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Data model

Objects, values and types

.. index::
   single: object
   single: data

:dfn:`Objects` are Python's abstraction for data. All data in a Python program is represented by objects or by relations between objects. (In a sense, and in conformance to Von Neumann's model of a "stored program computer," code is also represented by objects.)

.. index::
   builtin: id
   builtin: type
   single: identity of an object
   single: value of an object
   single: type of an object
   single: mutable object
   single: immutable object

Every object has an identity, a type and a value. An object's identity never changes once it has been created; you may think of it as the object's address in memory. The ':keyword:`is`' operator compares the identity of two objects; the :func:`id` function returns an integer representing its identity.

.. impl-detail::

   For CPython, ``id(x)`` is the memory address where ``x`` is stored.

An object's type determines the operations that the object supports (e.g., "does it have a length?") and also defines the possible values for objects of that type. The :func:`type` function returns an object's type (which is an object itself). Like its identity, an object's :dfn:`type` is also unchangeable. [1]

The value of some objects can change. Objects whose value can change are said to be mutable; objects whose value is unchangeable once they are created are called immutable. (The value of an immutable container object that contains a reference to a mutable object can change when the latter's value is changed; however the container is still considered immutable, because the collection of objects it contains cannot be changed. So, immutability is not strictly the same as having an unchangeable value, it is more subtle.) An object's mutability is determined by its type; for instance, numbers, strings and tuples are immutable, while dictionaries and lists are mutable.

.. index::
   single: garbage collection
   single: reference counting
   single: unreachable object

Objects are never explicitly destroyed; however, when they become unreachable they may be garbage-collected. An implementation is allowed to postpone garbage collection or omit it altogether --- it is a matter of implementation quality how garbage collection is implemented, as long as no objects are collected that are still reachable.

.. impl-detail::

   CPython currently uses a reference-counting scheme with (optional) delayed
   detection of cyclically linked garbage, which collects most objects as soon
   as they become unreachable, but is not guaranteed to collect garbage
   containing circular references.  See the documentation of the :mod:`gc`
   module for information on controlling the collection of cyclic garbage.
   Other implementations act differently and CPython may change.
   Do not depend on immediate finalization of objects when they become
   unreachable (so you should always close files explicitly).

Note that the use of the implementation's tracing or debugging facilities may keep objects alive that would normally be collectable. Also note that catching an exception with a ':keyword:`try`...:keyword:`except`' statement may keep objects alive.

Some objects contain references to "external" resources such as open files or windows. It is understood that these resources are freed when the object is garbage-collected, but since garbage collection is not guaranteed to happen, such objects also provide an explicit way to release the external resource, usually a :meth:`close` method. Programs are strongly recommended to explicitly close such objects. The ':keyword:`try`...:keyword:`finally`' statement and the ':keyword:`with`' statement provide convenient ways to do this.

.. index:: single: container

Some objects contain references to other objects; these are called containers. Examples of containers are tuples, lists and dictionaries. The references are part of a container's value. In most cases, when we talk about the value of a container, we imply the values, not the identities of the contained objects; however, when we talk about the mutability of a container, only the identities of the immediately contained objects are implied. So, if an immutable container (like a tuple) contains a reference to a mutable object, its value changes if that mutable object is changed.

Types affect almost all aspects of object behavior. Even the importance of object identity is affected in some sense: for immutable types, operations that compute new values may actually return a reference to any existing object with the same type and value, while for mutable objects this is not allowed. E.g., after a = 1; b = 1, a and b may or may not refer to the same object with the value one, depending on the implementation, but after c = []; d = [], c and d are guaranteed to refer to two different, unique, newly created empty lists. (Note that c = d = [] assigns the same object to both c and d.)

The standard type hierarchy

.. index::
   single: type
   pair: data; type
   pair: type; hierarchy
   pair: extension; module
   pair: C; language

Below is a list of the types that are built into Python. Extension modules (written in C, Java, or other languages, depending on the implementation) can define additional types. Future versions of Python may add types to the type hierarchy (e.g., rational numbers, efficiently stored arrays of integers, etc.), although such additions will often be provided via the standard library instead.

.. index::
   single: attribute
   pair: special; attribute
   triple: generic; special; attribute

Some of the type descriptions below contain a paragraph listing 'special attributes.' These are attributes that provide access to the implementation and are not intended for general use. Their definition may change in the future.

.. index:: object: None

This type has a single value. There is a single object with this value. This object is accessed through the built-in name None. It is used to signify the absence of a value in many situations, e.g., it is returned from functions that don't explicitly return anything. Its truth value is false.

.. index:: object: NotImplemented

This type has a single value. There is a single object with this value. This object is accessed through the built-in name NotImplemented. Numeric methods and rich comparison methods should return this value if they do not implement the operation for the operands provided. (The interpreter will then try the reflected operation, or some other fallback, depending on the operator.) Its truth value is true.

See :ref:`implementing-the-arithmetic-operations` for more details.

.. index::
   object: Ellipsis
   single: ...; ellipsis literal

This type has a single value. There is a single object with this value. This object is accessed through the literal ... or the built-in name Ellipsis. Its truth value is true.

.. index:: object: numeric

These are created by numeric literals and returned as results by arithmetic operators and arithmetic built-in functions. Numeric objects are immutable; once created their value never changes. Python numbers are of course strongly related to mathematical numbers, but subject to the limitations of numerical representation in computers.

Python distinguishes between integers, floating point numbers, and complex numbers:

.. index:: object: integer

These represent elements from the mathematical set of integers (positive and negative).

There are two types of integers:

Integers (:class:`int`)

These represent numbers in an unlimited range, subject to available (virtual) memory only. For the purpose of shift and mask operations, a binary representation is assumed, and negative numbers are represented in a variant of 2's complement which gives the illusion of an infinite string of sign bits extending to the left.
Booleans (:class:`bool`)
.. index::
   object: Boolean
   single: False
   single: True

These represent the truth values False and True. The two objects representing the values False and True are the only Boolean objects. The Boolean type is a subtype of the integer type, and Boolean values behave like the values 0 and 1, respectively, in almost all contexts, the exception being that when converted to a string, the strings "False" or "True" are returned, respectively.

.. index:: pair: integer; representation

The rules for integer representation are intended to give the most meaningful interpretation of shift and mask operations involving negative integers.

:class:`numbers.Real` (:class:`float`)
.. index::
   object: floating point
   pair: floating point; number
   pair: C; language
   pair: Java; language

These represent machine-level double precision floating point numbers. You are at the mercy of the underlying machine architecture (and C or Java implementation) for the accepted range and handling of overflow. Python does not support single-precision floating point numbers; the savings in processor and memory usage that are usually the reason for using these are dwarfed by the overhead of using objects in Python, so there is no reason to complicate the language with two kinds of floating point numbers.

:class:`numbers.Complex` (:class:`complex`)
.. index::
   object: complex
   pair: complex; number

These represent complex numbers as a pair of machine-level double precision floating point numbers. The same caveats apply as for floating point numbers. The real and imaginary parts of a complex number z can be retrieved through the read-only attributes z.real and z.imag.

.. index::
   builtin: len
   object: sequence
   single: index operation
   single: item selection
   single: subscription

These represent finite ordered sets indexed by non-negative numbers. The built-in function :func:`len` returns the number of items of a sequence. When the length of a sequence is n, the index set contains the numbers 0, 1, ..., n-1. Item i of sequence a is selected by a[i].

.. index:: single: slicing

Sequences also support slicing: a[i:j] selects all items with index k such that i <= k < j. When used as an expression, a slice is a sequence of the same type. This implies that the index set is renumbered so that it starts at 0.

Some sequences also support "extended slicing" with a third "step" parameter: a[i:j:k] selects all items of a with index x where x = i + n*k, n >= 0 and i <= x < j.

Sequences are distinguished according to their mutability:

Immutable sequences
.. index::
   object: immutable sequence
   object: immutable

An object of an immutable sequence type cannot change once it is created. (If the object contains references to other objects, these other objects may be mutable and may be changed; however, the collection of objects directly referenced by an immutable object cannot change.)

The following types are immutable sequences:

.. index::
   single: string; immutable sequences

.. index::
   builtin: chr
   builtin: ord
   single: character
   single: integer
   single: Unicode

A string is a sequence of values that represent Unicode code points. All the code points in the range U+0000 - U+10FFFF can be represented in a string. Python doesn't have a :c:type:`char` type; instead, every code point in the string is represented as a string object with length 1. The built-in function :func:`ord` converts a code point from its string form to an integer in the range 0 - 10FFFF; :func:`chr` converts an integer in the range 0 - 10FFFF to the corresponding length 1 string object. :meth:`str.encode` can be used to convert a :class:`str` to :class:`bytes` using the given text encoding, and :meth:`bytes.decode` can be used to achieve the opposite.

.. index::
   object: tuple
   pair: singleton; tuple
   pair: empty; tuple

The items of a tuple are arbitrary Python objects. Tuples of two or more items are formed by comma-separated lists of expressions. A tuple of one item (a 'singleton') can be formed by affixing a comma to an expression (an expression by itself does not create a tuple, since parentheses must be usable for grouping of expressions). An empty tuple can be formed by an empty pair of parentheses.

.. index:: bytes, byte

A bytes object is an immutable array. The items are 8-bit bytes, represented by integers in the range 0 <= x < 256. Bytes literals (like b'abc') and the built-in :func:`bytes()` constructor can be used to create bytes objects. Also, bytes objects can be decoded to strings via the :meth:`~bytes.decode` method.

Mutable sequences
.. index::
   object: mutable sequence
   object: mutable
   pair: assignment; statement
   single: subscription
   single: slicing

Mutable sequences can be changed after they are created. The subscription and slicing notations can be used as the target of assignment and :keyword:`del` (delete) statements.

There are currently two intrinsic mutable sequence types:

.. index:: object: list

The items of a list are arbitrary Python objects. Lists are formed by placing a comma-separated list of expressions in square brackets. (Note that there are no special cases needed to form lists of length 0 or 1.)

Byte Arrays
.. index:: bytearray

A bytearray object is a mutable array. They are created by the built-in :func:`bytearray` constructor. Aside from being mutable (and hence unhashable), byte arrays otherwise provide the same interface and functionality as immutable :class:`bytes` objects.

.. index:: module: array

The extension module :mod:`array` provides an additional example of a mutable sequence type, as does the :mod:`collections` module.

Set types
.. index::
   builtin: len
   object: set type

These represent unordered, finite sets of unique, immutable objects. As such, they cannot be indexed by any subscript. However, they can be iterated over, and the built-in function :func:`len` returns the number of items in a set. Common uses for sets are fast membership testing, removing duplicates from a sequence, and computing mathematical operations such as intersection, union, difference, and symmetric difference.

For set elements, the same immutability rules apply as for dictionary keys. Note that numeric types obey the normal rules for numeric comparison: if two numbers compare equal (e.g., 1 and 1.0), only one of them can be contained in a set.

