +.. % +.. % \footnote{ +.. % I'd prefer to use different fonts to distinguish input +.. % from output, but the amount of LaTeX hacking that would require +.. % is currently beyond my ability. +.. % } + +Many of the examples in this manual, even those entered at the interactive +prompt, include comments. Comments in Python start with the hash character, +``'#'``, and extend to the end of the physical line. A comment may appear at +the start of a line or following whitespace or code, but not within a string +literal. A hash character within a string literal is just a hash character. + +Some examples:: + + # this is the first comment + SPAM = 1 # and this is the second comment + # ... and now a third! + STRING = "# This is not a comment." + + +.. _tut-calculator: + +Using Python as a Calculator +============================ + +Let's try some simple Python commands. Start the interpreter and wait for the +primary prompt, ``>>>``. (It shouldn't take long.) + + +.. _tut-numbers: + +Numbers +------- + +The interpreter acts as a simple calculator: you can type an expression at it +and it will write the value. Expression syntax is straightforward: the +operators ``+``, ``-``, ``*`` and ``/`` work just like in most other languages +(for example, Pascal or C); parentheses can be used for grouping. For example:: + + >>> 2+2 + 4 + >>> # This is a comment + ... 2+2 + 4 + >>> 2+2 # and a comment on the same line as code + 4 + >>> (50-5*6)/4 + 5 + >>> # Integer division returns the floor: + ... 7/3 + 2 + >>> 7/-3 + -3 + +The equal sign (``'='``) is used to assign a value to a variable. Afterwards, no +result is displayed before the next interactive prompt:: + + >>> width = 20 + >>> height = 5*9 + >>> width * height + 900 + +A value can be assigned to several variables simultaneously:: + + >>> x = y = z = 0 # Zero x, y and z + >>> x + 0 + >>> y + 0 + >>> z + 0 + +There is full support for floating point; operators with mixed type operands +convert the integer operand to floating point:: + + >>> 3 * 3.75 / 1.5 + 7.5 + >>> 7.0 / 2 + 3.5 + +Complex numbers are also supported; imaginary numbers are written with a suffix +of ``j`` or ``J``. Complex numbers with a nonzero real component are written as +``(real+imagj)``, or can be created with the ``complex(real, imag)`` function. +:: + + >>> 1j * 1J + (-1+0j) + >>> 1j * complex(0,1) + (-1+0j) + >>> 3+1j*3 + (3+3j) + >>> (3+1j)*3 + (9+3j) + >>> (1+2j)/(1+1j) + (1.5+0.5j) + +Complex numbers are always represented as two floating point numbers, the real +and imaginary part. To extract these parts from a complex number *z*, use +``z.real`` and ``z.imag``. :: + + >>> a=1.5+0.5j + >>> a.real + 1.5 + >>> a.imag + 0.5 + +The conversion functions to floating point and integer (:func:`float`, +:func:`int` and :func:`long`) don't work for complex numbers --- there is no one +correct way to convert a complex number to a real number. Use ``abs(z)`` to get +its magnitude (as a float) or ``z.real`` to get its real part. :: + + >>> a=3.0+4.0j + >>> float(a) + Traceback (most recent call last): + File "<stdin>", line 1, in ? + TypeError: can't convert complex to float; use abs(z) + >>> a.real + 3.0 + >>> a.imag + 4.0 + >>> abs(a) # sqrt(a.real**2 + a.imag**2) + 5.0 + >>> + +In interactive mode, the last printed expression is assigned to the variable +``_``. This means that when you are using Python as a desk calculator, it is +somewhat easier to continue calculations, for example:: + + >>> tax = 12.5 / 100 + >>> price = 100.50 + >>> price * tax + 12.5625 + >>> price + _ + 113.0625 + >>> round(_, 2) + 113.06 + >>> + +This variable should be treated as read-only by the user. Don't explicitly +assign a value to it --- you would create an independent local variable with the +same name masking the built-in variable with its magic behavior. + + +.. _tut-strings: + +Strings +------- + +Besides numbers, Python can also manipulate strings, which can be expressed in +several ways. They can be enclosed in single quotes or double quotes:: + + >>> 'spam eggs' + 'spam eggs' + >>> 'doesn\'t' + "doesn't" + >>> "doesn't" + "doesn't" + >>> '"Yes," he said.' + '"Yes," he said.' + >>> "\"Yes,\" he said." + '"Yes," he said.' + >>> '"Isn\'t," she said.' + '"Isn\'t," she said.' + +String literals can span multiple lines in several ways. Continuation lines can +be used, with a backslash as the last character on the line indicating that the +next line is a logical continuation of the line:: + + hello = "This is a rather long string containing\n\ + several lines of text just as you would do in C.\n\ + Note that whitespace at the beginning of the line is\ + significant." + + print hello + +Note that newlines still need to be embedded in the string using ``\n``; the +newline following the trailing backslash is discarded. This example would print +the following:: + + This is a rather long string containing + several lines of text just as you would do in C. + Note that whitespace at the beginning of the line is significant. + +If we make the string literal a "raw" string, however, the ``\n`` sequences are +not converted to newlines, but the backslash at the end of the line, and the +newline character in the source, are both included in the string as data. Thus, +the example:: + + hello = r"This is a rather long string containing\n\ + several lines of text much as you would do in C." + + print hello + +would print:: + + This is a rather long string containing\n\ + several lines of text much as you would do in C. + +Or, strings can be surrounded in a pair of matching triple-quotes: ``"""`` or +``'''``. End of lines do not need to be escaped when using triple-quotes, but +they will be included in the string. :: + + print """ + Usage: thingy [OPTIONS] + -h Display this usage message + -H hostname Hostname to connect to + """ + +produces the following output:: + + Usage: thingy [OPTIONS] + -h Display this usage message + -H hostname Hostname to connect to + +The interpreter prints the result of string operations in the same way as they +are typed for input: inside quotes, and with quotes and other funny characters +escaped by backslashes, to show the precise value. The string is enclosed in +double quotes if the string contains a single quote and no double quotes, else +it's enclosed in single quotes. (The :keyword:`print` statement, described +later, can be used to write strings without quotes or escapes.) + +Strings can be concatenated (glued together) with the ``+`` operator, and +repeated with ``*``:: + + >>> word = 'Help' + 'A' + >>> word + 'HelpA' + >>> '<' + word*5 + '>' + '<HelpAHelpAHelpAHelpAHelpA>' + +Two string literals next to each other are automatically concatenated; the first +line above could also have been written ``word = 'Help' 'A'``; this only works +with two literals, not with arbitrary string expressions:: + + >>> 'str' 'ing' # <- This is ok + 'string' + >>> 'str'.strip() + 'ing' # <- This is ok + 'string' + >>> 'str'.strip() 'ing' # <- This is invalid + File "<stdin>", line 1, in ? + 'str'.strip() 'ing' + ^ + SyntaxError: invalid syntax + +Strings can be subscripted (indexed); like in C, the first character of a string +has subscript (index) 0. There is no separate character type; a character is +simply a string of size one. Like in Icon, substrings can be specified with the +*slice notation*: two indices separated by a colon. :: + + >>> word[4] + 'A' + >>> word[0:2] + 'He' + >>> word[2:4] + 'lp' + +Slice indices have useful defaults; an omitted first index defaults to zero, an +omitted second index defaults to the size of the string being sliced. :: + + >>> word[:2] # The first two characters + 'He' + >>> word[2:] # Everything except the first two characters + 'lpA' + +Unlike a C string, Python strings cannot be changed. Assigning to an indexed +position in the string results in an error:: + + >>> word[0] = 'x' + Traceback (most recent call last): + File "<stdin>", line 1, in ? + TypeError: object doesn't support item assignment + >>> word[:1] = 'Splat' + Traceback (most recent call last): + File "<stdin>", line 1, in ? + TypeError: object doesn't support slice assignment + +However, creating a new string with the combined content is easy and efficient:: + + >>> 'x' + word[1:] + 'xelpA' + >>> 'Splat' + word[4] + 'SplatA' + +Here's a useful invariant of slice operations: ``s[:i] + s[i:]`` equals ``s``. +:: + + >>> word[:2] + word[2:] + 'HelpA' + >>> word[:3] + word[3:] + 'HelpA' + +Degenerate slice indices are handled gracefully: an index that is too large is +replaced by the string size, an upper bound smaller than the lower bound returns +an empty string. :: + + >>> word[1:100] + 'elpA' + >>> word[10:] + '' + >>> word[2:1] + '' + +Indices may be negative numbers, to start counting from the right. For example:: + + >>> word[-1] # The last character + 'A' + >>> word[-2] # The last-but-one character + 