Lines Matching refs:guarantees
21 guarantees
25 'customization': '\nBasic customization\n*******************\n\nobject.__new__(cls[, ...])\n\n Called to create a new instance of class *cls*. ``__new__()`` is a\n static method (special-cased so you need not declare it as such)\n that takes the class of which an instance was requested as its\n first argument. The remaining arguments are those passed to the\n object constructor expression (the call to the class). The return\n value of ``__new__()`` should be the new object instance (usually\n an instance of *cls*).\n\n Typical implementations create a new instance of the class by\n invoking the superclass\'s ``__new__()`` method using\n ``super(currentclass, cls).__new__(cls[, ...])`` with appropriate\n arguments and then modifying the newly-created instance as\n necessary before returning it.\n\n If ``__new__()`` returns an instance of *cls*, then the new\n instance\'s ``__init__()`` method will be invoked like\n ``__init__(self[, ...])``, where *self* is the new instance and the\n remaining arguments are the same as were passed to ``__new__()``.\n\n If ``__new__()`` does not return an instance of *cls*, then the new\n instance\'s ``__init__()`` method will not be invoked.\n\n ``__new__()`` is intended mainly to allow subclasses of immutable\n types (like int, str, or tuple) to customize instance creation. It\n is also commonly overridden in custom metaclasses in order to\n customize class creation.\n\nobject.__init__(self[, ...])\n\n Called when the instance is created. The arguments are those\n passed to the class constructor expression. If a base class has an\n ``__init__()`` method, the derived class\'s ``__init__()`` method,\n if any, must explicitly call it to ensure proper initialization of\n the base class part of the instance; for example:\n ``BaseClass.__init__(self, [args...])``. As a special constraint\n on constructors, no value may be returned; doing so will cause a\n ``TypeError`` to be raised at runtime.\n\nobject.__del__(self)\n\n Called when the instance is about to be destroyed. This is also\n called a destructor. If a base class has a ``__del__()`` method,\n the derived class\'s ``__del__()`` method, if any, must explicitly\n call it to ensure proper deletion of the base class part of the\n instance. Note that it is possible (though not recommended!) for\n the ``__del__()`` method to postpone destruction of the instance by\n creating a new reference to it. It may then be called at a later\n time when this new reference is deleted. It is not guaranteed that\n ``__del__()`` methods are called for objects that still exist when\n the interpreter exits.\n\n Note: ``del x`` doesn\'t directly call ``x.__del__()`` --- the former\n decrements the reference count for ``x`` by one, and the latter\n is only called when ``x``\'s reference count reaches zero. Some\n common situations that may prevent the reference count of an\n object from going to zero include: circular references between\n objects (e.g., a doubly-linked list or a tree data structure with\n parent and child pointers); a reference to the object on the\n stack frame of a function that caught an exception (the traceback\n stored in ``sys.exc_traceback`` keeps the stack frame alive); or\n a reference to the object on the stack frame that raised an\n unhandled exception in interactive mode (the traceback stored in\n ``sys.last_traceback`` keeps the stack frame alive). The first\n situation can only be remedied by explicitly breaking the cycles;\n the latter two situations can be resolved by storing ``None`` in\n ``sys.exc_traceback`` or ``sys.last_traceback``. Circular\n references which are garbage are detected when the option cycle\n detector is enabled (it\'s on by default), but can only be cleaned\n up if there are no Python-level ``__del__()`` methods involved.\n Refer to the documentation for the ``gc`` module for more\n information about how ``__del__()`` methods are handled by the\n cycle detector, particularly the description of the ``garbage``\n value.\n\n Warning: Due to the precarious circumstances under which ``__del__()``\n methods are invoked, exceptions that occur during their execution\n are ignored, and a warning is printed to ``sys.stderr`` instead.\n Also, when ``__del__()`` is invoked in response to a module being\n deleted (e.g., when execution of the program is done), other\n globals referenced by the ``__del__()`` method may already have\n been deleted or in the process of being torn down (e.g. the\n import machinery shutting down). For this reason, ``__del__()``\n methods should do the absolute minimum needed to maintain\n external invariants. Starting with version 1.5, Python\n guarantees