There are currently two intrinsic set types:

.. index:: object: set

These represent a mutable set. They are created by the built-in :func:`set` constructor and can be modified afterwards by several methods, such as :meth:`~set.add`.

Frozen sets
.. index:: object: frozenset

These represent an immutable set. They are created by the built-in :func:`frozenset` constructor. As a frozenset is immutable and :term:`hashable`, it can be used again as an element of another set, or as a dictionary key.

.. index::
   builtin: len
   single: subscription
   object: mapping

These represent finite sets of objects indexed by arbitrary index sets. The subscript notation a[k] selects the item indexed by k from the mapping a; this can be used in expressions and as the target of assignments or :keyword:`del` statements. The built-in function :func:`len` returns the number of items in a mapping.

There is currently a single intrinsic mapping type:

.. index:: object: dictionary

These represent finite sets of objects indexed by nearly arbitrary values. The only types of values not acceptable as keys are values containing lists or dictionaries or other mutable types that are compared by value rather than by object identity, the reason being that the efficient implementation of dictionaries requires a key's hash value to remain constant. Numeric types used for keys obey the normal rules for numeric comparison: if two numbers compare equal (e.g., 1 and 1.0) then they can be used interchangeably to index the same dictionary entry.

Dictionaries are mutable; they can be created by the {...} notation (see section :ref:`dict`).

.. index::
   module: dbm.ndbm
   module: dbm.gnu

The extension modules :mod:`dbm.ndbm` and :mod:`dbm.gnu` provide additional examples of mapping types, as does the :mod:`collections` module.

Callable types
.. index::
   object: callable
   pair: function; call
   single: invocation
   pair: function; argument

These are the types to which the function call operation (see section :ref:`calls`) can be applied:

User-defined functions
.. index::
   pair: user-defined; function
   object: function
   object: user-defined function

A user-defined function object is created by a function definition (see section :ref:`function`). It should be called with an argument list containing the same number of items as the function's formal parameter list.

Special attributes:

.. tabularcolumns:: |l|L|l|

.. index::
   single: __doc__ (function attribute)
   single: __name__ (function attribute)
   single: __module__ (function attribute)
   single: __dict__ (function attribute)
   single: __defaults__ (function attribute)
   single: __closure__ (function attribute)
   single: __code__ (function attribute)
   single: __globals__ (function attribute)
   single: __annotations__ (function attribute)
   single: __kwdefaults__ (function attribute)
   pair: global; namespace

Attribute Meaning  
:attr:`__doc__` The function's documentation string, or None if unavailable; not inherited by subclasses. Writable
:attr:`~definition.\ __name__` The function's name. Writable
:attr:`~definition.\ __qualname__`

The function's :term:`qualified name`.

.. versionadded:: 3.3
:attr:`__module__` The name of the module the function was defined in, or None if unavailable. Writable
:attr:`__defaults__` A tuple containing default argument values for those arguments that have defaults, or None if no arguments have a default value. Writable
:attr:`__code__` The code object representing the compiled function body. Writable
:attr:`__globals__` A reference to the dictionary that holds the function's global variables --- the global namespace of the module in which the function was defined. Read-only
:attr:`~object.__dict__` The namespace supporting arbitrary function attributes. Writable
:attr:`__closure__` None or a tuple of cells that contain bindings for the function's free variables. See below for information on the cell_contents attribute. Read-only
:attr:`__annotations__` A dict containing annotations of parameters. The keys of the dict are the parameter names, and 'return' for the return annotation, if provided. Writable
:attr:`__kwdefaults__` A dict containing defaults for keyword-only parameters. Writable

Most of the attributes labelled "Writable" check the type of the assigned value.

Function objects also support getting and setting arbitrary attributes, which can be used, for example, to attach metadata to functions. Regular attribute dot-notation is used to get and set such attributes. Note that the current implementation only supports function attributes on user-defined functions. Function attributes on built-in functions may be supported in the future.

A cell object has the attribute cell_contents. This can be used to get the value of the cell, as well as set the value.

Additional information about a function's definition can be retrieved from its code object; see the description of internal types below. The :data:`cell <types.CellType>` type can be accessed in the :mod:`types` module.

Instance methods
.. index::
   object: method
   object: user-defined method
   pair: user-defined; method

An instance method object combines a class, a class instance and any callable object (normally a user-defined function).

.. index::
   single: __func__ (method attribute)
   single: __self__ (method attribute)
   single: __doc__ (method attribute)
   single: __name__ (method attribute)
   single: __module__ (method attribute)

Special read-only attributes: :attr:`__self__` is the class instance object, :attr:`__func__` is the function object; :attr:`__doc__` is the method's documentation (same as __func__.__doc__); :attr:`~definition.__name__` is the method name (same as __func__.__name__); :attr:`__module__` is the name of the module the method was defined in, or None if unavailable.

Methods also support accessing (but not setting) the arbitrary function attributes on the underlying function object.

User-defined method objects may be created when getting an attribute of a class (perhaps via an instance of that class), if that attribute is a user-defined function object or a class method object.

When an instance method object is created by retrieving a user-defined function object from a class via one of its instances, its :attr:`__self__` attribute is the instance, and the method object is said to be bound. The new method's :attr:`__func__` attribute is the original function object.

When an instance method object is created by retrieving a class method object from a class or instance, its :attr:`__self__` attribute is the class itself, and its :attr:`__func__` attribute is the function object underlying the class method.

When an instance method object is called, the underlying function (:attr:`__func__`) is called, inserting the class instance (:attr:`__self__`) in front of the argument list. For instance, when :class:`C` is a class which contains a definition for a function :meth:`f`, and x is an instance of :class:`C`, calling x.f(1) is equivalent to calling C.f(x, 1).

When an instance method object is derived from a class method object, the "class instance" stored in :attr:`__self__` will actually be the class itself, so that calling either x.f(1) or C.f(1) is equivalent to calling f(C,1) where f is the underlying function.

Note that the transformation from function object to instance method object happens each time the attribute is retrieved from the instance. In some cases, a fruitful optimization is to assign the attribute to a local variable and call that local variable. Also notice that this transformation only happens for user-defined functions; other callable objects (and all non-callable objects) are retrieved without transformation. It is also important to note that user-defined functions which are attributes of a class instance are not converted to bound methods; this only happens when the function is an attribute of the class.

Generator functions
.. index::
   single: generator; function
   single: generator; iterator

A function or method which uses the :keyword:`yield` statement (see section :ref:`yield`) is called a :dfn:`generator function`. Such a function, when called, always returns an iterator object which can be used to execute the body of the function: calling the iterator's :meth:`iterator.__next__` method will cause the function to execute until it provides a value using the :keyword:`!yield` statement. When the function executes a :keyword:`return` statement or falls off the end, a :exc:`StopIteration` exception is raised and the iterator will have reached the end of the set of values to be returned.

Coroutine functions
.. index::
   single: coroutine; function

A function or method which is defined using :keyword:`async def` is called a :dfn:`coroutine function`. Such a function, when called, returns a :term:`coroutine` object. It may contain :keyword:`await` expressions, as well as :keyword:`async with` and :keyword:`async for` statements. See also the :ref:`coroutine-objects` section.

Asynchronous generator functions
.. index::
   single: asynchronous generator; function
   single: asynchronous generator; asynchronous iterator

A function or method which is defined using :keyword:`async def` and which uses the :keyword:`yield` statement is called a :dfn:`asynchronous generator function`. Such a function, when called, returns an asynchronous iterator object which can be used in an :keyword:`async for` statement to execute the body of the function.

Calling the asynchronous iterator's :meth:`aiterator.__anext__` method will return an :term:`awaitable` which when awaited will execute until it provides a value using the :keyword:`yield` expression. When the function executes an empty :keyword:`return` statement or falls off the end, a :exc:`StopAsyncIteration` exception is raised and the asynchronous iterator will have reached the end of the set of values to be yielded.

Built-in functions
.. index::
   object: built-in function
   object: function
   pair: C; language

A built-in function object is a wrapper around a C function. Examples of built-in functions are :func:`len` and :func:`math.sin` (:mod:`math` is a standard built-in module). The number and type of the arguments are determined by the C function. Special read-only attributes: :attr:`__doc__` is the function's documentation string, or None if unavailable; :attr:`~definition.__name__` is the function's name; :attr:`__self__` is set to None (but see the next item); :attr:`__module__` is the name of the module the function was defined in or None if unavailable.

Built-in methods
.. index::
   object: built-in method
   object: method
   pair: built-in; method

This is really a different disguise of a built-in function, this time containing an object passed to the C function as an implicit extra argument. An example of a built-in method is alist.append(), assuming alist is a list object. In this case, the special read-only attribute :attr:`__self__` is set to the object denoted by alist.

Classes are callable. These objects normally act as factories for new instances of themselves, but variations are possible for class types that override :meth:`__new__`. The arguments of the call are passed to :meth:`__new__` and, in the typical case, to :meth:`__init__` to initialize the new instance.
Class Instances
Instances of arbitrary classes can be made callable by defining a :meth:`__call__` method in their class.
.. index::
   statement: import
   object: module

Modules are a basic organizational unit of Python code, and are created by the :ref:`import system <importsystem>` as invoked either by the :keyword:`import` statement, or by calling functions such as :func:`importlib.import_module` and built-in :func:`__import__`. A module object has a namespace implemented by a dictionary object (this is the dictionary referenced by the __globals__ attribute of functions defined in the module). Attribute references are translated to lookups in this dictionary, e.g., m.x is equivalent to m.__dict__["x"]. A module object does not contain the code object used to initialize the module (since it isn't needed once the initialization is done).

Attribute assignment updates the module's namespace dictionary, e.g., m.x = 1 is equivalent to m.__dict__["x"] = 1.

.. index::
   single: __name__ (module attribute)
   single: __doc__ (module attribute)
   single: __file__ (module attribute)
   single: __annotations__ (module attribute)
   pair: module; namespace

Predefined (writable) attributes: :attr:`__name__` is the module's name; :attr:`__doc__` is the module's documentation string, or None if unavailable; :attr:`__annotations__` (optional) is a dictionary containing :term:`variable annotations <variable annotation>` collected during module body execution; :attr:`__file__` is the pathname of the file from which the module was loaded, if it was loaded from a file. The :attr:`__file__` attribute may be missing for certain types of modules, such as C modules that are statically linked into the interpreter; for extension modules loaded dynamically from a shared library, it is the pathname of the shared library file.

.. index:: single: __dict__ (module attribute)

Special read-only attribute: :attr:`~object.__dict__` is the module's namespace as a dictionary object.

.. impl-detail::

   Because of the way CPython clears module dictionaries, the module
   dictionary will be cleared when the module falls out of scope even if the
   dictionary still has live references.  To avoid this, copy the dictionary
   or keep the module around while using its dictionary directly.