'p' + >>> word[-2:] # The last two characters + 'pA' + >>> word[:-2] # Everything except the last two characters + 'Hel' + +But note that -0 is really the same as 0, so it does not count from the right! +:: + + >>> word[-0] # (since -0 equals 0) + 'H' + +Out-of-range negative slice indices are truncated, but don't try this for +single-element (non-slice) indices:: + + >>> word[-100:] + 'HelpA' + >>> word[-10] # error + Traceback (most recent call last): + File "<stdin>", line 1, in ? + IndexError: string index out of range + +One way to remember how slices work is to think of the indices as pointing +*between* characters, with the left edge of the first character numbered 0. +Then the right edge of the last character of a string of *n* characters has +index *n*, for example:: + + +---+---+---+---+---+ + | H | e | l | p | A | + +---+---+---+---+---+ + 0 1 2 3 4 5 + -5 -4 -3 -2 -1 + +The first row of numbers gives the position of the indices 0...5 in the string; +the second row gives the corresponding negative indices. The slice from *i* to +*j* consists of all characters between the edges labeled *i* and *j*, +respectively. + +For non-negative indices, the length of a slice is the difference of the +indices, if both are within bounds. For example, the length of ``word[1:3]`` is +2. + +The built-in function :func:`len` returns the length of a string:: + + >>> s = 'supercalifragilisticexpialidocious' + >>> len(s) + 34 + + +.. seealso:: + + :ref:`typesseq` + Strings, and the Unicode strings described in the next section, are + examples of *sequence types*, and support the common operations supported + by such types. + + :ref:`string-methods` + Both strings and Unicode strings support a large number of methods for + basic transformations and searching. + + :ref:`string-formatting` + The formatting operations invoked when strings and Unicode strings are the + left operand of the ``%`` operator are described in more detail here. + + +.. _tut-unicodestrings: + +Unicode Strings +--------------- + +.. sectionauthor:: Marc-Andre Lemburg <mal@lemburg.com> + + +Starting with Python 2.0 a new data type for storing text data is available to +the programmer: the Unicode object. It can be used to store and manipulate +Unicode data (see http://www.unicode.org/) and integrates well with the existing +string objects, providing auto-conversions where necessary. + +Unicode has the advantage of providing one ordinal for every character in every +script used in modern and ancient texts. Previously, there were only 256 +possible ordinals for script characters. Texts were typically bound to a code +page which mapped the ordinals to script characters. This lead to very much +confusion especially with respect to internationalization (usually written as +``i18n`` --- ``'i'`` + 18 characters + ``'n'``) of software. Unicode solves +these problems by defining one code page for all scripts. + +Creating Unicode strings in Python is just as simple as creating normal +strings:: + + >>> u'Hello World !' + u'Hello World !' + +The small ``'u'`` in front of the quote indicates that a Unicode string is +supposed to be created. If you want to include special characters in the string, +you can do so by using the Python *Unicode-Escape* encoding. The following +example shows how:: + + >>> u'Hello\u0020World !' + u'Hello World !' + +The escape sequence ``\u0020`` indicates to insert the Unicode character with +the ordinal value 0x0020 (the space character) at the given position. + +Other characters are interpreted by using their respective ordinal values +directly as Unicode ordinals. If you have literal strings in the standard +Latin-1 encoding that is used in many Western countries, you will find it +convenient that the lower 256 characters of Unicode are the same as the 256 +characters of Latin-1. + +For experts, there is also a raw mode just like the one for normal strings. You +have to prefix the opening quote with 'ur' to have Python use the +*Raw-Unicode-Escape* encoding. It will only apply the above ``\uXXXX`` +conversion if there is an uneven number of backslashes in front of the small +'u'. :: + + >>> ur'Hello\u0020World !' + u'Hello World !' + >>> ur'Hello\\u0020World !' + u'Hello\\\\u0020World !' + +The raw mode is most useful when you have to enter lots of backslashes, as can +be necessary in regular expressions. + +Apart from these standard encodings, Python provides a whole set of other ways +of creating Unicode strings on the basis of a known encoding. + +.. index:: builtin: unicode + +The built-in function :func:`unicode` provides access to all registered Unicode +codecs (COders and DECoders). Some of the more well known encodings which these +codecs can convert are *Latin-1*, *ASCII*, *UTF-8*, and *UTF-16*. The latter two +are variable-length encodings that store each Unicode character in one or more +bytes. The default encoding is normally set to ASCII, which passes through +characters in the range 0 to 127 and rejects any other characters with an error. +When a Unicode string is printed, written to a file, or converted with +:func:`str`, conversion takes place using this default encoding. :: + + >>> u"abc" + u'abc' + >>> str(u"abc") + 'abc' + >>> u"äöü" + u'\xe4\xf6\xfc' + >>> str(u"äöü") + Traceback (most recent call last): + File "<stdin>", line 1, in ? + UnicodeEncodeError: 'ascii' codec can't encode characters in position 0-2: ordinal not in range(128) + +To convert a Unicode string into an 8-bit string using a specific encoding, +Unicode objects provide an :func:`encode` method that takes one argument, the +name of the encoding. Lowercase names for encodings are preferred. :: + + >>> u"äöü".encode('utf-8') + '\xc3\xa4\xc3\xb6\xc3\xbc' + +If you have data in a specific encoding and want to produce a corresponding +Unicode string from it, you can use the :func:`unicode` function with the +encoding name as the second argument. :: + + >>> unicode('\xc3\xa4\xc3\xb6\xc3\xbc', 'utf-8') + u'\xe4\xf6\xfc' + + +.. _tut-lists: + +Lists +----- + +Python knows a number of *compound* data types, used to group together other +values. The most versatile is the *list*, which can be written as a list of +comma-separated values (items) between square brackets. List items need not all +have the same type. :: + + >>> a = ['spam', 'eggs', 100, 1234] + >>> a + ['spam', 'eggs', 100, 1234] + +Like string indices, list indices start at 0, and lists can be sliced, +concatenated and so on:: + + >>> a[0] + 'spam' + >>> a[3] + 1234 + >>> a[-2] + 100 + >>> a[1:-1] + ['eggs', 100] + >>> a[:2] + ['bacon', 2*2] + ['spam', 'eggs', 'bacon', 4] + >>> 3*a[:3] + ['Boo!'] + ['spam', 'eggs', 100, 'spam', 'eggs', 100, 'spam', 'eggs', 100, 'Boo!'] + +Unlike strings, which are *immutable*, it is possible to change individual +elements of a list:: + + >>> a + ['spam', 'eggs', 100, 1234] + >>> a[2] = a[2] + 23 + >>> a + ['spam', 'eggs', 123, 1234] + +Assignment to slices is also possible, and this can even change the size of the +list or clear it entirely:: + + >>> # Replace some items: + ... a[0:2] = [1, 12] + >>> a + [1, 12, 123, 1234] + >>> # Remove some: + ... a[0:2] = [] + >>> a + [123, 1234] + >>> # Insert some: + ... a[1:1] = ['bletch', 'xyzzy'] + >>> a + [123, 'bletch', 'xyzzy', 1234] + >>> # Insert (a copy of) itself at the beginning + >>> a[:0] = a + >>> a + [123, 'bletch', 'xyzzy', 1234, 123, 'bletch', 'xyzzy', 1234] + >>> # Clear the list: replace all items with an empty list + >>> a[:] = [] + >>> a + [] + +The built-in function :func:`len` also applies to lists:: + + >>> len(a) + 8 + +It is possible to nest lists (create lists containing other lists), for +example:: + + >>> q = [2, 3] + >>> p = [1, q, 4] + >>> len(p) + 3 + >>> p[1] + [2, 3] + >>> p[1][0] + 2 + >>> p[1].append('xtra') # See section 5.1 + >>> p + [1, [2, 3, 'xtra'], 4] + >>> q + [2, 3, 'xtra'] + +Note that in the last example, ``p[1]`` and ``q`` really refer to the same +object! We'll come back to *object semantics* later. + + +.. _tut-firststeps: + +First Steps Towards Programming +=============================== + +Of course, we can use Python for more complicated tasks than adding two and two +together. For instance, we can write an initial sub-sequence of the *Fibonacci* +series as follows:: + + >>> # Fibonacci series: + ... # the sum of two elements defines the next + ... a, b = 0, 1 + >>> while b < 10: + ... print b + ... a, b = b, a+b + ... + 1 + 1 + 2 + 3 + 5 + 8 + +This example introduces several new features. + +* The first line contains a *multiple assignment*: the variables ``a`` and ``b`` + simultaneously get the new values 0 and 1. On the last line this is used again, + demonstrating that the expressions on the right-hand side are all evaluated + first before any of the assignments take place. The right-hand side expressions + are evaluated from the left to the right. + +* The :keyword:`while` loop executes as long as the condition (here: ``b < 10``) + remains true. In Python, like in C, any non-zero integer value is true; zero is + false. The condition may also be a string or list value, in fact any sequence; + anything with a non-zero length is true, empty sequences are false. The test + used in the example is a simple comparison. The standard comparison operators + are written the same as in C: ``<`` (less than), ``>`` (greater than), ``==`` + (equal to), ``<=`` (less than or equal to), ``>=`` (greater than or equal to) + and ``!