61 guarantees
72 guarantees not to change the\n relative order of elements that compare equal --- this is helpful\n for sorting in multiple passes (for example, sort by department,\n then by salary grade).\n\n10. **CPython implementation detail:** While a list is being sorted,\n the effect of attempting to mutate, or even inspect, the list is\n undefined. The C implementation of Python 2.3 and newer makes the\n list appear empty for the duration, and raises ``ValueError`` if\n it can detect that the list has been mutated during a sort.\n',
73 'typesseq-mutable': "\nMutable Sequence Types\n**********************\n\nList and ``bytearray`` objects support additional operations that\nallow in-place modification of the object. Other mutable sequence\ntypes (when added to the language) should also support these\noperations. Strings and tuples are immutable sequence types: such\nobjects cannot be modified once created. The following operations are\ndefined on mutable sequence types (where *x* is an arbitrary object):\n\n+--------------------------------+----------------------------------+-----------------------+\n| Operation | Result | Notes |\n+================================+==================================+=======================+\n| ``s[i] = x`` | item *i* of *s* is replaced by | |\n| | *x* | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s[i:j] = t`` | slice of *s* from *i* to *j* is | |\n| | replaced by the contents of the | |\n| | iterable *t* | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``del s[i:j]`` | same as ``s[i:j] = []`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s[i:j:k] = t`` | the elements of ``s[i:j:k]`` are | (1) |\n| | replaced by those of *t* | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``del s[i:j:k]`` | removes the elements of | |\n| | ``s[i:j:k]`` from the list | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.append(x)`` | same as ``s[len(s):len(s)] = | (2) |\n| | [x]`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.extend(x)`` | same as ``s[len(s):len(s)] = x`` | (3) |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.count(x)`` | return number of *i*'s for which | |\n| | ``s[i] == x`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.index(x[, i[, j]])`` | return smallest *k* such that | (4) |\n| | ``s[k] == x`` and ``i <= k < j`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.insert(i, x)`` | same as ``s[i:i] = [x]`` | (5) |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.pop([i])`` | same as ``x = s[i]; del s[i]; | (6) |\n| | return x`` | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.remove(x)`` | same as ``del s[s.index(x)]`` | (4) |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.reverse()`` | reverses the items of *s* in | (7) |\n| | place | |\n+--------------------------------+----------------------------------+-----------------------+\n| ``s.sort([cmp[, key[, | sort the items of *s* in place | (7)(8)(9)(10) |\n| reverse]]])`` | | |\n+--------------------------------+----------------------------------+-----------------------+\n\nNotes:\n\n1. *t* must have the same length as the slice it is replacing.\n\n2. The C implementation of Python has historically accepted multiple\n parameters and implicitly joined them into a tuple; this no longer\n works in Python 2.0. Use of this misfeature has been deprecated\n since Python 1.4.\n\n3. *x* can be any iterable object.\n\n4. Raises ``ValueError`` when *x* is not found in *s*. When a negative\n index is passed as the second or third parameter to the ``index()``\n method, the list length is added, as for slice indices. If it is\n still negative, it is truncated to zero, as for slice indices.\n\n Changed in version 2.3: Previously, ``index()`` didn't have\n arguments for specifying start and stop positions.\n\n5. When a negative index is passed as the first parameter to the\n ``insert()`` method, the list length is added, as for slice\n indices. If it is still negative, it is truncated to zero, as for\n slice indices.\n\n Changed in version 2.3: Previously, all negative indices were\n truncated to zero.\n\n6. The ``pop()`` method is only supported by the list and array types.\n The optional argument *i* defaults to ``-1``, so that by default\n the last item is removed and returned.