Custom classes

Custom class types are typically created by class definitions (see section :ref:`class`). A class has a namespace implemented by a dictionary object. Class attribute references are translated to lookups in this dictionary, e.g., C.x is translated to C.__dict__["x"] (although there are a number of hooks which allow for other means of locating attributes). When the attribute name is not found there, the attribute search continues in the base classes. This search of the base classes uses the C3 method resolution order which behaves correctly even in the presence of 'diamond' inheritance structures where there are multiple inheritance paths leading back to a common ancestor. Additional details on the C3 MRO used by Python can be found in the documentation accompanying the 2.3 release at

.. index::
   object: class
   object: class instance
   object: instance
   pair: class object; call
   single: container
   object: dictionary
   pair: class; attribute

When a class attribute reference (for class :class:`C`, say) would yield a class method object, it is transformed into an instance method object whose :attr:`__self__` attribute is :class:`C`. When it would yield a static method object, it is transformed into the object wrapped by the static method object. See section :ref:`descriptors` for another way in which attributes retrieved from a class may differ from those actually contained in its :attr:`~object.__dict__`.

.. index:: triple: class; attribute; assignment

Class attribute assignments update the class's dictionary, never the dictionary of a base class.

.. index:: pair: class object; call

A class object can be called (see above) to yield a class instance (see below).

.. index::
   single: __name__ (class attribute)
   single: __module__ (class attribute)
   single: __dict__ (class attribute)
   single: __bases__ (class attribute)
   single: __doc__ (class attribute)
   single: __annotations__ (class attribute)

Special attributes: :attr:`~definition.__name__` is the class name; :attr:`__module__` is the module name in which the class was defined; :attr:`~object.__dict__` is the dictionary containing the class's namespace; :attr:`~class.__bases__` is a tuple containing the base classes, in the order of their occurrence in the base class list; :attr:`__doc__` is the class's documentation string, or None if undefined; :attr:`__annotations__` (optional) is a dictionary containing :term:`variable annotations <variable annotation>` collected during class body execution.

Class instances
.. index::
   object: class instance
   object: instance
   pair: class; instance
   pair: class instance; attribute

A class instance is created by calling a class object (see above). A class instance has a namespace implemented as a dictionary which is the first place in which attribute references are searched. When an attribute is not found there, and the instance's class has an attribute by that name, the search continues with the class attributes. If a class attribute is found that is a user-defined function object, it is transformed into an instance method object whose :attr:`__self__` attribute is the instance. Static method and class method objects are also transformed; see above under "Classes". See section :ref:`descriptors` for another way in which attributes of a class retrieved via its instances may differ from the objects actually stored in the class's :attr:`~object.__dict__`. If no class attribute is found, and the object's class has a :meth:`__getattr__` method, that is called to satisfy the lookup.

.. index:: triple: class instance; attribute; assignment

Attribute assignments and deletions update the instance's dictionary, never a class's dictionary. If the class has a :meth:`__setattr__` or :meth:`__delattr__` method, this is called instead of updating the instance dictionary directly.

.. index::
   object: numeric
   object: sequence
   object: mapping

Class instances can pretend to be numbers, sequences, or mappings if they have methods with certain special names. See section :ref:`specialnames`.

.. index::
   single: __dict__ (instance attribute)
   single: __class__ (instance attribute)

Special attributes: :attr:`~object.__dict__` is the attribute dictionary; :attr:`~instance.__class__` is the instance's class.

I/O objects (also known as file objects)
.. index::
   builtin: open
   module: io
   single: popen() (in module os)
   single: makefile() (socket method)
   single: sys.stdin
   single: sys.stdout
   single: sys.stderr
   single: stdio
   single: stdin (in module sys)
   single: stdout (in module sys)
   single: stderr (in module sys)

A :term:`file object` represents an open file. Various shortcuts are available to create file objects: the :func:`open` built-in function, and also :func:`os.popen`, :func:`os.fdopen`, and the :meth:`~socket.socket.makefile` method of socket objects (and perhaps by other functions or methods provided by extension modules).

The objects sys.stdin, sys.stdout and sys.stderr are initialized to file objects corresponding to the interpreter's standard input, output and error streams; they are all open in text mode and therefore follow the interface defined by the :class:`io.TextIOBase` abstract class.

Internal types
.. index::
   single: internal type
   single: types, internal

A few types used internally by the interpreter are exposed to the user. Their definitions may change with future versions of the interpreter, but they are mentioned here for completeness.

.. index:: bytecode, object; code, code object

Code objects

Code objects represent byte-compiled executable Python code, or :term:`bytecode`. The difference between a code object and a function object is that the function object contains an explicit reference to the function's globals (the module in which it was defined), while a code object contains no context; also the default argument values are stored in the function object, not in the code object (because they represent values calculated at run-time). Unlike function objects, code objects are immutable and contain no references (directly or indirectly) to mutable objects.

.. index::
   single: co_argcount (code object attribute)
   single: co_code (code object attribute)
   single: co_consts (code object attribute)
   single: co_filename (code object attribute)
   single: co_firstlineno (code object attribute)
   single: co_flags (code object attribute)
   single: co_lnotab (code object attribute)
   single: co_name (code object attribute)
   single: co_names (code object attribute)
   single: co_nlocals (code object attribute)
   single: co_stacksize (code object attribute)
   single: co_varnames (code object attribute)
   single: co_cellvars (code object attribute)
   single: co_freevars (code object attribute)

Special read-only attributes: :attr:`co_name` gives the function name; :attr:`co_argcount` is the number of positional arguments (including arguments with default values); :attr:`co_nlocals` is the number of local variables used by the function (including arguments); :attr:`co_varnames` is a tuple containing the names of the local variables (starting with the argument names); :attr:`co_cellvars` is a tuple containing the names of local variables that are referenced by nested functions; :attr:`co_freevars` is a tuple containing the names of free variables; :attr:`co_code` is a string representing the sequence of bytecode instructions; :attr:`co_consts` is a tuple containing the literals used by the bytecode; :attr:`co_names` is a tuple containing the names used by the bytecode; :attr:`co_filename` is the filename from which the code was compiled; :attr:`co_firstlineno` is the first line number of the function; :attr:`co_lnotab` is a string encoding the mapping from bytecode offsets to line numbers (for details see the source code of the interpreter); :attr:`co_stacksize` is the required stack size (including local variables); :attr:`co_flags` is an integer encoding a number of flags for the interpreter.

.. index:: object: generator

The following flag bits are defined for :attr:`co_flags`: bit 0x04 is set if the function uses the *arguments syntax to accept an arbitrary number of positional arguments; bit 0x08 is set if the function uses the **keywords syntax to accept arbitrary keyword arguments; bit 0x20 is set if the function is a generator.

Future feature declarations (from __future__ import division) also use bits in :attr:`co_flags` to indicate whether a code object was compiled with a particular feature enabled: bit 0x2000 is set if the function was compiled with future division enabled; bits 0x10 and 0x1000 were used in earlier versions of Python.

Other bits in :attr:`co_flags` are reserved for internal use.

.. index:: single: documentation string

If a code object represents a function, the first item in :attr:`co_consts` is the documentation string of the function, or None if undefined.

Frame objects
.. index:: object: frame

Frame objects represent execution frames. They may occur in traceback objects (see below), and are also passed to registered trace functions.

.. index::
   single: f_back (frame attribute)
   single: f_code (frame attribute)
   single: f_globals (frame attribute)
   single: f_locals (frame attribute)
   single: f_lasti (frame attribute)
   single: f_builtins (frame attribute)

Special read-only attributes: :attr:`f_back` is to the previous stack frame (towards the caller), or None if this is the bottom stack frame; :attr:`f_code` is the code object being executed in this frame; :attr:`f_locals` is the dictionary used to look up local variables; :attr:`f_globals` is used for global variables; :attr:`f_builtins` is used for built-in (intrinsic) names; :attr:`f_lasti` gives the precise instruction (this is an index into the bytecode string of the code object).

.. index::
   single: f_trace (frame attribute)
   single: f_trace_lines (frame attribute)
   single: f_trace_opcodes (frame attribute)
   single: f_lineno (frame attribute)

Special writable attributes: :attr:`f_trace`, if not None, is a function called for various events during code execution (this is used by the debugger). Normally an event is triggered for each new source line - this can be disabled by setting :attr:`f_trace_lines` to :const:`False`.

Implementations may allow per-opcode events to be requested by setting :attr:`f_trace_opcodes` to :const:`True`. Note that this may lead to undefined interpreter behaviour if exceptions raised by the trace function escape to the function being traced.

:attr:`f_lineno` is the current line number of the frame --- writing to this from within a trace function jumps to the given line (only for the bottom-most frame). A debugger can implement a Jump command (aka Set Next Statement) by writing to f_lineno.

Frame objects support one method:

.. method:: frame.clear()

   This method clears all references to local variables held by the
   frame.  Also, if the frame belonged to a generator, the generator
   is finalized.  This helps break reference cycles involving frame
   objects (for example when catching an exception and storing its
   traceback for later use).

   :exc:`RuntimeError` is raised if the frame is currently executing.

   .. versionadded:: 3.4

Traceback objects
.. index::
   object: traceback
   pair: stack; trace
   pair: exception; handler
   pair: execution; stack
   single: exc_info (in module sys)
   single: last_traceback (in module sys)
   single: sys.exc_info
   single: sys.last_traceback

Traceback objects represent a stack trace of an exception. A traceback object is implicitly created when an exception occurs, and may also be explicitly created by calling :class:`types.TracebackType`.

For implicitly created tracebacks, when the search for an exception handler unwinds the execution stack, at each unwound level a traceback object is inserted in front of the current traceback. When an exception handler is entered, the stack trace is made available to the program. (See section :ref:`try`.) It is accessible as the third item of the tuple returned by sys.exc_info(), and as the __traceback__ attribute of the caught exception.

When the program contains no suitable handler, the stack trace is written (nicely formatted) to the standard error stream; if the interpreter is interactive, it is also made available to the user as sys.last_traceback.

For explicitly created tracebacks, it is up to the creator of the traceback to determine how the tb_next attributes should be linked to form a full stack trace.

.. index::
   single: tb_frame (traceback attribute)
   single: tb_lineno (traceback attribute)
   single: tb_lasti (traceback attribute)
   statement: try

Special read-only attributes: :attr:`tb_frame` points to the execution frame of the current level; :attr:`tb_lineno` gives the line number where the exception occurred; :attr:`tb_lasti` indicates the precise instruction. The line number and last instruction in the traceback may differ from the line number of its frame object if the exception occurred in a :keyword:`try` statement with no matching except clause or with a finally clause.

.. index::
   single: tb_next (traceback attribute)

Special writable attribute: :attr:`tb_next` is the next level in the stack trace (towards the frame where the exception occurred), or None if there is no next level.

.. versionchanged:: 3.7
   Traceback objects can now be explicitly instantiated from Python code,
   and the ``tb_next`` attribute of existing instances can be updated.