=`` (not equal to). + +* The *body* of the loop is *indented*: indentation is Python's way of grouping + statements. Python does not (yet!) provide an intelligent input line editing + facility, so you have to type a tab or space(s) for each indented line. In + practice you will prepare more complicated input for Python with a text editor; + most text editors have an auto-indent facility. When a compound statement is + entered interactively, it must be followed by a blank line to indicate + completion (since the parser cannot guess when you have typed the last line). + Note that each line within a basic block must be indented by the same amount. + +* The :keyword:`print` statement writes the value of the expression(s) it is + given. It differs from just writing the expression you want to write (as we did + earlier in the calculator examples) in the way it handles multiple expressions + and strings. Strings are printed without quotes, and a space is inserted + between items, so you can format things nicely, like this:: + + >>> i = 256*256 + >>> print 'The value of i is', i + The value of i is 65536 + + A trailing comma avoids the newline after the output:: + + >>> a, b = 0, 1 + >>> while b < 1000: + ... print b, + ... a, b = b, a+b + ... + 1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987 + + Note that the interpreter inserts a newline before it prints the next prompt if + the last line was not completed. + + diff --git a/Doc/tutorial/modules.rst b/Doc/tutorial/modules.rst new file mode 100644 index 0000000..0b0dabd --- /dev/null +++ b/Doc/tutorial/modules.rst @@ -0,0 +1,551 @@ +.. _tut-modules: + +******* +Modules +******* + +If you quit from the Python interpreter and enter it again, the definitions you +have made (functions and variables) are lost. Therefore, if you want to write a +somewhat longer program, you are better off using a text editor to prepare the +input for the interpreter and running it with that file as input instead. This +is known as creating a *script*. As your program gets longer, you may want to +split it into several files for easier maintenance. You may also want to use a +handy function that you've written in several programs without copying its +definition into each program. + +To support this, Python has a way to put definitions in a file and use them in a +script or in an interactive instance of the interpreter. Such a file is called a +*module*; definitions from a module can be *imported* into other modules or into +the *main* module (the collection of variables that you have access to in a +script executed at the top level and in calculator mode). + +A module is a file containing Python definitions and statements. The file name +is the module name with the suffix :file:`.py` appended. Within a module, the +module's name (as a string) is available as the value of the global variable +``__name__``. For instance, use your favorite text editor to create a file +called :file:`fibo.py` in the current directory with the following contents:: + + # Fibonacci numbers module + + def fib(n): # write Fibonacci series up to n + a, b = 0, 1 + while b < n: + print b, + a, b = b, a+b + + def fib2(n): # return Fibonacci series up to n + result = [] + a, b = 0, 1 + while b < n: + result.append(b) + a, b = b, a+b + return result + +Now enter the Python interpreter and import this module with the following +command:: + + >>> import fibo + +This does not enter the names of the functions defined in ``fibo`` directly in +the current symbol table; it only enters the module name ``fibo`` there. Using +the module name you can access the functions:: + + >>> fibo.fib(1000) + 1 1 2 3 5 8 13 21 34 55 89 144 233 377 610 987 + >>> fibo.fib2(100) + [1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89] + >>> fibo.__name__ + 'fibo' + +If you intend to use a function often you can assign it to a local name:: + + >>> fib = fibo.fib + >>> fib(500) + 1 1 2 3 5 8 13 21 34 55 89 144 233 377 + + +.. _tut-moremodules: + +More on Modules +=============== + +A module can contain executable statements as well as function definitions. +These statements are intended to initialize the module. They are executed only +the *first* time the module is imported somewhere. [#]_ + +Each module has its own private symbol table, which is used as the global symbol +table by all functions defined in the module. Thus, the author of a module can +use global variables in the module without worrying about accidental clashes +with a user's global variables. On the other hand, if you know what you are +doing you can touch a module's global variables with the same notation used to +refer to its functions, ``modname.itemname``. + +Modules can import other modules. It is customary but not required to place all +:keyword:`import` statements at the beginning of a module (or script, for that +matter). The imported module names are placed in the importing module's global +symbol table. + +There is a variant of the :keyword:`import` statement that imports names from a +module directly into the importing module's symbol table. For example:: + + >>> from fibo import fib, fib2 + >>> fib(500) + 1 1 2 3 5 8 13 21 34 55 89 144 233 377 + +This does not introduce the module name from which the imports are taken in the +local symbol table (so in the example, ``fibo`` is not defined). + +There is even a variant to import all names that a module defines:: + + >>> from fibo import * + >>> fib(500) + 1 1 2 3 5 8 13 21 34 55 89 144 233 377 + +This imports all names except those beginning with an underscore (``_``). + + +.. _tut-modulesasscripts: + +Executing modules as scripts +---------------------------- + +When you run a Python module with :: + + python fibo.py <arguments> + +the code in the module will be executed, just as if you imported it, but with +the ``__name__`` set to ``"__main__"``. That means that by adding this code at +the end of your module:: + + if __name__ == "__main__": + import sys + fib(int(sys.argv[1])) + +you can make the file usable as a script as well as an importable module, +because the code that parses the command line only runs if the module is +executed as the "main" file:: + + $ python fibo.py 50 + 1 1 2 3 5 8 13 21 34 + +If the module is imported, the code is not run:: + + >>> import fibo + >>> + +This is often used either to provide a convenient user interface to a module, or +for testing purposes (running the module as a script executes a test suite). + + +.. _tut-searchpath: + +The Module Search Path +---------------------- + +.. index:: triple: module; search; path + +When a module named :mod:`spam` is imported, the interpreter searches for a file +named :file:`spam.py` in the current directory, and then in the list of +directories specified by the environment variable :envvar:`PYTHONPATH`. This +has the same syntax as the shell variable :envvar:`PATH`, that is, a list of +directory names. When :envvar:`PYTHONPATH` is not set, or when the file is not +found there, the search continues in an installation-dependent default path; on +Unix, this is usually :file:`.:/usr/local/lib/python`. + +Actually, modules are searched in the list of directories given by the variable +``sys.path`` which is initialized from the directory containing the input script +(or the current directory), :envvar:`PYTHONPATH` and the installation- dependent +default. This allows Python programs that know what they're doing to modify or +replace the module search path. Note that because the directory containing the +script being run is on the search path, it is important that the script not have +the same name as a standard module, or Python will attempt to load the script as +a module when that module is imported. This will generally be an error. See +section :ref:`tut-standardmodules` for more information. + + +"Compiled" Python files +----------------------- + +As an important speed-up of the start-up time for short programs that use a lot +of standard modules, if a file called :file:`spam.pyc` exists in the directory +where :file:`spam.py` is found, this is assumed to contain an +already-"byte-compiled" version of the module :mod:`spam`. The modification time +of the version of :file:`spam.py` used to create :file:`spam.pyc` is recorded in +:file:`spam.pyc`, and the :file:`.pyc` file is ignored if