\n\n7. The ``sort()`` and ``reverse()`` methods modify the list in place\n for economy of space when sorting or reversing a large list. To\n remind you that they operate by side effect, they don't return the\n sorted or reversed list.\n\n8. The ``sort()`` method takes optional arguments for controlling the\n comparisons.\n\n *cmp* specifies a custom comparison function of two arguments (list\n items) which should return a negative, zero or positive number\n depending on whether the first argument is considered smaller than,\n equal to, or larger than the second argument: ``cmp=lambda x,y:\n cmp(x.lower(), y.lower())``. The default value is ``None``.\n\n *key* specifies a function of one argument that is used to extract\n a comparison key from each list element: ``key=str.lower``. The\n default value is ``None``.\n\n *reverse* is a boolean value. If set to ``True``, then the list\n elements are sorted as if each comparison were reversed.\n\n In general, the *key* and *reverse* conversion processes are much\n faster than specifying an equivalent *cmp* function. This is\n because *cmp* is called multiple times for each list element while\n *key* and *reverse* touch each element only once. Use\n ``functools.cmp_to_key()`` to convert an old-style *cmp* function\n to a *key* function.\n\n Changed in version 2.3: Support for ``None`` as an equivalent to\n omitting *cmp* was added.\n\n Changed in version 2.4: Support for *key* and *reverse* was added.\n\n9. Starting with Python 2.3, the ``sort()`` method is guaranteed to be\n stable. A sort is stable if it guarantees not to change the\n relative order of elements that compare equal --- this is helpful\n for sorting in multiple passes (for example, sort by department,\n then by salary grade).\n\n10. **CPython implementation detail:** While a list is being sorted,\n the effect of attempting to mutate, or even inspect, the list is\n undefined. The C implementation of Python 2.3 and newer makes the\n list appear empty for the duration, and raises ``ValueError`` if\n it can detect that the list has been mutated during a sort.\n",
76 'with': '\nThe ``with`` statement\n**********************\n\nNew in version 2.5.\n\nThe ``with`` statement is used to wrap the execution of a block with\nmethods defined by a context manager (see section *With Statement\nContext Managers*). This allows common\n``try``...``except``...``finally`` usage patterns to be encapsulated\nfor convenient reuse.\n\n with_stmt ::= "with" with_item ("," with_item)* ":" suite\n with_item ::= expression ["as" target]\n\nThe execution of the ``with`` statement with one "item" proceeds as\nfollows:\n\n1. The context expression (the expression given in the ``with_item``)\n is evaluated to obtain a context manager.\n\n2. The context manager\'s ``__exit__()`` is loaded for later use.\n\n3. The context manager\'s ``__enter__()`` method is invoked.\n\n4. If a target was included in the ``with`` statement, the return\n value from ``__enter__()`` is assigned to it.\n\n Note: The ``with`` statement guarantees that if the ``__enter__()``\n method returns without an error, then ``__exit__()`` will always\n be called. Thus, if an error occurs during the assignment to the\n target list, it will be treated the same as an error occurring\n within the suite would be. See step 6 below.\n\n5. The suite is executed.\n\n6. The context manager\'s ``__exit__()`` method is invoked. If an\n exception caused the suite to be exited, its type, value, and\n traceback are passed as arguments to ``__exit__()``. Otherwise,\n three ``None`` arguments are supplied.\n\n If the suite was exited due to an exception, and the return value\n from the ``__exit__()`` method was false, the exception is\n reraised. If the return value was true, the exception is\n suppressed, and execution continues with the statement following\n the ``with`` statement.\n\n If the suite was exited for any reason other than an exception, the\n return value from ``__exit__()`` is ignored, and execution proceeds\n at the normal location for the kind of exit that was taken.\n\nWith more than one item, the context managers are processed as if\nmultiple ``with`` statements were nested:\n\n with A() as a, B() as b:\n suite\n\nis equivalent to\n\n with A() as a:\n with B() as b:\n suite\n\nNote: In Python 2.5, the ``with`` statement is only allowed when the\n ``with_statement`` feature has been enabled. It is always enabled\n in Python 2.6.\n\nChanged in version 2.7: Support for multiple context expressions.\n\nSee also:\n\n **PEP 0343** - The "with" statement\n The specification, background, and examples for the Python\n ``with`` statement.\n',