Slice objects
.. index:: builtin: slice

Slice objects are used to represent slices for :meth:`__getitem__` methods. They are also created by the built-in :func:`slice` function.

.. index::
   single: start (slice object attribute)
   single: stop (slice object attribute)
   single: step (slice object attribute)

Special read-only attributes: :attr:`~slice.start` is the lower bound; :attr:`~slice.stop` is the upper bound; :attr:`~slice.step` is the step value; each is None if omitted. These attributes can have any type.

Slice objects support one method:

.. method:: slice.indices(self, length)

   This method takes a single integer argument *length* and computes
   information about the slice that the slice object would describe if
   applied to a sequence of *length* items.  It returns a tuple of three
   integers; respectively these are the *start* and *stop* indices and the
   *step* or stride length of the slice. Missing or out-of-bounds indices
   are handled in a manner consistent with regular slices.

Static method objects
Static method objects provide a way of defeating the transformation of function objects to method objects described above. A static method object is a wrapper around any other object, usually a user-defined method object. When a static method object is retrieved from a class or a class instance, the object actually returned is the wrapped object, which is not subject to any further transformation. Static method objects are not themselves callable, although the objects they wrap usually are. Static method objects are created by the built-in :func:`staticmethod` constructor.
Class method objects
A class method object, like a static method object, is a wrapper around another object that alters the way in which that object is retrieved from classes and class instances. The behaviour of class method objects upon such retrieval is described above, under "User-defined methods". Class method objects are created by the built-in :func:`classmethod` constructor.

Special method names

.. index::
   pair: operator; overloading
   single: __getitem__() (mapping object method)

A class can implement certain operations that are invoked by special syntax (such as arithmetic operations or subscripting and slicing) by defining methods with special names. This is Python's approach to :dfn:`operator overloading`, allowing classes to define their own behavior with respect to language operators. For instance, if a class defines a method named :meth:`__getitem__`, and x is an instance of this class, then x[i] is roughly equivalent to type(x).__getitem__(x, i). Except where mentioned, attempts to execute an operation raise an exception when no appropriate method is defined (typically :exc:`AttributeError` or :exc:`TypeError`).

Setting a special method to None indicates that the corresponding operation is not available. For example, if a class sets :meth:`__iter__` to None, the class is not iterable, so calling :func:`iter` on its instances will raise a :exc:`TypeError` (without falling back to :meth:`__getitem__`). [2]

When implementing a class that emulates any built-in type, it is important that the emulation only be implemented to the degree that it makes sense for the object being modelled. For example, some sequences may work well with retrieval of individual elements, but extracting a slice may not make sense. (One example of this is the :class:`~xml.dom.NodeList` interface in the W3C's Document Object Model.)

Basic customization

.. method:: object.__new__(cls[, ...])

   .. index:: pair: subclassing; immutable types

   Called to create a new instance of class *cls*.  :meth:`__new__` is a static
   method (special-cased so you need not declare it as such) that takes the class
   of which an instance was requested as its first argument.  The remaining
   arguments are those passed to the object constructor expression (the call to the
   class).  The return value of :meth:`__new__` should be the new object instance
   (usually an instance of *cls*).

   Typical implementations create a new instance of the class by invoking the
   superclass's :meth:`__new__` method using ``super().__new__(cls[, ...])``
   with appropriate arguments and then modifying the newly-created instance
   as necessary before returning it.

   If :meth:`__new__` returns an instance of *cls*, then the new instance's
   :meth:`__init__` method will be invoked like ``__init__(self[, ...])``, where
   *self* is the new instance and the remaining arguments are the same as were
   passed to :meth:`__new__`.

   If :meth:`__new__` does not return an instance of *cls*, then the new instance's
   :meth:`__init__` method will not be invoked.

   :meth:`__new__` is intended mainly to allow subclasses of immutable types (like
   int, str, or tuple) to customize instance creation.  It is also commonly
   overridden in custom metaclasses in order to customize class creation.

.. method:: object.__init__(self[, ...])

   .. index:: pair: class; constructor

   Called after the instance has been created (by :meth:`__new__`), but before
   it is returned to the caller.  The arguments are those passed to the
   class constructor expression.  If a base class has an :meth:`__init__`
   method, the derived class's :meth:`__init__` method, if any, must explicitly
   call it to ensure proper initialization of the base class part of the
   instance; for example: ``super().__init__([args...])``.

   Because :meth:`__new__` and :meth:`__init__` work together in constructing
   objects (:meth:`__new__` to create it, and :meth:`__init__` to customize it),
   no non-``None`` value may be returned by :meth:`__init__`; doing so will
   cause a :exc:`TypeError` to be raised at runtime.

.. method:: object.__del__(self)

   .. index::
      single: destructor
      single: finalizer
      statement: del

   Called when the instance is about to be destroyed.  This is also called a
   finalizer or (improperly) a destructor.  If a base class has a
   :meth:`__del__` method, the derived class's :meth:`__del__` method,
   if any, must explicitly call it to ensure proper deletion of the base
   class part of the instance.

   It is possible (though not recommended!) for the :meth:`__del__` method
   to postpone destruction of the instance by creating a new reference to
   it.  This is called object *resurrection*.  It is implementation-dependent
   whether :meth:`__del__` is called a second time when a resurrected object
   is about to be destroyed; the current :term:`CPython` implementation
   only calls it once.

   It is not guaranteed that :meth:`__del__` methods are called for objects
   that still exist when the interpreter exits.

   .. note::

      ``del x`` doesn't directly call ``x.__del__()`` --- the former decrements
      the reference count for ``x`` by one, and the latter is only called when
      ``x``'s reference count reaches zero.

   .. impl-detail::
      It is possible for a reference cycle to prevent the reference count
      of an object from going to zero.  In this case, the cycle will be
      later detected and deleted by the :term:`cyclic garbage collector
      <garbage collection>`.  A common cause of reference cycles is when
      an exception has been caught in a local variable.  The frame's
      locals then reference the exception, which references its own
      traceback, which references the locals of all frames caught in the

      .. seealso::
         Documentation for the :mod:`gc` module.

   .. warning::

      Due to the precarious circumstances under which :meth:`__del__` methods are
      invoked, exceptions that occur during their execution are ignored, and a warning
      is printed to ``sys.stderr`` instead.  In particular:

      * :meth:`__del__` can be invoked when arbitrary code is being executed,
        including from any arbitrary thread.  If :meth:`__del__` needs to take
        a lock or invoke any other blocking resource, it may deadlock as
        the resource may already be taken by the code that gets interrupted
        to execute :meth:`__del__`.

      * :meth:`__del__` can be executed during interpreter shutdown.  As a
        consequence, the global variables it needs to access (including other
        modules) may already have been deleted or set to ``None``. Python
        guarantees that globals whose name begins with a single underscore
        are deleted from their module before other globals are deleted; if
        no other references to such globals exist, this may help in assuring
        that imported modules are still available at the time when the
        :meth:`__del__` method is called.

   .. index::
      single: repr() (built-in function); __repr__() (object method)

.. method:: object.__repr__(self)

   Called by the :func:`repr` built-in function to compute the "official" string
   representation of an object.  If at all possible, this should look like a
   valid Python expression that could be used to recreate an object with the
   same value (given an appropriate environment).  If this is not possible, a
   string of the form ``<...some useful description...>`` should be returned.
   The return value must be a string object. If a class defines :meth:`__repr__`
   but not :meth:`__str__`, then :meth:`__repr__` is also used when an
   "informal" string representation of instances of that class is required.

   This is typically used for debugging, so it is important that the representation
   is information-rich and unambiguous.

   .. index::
      single: string; __str__() (object method)
      single: format() (built-in function); __str__() (object method)
      single: print() (built-in function); __str__() (object method)

.. method:: object.__str__(self)

   Called by :func:`str(object) <str>` and the built-in functions
   :func:`format` and :func:`print` to compute the "informal" or nicely
   printable string representation of an object.  The return value must be a
   :ref:`string <textseq>` object.

   This method differs from :meth:`object.__repr__` in that there is no
   expectation that :meth:`__str__` return a valid Python expression: a more
   convenient or concise representation can be used.

   The default implementation defined by the built-in type :class:`object`
   calls :meth:`object.__repr__`.

   .. XXX what about subclasses of string?

.. method:: object.__bytes__(self)

   .. index:: builtin: bytes

   Called by :ref:`bytes <func-bytes>` to compute a byte-string representation
   of an object. This should return a :class:`bytes` object.

   .. index::
      single: string; __format__() (object method)
      pair: string; conversion
      builtin: print

.. method:: object.__format__(self, format_spec)

   Called by the :func:`format` built-in function,
   and by extension, evaluation of :ref:`formatted string literals
   <f-strings>` and the :meth:`str.format` method, to produce a "formatted"
   string representation of an object. The ``format_spec`` argument is
   a string that contains a description of the formatting options desired.
   The interpretation of the ``format_spec`` argument is up to the type
   implementing :meth:`__format__`, however most classes will either
   delegate formatting to one of the built-in types, or use a similar
   formatting option syntax.

   See :ref:`formatspec` for a description of the standard formatting syntax.

   The return value must be a string object.

   .. versionchanged:: 3.4
      The __format__ method of ``object`` itself raises a :exc:`TypeError`
      if passed any non-empty string.

   .. versionchanged:: 3.7
      ``object.__format__(x, '')`` is now equivalent to ``str(x)`` rather
      than ``format(str(self), '')``.

.. method:: object.__lt__(self, other)
            object.__le__(self, other)
            object.__eq__(self, other)
            object.__ne__(self, other)
            object.__gt__(self, other)
            object.__ge__(self, other)

   .. index::
      single: comparisons

   These are the so-called "rich comparison" methods. The correspondence between
   operator symbols and method names is as follows: ``x<y`` calls ``x.__lt__(y)``,
   ``x<=y`` calls ``x.__le__(y)``, ``x==y`` calls ``x.__eq__(y)``, ``x!=y`` calls
   ``x.__ne__(y)``, ``x>y`` calls ``x.__gt__(y)``, and ``x>=y`` calls

   A rich comparison method may return the singleton ``NotImplemented`` if it does
   not implement the operation for a given pair of arguments. By convention,
   ``False`` and ``True`` are returned for a successful comparison. However, these
   methods can return any value, so if the comparison operator is used in a Boolean
   context (e.g., in the condition of an ``if`` statement), Python will call
   :func:`bool` on the value to determine if the result is true or false.

   By default, :meth:`__ne__` delegates to :meth:`__eq__` and
   inverts the result unless it is ``NotImplemented``.  There are no other
   implied relationships among the comparison operators, for example,
   the truth of ``(x<y or x==y)`` does not imply ``x<=y``.
   To automatically generate ordering operations from a single root operation,
   see :func:`functools.total_ordering`.