these don't match. + +Normally, you don't need to do anything to create the :file:`spam.pyc` file. +Whenever :file:`spam.py` is successfully compiled, an attempt is made to write +the compiled version to :file:`spam.pyc`. It is not an error if this attempt +fails; if for any reason the file is not written completely, the resulting +:file:`spam.pyc` file will be recognized as invalid and thus ignored later. The +contents of the :file:`spam.pyc` file are platform independent, so a Python +module directory can be shared by machines of different architectures. + +Some tips for experts: + +* When the Python interpreter is invoked with the :option:`-O` flag, optimized + code is generated and stored in :file:`.pyo` files. The optimizer currently + doesn't help much; it only removes :keyword:`assert` statements. When + :option:`-O` is used, *all* bytecode is optimized; ``.pyc`` files are ignored + and ``.py`` files are compiled to optimized bytecode. + +* Passing two :option:`-O` flags to the Python interpreter (:option:`-OO`) will + cause the bytecode compiler to perform optimizations that could in some rare + cases result in malfunctioning programs. Currently only ``__doc__`` strings are + removed from the bytecode, resulting in more compact :file:`.pyo` files. Since + some programs may rely on having these available, you should only use this + option if you know what you're doing. + +* A program doesn't run any faster when it is read from a :file:`.pyc` or + :file:`.pyo` file than when it is read from a :file:`.py` file; the only thing + that's faster about :file:`.pyc` or :file:`.pyo` files is the speed with which + they are loaded. + +* When a script is run by giving its name on the command line, the bytecode for + the script is never written to a :file:`.pyc` or :file:`.pyo` file. Thus, the + startup time of a script may be reduced by moving most of its code to a module + and having a small bootstrap script that imports that module. It is also + possible to name a :file:`.pyc` or :file:`.pyo` file directly on the command + line. + +* It is possible to have a file called :file:`spam.pyc` (or :file:`spam.pyo` + when :option:`-O` is used) without a file :file:`spam.py` for the same module. + This can be used to distribute a library of Python code in a form that is + moderately hard to reverse engineer. + + .. index:: module: compileall + +* The module :mod:`compileall` can create :file:`.pyc` files (or :file:`.pyo` + files when :option:`-O` is used) for all modules in a directory. + + .. % + + +.. _tut-standardmodules: + +Standard Modules +================ + +.. index:: module: sys + +Python comes with a library of standard modules, described in a separate +document, the Python Library Reference ("Library Reference" hereafter). Some +modules are built into the interpreter; these provide access to operations that +are not part of the core of the language but are nevertheless built in, either +for efficiency or to provide access to operating system primitives such as +system calls. The set of such modules is a configuration option which also +depends on the underlying platform For example, the :mod:`winreg` module is only +provided on Windows systems. One particular module deserves some attention: +:mod:`sys`, which is built into every Python interpreter. The variables +``sys.ps1`` and ``sys.ps2`` define the strings used as primary and secondary +prompts: + +.. % + +:: + + >>> import sys + >>> sys.ps1 + '>>> ' + >>> sys.ps2 + '... ' + >>> sys.ps1 = 'C> ' + C> print 'Yuck!' + Yuck! + C> + + +These two variables are only defined if the interpreter is in interactive mode. + +The variable ``sys.path`` is a list of strings that determines the interpreter's +search path for modules. It is initialized to a default path taken from the +environment variable :envvar:`PYTHONPATH`, or from a built-in default if +:envvar:`PYTHONPATH` is not set. You can modify it using standard list +operations:: + + >>> import sys + >>> sys.path.append('/ufs/guido/lib/python') + + +.. _tut-dir: + +The :func:`dir` Function +======================== + +The built-in function :func:`dir` is used to find out which names a module +defines. It returns a sorted list of strings:: + + >>> import fibo, sys + >>> dir(fibo) + ['__name__', 'fib', 'fib2'] + >>> dir(sys) + ['__displayhook__', '__doc__', '__excepthook__', '__name__', '__stderr__', + '__stdin__', '__stdout__', '_getframe', 'api_version', 'argv', + 'builtin_module_names', 'byteorder', 'callstats', 'copyright', + 'displayhook', 'exc_info', 'excepthook', + 'exec_prefix', 'executable', 'exit', 'getdefaultencoding', 'getdlopenflags', + 'getrecursionlimit', 'getrefcount', 'hexversion', 'maxint', 'maxunicode', + 'meta_path', 'modules', 'path', 'path_hooks', 'path_importer_cache', + 'platform', 'prefix', 'ps1', 'ps2', 'setcheckinterval', 'setdlopenflags', + 'setprofile', 'setrecursionlimit', 'settrace', 'stderr', 'stdin', 'stdout', + 'version', 'version_info', 'warnoptions'] + +Without arguments, :func:`dir` lists the names you have defined currently:: + + >>> a = [1, 2, 3, 4, 5] + >>> import fibo + >>> fib = fibo.fib + >>> dir() + ['__builtins__', '__doc__', '__file__', '__name__', 'a', 'fib', 'fibo', 'sys'] + +Note that it lists all types of names: variables, modules, functions, etc. + +.. index:: module: __builtin__ + +:func:`dir` does not list the names of built-in functions and variables. If you +want a list of those, they are defined in the standard module +:mod:`__builtin__`:: + + >>> import __builtin__ + >>> dir(__builtin__) + ['ArithmeticError', 'AssertionError', 'AttributeError', 'DeprecationWarning', + 'EOFError', 'Ellipsis', 'EnvironmentError', 'Exception', 'False', + 'FloatingPointError', 'FutureWarning', 'IOError', 'ImportError', + 'IndentationError', 'IndexError', 'KeyError', 'KeyboardInterrupt', + 'LookupError', 'MemoryError', 'NameError', 'None', 'NotImplemented', + 'NotImplementedError', 'OSError', 'OverflowError', + 'PendingDeprecationWarning', 'ReferenceError', 'RuntimeError', + 'RuntimeWarning', 'StopIteration', 'SyntaxError', + 'SyntaxWarning', 'SystemError', 'SystemExit', 'TabError', 'True', + 'TypeError', 'UnboundLocalError', 'UnicodeDecodeError', + 'UnicodeEncodeError', 'UnicodeError', 'UnicodeTranslateError', + 'UserWarning', 'ValueError', 'Warning', 'WindowsError', + 'ZeroDivisionError', '_', '__debug__', '__doc__', '__import__', + '__name__', 'abs', 'basestring', 'bool', 'buffer', + 'chr', 'classmethod', 'cmp', 'compile', + 'complex', 'copyright', 'credits', 'delattr', 'dict', 'dir', 'divmod', + 'enumerate', 'eval', 'exec', 'exit', 'filter', 'float', + 'frozenset', 'getattr', 'globals', 'hasattr', 'hash', 'help', 'hex', + 'id', 'input', 'int', 'isinstance', 'issubclass', 'iter', + 'len', 'license', 'list', 'locals', 'map', 'max', 'min', + 'object', 'oct', 'open', 'ord', 'pow', 'property', 'quit', 'range', + 'repr', 'reversed', 'round', 'set', + 'setattr', 'slice', 'sorted', 'staticmethod', 'str', 'sum', 'super', + 'tuple', 'type', 'vars', 'zip'] + + +.. _tut-packages: + +Packages +======== + +Packages are a way of structuring Python's module namespace by using "dotted +module names". For example, the module name :mod:`A.B` designates a submodule +named ``B`` in a package named ``A``. Just like the use of modules saves the +authors of different modules from having to worry about each other's global +variable names, the use of dotted module names saves the authors of multi-module +packages like NumPy or the Python Imaging Library from having to worry about +each other's module names. + +Suppose you want to design a collection of modules (a "package") for the uniform +handling of sound files and sound data. There are many different sound file +formats (usually recognized by their extension, for example: :file:`.wav`, +:file:`.aiff`, :file:`.au`), so you may need to create and maintain a growing +collection of modules for the conversion between the various file formats. +There are also many different operations you might want to perform on sound data +(such as mixing, adding echo, applying an equalizer function, creating an +artificial stereo effect), so in addition you will be writing a never-ending +stream of modules to perform these operations. Here's a possible structure for +your package (expressed in terms of a hierarchical filesystem):: + + sound/ Top-level package + __init__.py Initialize the sound package + formats/ Subpackage for file format conversions + __init__.py + wavread.py + wavwrite.py + aiffread.py + aiffwrite.py + auread.py + auwrite.py + ... + effects/ Subpackage for sound effects + __init__.py + echo.py + surround.py + reverse.py + ... + filters/ Subpackage for filters + __init__.py + equalizer.py + vocoder.py + karaoke.py + ... + +When importing the package, Python searches through the directories on +``sys.path`` looking for the package subdirectory. + +The :file:`__init__.py` files are required to make Python treat the directories +as containing packages; this is done to prevent directories with a common name, +such as ``string``, from unintentionally hiding valid modules that occur later +on the module search path. In the simplest case, :file:`__init__.py` can just be +an empty file, but it can also execute initialization code for the package or +set the ``__all__`` variable, described later. + +Users of the package can import individual modules from the package, for +example:: + + import sound.effects.echo + +This loads the submodule :mod:`sound.effects.echo`. It must be referenced with +its full name. :: + + sound.effects.echo.echofilter(input, output, delay=0.7, atten=4) + +An alternative way of importing the submodule is:: + + from sound.effects import echo + +This also loads the submodule :mod:`echo`, and makes it available without its +package prefix, so it can be used as follows:: + + echo.echofilter(input, output, delay=0.7, atten=4) + +Yet another variation is to import the desired function or variable directly:: + + from sound.effects.echo import echofilter + +Again, this loads the submodule :mod:`echo`, but this makes its function +:func:`echofilter` directly available:: + + echofilter(input, output, delay=0.7, atten=4) + +Note that when using ``from package import item``, the item can be either a +submodule (or subpackage) of the package, or some other name defined in the +package, like a function, class or variable. The ``import`` statement first +tests whether the item is defined in the package; if not, it assumes it is a +module and attempts to load it. If it fails to find it, an :exc:`ImportError` +exception is raised. + +Contrarily, when using syntax like ``import item.subitem.subsubitem``, each item +except for the last must be a package; the last item can be a module or a +package but can't be a class or function or variable defined in the previous +item. + + +.. _tut-pkg-import-star: + +Importing \* From a Package +--------------------------- + +.. index:: single: __all__ + +Now what happens when the user writes ``from sound.effects import *``? Ideally, +one would hope that this somehow goes out to the filesystem, finds which +submodules are present in the package, and imports them all. Unfortunately, +this operation does not work very well on Windows platforms, where the +filesystem does not always have accurate information about the case of a +filename! On these platforms, there is no guaranteed way to know whether a file +:file:`ECHO.PY` should be imported as a module :mod:`echo`, :mod:`Echo` or +:mod:`ECHO`. (For example, Windows 95 has the annoying practice of showing all +file names with a capitalized first letter.) The DOS 8+3 filename restriction +adds another interesting problem for long module names. + +.. % The \code{__all__} Attribute + +The only solution is for the package author to provide an explicit index of the +package. The import statement uses the following convention: if a package's +:file:`__init__.py` code defines a list named ``__all__``, it is taken to be the +list of module names that should be imported when ``from package import *`` is +encountered. It is up to the package author to keep this list up-to-date when a +new version of the package is released. Package authors may also decide not to +support it, if they don't see a use for importing \* from their package. For +example, the file :file:`sounds/effects/__init__.py` could contain the following +code:: + + __all__ = ["echo", "surround", "reverse"] + +This would mean that ``from sound.effects import *`` would import the three +named submodules of the :mod:`sound` package. + +If ``__all__`` is not defined, the statement ``from sound.effects import *`` +does *not* import all submodules from the package :mod:`sound.effects` into the +current namespace; it only ensures that the package :mod:`sound.effects` has +been imported (possibly running any initialization code in :file:`__init__.py`) +and then imports whatever names are defined in the package. This includes any +names defined (and submodules explicitly loaded) by :file:`__init__.py`. It +also includes any submodules of the package that were explicitly loaded by +previous import statements. Consider this code:: + + import sound.effects.echo + import sound.effects.surround + from sound.effects import * + +In this example, the echo and surround modules are imported in the current +namespace because they are defined in the :mod:`sound.effects` package when the +``from...import`` statement is executed. (This also works when ``__all__`` is +defined.) + +Note that in general the practice of importing ``*`` from a module or package is +frowned upon, since it often causes poorly readable code. However, it is okay to +use it to save typing in interactive sessions, and certain modules are designed +to export only names that follow certain patterns. + +Remember, there is nothing wrong with using ``from Package import +specific_submodule``! In fact, this is the recommended notation unless the +importing module needs to use submodules with the same name from different +packages. + + +Intra-package References +------------------------ + +The submodules often need to refer to each other. For example, the +:mod:`surround` module might use the :mod:`echo` module. In fact, such +references are so common that the :keyword:`import` statement first looks in the +containing package before looking in the standard module search path. Thus, the +:mod:`surround` module can simply use ``import echo`` or ``from echo import +echofilter``. If the imported module is not found in the current package (the +package of which the current module is a submodule), the :keyword:`import` +statement looks for a top-level module with the given name. + +When packages are structured into subpackages (as with the :mod:`sound` package +in the example), you can use absolute imports to refer to submodules of siblings +packages. For example, if the module :mod:`sound.filters.vocoder` needs to use +the :mod:`echo` module in the :mod:`sound.effects` package, it can use ``from +sound.effects import echo``. + +Starting with Python 2.5, in addition to the implicit relative imports described +above, you can write explicit relative imports with the ``from module import +name`` form of import statement. These explicit relative imports use leading +dots to indicate the current and parent packages involved in the relative +import. From the :mod:`surround` module for example, you might use:: + + from . import echo + from .. import formats + from ..filters import equalizer + +Note that both explicit and implicit relative imports are based on the name of +the current module. Since the name of the main module is always ``"__main__"``, +modules intended for use as the main module of a Python application should +always use absolute imports. + + +Packages in Multiple Directories +-------------------------------- + +Packages support one more special attribute, :attr:`__path__`. This is +initialized to be a list containing the name of the directory holding the +package's :file:`__init__.py` before the code in that file is executed. This +variable can be modified; doing so affects future searches for modules and +subpackages contained in the package. + +While this feature is not often needed, it can be used to extend the set of +modules found in a package. + + +.. rubric:: Footnotes + +.. [#] In fact function definitions are also 'statements' that are 'executed'; the + execution enters the function name in the module's global symbol table. + diff --git a/Doc/tutorial/stdlib.rst b/Doc/tutorial/stdlib.rst new file mode 100644 index 0000000..7bbc5ef --- /dev/null +++ b/Doc/tutorial/stdlib.rst @@ -0,0 +1,313 @@ +.. _tut-brieftour: + +********************************** +Brief Tour of the Standard Library +********************************** + + +.. _tut-os-interface: + +Operating System Interface +========================== + +The :mod:`os` module provides dozens of functions for interacting with the +operating system:: + + >>> import os + >>> os.system('time 0:02') + 0 + >>> os.getcwd() # Return the current working directory + 'C:\\Python30' + >>> os.chdir('/server/accesslogs') + +Be sure to use the ``import os`` style instead of ``from os import *``. This +will keep :func:`os.open` from shadowing the builtin :func:`open` function which +operates much differently. + +.. index:: builtin: help + +The builtin :func:`dir` and :func:`help` functions are useful as interactive +aids for working with large modules like :mod:`os`:: + + >>> import os + >>> dir(os) + <returns a list of all module functions> + >>> help(os) + <returns an extensive manual page created from the module's docstrings> + +For daily file and directory management tasks, the :mod:`shutil` module provides +a higher level