diff options
| -rw-r--r-- | Doc/howto/descriptor.rst | 24 | ||||
| -rw-r--r-- | Doc/library/copyreg.rst | 2 | ||||
| -rw-r--r-- | Doc/library/functools.rst | 2 |
3 files changed, 14 insertions, 14 deletions
diff --git a/Doc/howto/descriptor.rst b/Doc/howto/descriptor.rst index b29e590..324625d 100644 --- a/Doc/howto/descriptor.rst +++ b/Doc/howto/descriptor.rst @@ -145,7 +145,7 @@ print a message for each get or set. Overriding :meth:`__getattribute__` is alternate approach that could do this for every attribute. However, this descriptor is useful for monitoring just a few chosen attributes:: - class RevealAccess(object): + class RevealAccess: """A data descriptor that sets and returns values normally and prints a message logging their access. """ @@ -162,7 +162,7 @@ descriptor is useful for monitoring just a few chosen attributes:: print('Updating', self.name) self.val = val - >>> class MyClass(object): + >>> class MyClass: ... x = RevealAccess(10, 'var "x"') ... y = 5 ... @@ -194,7 +194,7 @@ triggers function calls upon access to an attribute. Its signature is:: The documentation shows a typical use to define a managed attribute ``x``:: - class C(object): + class C: def getx(self): return self.__x def setx(self, value): self.__x = value def delx(self): del self.__x @@ -203,7 +203,7 @@ The documentation shows a typical use to define a managed attribute ``x``:: To see how :func:`property` is implemented in terms of the descriptor protocol, here is a pure Python equivalent:: - class Property(object): + class Property: "Emulate PyProperty_Type() in Objects/descrobject.c" def __init__(self, fget=None, fset=None, fdel=None, doc=None): @@ -250,7 +250,7 @@ to be recalculated on every access; however, the programmer does not want to affect existing client code accessing the attribute directly. The solution is to wrap access to the value attribute in a property data descriptor:: - class Cell(object): + class Cell: . . . def getvalue(self): "Recalculate the cell before returning value" @@ -277,7 +277,7 @@ binding methods during attribute access. This means that all functions are non-data descriptors which return bound methods when they are invoked from an object. In pure Python, it works like this:: - class Function(object): + class Function: . . . def __get__(self, obj, objtype=None): "Simulate func_descr_get() in Objects/funcobject.c" @@ -287,7 +287,7 @@ object. In pure Python, it works like this:: Running the interpreter shows how the function descriptor works in practice:: - >>> class D(object): + >>> class D: ... def f(self, x): ... return x ... @@ -367,7 +367,7 @@ It can be called either from an object or the class: ``s.erf(1.5) --> .9332`` o Since staticmethods return the underlying function with no changes, the example calls are unexciting:: - >>> class E(object): + >>> class E: ... def f(x): ... print(x) ... f = staticmethod(f) @@ -380,7 +380,7 @@ calls are unexciting:: Using the non-data descriptor protocol, a pure Python version of :func:`staticmethod` would look like this:: - class StaticMethod(object): + class StaticMethod: "Emulate PyStaticMethod_Type() in Objects/funcobject.c" def __init__(self, f): @@ -393,7 +393,7 @@ Unlike static methods, class methods prepend the class reference to the argument list before calling the function. This format is the same for whether the caller is an object or a class:: - >>> class E(object): + >>> class E: ... def f(klass, x): ... return klass.__name__, x ... f = classmethod(f) @@ -410,7 +410,7 @@ is to create alternate class constructors. In Python 2.3, the classmethod :func:`dict.fromkeys` creates a new dictionary from a list of keys. The pure Python equivalent is:: - class Dict(object): + class Dict: . . . def fromkeys(klass, iterable, value=None): "Emulate dict_fromkeys() in Objects/dictobject.c" @@ -428,7 +428,7 @@ Now a new dictionary of unique keys can be constructed like this:: Using the non-data descriptor protocol, a pure Python version of :func:`classmethod` would look like this:: - class ClassMethod(object): + class ClassMethod: "Emulate PyClassMethod_Type() in Objects/funcobject.c" def __init__(self, f): diff --git a/Doc/library/copyreg.rst b/Doc/library/copyreg.rst index 40fca56..4392021 100644 --- a/Doc/library/copyreg.rst +++ b/Doc/library/copyreg.rst @@ -49,7 +49,7 @@ The example below would like to show how to register a pickle function and how it will be used: >>> import copyreg, copy, pickle - >>> class C(object): + >>> class C: ... def __init__(self, a): ... self.a = a ... diff --git a/Doc/library/functools.rst b/Doc/library/functools.rst index 3a0b554..d3debac 100644 --- a/Doc/library/functools.rst +++ b/Doc/library/functools.rst @@ -275,7 +275,7 @@ The :mod:`functools` module defines the following functions: Example:: - >>> class Cell(object): + >>> class Cell: ... def __init__(self): ... self._alive = False ... @property |