   See the paragraph on :meth:`__hash__` for
   some important notes on creating :term:`hashable` objects which support
   custom comparison operations and are usable as dictionary keys.

   There are no swapped-argument versions of these methods (to be used when the
   left argument does not support the operation but the right argument does);
   rather, :meth:`__lt__` and :meth:`__gt__` are each other's reflection,
   :meth:`__le__` and :meth:`__ge__` are each other's reflection, and
   :meth:`__eq__` and :meth:`__ne__` are their own reflection.
   If the operands are of different types, and right operand's type is
   a direct or indirect subclass of the left operand's type,
   the reflected method of the right operand has priority, otherwise
   the left operand's method has priority.  Virtual subclassing is
   not considered.

.. method:: object.__hash__(self)

   .. index::
      object: dictionary
      builtin: hash

   Called by built-in function :func:`hash` and for operations on members of
   hashed collections including :class:`set`, :class:`frozenset`, and
   :class:`dict`.  :meth:`__hash__` should return an integer. The only required
   property is that objects which compare equal have the same hash value; it is
   advised to mix together the hash values of the components of the object that
   also play a part in comparison of objects by packing them into a tuple and
   hashing the tuple. Example::

       def __hash__(self):
           return hash((, self.nick, self.color))

   .. note::

     :func:`hash` truncates the value returned from an object's custom
     :meth:`__hash__` method to the size of a :c:type:`Py_ssize_t`.  This is
     typically 8 bytes on 64-bit builds and 4 bytes on 32-bit builds.  If an
     object's   :meth:`__hash__` must interoperate on builds of different bit
     sizes, be sure to check the width on all supported builds.  An easy way
     to do this is with
     ``python -c "import sys; print(sys.hash_info.width)"``.

   If a class does not define an :meth:`__eq__` method it should not define a
   :meth:`__hash__` operation either; if it defines :meth:`__eq__` but not
   :meth:`__hash__`, its instances will not be usable as items in hashable
   collections.  If a class defines mutable objects and implements an
   :meth:`__eq__` method, it should not implement :meth:`__hash__`, since the
   implementation of hashable collections requires that a key's hash value is
   immutable (if the object's hash value changes, it will be in the wrong hash

   User-defined classes have :meth:`__eq__` and :meth:`__hash__` methods
   by default; with them, all objects compare unequal (except with themselves)
   and ``x.__hash__()`` returns an appropriate value such that ``x == y``
   implies both that ``x is y`` and ``hash(x) == hash(y)``.

   A class that overrides :meth:`__eq__` and does not define :meth:`__hash__`
   will have its :meth:`__hash__` implicitly set to ``None``.  When the
   :meth:`__hash__` method of a class is ``None``, instances of the class will
   raise an appropriate :exc:`TypeError` when a program attempts to retrieve
   their hash value, and will also be correctly identified as unhashable when
   checking ``isinstance(obj,``.

   If a class that overrides :meth:`__eq__` needs to retain the implementation
   of :meth:`__hash__` from a parent class, the interpreter must be told this
   explicitly by setting ``__hash__ = <ParentClass>.__hash__``.

   If a class that does not override :meth:`__eq__` wishes to suppress hash
   support, it should include ``__hash__ = None`` in the class definition.
   A class which defines its own :meth:`__hash__` that explicitly raises
   a :exc:`TypeError` would be incorrectly identified as hashable by
   an ``isinstance(obj,`` call.

   .. note::

      By default, the :meth:`__hash__` values of str, bytes and datetime
      objects are "salted" with an unpredictable random value.  Although they
      remain constant within an individual Python process, they are not
      predictable between repeated invocations of Python.

      This is intended to provide protection against a denial-of-service caused
      by carefully-chosen inputs that exploit the worst case performance of a
      dict insertion, O(n^2) complexity.  See for details.

      Changing hash values affects the iteration order of sets.
      Python has never made guarantees about this ordering
      (and it typically varies between 32-bit and 64-bit builds).

      See also :envvar:`PYTHONHASHSEED`.

   .. versionchanged:: 3.3
      Hash randomization is enabled by default.

.. method:: object.__bool__(self)

   .. index:: single: __len__() (mapping object method)

   Called to implement truth value testing and the built-in operation
   ``bool()``; should return ``False`` or ``True``.  When this method is not
   defined, :meth:`__len__` is called, if it is defined, and the object is
   considered true if its result is nonzero.  If a class defines neither
   :meth:`__len__` nor :meth:`__bool__`, all its instances are considered

Customizing attribute access

The following methods can be defined to customize the meaning of attribute access (use of, assignment to, or deletion of for class instances.

.. method:: object.__getattr__(self, name)

   Called when the default attribute access fails with an :exc:`AttributeError`
   (either :meth:`__getattribute__` raises an :exc:`AttributeError` because
   *name* is not an instance attribute or an attribute in the class tree
   for ``self``; or :meth:`__get__` of a *name* property raises
   :exc:`AttributeError`).  This method should either return the (computed)
   attribute value or raise an :exc:`AttributeError` exception.

   Note that if the attribute is found through the normal mechanism,
   :meth:`__getattr__` is not called.  (This is an intentional asymmetry between
   :meth:`__getattr__` and :meth:`__setattr__`.) This is done both for efficiency
   reasons and because otherwise :meth:`__getattr__` would have no way to access
   other attributes of the instance.  Note that at least for instance variables,
   you can fake total control by not inserting any values in the instance attribute
   dictionary (but instead inserting them in another object).  See the
   :meth:`__getattribute__` method below for a way to actually get total control
   over attribute access.

.. method:: object.__getattribute__(self, name)

   Called unconditionally to implement attribute accesses for instances of the
   class. If the class also defines :meth:`__getattr__`, the latter will not be
   called unless :meth:`__getattribute__` either calls it explicitly or raises an
   :exc:`AttributeError`. This method should return the (computed) attribute value
   or raise an :exc:`AttributeError` exception. In order to avoid infinite
   recursion in this method, its implementation should always call the base class
   method with the same name to access any attributes it needs, for example,
   ``object.__getattribute__(self, name)``.

   .. note::

      This method may still be bypassed when looking up special methods as the
      result of implicit invocation via language syntax or built-in functions.
      See :ref:`special-lookup`.

.. method:: object.__setattr__(self, name, value)

   Called when an attribute assignment is attempted.  This is called instead of
   the normal mechanism (i.e. store the value in the instance dictionary).
   *name* is the attribute name, *value* is the value to be assigned to it.

   If :meth:`__setattr__` wants to assign to an instance attribute, it should
   call the base class method with the same name, for example,
   ``object.__setattr__(self, name, value)``.

.. method:: object.__delattr__(self, name)

   Like :meth:`__setattr__` but for attribute deletion instead of assignment.  This
   should only be implemented if ``del`` is meaningful for the object.

.. method:: object.__dir__(self)

   Called when :func:`dir` is called on the object. A sequence must be
   returned. :func:`dir` converts the returned sequence to a list and sorts it.

Customizing module attribute access

.. index::
   single: __getattr__ (module attribute)
   single: __dir__ (module attribute)
   single: __class__ (module attribute)

Special names __getattr__ and __dir__ can be also used to customize access to module attributes. The __getattr__ function at the module level should accept one argument which is the name of an attribute and return the computed value or raise an :exc:`AttributeError`. If an attribute is not found on a module object through the normal lookup, i.e. :meth:`object.__getattribute__`, then __getattr__ is searched in the module __dict__ before raising an :exc:`AttributeError`. If found, it is called with the attribute name and the result is returned.

The __dir__ function should accept no arguments, and return a list of strings that represents the names accessible on module. If present, this function overrides the standard :func:`dir` search on a module.

For a more fine grained customization of the module behavior (setting attributes, properties, etc.), one can set the __class__ attribute of a module object to a subclass of :class:`types.ModuleType`. For example:

import sys
from types import ModuleType

class VerboseModule(ModuleType):
    def __repr__(self):
        return f'Verbose {self.__name__}'

    def __setattr__(self, attr, value):
        print(f'Setting {attr}...')
        super().__setattr__(attr, value)

sys.modules[__name__].__class__ = VerboseModule


Defining module __getattr__ and setting module __class__ only affect lookups made using the attribute access syntax -- directly accessing the module globals (whether by code within the module, or via a reference to the module's globals dictionary) is unaffected.

.. versionchanged:: 3.5
   ``__class__`` module attribute is now writable.

.. versionadded:: 3.7
   ``__getattr__`` and ``__dir__`` module attributes.

.. seealso::

   :pep:`562` - Module __getattr__ and __dir__
      Describes the ``__getattr__`` and ``__dir__`` functions on modules.

Implementing Descriptors

The following methods only apply when an instance of the class containing the method (a so-called descriptor class) appears in an owner class (the descriptor must be in either the owner's class dictionary or in the class dictionary for one of its parents). In the examples below, "the attribute" refers to the attribute whose name is the key of the property in the owner class' :attr:`~object.__dict__`.

.. method:: object.__get__(self, instance, owner)

   Called to get the attribute of the owner class (class attribute access) or of an
   instance of that class (instance attribute access). *owner* is always the owner
   class, while *instance* is the instance that the attribute was accessed through,
   or ``None`` when the attribute is accessed through the *owner*.  This method
   should return the (computed) attribute value or raise an :exc:`AttributeError`

.. method:: object.__set__(self, instance, value)

   Called to set the attribute on an instance *instance* of the owner class to a
   new value, *value*.

.. method:: object.__delete__(self, instance)

   Called to delete the attribute on an instance *instance* of the owner class.

.. method:: object.__set_name__(self, owner, name)

   Called at the time the owning class *owner* is created. The
   descriptor has been assigned to *name*.

   .. versionadded:: 3.6

The attribute :attr:`__objclass__` is interpreted by the :mod:`inspect` module as specifying the class where this object was defined (setting this appropriately can assist in runtime introspection of dynamic class attributes). For callables, it may indicate that an instance of the given type (or a subclass) is expected or required as the first positional argument (for example, CPython sets this attribute for unbound methods that are implemented in C).

Invoking Descriptors

In general, a descriptor is an object attribute with "binding behavior", one whose attribute access has been overridden by methods in the descriptor protocol: :meth:`__get__`, :meth:`__set__`, and :meth:`__delete__`. If any of those methods are defined for an object, it is said to be a descriptor.

The default behavior for attribute access is to get, set, or delete the attribute from an object's dictionary. For instance, a.x has a lookup chain starting with a.__dict__['x'], then type(a).__dict__['x'], and continuing through the base classes of type(a) excluding metaclasses.

However, if the looked-up value is an object defining one of the descriptor methods, then Python may override the default behavior and invoke the descriptor method instead. Where this occurs in the precedence chain depends on which descriptor methods were defined and how they were called.