interface that is easier to use:: + + >>> import shutil + >>> shutil.copyfile('data.db', 'archive.db') + >>> shutil.move('/build/executables', 'installdir') + + +.. _tut-file-wildcards: + +File Wildcards +============== + +The :mod:`glob` module provides a function for making file lists from directory +wildcard searches:: + + >>> import glob + >>> glob.glob('*.py') + ['primes.py', 'random.py', 'quote.py'] + + +.. _tut-command-line-arguments: + +Command Line Arguments +====================== + +Common utility scripts often need to process command line arguments. These +arguments are stored in the :mod:`sys` module's *argv* attribute as a list. For +instance the following output results from running ``python demo.py one two +three`` at the command line:: + + >>> import sys + >>> print sys.argv + ['demo.py', 'one', 'two', 'three'] + +The :mod:`getopt` module processes *sys.argv* using the conventions of the Unix +:func:`getopt` function. More powerful and flexible command line processing is +provided by the :mod:`optparse` module. + + +.. _tut-stderr: + +Error Output Redirection and Program Termination +================================================ + +The :mod:`sys` module also has attributes for *stdin*, *stdout*, and *stderr*. +The latter is useful for emitting warnings and error messages to make them +visible even when *stdout* has been redirected:: + + >>> sys.stderr.write('Warning, log file not found starting a new one\n') + Warning, log file not found starting a new one + +The most direct way to terminate a script is to use ``sys.exit()``. + + +.. _tut-string-pattern-matching: + +String Pattern Matching +======================= + +The :mod:`re` module provides regular expression tools for advanced string +processing. For complex matching and manipulation, regular expressions offer +succinct, optimized solutions:: + + >>> import re + >>> re.findall(r'\bf[a-z]*', 'which foot or hand fell fastest') + ['foot', 'fell', 'fastest'] + >>> re.sub(r'(\b[a-z]+) \1', r'\1', 'cat in the the hat') + 'cat in the hat' + +When only simple capabilities are needed, string methods are preferred because +they are easier to read and debug:: + + >>> 'tea for too'.replace('too', 'two') + 'tea for two' + + +.. _tut-mathematics: + +Mathematics +=========== + +The :mod:`math` module gives access to the underlying C library functions for +floating point math:: + + >>> import math + >>> math.cos(math.pi / 4.0) + 0.70710678118654757 + >>> math.log(1024, 2) + 10.0 + +The :mod:`random` module provides tools for making random selections:: + + >>> import random + >>> random.choice(['apple', 'pear', 'banana']) + 'apple' + >>> random.sample(range(100), 10) # sampling without replacement + [30, 83, 16, 4, 8, 81, 41, 50, 18, 33] + >>> random.random() # random float + 0.17970987693706186 + >>> random.randrange(6) # random integer chosen from range(6) + 4 + + +.. _tut-internet-access: + +Internet Access +=============== + +There are a number of modules for accessing the internet and processing internet +protocols. Two of the simplest are :mod:`urllib2` for retrieving data from urls +and :mod:`smtplib` for sending mail:: + + >>> import urllib2 + >>> for line in urllib2.urlopen('http://tycho.usno.navy.mil/cgi-bin/timer.pl'): + ... if 'EST' in line or 'EDT' in line: # look for Eastern Time + ... print line + + <BR>Nov. 25, 09:43:32 PM EST + + >>> import smtplib + >>> server = smtplib.SMTP('localhost') + >>> server.sendmail('soothsayer@example.org', 'jcaesar@example.org', + """To: jcaesar@example.org + From: soothsayer@example.org + + Beware the Ides of March. + """) + >>> server.quit() + + +.. _tut-dates-and-times: + +Dates and Times +=============== + +The :mod:`datetime` module supplies classes for manipulating dates and times in +both simple and complex ways. While date and time arithmetic is supported, the +focus of the implementation is on efficient member extraction for output +formatting and manipulation. The module also supports objects that are timezone +aware. :: + + # dates are easily constructed and formatted + >>> from datetime import date + >>> now = date.today() + >>> now + datetime.date(2003, 12, 2) + >>> now.strftime("%m-%d-%y. %d %b %Y is a %A on the %d day of %B.") + '12-02-03. 02 Dec 2003 is a Tuesday on the 02 day of December.' + + # dates support calendar arithmetic + >>> birthday = date(1964, 7, 31) + >>> age = now - birthday + >>> age.days + 14368 + + +.. _tut-data-compression: + +Data Compression +================ + +Common data archiving and compression formats are directly supported by modules +including: :mod:`zlib`, :mod:`gzip`, :mod:`bz2`, :mod:`zipfile` and +:mod:`tarfile`. :: + + >>> import zlib + >>> s = 'witch which has which witches wrist watch' + >>> len(s) + 41 + >>> t = zlib.compress(s) + >>> len(t) + 37 + >>> zlib.decompress(t) + 'witch which has which witches wrist watch' + >>> zlib.crc32(s) + 226805979 + + +.. _tut-performance-measurement: + +Performance Measurement +======================= + +Some Python users develop a deep interest in knowing the relative performance of +different approaches to the same problem. Python provides a measurement tool +that answers those questions immediately. + +For example, it may be tempting to use the tuple packing and unpacking feature +instead of the traditional approach to swapping arguments. The :mod:`timeit` +module quickly demonstrates a modest performance advantage:: + + >>> from timeit import Timer + >>> Timer('t=a; a=b; b=t', 'a=1; b=2').timeit() + 0.57535828626024577 + >>> Timer('a,b = b,a', 'a=1; b=2').timeit() + 0.54962537085770791 + +In contrast to :mod:`timeit`'s fine level of granularity, the :mod:`profile` and +:mod:`pstats` modules provide tools for identifying time critical sections in +larger blocks of code. + + +.. _tut-quality-control: + +Quality Control +=============== + +One approach for developing high quality software is to write tests for each +function as it is developed and to run those tests frequently during the +development process. + +The :mod:`doctest` module provides a tool for scanning a module and validating +tests embedded in a program's docstrings. Test construction is as simple as +cutting-and-pasting a typical call along with its results into the docstring. +This improves the documentation by providing the user with an example and it +allows the doctest module to make sure the code remains true to the +documentation:: + + def average(values): + """Computes the arithmetic mean of a list of numbers. + + >>> print average([20, 30, 70]) + 40.0 + """ + return sum(values, 0.0) / len(values) + + import doctest + doctest.testmod() # automatically validate the embedded tests + +The :mod:`unittest` module is not as effortless as the :mod:`doctest` module, +but it allows a more comprehensive set of tests to be maintained in a separate +file:: + + import unittest + + class TestStatisticalFunctions(unittest.TestCase): + + def test_average(self): + self.assertEqual(average([20, 30, 70]), 40.0) + self.assertEqual(round(average([1, 5, 7]), 1), 4.3) + self.assertRaises(ZeroDivisionError, average, []) + self.assertRaises(TypeError, average, 20, 30, 70) + + unittest.main() # Calling from the command line invokes all tests + + +.. _tut-batteries-included: + +Batteries Included +================== + +Python has a "batteries included" philosophy. This is best seen through the +sophisticated and robust capabilities of its larger packages. For example: + +* The :mod:`xmlrpclib` and :mod:`SimpleXMLRPCServer` modules make implementing + remote procedure calls into an almost trivial task. Despite the modules + names, no direct knowledge or handling of XML is needed. + +* The :mod:`email` package is a library for managing email messages, including + MIME and other RFC 2822-based message documents. Unlike :mod:`smtplib` and + :mod:`poplib` which actually send and receive messages, the email package has + a complete toolset for building or decoding complex message structures + (including attachments) and for implementing internet encoding and header + protocols. + +* The :mod:`xml.dom` and :mod:`xml.sax` packages provide robust support for + parsing this popular data interchange format. Likewise, the :mod:`csv` module + supports direct reads and writes in a common database format. Together, these + modules and packages greatly simplify data interchange between python + applications and other tools. + +* Internationalization is supported by a number of modules including + :mod:`gettext`, :mod:`locale`, and the :mod:`codecs` package. + + diff --git a/Doc/tutorial/stdlib2.rst b/Doc/tutorial/stdlib2.rst new file mode 100644 index 0000000..0ce2757 --- /dev/null +++ b/Doc/tutorial/stdlib2.rst @@ -0,0 +1,394 @@ +.. _tut-brieftourtwo: + +********************************************* +Brief Tour of the Standard Library -- Part II +********************************************* + +This second tour covers more advanced modules that support professional +programming needs. These modules rarely occur in small scripts. + + +.. _tut-output-formatting: + +Output Formatting +================= + +The :mod:`repr` module provides a version of :func:`repr` customized for +abbreviated displays of large or deeply nested containers:: + + >>> import repr + >>> repr.repr(set('supercalifragilisticexpialidocious')) + "set(['a', 'c', 'd', 'e', 'f', 'g', ...])" + +The :mod:`pprint` module offers more sophisticated control over printing both +built-in and user defined objects in a way that is readable by the interpreter. +When the result is longer than one line, the "pretty printer" adds line breaks +and indentation to more clearly reveal data structure:: + + >>> import pprint + >>> t = [[[['black', 'cyan'], 'white', ['green', 'red']], [['magenta', + ... 