The starting point for descriptor invocation is a binding, a.x. How the arguments are assembled depends on a:

Direct Call
The simplest and least common call is when user code directly invokes a descriptor method: x.__get__(a).
Instance Binding
If binding to an object instance, a.x is transformed into the call: type(a).__dict__['x'].__get__(a, type(a)).
Class Binding
If binding to a class, A.x is transformed into the call: A.__dict__['x'].__get__(None, A).
Super Binding
If a is an instance of :class:`super`, then the binding super(B, obj).m() searches obj.__class__.__mro__ for the base class A immediately preceding B and then invokes the descriptor with the call: A.__dict__['m'].__get__(obj, obj.__class__).

For instance bindings, the precedence of descriptor invocation depends on the which descriptor methods are defined. A descriptor can define any combination of :meth:`__get__`, :meth:`__set__` and :meth:`__delete__`. If it does not define :meth:`__get__`, then accessing the attribute will return the descriptor object itself unless there is a value in the object's instance dictionary. If the descriptor defines :meth:`__set__` and/or :meth:`__delete__`, it is a data descriptor; if it defines neither, it is a non-data descriptor. Normally, data descriptors define both :meth:`__get__` and :meth:`__set__`, while non-data descriptors have just the :meth:`__get__` method. Data descriptors with :meth:`__set__` and :meth:`__get__` defined always override a redefinition in an instance dictionary. In contrast, non-data descriptors can be overridden by instances.

Python methods (including :func:`staticmethod` and :func:`classmethod`) are implemented as non-data descriptors. Accordingly, instances can redefine and override methods. This allows individual instances to acquire behaviors that differ from other instances of the same class.

The :func:`property` function is implemented as a data descriptor. Accordingly, instances cannot override the behavior of a property.


__slots__ allow us to explicitly declare data members (like properties) and deny the creation of __dict__ and __weakref__ (unless explicitly declared in __slots__ or available in a parent.)

The space saved over using __dict__ can be significant. Attribute lookup speed can be significantly improved as well.

.. data:: object.__slots__

   This class variable can be assigned a string, iterable, or sequence of
   strings with variable names used by instances.  *__slots__* reserves space
   for the declared variables and prevents the automatic creation of *__dict__*
   and *__weakref__* for each instance.

Notes on using __slots__
  • When inheriting from a class without __slots__, the __dict__ and __weakref__ attribute of the instances will always be accessible.
  • Without a __dict__ variable, instances cannot be assigned new variables not listed in the __slots__ definition. Attempts to assign to an unlisted variable name raises :exc:`AttributeError`. If dynamic assignment of new variables is desired, then add '__dict__' to the sequence of strings in the __slots__ declaration.
  • Without a __weakref__ variable for each instance, classes defining __slots__ do not support weak references to its instances. If weak reference support is needed, then add '__weakref__' to the sequence of strings in the __slots__ declaration.
  • __slots__ are implemented at the class level by creating descriptors (:ref:`descriptors`) for each variable name. As a result, class attributes cannot be used to set default values for instance variables defined by __slots__; otherwise, the class attribute would overwrite the descriptor assignment.
  • The action of a __slots__ declaration is not limited to the class where it is defined. __slots__ declared in parents are available in child classes. However, child subclasses will get a __dict__ and __weakref__ unless they also define __slots__ (which should only contain names of any additional slots).
  • If a class defines a slot also defined in a base class, the instance variable defined by the base class slot is inaccessible (except by retrieving its descriptor directly from the base class). This renders the meaning of the program undefined. In the future, a check may be added to prevent this.
  • Nonempty __slots__ does not work for classes derived from "variable-length" built-in types such as :class:`int`, :class:`bytes` and :class:`tuple`.
  • Any non-string iterable may be assigned to __slots__. Mappings may also be used; however, in the future, special meaning may be assigned to the values corresponding to each key.
  • __class__ assignment works only if both classes have the same __slots__.
  • Multiple inheritance with multiple slotted parent classes can be used, but only one parent is allowed to have attributes created by slots (the other bases must have empty slot layouts) - violations raise :exc:`TypeError`.

Customizing class creation

Whenever a class inherits from another class, __init_subclass__ is called on that class. This way, it is possible to write classes which change the behavior of subclasses. This is closely related to class decorators, but where class decorators only affect the specific class they're applied to, __init_subclass__ solely applies to future subclasses of the class defining the method.

.. classmethod:: object.__init_subclass__(cls)

   This method is called whenever the containing class is subclassed.
   *cls* is then the new subclass. If defined as a normal instance method,
   this method is implicitly converted to a class method.

   Keyword arguments which are given to a new class are passed to
   the parent's class ``__init_subclass__``. For compatibility with
   other classes using ``__init_subclass__``, one should take out the
   needed keyword arguments and pass the others over to the base
   class, as in::

       class Philosopher:
           def __init_subclass__(cls, default_name, **kwargs):
               cls.default_name = default_name

       class AustralianPhilosopher(Philosopher, default_name="Bruce"):

   The default implementation ``object.__init_subclass__`` does
   nothing, but raises an error if it is called with any arguments.

   .. note::

      The metaclass hint ``metaclass`` is consumed by the rest of the type
      machinery, and is never passed to ``__init_subclass__`` implementations.
      The actual metaclass (rather than the explicit hint) can be accessed as

   .. versionadded:: 3.6


.. index::
   single: metaclass
   builtin: type
   single: = (equals); class definition

By default, classes are constructed using :func:`type`. The class body is executed in a new namespace and the class name is bound locally to the result of type(name, bases, namespace).

The class creation process can be customized by passing the metaclass keyword argument in the class definition line, or by inheriting from an existing class that included such an argument. In the following example, both MyClass and MySubclass are instances of Meta:

class Meta(type):

class MyClass(metaclass=Meta):

class MySubclass(MyClass):

Any other keyword arguments that are specified in the class definition are passed through to all metaclass operations described below.

When a class definition is executed, the following steps occur:

  • MRO entries are resolved;
  • the appropriate metaclass is determined;
  • the class namespace is prepared;
  • the class body is executed;
  • the class object is created.

Resolving MRO entries

If a base that appears in class definition is not an instance of :class:`type`, then an __mro_entries__ method is searched on it. If found, it is called with the original bases tuple. This method must return a tuple of classes that will be used instead of this base. The tuple may be empty, in such case the original base is ignored.

.. seealso::

   :pep:`560` - Core support for typing module and generic types

Determining the appropriate metaclass

.. index::
    single: metaclass hint

The appropriate metaclass for a class definition is determined as follows:

  • if no bases and no explicit metaclass are given, then :func:`type` is used;
  • if an explicit metaclass is given and it is not an instance of :func:`type`, then it is used directly as the metaclass;
  • if an instance of :func:`type` is given as the explicit metaclass, or bases are defined, then the most derived metaclass is used.

The most derived metaclass is selected from the explicitly specified metaclass (if any) and the metaclasses (i.e. type(cls)) of all specified base classes. The most derived metaclass is one which is a subtype of all of these candidate metaclasses. If none of the candidate metaclasses meets that criterion, then the class definition will fail with TypeError.

Preparing the class namespace

.. index::
    single: __prepare__ (metaclass method)

Once the appropriate metaclass has been identified, then the class namespace is prepared. If the metaclass has a __prepare__ attribute, it is called as namespace = metaclass.__prepare__(name, bases, **kwds) (where the additional keyword arguments, if any, come from the class definition).

If the metaclass has no __prepare__ attribute, then the class namespace is initialised as an empty ordered mapping.

.. seealso::

   :pep:`3115` - Metaclasses in Python 3000
      Introduced the ``__prepare__`` namespace hook

Executing the class body

.. index::
    single: class; body

The class body is executed (approximately) as exec(body, globals(), namespace). The key difference from a normal call to :func:`exec` is that lexical scoping allows the class body (including any methods) to reference names from the current and outer scopes when the class definition occurs inside a function.

However, even when the class definition occurs inside the function, methods defined inside the class still cannot see names defined at the class scope. Class variables must be accessed through the first parameter of instance or class methods, or through the implicit lexically scoped __class__ reference described in the next section.

Creating the class object

.. index::
    single: __class__ (method cell)
    single: __classcell__ (class namespace entry)

Once the class namespace has been populated by executing the class body, the class object is created by calling metaclass(name, bases, namespace, **kwds) (the additional keywords passed here are the same as those passed to __prepare__).

This class object is the one that will be referenced by the zero-argument form of :func:`super`. __class__ is an implicit closure reference created by the compiler if any methods in a class body refer to either __class__ or super. This allows the zero argument form of :func:`super` to correctly identify the class being defined based on lexical scoping, while the class or instance that was used to make the current call is identified based on the first argument passed to the method.

.. impl-detail::

   In CPython 3.6 and later, the ``__class__`` cell is passed to the metaclass
   as a ``__classcell__`` entry in the class namespace. If present, this must
   be propagated up to the ``type.__new__`` call in order for the class to be
   initialised correctly.
   Failing to do so will result in a :exc:`RuntimeError` in Python 3.8.

When using the default metaclass :class:`type`, or any metaclass that ultimately calls type.__new__, the following additional customisation steps are invoked after creating the class object:

  • first, type.__new__ collects all of the descriptors in the class namespace that define a :meth:`~object.__set_name__` method;
  • second, all of these __set_name__ methods are called with the class being defined and the assigned name of that particular descriptor;
  • finally, the :meth:`~object.__init_subclass__` hook is called on the immediate parent of the new class in its method resolution order.

After the class object is created, it is passed to the class decorators included in the class definition (if any) and the resulting object is bound in the local namespace as the defined class.

When a new class is created by type.__new__, the object provided as the namespace parameter is copied to a new ordered mapping and the original object is discarded. The new copy is wrapped in a read-only proxy, which becomes the :attr:`~object.__dict__` attribute of the class object.

.. seealso::

   :pep:`3135` - New super
      Describes the implicit ``__class__`` closure reference

Uses for metaclasses

The potential uses for metaclasses are boundless. Some ideas that have been explored include enum, logging, interface checking, automatic delegation, automatic property creation, proxies, frameworks, and automatic resource locking/synchronization.

Customizing instance and subclass checks

The following methods are used to override the default behavior of the :func:`isinstance` and :func:`issubclass` built-in functions.

In particular, the metaclass :class:`abc.ABCMeta` implements these methods in order to allow the addition of Abstract Base Classes (ABCs) as "virtual base classes" to any class or type (including built-in types), including other ABCs.

.. method:: class.__instancecheck__(self, instance)

   Return true if *instance* should be considered a (direct or indirect)
   instance of *class*. If defined, called to implement ``isinstance(instance,

.. method:: class.__subclasscheck__(self, subclass)

   Return true if *subclass* should be considered a (direct or indirect)
   subclass of *class*.  If defined, called to implement ``issubclass(subclass,

Note that these methods are looked up on the type (metaclass) of a class. They cannot be defined as class methods in the actual class. This is consistent with the lookup of special methods that are called on instances, only in this case the instance is itself a class.

.. seealso::

   :pep:`3119` - Introducing Abstract Base Classes
      Includes the specification for customizing :func:`isinstance` and
      :func:`issubclass` behavior through :meth:`~class.__instancecheck__` and
      :meth:`~class.__subclasscheck__`, with motivation for this functionality
      in the context of adding Abstract Base Classes (see the :mod:`abc`
      module) to the language.

Emulating generic types

One can implement the generic class syntax as specified by PEP 484 (for example List[int]) by defining a special method:

.. classmethod:: object.__class_getitem__(cls, key)

   Return an object representing the specialization of a generic class
   by type arguments found in *key*.

This method is looked up on the class object itself, and when defined in the class body, this method is implicitly a class method. Note, this mechanism is primarily reserved for use with static type hints, other usage is discouraged.

.. seealso::

   :pep:`560` - Core support for typing module and generic types

Emulating callable objects

.. method:: object.__call__(self[, args...])

   .. index:: pair: call; instance

   Called when the instance is "called" as a function; if this method is defined,
   ``x(arg1, arg2, ...)`` is a shorthand for ``x.__call__(arg1, arg2, ...)``.

Emulating container types

The following methods can be defined to implement container objects. Containers usually are sequences (such as lists or tuples) or mappings (like dictionaries), but can represent other containers as well. The first set of methods is used either to emulate a sequence or to emulate a mapping; the difference is that for a sequence, the allowable keys should be the integers k for which 0 <= k < N where N is the length of the sequence, or slice objects, which define a range of items. It is also recommended that mappings provide the methods :meth:`keys`, :meth:`values`, :meth:`items`, :meth:`get`, :meth:`clear`, :meth:`setdefault`, :meth:`pop`, :meth:`popitem`, :meth:`!copy`, and :meth:`update` behaving similar to those for Python's standard dictionary objects. The :mod:`` module provides a :class:`` abstract base class to help create those methods from a base set of :meth:`__getitem__`, :meth:`__setitem__`, :meth:`__delitem__`, and :meth:`keys`. Mutable sequences should provide methods :meth:`append`, :meth:`count`, :meth:`index`, :meth:`extend`, :meth:`insert`, :meth:`pop`, :meth:`remove`, :meth:`reverse` and :meth:`sort`, like Python standard list objects. Finally, sequence types should implement addition (meaning concatenation) and multiplication (meaning repetition) by defining the methods :meth:`__add__`, :meth:`__radd__`, :meth:`__iadd__`, :meth:`__mul__`, :meth:`__rmul__` and :meth:`__imul__` described below; they should not define other numerical operators. It is recommended that both mappings and sequences implement the :meth:`__contains__` method to allow efficient use of the in operator; for mappings, in should search the mapping's keys; for sequences, it should search through the values. It is further recommended that both mappings and sequences implement the :meth:`__iter__` method to allow efficient iteration through the container; for mappings, :meth:`__iter__` should be the same as :meth:`keys`; for sequences, it should iterate through the values.

.. method:: object.__len__(self)

   .. index::
      builtin: len
      single: __bool__() (object method)

   Called to implement the built-in function :func:`len`.  Should return the length
   of the object, an integer ``>=`` 0.  Also, an object that doesn't define a
   :meth:`__bool__` method and whose :meth:`__len__` method returns zero is
   considered to be false in a Boolean context.

   .. impl-detail::

      In CPython, the length is required to be at most :attr:`sys.maxsize`.
      If the length is larger than :attr:`!sys.maxsize` some features (such as
      :func:`len`) may raise :exc:`OverflowError`.  To prevent raising
      :exc:`!OverflowError` by truth value testing, an object must define a
      :meth:`__bool__` method.

.. method:: object.__length_hint__(self)

   Called to implement :func:`operator.length_hint`. Should return an estimated
   length for the object (which may be greater or less than the actual length).
   The length must be an integer ``>=`` 0. This method is purely an
   optimization and is never required for correctness.

   .. versionadded:: 3.4

.. index:: object: slice


Slicing is done exclusively with the following three methods. A call like

a[1:2] = b

is translated to

a[slice(1, 2, None)] = b

and so forth. Missing slice items are always filled in with None.

.. method:: object.__getitem__(self, key)

   Called to implement evaluation of ``self[key]``. For sequence types, the
   accepted keys should be integers and slice objects.  Note that the special
   interpretation of negative indexes (if the class wishes to emulate a sequence
   type) is up to the :meth:`__getitem__` method. If *key* is of an inappropriate
   type, :exc:`TypeError` may be raised; if of a value outside the set of indexes
   for the sequence (after any special interpretation of negative values),
   :exc:`IndexError` should be raised. For mapping types, if *key* is missing (not
   in the container), :exc:`KeyError` should be raised.

   .. note::

      :keyword:`for` loops expect that an :exc:`IndexError` will be raised for illegal
      indexes to allow proper detection of the end of the sequence.

.. method:: object.__setitem__(self, key, value)

   Called to implement assignment to ``self[key]``.  Same note as for
   :meth:`__getitem__`.  This should only be implemented for mappings if the
   objects support changes to the values for keys, or if new keys can be added, or
   for sequences if elements can be replaced.  The same exceptions should be raised
   for improper *key* values as for the :meth:`__getitem__` method.

.. method:: object.__delitem__(self, key)

   Called to implement deletion of ``self[key]``.  Same note as for
   :meth:`__getitem__`.  This should only be implemented for mappings if the
   objects support removal of keys, or for sequences if elements can be removed
   from the sequence.  The same exceptions should be raised for improper *key*
   values as for the :meth:`__getitem__` method.

.. method:: object.__missing__(self, key)

   Called by :class:`dict`\ .\ :meth:`__getitem__` to implement ``self[key]`` for dict subclasses
   when key is not in the dictionary.

.. method:: object.__iter__(self)

   This method is called when an iterator is required for a container. This method
   should return a new iterator object that can iterate over all the objects in the
   container.  For mappings, it should iterate over the keys of the container.

   Iterator objects also need to implement this method; they are required to return
   themselves.  For more information on iterator objects, see :ref:`typeiter`.

.. method:: object.__reversed__(self)

   Called (if present) by the :func:`reversed` built-in to implement
   reverse iteration.  It should return a new iterator object that iterates
   over all the objects in the container in reverse order.

   If the :meth:`__reversed__` method is not provided, the :func:`reversed`
   built-in will fall back to using the sequence protocol (:meth:`__len__` and
   :meth:`__getitem__`).  Objects that support the sequence protocol should
   only provide :meth:`__reversed__` if they can provide an implementation
   that is more efficient than the one provided by :func:`reversed`.

The membership test operators (:keyword:`in` and :keyword:`not in`) are normally implemented as an iteration through a sequence. However, container objects can supply the following special method with a more efficient implementation, which also does not require the object be a sequence.

.. method:: object.__contains__(self, item)

   Called to implement membership test operators.  Should return true if *item*
   is in *self*, false otherwise.  For mapping objects, this should consider the
   keys of the mapping rather than the values or the key-item pairs.

   For objects that don't define :meth:`__contains__`, the membership test first
   tries iteration via :meth:`__iter__`, then the old sequence iteration
   protocol via :meth:`__getitem__`, see :ref:`this section in the language
   reference <membership-test-details>`.

Emulating numeric types

The following methods can be defined to emulate numeric objects. Methods corresponding to operations that are not supported by the particular kind of number implemented (e.g., bitwise operations for non-integral numbers) should be left undefined.

.. method:: object.__add__(self, other)
            object.__sub__(self, other)
            object.__mul__(self, other)
            object.__matmul__(self, other)
            object.__truediv__(self, other)
            object.__floordiv__(self, other)
            object.__mod__(self, other)
            object.__divmod__(self, other)
            object.__pow__(self, other[, modulo])
            object.__lshift__(self, other)
            object.__rshift__(self, other)
            object.__and__(self, other)
            object.__xor__(self, other)
            object.__or__(self, other)

   .. index::
      builtin: divmod
      builtin: pow
      builtin: pow

   These methods are called to implement the binary arithmetic operations
   (``+``, ``-``, ``*``, ``@``, ``/``, ``//``, ``%``, :func:`divmod`,
   :func:`pow`, ``**``, ``<<``, ``>>``, ``&``, ``^``, ``|``).  For instance, to
   evaluate the expression ``x + y``, where *x* is an instance of a class that
   has an :meth:`__add__` method, ``x.__add__(y)`` is called.  The
   :meth:`__divmod__` method should be the equivalent to using
   :meth:`__floordiv__` and :meth:`__mod__`; it should not be related to
   :meth:`__truediv__`.  Note that :meth:`__pow__` should be defined to accept
   an optional third argument if the ternary version of the built-in :func:`pow`
   function is to be supported.

   If one of those methods does not support the operation with the supplied
   arguments, it should return ``NotImplemented``.

.. method:: object.__radd__(self, other)
            object.__rsub__(self, other)
            object.__rmul__(self, other)
            object.__rmatmul__(self, other)
            object.__rtruediv__(self, other)
            object.__rfloordiv__(self, other)
            object.__rmod__(self, other)
            object.__rdivmod__(self, other)
            object.__rpow__(self, other)
            object.__rlshift__(self, other)
            object.__rrshift__(self, other)
            object.__rand__(self, other)
            object.__rxor__(self, other)
            object.__ror__(self, other)

   .. index::
      builtin: divmod
      builtin: pow

   These methods are called to implement the binary arithmetic operations
   (``+``, ``-``, ``*``, ``@``, ``/``, ``//``, ``%``, :func:`divmod`,
   :func:`pow`, ``**``, ``<<``, ``>>``, ``&``, ``^``, ``|``) with reflected
   (swapped) operands.  These functions are only called if the left operand does
   not support the corresponding operation [#]_ and the operands are of different
   types. [#]_ For instance, to evaluate the expression ``x - y``, where *y* is
   an instance of a class that has an :meth:`__rsub__` method, ``y.__rsub__(x)``
   is called if ``x.__sub__(y)`` returns *NotImplemented*.

   .. index:: builtin: pow

   Note that ternary :func:`pow` will not try calling :meth:`__rpow__` (the
   coercion rules would become too complicated).

   .. note::

      If the right operand's type is a subclass of the left operand's type and that
      subclass provides the reflected method for the operation, this method will be
      called before the left operand's non-reflected method.  This behavior allows
      subclasses to override their ancestors' operations.