'yellow'], 'blue']]] + ... + >>> pprint.pprint(t, width=30) + [[[['black', 'cyan'], + 'white', + ['green', 'red']], + [['magenta', 'yellow'], + 'blue']]] + +The :mod:`textwrap` module formats paragraphs of text to fit a given screen +width:: + + >>> import textwrap + >>> doc = """The wrap() method is just like fill() except that it returns + ... a list of strings instead of one big string with newlines to separate + ... the wrapped lines.""" + ... + >>> print textwrap.fill(doc, width=40) + The wrap() method is just like fill() + except that it returns a list of strings + instead of one big string with newlines + to separate the wrapped lines. + +The :mod:`locale` module accesses a database of culture specific data formats. +The grouping attribute of locale's format function provides a direct way of +formatting numbers with group separators:: + + >>> import locale + >>> locale.setlocale(locale.LC_ALL, 'English_United States.1252') + 'English_United States.1252' + >>> conv = locale.localeconv() # get a mapping of conventions + >>> x = 1234567.8 + >>> locale.format("%d", x, grouping=True) + '1,234,567' + >>> locale.format("%s%.*f", (conv['currency_symbol'], + ... conv['frac_digits'], x), grouping=True) + '$1,234,567.80' + + +.. _tut-templating: + +Templating +========== + +The :mod:`string` module includes a versatile :class:`Template` class with a +simplified syntax suitable for editing by end-users. This allows users to +customize their applications without having to alter the application. + +The format uses placeholder names formed by ``$`` with valid Python identifiers +(alphanumeric characters and underscores). Surrounding the placeholder with +braces allows it to be followed by more alphanumeric letters with no intervening +spaces. Writing ``$$`` creates a single escaped ``$``:: + + >>> from string import Template + >>> t = Template('${village}folk send $$10 to $cause.') + >>> t.substitute(village='Nottingham', cause='the ditch fund') + 'Nottinghamfolk send $10 to the ditch fund.' + +The :meth:`substitute` method raises a :exc:`KeyError` when a placeholder is not +supplied in a dictionary or a keyword argument. For mail-merge style +applications, user supplied data may be incomplete and the +:meth:`safe_substitute` method may be more appropriate --- it will leave +placeholders unchanged if data is missing:: + + >>> t = Template('Return the $item to $owner.') + >>> d = dict(item='unladen swallow') + >>> t.substitute(d) + Traceback (most recent call last): + . . . + KeyError: 'owner' + >>> t.safe_substitute(d) + 'Return the unladen swallow to $owner.' + +Template subclasses can specify a custom delimiter. For example, a batch +renaming utility for a photo browser may elect to use percent signs for +placeholders such as the current date, image sequence number, or file format:: + + >>> import time, os.path, sys + >>> def raw_input(prompt): + ... sys.stdout.write(prompt) + ... sys.stdout.flush() + ... return sys.stdin.readline() + ... + >>> photofiles = ['img_1074.jpg', 'img_1076.jpg', 'img_1077.jpg'] + >>> class BatchRename(Template): + ... delimiter = '%' + >>> fmt = raw_input('Enter rename style (%d-date %n-seqnum %f-format): ') + Enter rename style (%d-date %n-seqnum %f-format): Ashley_%n%f + + >>> t = BatchRename(fmt) + >>> date = time.strftime('%d%b%y') + >>> for i, filename in enumerate(photofiles): + ... base, ext = os.path.splitext(filename) + ... newname = t.substitute(d=date, n=i, f=ext) + ... print '%s --> %s' % (filename, newname) + + img_1074.jpg --> Ashley_0.jpg + img_1076.jpg --> Ashley_1.jpg + img_1077.jpg --> Ashley_2.jpg + +Another application for templating is separating program logic from the details +of multiple output formats. This makes it possible to substitute custom +templates for XML files, plain text reports, and HTML web reports. + + +.. _tut-binary-formats: + +Working with Binary Data Record Layouts +======================================= + +The :mod:`struct` module provides :func:`pack` and :func:`unpack` functions for +working with variable length binary record formats. The following example shows +how to loop through header information in a ZIP file (with pack codes ``"H"`` +and ``"L"`` representing two and four byte unsigned numbers respectively):: + + import struct + + data = open('myfile.zip', 'rb').read() + start = 0 + for i in range(3): # show the first 3 file headers + start += 14 + fields = struct.unpack('LLLHH', data[start:start+16]) + crc32, comp_size, uncomp_size, filenamesize, extra_size = fields + + start += 16 + filename = data[start:start+filenamesize] + start += filenamesize + extra = data[start:start+extra_size] + print filename, hex(crc32), comp_size, uncomp_size + + start += extra_size + comp_size # skip to the next header + + +.. _tut-multi-threading: + +Multi-threading +=============== + +Threading is a technique for decoupling tasks which are not sequentially +dependent. Threads can be used to improve the responsiveness of applications +that accept user input while other tasks run in the background. A related use +case is running I/O in parallel with computations in another thread. + +The following code shows how the high level :mod:`threading` module can run +tasks in background while the main program continues to run:: + + import threading, zipfile + + class AsyncZip(threading.Thread): + def __init__(self, infile, outfile): + threading.Thread.__init__(self) + self.infile = infile + self.outfile = outfile + def run(self): + f = zipfile.ZipFile(self.outfile, 'w', zipfile.ZIP_DEFLATED) + f.write(self.infile) + f.close() + print 'Finished background zip of: ', self.infile + + background = AsyncZip('mydata.txt', 'myarchive.zip') + background.start() + print 'The main program continues to run in foreground.' + + background.join() # Wait for the background task to finish + print 'Main program waited until background was done.' + +The principal challenge of multi-threaded applications is coordinating threads +that share data or other resources. To that end, the threading module provides +a number of synchronization primitives including locks, events, condition +variables, and semaphores. + +While those tools are powerful, minor design errors can result in problems that +are difficult to reproduce. So, the preferred approach to task coordination is +to concentrate all access to a resource in a single thread and then use the +:mod:`Queue` module to feed that thread with requests from other threads. +Applications using :class:`Queue` objects for inter-thread communication and +coordination are easier to design, more readable, and more reliable. + + +.. _tut-logging: + +Logging +======= + +The :mod:`logging` module offers a full featured and flexible logging system. +At its simplest, log messages are sent to a file or to ``sys.stderr``:: + + import logging + logging.debug('Debugging information') + logging.info('Informational message') + logging.warning('Warning:config file %s not found', 'server.conf') + logging.error('Error occurred') + logging.critical('Critical error -- shutting down') + +This produces the following output:: + + WARNING:root:Warning:config file server.conf not found + ERROR:root:Error occurred + CRITICAL:root:Critical error -- shutting down + +By default, informational and debugging messages are suppressed and the output +is sent to standard error. Other output options include routing messages +through email, datagrams, sockets, or to an HTTP Server. New filters can select +different routing based on message priority: :const:`DEBUG`, :const:`INFO`, +:const:`WARNING`, :const:`ERROR`, and :const:`CRITICAL`. + +The logging system can be configured directly from Python or can be loaded from +a user editable configuration file for customized logging without altering the +application. + + +.. _tut-weak-references: + +Weak References +=============== + +Python does automatic memory management (reference counting for most objects and +garbage collection to eliminate cycles). The memory