.. method:: object.__iadd__(self, other)
            object.__isub__(self, other)
            object.__imul__(self, other)
            object.__imatmul__(self, other)
            object.__itruediv__(self, other)
            object.__ifloordiv__(self, other)
            object.__imod__(self, other)
            object.__ipow__(self, other[, modulo])
            object.__ilshift__(self, other)
            object.__irshift__(self, other)
            object.__iand__(self, other)
            object.__ixor__(self, other)
            object.__ior__(self, other)

   These methods are called to implement the augmented arithmetic assignments
   (``+=``, ``-=``, ``*=``, ``@=``, ``/=``, ``//=``, ``%=``, ``**=``, ``<<=``,
   ``>>=``, ``&=``, ``^=``, ``|=``).  These methods should attempt to do the
   operation in-place (modifying *self*) and return the result (which could be,
   but does not have to be, *self*).  If a specific method is not defined, the
   augmented assignment falls back to the normal methods.  For instance, if *x*
   is an instance of a class with an :meth:`__iadd__` method, ``x += y`` is
   equivalent to ``x = x.__iadd__(y)`` . Otherwise, ``x.__add__(y)`` and
   ``y.__radd__(x)`` are considered, as with the evaluation of ``x + y``. In
   certain situations, augmented assignment can result in unexpected errors (see
   :ref:`faq-augmented-assignment-tuple-error`), but this behavior is in fact
   part of the data model.

.. method:: object.__neg__(self)

   .. index:: builtin: abs

   Called to implement the unary arithmetic operations (``-``, ``+``, :func:`abs`
   and ``~``).

.. method:: object.__complex__(self)

   .. index::
      builtin: complex
      builtin: int
      builtin: float

   Called to implement the built-in functions :func:`complex`,
   :func:`int` and :func:`float`.  Should return a value
   of the appropriate type.

.. method:: object.__index__(self)

   Called to implement :func:`operator.index`, and whenever Python needs to
   losslessly convert the numeric object to an integer object (such as in
   slicing, or in the built-in :func:`bin`, :func:`hex` and :func:`oct`
   functions). Presence of this method indicates that the numeric object is
   an integer type.  Must return an integer.

   .. note::

      In order to have a coherent integer type class, when :meth:`__index__` is
      defined :meth:`__int__` should also be defined, and both should return
      the same value.

.. method:: object.__round__(self, [,ndigits])

   .. index:: builtin: round

   Called to implement the built-in function :func:`round` and :mod:`math`
   functions :func:`~math.trunc`, :func:`~math.floor` and :func:`~math.ceil`.
   Unless *ndigits* is passed to :meth:`!__round__` all these methods should
   return the value of the object truncated to an :class:`~numbers.Integral`
   (typically an :class:`int`).

   If :meth:`__int__` is not defined then the built-in function :func:`int`
   falls back to :meth:`__trunc__`.

With Statement Context Managers

A :dfn:`context manager` is an object that defines the runtime context to be established when executing a :keyword:`with` statement. The context manager handles the entry into, and the exit from, the desired runtime context for the execution of the block of code. Context managers are normally invoked using the :keyword:`!with` statement (described in section :ref:`with`), but can also be used by directly invoking their methods.

.. index::
   statement: with
   single: context manager

Typical uses of context managers include saving and restoring various kinds of global state, locking and unlocking resources, closing opened files, etc.

For more information on context managers, see :ref:`typecontextmanager`.

.. method:: object.__enter__(self)

   Enter the runtime context related to this object. The :keyword:`with` statement
   will bind this method's return value to the target(s) specified in the
   :keyword:`!as` clause of the statement, if any.

.. method:: object.__exit__(self, exc_type, exc_value, traceback)

   Exit the runtime context related to this object. The parameters describe the
   exception that caused the context to be exited. If the context was exited
   without an exception, all three arguments will be :const:`None`.

   If an exception is supplied, and the method wishes to suppress the exception
   (i.e., prevent it from being propagated), it should return a true value.
   Otherwise, the exception will be processed normally upon exit from this method.

   Note that :meth:`__exit__` methods should not reraise the passed-in exception;
   this is the caller's responsibility.

.. seealso::

   :pep:`343` - The "with" statement
      The specification, background, and examples for the Python :keyword:`with`

Special method lookup

For custom classes, implicit invocations of special methods are only guaranteed to work correctly if defined on an object's type, not in the object's instance dictionary. That behaviour is the reason why the following code raises an exception:

>>> class C:
...     pass
>>> c = C()
>>> c.__len__ = lambda: 5
>>> len(c)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: object of type 'C' has no len()

The rationale behind this behaviour lies with a number of special methods such as :meth:`__hash__` and :meth:`__repr__` that are implemented by all objects, including type objects. If the implicit lookup of these methods used the conventional lookup process, they would fail when invoked on the type object itself:

>>> 1 .__hash__() == hash(1)
>>> int.__hash__() == hash(int)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
TypeError: descriptor '__hash__' of 'int' object needs an argument

Incorrectly attempting to invoke an unbound method of a class in this way is sometimes referred to as 'metaclass confusion', and is avoided by bypassing the instance when looking up special methods:

>>> type(1).__hash__(1) == hash(1)
>>> type(int).__hash__(int) == hash(int)

In addition to bypassing any instance attributes in the interest of correctness, implicit special method lookup generally also bypasses the :meth:`__getattribute__` method even of the object's metaclass:

>>> class Meta(type):
...     def __getattribute__(*args):
...         print("Metaclass getattribute invoked")
...         return type.__getattribute__(*args)
>>> class C(object, metaclass=Meta):
...     def __len__(self):
...         return 10
...     def __getattribute__(*args):
...         print("Class getattribute invoked")
...         return object.__getattribute__(*args)
>>> c = C()
>>> c.__len__()                 # Explicit lookup via instance
Class getattribute invoked
>>> type(c).__len__(c)          # Explicit lookup via type
Metaclass getattribute invoked
>>> len(c)                      # Implicit lookup

Bypassing the :meth:`__getattribute__` machinery in this fashion provides significant scope for speed optimisations within the interpreter, at the cost of some flexibility in the handling of special methods (the special method must be set on the class object itself in order to be consistently invoked by the interpreter).

.. index::
   single: coroutine


Awaitable Objects

An :term:`awaitable` object generally implements an :meth:`__await__` method. :term:`Coroutine` objects returned from :keyword:`async def` functions are awaitable.


The :term:`generator iterator` objects returned from generators decorated with :func:`types.coroutine` or :func:`asyncio.coroutine` are also awaitable, but they do not implement :meth:`__await__`.

.. method:: object.__await__(self)

   Must return an :term:`iterator`.  Should be used to implement
   :term:`awaitable` objects.  For instance, :class:`asyncio.Future` implements
   this method to be compatible with the :keyword:`await` expression.

.. versionadded:: 3.5

.. seealso:: :pep:`492` for additional information about awaitable objects.

Coroutine Objects

:term:`Coroutine` objects are :term:`awaitable` objects. A coroutine's execution can be controlled by calling :meth:`__await__` and iterating over the result. When the coroutine has finished executing and returns, the iterator raises :exc:`StopIteration`, and the exception's :attr:`~StopIteration.value` attribute holds the return value. If the coroutine raises an exception, it is propagated by the iterator. Coroutines should not directly raise unhandled :exc:`StopIteration` exceptions.

Coroutines also have the methods listed below, which are analogous to those of generators (see :ref:`generator-methods`). However, unlike generators, coroutines do not directly support iteration.

.. versionchanged:: 3.5.2
   It is a :exc:`RuntimeError` to await on a coroutine more than once.

.. method:: coroutine.send(value)

   Starts or resumes execution of the coroutine.  If *value* is ``None``,
   this is equivalent to advancing the iterator returned by
   :meth:`__await__`.  If *value* is not ``None``, this method delegates
   to the :meth:`~generator.send` method of the iterator that caused
   the coroutine to suspend.  The result (return value,
   :exc:`StopIteration`, or other exception) is the same as when
   iterating over the :meth:`__await__` return value, described above.

.. method:: coroutine.throw(type[, value[, traceback]])

   Raises the specified exception in the coroutine.  This method delegates
   to the :meth:`~generator.throw` method of the iterator that caused
   the coroutine to suspend, if it has such a method.  Otherwise,
   the exception is raised at the suspension point.  The result
   (return value, :exc:`StopIteration`, or other exception) is the same as
   when iterating over the :meth:`__await__` return value, described
   above.  If the exception is not caught in the coroutine, it propagates
   back to the caller.

.. method:: coroutine.close()

   Causes the coroutine to clean itself up and exit.  If the coroutine
   is suspended, this method first delegates to the :meth:`~generator.close`
   method of the iterator that caused the coroutine to suspend, if it
   has such a method.  Then it raises :exc:`GeneratorExit` at the
   suspension point, causing the coroutine to immediately clean itself up.
   Finally, the coroutine is marked as having finished executing, even if
   it was never started.

   Coroutine objects are automatically closed using the above process when
   they are about to be destroyed.

Asynchronous Iterators

An asynchronous iterator can call asynchronous code in its __anext__ method.

Asynchronous iterators can be used in an :keyword:`async for` statement.

.. method:: object.__aiter__(self)

   Must return an *asynchronous iterator* object.

.. method:: object.__anext__(self)

   Must return an *awaitable* resulting in a next value of the iterator.  Should
   raise a :exc:`StopAsyncIteration` error when the iteration is over.

An example of an asynchronous iterable object:

class Reader:
    async def readline(self):

    def __aiter__(self):
        return self

    async def __anext__(self):
        val = await self.readline()
        if val == b'':
            raise StopAsyncIteration
        return val
.. versionadded:: 3.5

.. versionchanged:: 3.7
   Prior to Python 3.7, ``__aiter__`` could return an *awaitable*
   that would resolve to an
   :term:`asynchronous iterator <asynchronous iterator>`.

   Starting with Python 3.7, ``__aiter__`` must return an
   asynchronous iterator object.  Returning anything else
   will result in a :exc:`TypeError` error.

Asynchronous Context Managers

An asynchronous context manager is a context manager that is able to suspend execution in its __aenter__ and __aexit__ methods.

Asynchronous context managers can be used in an :keyword:`async with` statement.

.. method:: object.__aenter__(self)

   This method is semantically similar to the :meth:`__enter__`, with only
   difference that it must return an *awaitable*.

.. method:: object.__aexit__(self, exc_type, exc_value, traceback)

   This method is semantically similar to the :meth:`__exit__`, with only
   difference that it must return an *awaitable*.

An example of an asynchronous context manager class:

class AsyncContextManager:
    async def __aenter__(self):
        await log('entering context')

    async def __aexit__(self, exc_type, exc, tb):
        await log('exiting context')
.. versionadded:: 3.5


[1]It is possible in some cases to change an object's type, under certain controlled conditions. It generally isn't a good idea though, since it can lead to some very strange behaviour if it is handled incorrectly.
[2]The :meth:`__hash__`, :meth:`__iter__`, :meth:`__reversed__`, and :meth:`__contains__` methods have special handling for this; others will still raise a :exc:`TypeError`, but may do so by relying on the behavior that None is not callable.
[3]"Does not support" here means that the class has no such method, or the method returns NotImplemented. Do not set the method to None if you want to force fallback to the right operand's reflected method—that will instead have the opposite effect of explicitly blocking such fallback.
[4]For operands of the same type, it is assumed that if the non-reflected method (such as :meth:`__add__`) fails the operation is not supported, which is why the reflected method is not called.
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