is freed shortly after the +last reference to it has been eliminated. + +This approach works fine for most applications but occasionally there is a need +to track objects only as long as they are being used by something else. +Unfortunately, just tracking them creates a reference that makes them permanent. +The :mod:`weakref` module provides tools for tracking objects without creating a +reference. When the object is no longer needed, it is automatically removed +from a weakref table and a callback is triggered for weakref objects. Typical +applications include caching objects that are expensive to create:: + + >>> import weakref, gc + >>> class A: + ... def __init__(self, value): + ... self.value = value + ... def __repr__(self): + ... return str(self.value) + ... + >>> a = A(10) # create a reference + >>> d = weakref.WeakValueDictionary() + >>> d['primary'] = a # does not create a reference + >>> d['primary'] # fetch the object if it is still alive + 10 + >>> del a # remove the one reference + >>> gc.collect() # run garbage collection right away + 0 + >>> d['primary'] # entry was automatically removed + Traceback (most recent call last): + File "<pyshell#108>", line 1, in -toplevel- + d['primary'] # entry was automatically removed + File "C:/python30/lib/weakref.py", line 46, in __getitem__ + o = self.data[key]() + KeyError: 'primary' + + +.. _tut-list-tools: + +Tools for Working with Lists +============================ + +Many data structure needs can be met with the built-in list type. However, +sometimes there is a need for alternative implementations with different +performance trade-offs. + +The :mod:`array` module provides an :class:`array()` object that is like a list +that stores only homogenous data and stores it more compactly. The following +example shows an array of numbers stored as two byte unsigned binary numbers +(typecode ``"H"``) rather than the usual 16 bytes per entry for regular lists of +python int objects:: + + >>> from array import array + >>> a = array('H', [4000, 10, 700, 22222]) + >>> sum(a) + 26932 + >>> a[1:3] + array('H', [10, 700]) + +The :mod:`collections` module provides a :class:`deque()` object that is like a +list with faster appends and pops from the left side but slower lookups in the +middle. These objects are well suited for implementing queues and breadth first +tree searches:: + + >>> from collections import deque + >>> d = deque(["task1", "task2", "task3"]) + >>> d.append("task4") + >>> print "Handling", d.popleft() + Handling task1 + + unsearched = deque([starting_node]) + def breadth_first_search(unsearched): + node = unsearched.popleft() + for m in gen_moves(node): + if is_goal(m): + return m + unsearched.append(m) + +In addition to alternative list implementations, the library also offers other +tools such as the :mod:`bisect` module with functions for manipulating sorted +lists:: + + >>> import bisect + >>> scores = [(100, 'perl'), (200, 'tcl'), (400, 'lua'), (500, 'python')] + >>> bisect.insort(scores, (300, 'ruby')) + >>> scores + [(100, 'perl'), (200, 'tcl'), (300, 'ruby'), (400, 'lua'), (500, 'python')] + +The :mod:`heapq` module provides functions for implementing heaps based on +regular lists. The lowest valued entry is always kept at position zero. This +is useful for applications which repeatedly access the smallest element but do +not want to run a full list sort:: + + >>> from heapq import heapify, heappop, heappush + >>> data = [1, 3, 5, 7, 9, 2, 4, 6, 8, 0] + >>> heapify(data) # rearrange the list into heap order + >>> heappush(data, -5) # add a new entry + >>> [heappop(data) for i in range(3)] # fetch the three smallest entries + [-5, 0, 1] + + +.. _tut-decimal-fp: + +Decimal Floating Point Arithmetic +================================= + +The :mod:`decimal` module offers a :class:`Decimal` datatype for decimal +floating point arithmetic. Compared to the built-in :class:`float` +implementation of binary floating point, the new class is especially helpful for +financial applications and other uses which require exact decimal +representation, control over precision, control over rounding to meet legal or +regulatory requirements, tracking of significant decimal places, or for +applications where the user expects the results to match calculations done by +hand. + +For example, calculating a 5% tax on a 70 cent phone charge gives different +results in decimal floating point and binary floating point. The difference +becomes significant if the results are rounded to the nearest cent:: + + >>> from decimal import * + >>> Decimal('0.70') * Decimal('1.05') + Decimal("0.7350") + >>> .70 * 1.05 + 0.73499999999999999 + +The :class:`Decimal` result keeps a trailing zero, automatically inferring four +place significance from multiplicands with two place significance. Decimal +reproduces mathematics as done by hand and avoids issues that can arise when +binary floating point cannot exactly represent decimal quantities. + +Exact representation enables the :class:`Decimal` class to perform modulo +calculations and equality tests that are unsuitable for binary floating point:: + + >>> Decimal('1.00') % Decimal('.10') + Decimal("0.00") + >>> 1.00 % 0.10 + 0.09999999999999995 + + >>> sum([Decimal('0.1')]*10) == Decimal('1.0') + True + >>> sum([0.1]*10) == 1.0 + False + +The :mod:`decimal` module provides arithmetic with as much precision as needed:: + + >>> getcontext().prec = 36 + >>> Decimal(1) / Decimal(7) + Decimal("0.142857142857142857142857142857142857") + + diff --git a/Doc/tutorial/whatnow.rst b/Doc/tutorial/whatnow.rst new file mode 100644 index 0000000..599fcbd --- /dev/null +++ b/Doc/tutorial/whatnow.rst @@ -0,0 +1,68 @@ +.. _tut-whatnow: + +********* +What Now? +********* + +Reading this tutorial has probably reinforced your interest in using Python --- +you should be eager to apply Python to solving your real-world problems. Where +should you go to learn more? + +This tutorial is part of Python's documentation set. Some other documents in +the set are: + +* :ref:`library-index`: + + You should browse through this manual, which gives complete (though terse) + reference material about types, functions, and the modules in the standard + library. The standard Python distribution includes a *lot* of additional code. + There are modules to read Unix mailboxes, retrieve documents via HTTP, generate + random numbers, parse command-line options, write CGI programs, compress data, + and many other tasks. Skimming through the Library Reference will give you an + idea of what's available. + +* :ref:`install-index` explains how to install external modules written by other + Python users. + +* :ref:`reference-index`: A detailed explanation of Python's syntax and + semantics. It's heavy reading, but is useful as a complete guide to the + language itself. + +More Python resources: + +* http://www.python.org: The major Python Web site. It contains code, + documentation, and pointers to Python-related pages around the Web. This Web + site is mirrored in various places around the world, such as Europe, Japan, and + Australia; a mirror may be faster than the main site, depending on your + geographical location. + +* http://docs.python.org: Fast access to Python's documentation. + +* http://cheeseshop.python.org: The Python Package Index, nicknamed the Cheese + Shop, is an index of user-created Python modules that are available for + download. Once you begin releasing code, you can register it here so that + others can find it. + +* http://aspn.activestate.com/ASPN/Python/Cookbook/: The Python Cookbook is a + sizable collection of code examples, larger modules, and useful scripts. + Particularly notable contributions are collected in a book also titled Python + Cookbook (O'Reilly & Associates, ISBN 0-596-00797-3.) + +For Python-related questions and problem reports, you can post to the newsgroup +:newsgroup:`comp.lang.python`, or send them to the mailing list at +python-list@python.org. The newsgroup and mailing list are gatewayed, so +messages posted to one will automatically be forwarded to the other. There are +around 120 postings a day (with peaks up to several hundred), asking (and +answering) questions, suggesting new features, and announcing new modules. +Before posting, be sure to check the list of `Frequently Asked Questions +<http://www.python.org/doc/faq/>`_ (also called the FAQ), or look for it in the +:file:`Misc/` directory of the Python source distribution. Mailing list +archives are available at http://mail.python.org/pipermail/. The FAQ answers +many of the questions that come up again and again, and may already contain the +solution for your problem. + +.. % Postings figure based on average of last six months activity as +.. % reported by www.egroups.com; Jan. 2000 - June 2000: 21272 msgs / 182 +.. % days = 116.9 msgs / day and steadily increasing. + + |