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.. _datamodel:

**********
Data model
**********

.. _objects:

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

.. XXX it *is* now possible in some cases to change an object's
   type, under certain controlled conditions

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.
[#]_

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``.)

.. _types:

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.

None
   .. 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.

NotImplemented
   .. 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.)  It
   should not be evaluated in a boolean context.

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

.. versionchanged:: 3.9
      Evaluating ``NotImplemented`` in a boolean context is deprecated. While
      it currently evaluates as true, it will emit a :exc:`DeprecationWarning`.
      It will raise a :exc:`TypeError` in a future version of Python.

Ellipsis
   .. 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.

:class:`numbers.Number`
   .. 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.

The string representations of the numeric classes, computed by
   :meth:`__repr__` and :meth:`__str__`, have the following
   properties:

* They are valid numeric literals which, when passed to their
     class constructor, produce an object having the value of the
     original numeric.

* The representation is in base 10, when possible.

* Leading zeros, possibly excepting a single zero before a
     decimal point, are not shown.

* Trailing zeros, possibly excepting a single zero after a
     decimal point, are not shown.

* A sign is shown only when the number is negative.

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

:class:`numbers.Integral`
      .. 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``.

Sequences
   .. 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

Strings
         .. 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.

Tuples
         .. 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.

Bytes
         .. 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:

Lists
         .. 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:

Sets
      .. 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.

Mappings
   .. 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:

Dictionaries
      .. 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 preserve insertion order, meaning that keys will be produced
      in the same order they were added sequentially over the dictionary.
      Replacing an existing key does not change the order, however removing a key
      and re-inserting it will add it to the end instead of keeping its old place.

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.

.. versionchanged:: 3.7
         Dictionaries did not preserve insertion order in versions of Python before 3.6.
         In CPython 3.6, insertion order was preserved, but it was considered
         an implementation detail at that time rather than a language guarantee.

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

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
      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.

Modules
   .. 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
   https://www.python.org/download/releases/2.3/mro/.

.. XXX: Could we add that MRO doc as an appendix to the language ref?

.. 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_posonlyargcount (code object attribute)
         single: co_kwonlyargcount (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 total number of positional arguments
      (including positional-only arguments and arguments with default values);
      :attr:`co_posonlyargcount` is the number of positional-only arguments
      (including arguments with default values); :attr:`co_kwonlyargcount` is
      the number of keyword-only 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; :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:

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:

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.

.. _specialnames:

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__`). [#]_

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.)

.. _customization:

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__` is invoked during object construction and it returns an
   instance or subclass 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 the object constructor.

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
      traceback.

.. 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(x), '')``.

.. _richcmpfuncs:
.. 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
   ``x.__ge__(y)``.

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, ``object`` implements :meth:`__eq__` by using ``is``, returning
   ``NotImplemented`` in the case of a false comparison:
   ``True if x is y else NotImplemented``. For :meth:`__ne__`, by default it
   delegates to :meth:`__eq__` and inverts the result unless it is
   ``NotImplemented``.  There are no other implied relationships among the
   comparison operators or default implementations; 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.name, 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
   bucket).

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, collections.abc.Hashable)``.

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, collections.abc.Hashable)`` call.

.. note::

By default, the :meth:`__hash__` values of str and bytes 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
      http://www.ocert.org/advisories/ocert-2011-003.html 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
   true.

.. _attribute-access:

Customizing attribute access
----------------------------

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

.. XXX explain how descriptors interfere here!

.. 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`.

.. audit-event:: object.__getattr__ obj,name object.__getattribute__

For certain sensitive attribute accesses, raises an
      :ref:`auditing event <auditing>` ``object.__getattr__`` with arguments
      ``obj`` and ``name``.

.. 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)``.

.. audit-event:: object.__setattr__ obj,name,value object.__setattr__

For certain sensitive attribute assignments, raises an
      :ref:`auditing event <auditing>` ``object.__setattr__`` with arguments
      ``obj``, ``name``, ``value``.

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

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

.. audit-event:: object.__delattr__ obj,name object.__delattr__

For certain sensitive attribute deletions, raises an
      :ref:`auditing event <auditing>` ``object.__delattr__`` with arguments
      ``obj`` and ``name``.

.. 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 sequence 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

.. note::
   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.

.. _descriptors:

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=None)

Called to get the attribute of the owner class (class attribute access) or
   of an instance of that class (instance attribute access). The optional
   *owner* argument is 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` exception.

:PEP:`252` specifies that :meth:`__get__` is callable with one or two
   arguments.  Python's own built-in descriptors support this specification;
   however, it is likely that some third-party tools have descriptors
   that require both arguments.  Python's own :meth:`__getattribute__`
   implementation always passes in both arguments whether they are required
   or not.

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

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

Note, adding :meth:`__set__` or :meth:`__delete__` changes the kind of
   descriptor to a "data descriptor".  See :ref:`descriptor-invocation` for
   more details.

.. 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*.

.. note::

:meth:`__set_name__` is only called implicitly as part of the
      :class:`type` constructor, so it will need to be called explicitly with
      the appropriate parameters when a descriptor is added to a class after
      initial creation::

class A:
            pass
         descr = custom_descriptor()
         A.attr = descr
         descr.__set_name__(A, 'attr')

See :ref:`class-object-creation` for more details.

.. 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).

.. _descriptor-invocation:

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:`__get__` and :meth:`__set__` (and/or :meth:`__delete__`) 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:

__slots__
^^^^^^^^^

*__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`.

* If an iterator is used for *__slots__* then a descriptor is created for each
  of the iterator's values. However, the *__slots__* attribute will be an empty
  iterator.

.. _class-customization:

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):
               super().__init_subclass__(**kwargs)
               cls.default_name = default_name

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

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
      ``type(cls)``.

.. versionadded:: 3.6

.. _metaclasses:

Metaclasses
^^^^^^^^^^^

.. 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):
       pass

class MyClass(metaclass=Meta):
       pass

class MySubclass(MyClass):
       pass

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``.

.. _prepare:

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). The
``__prepare__`` method should be implemented as a :func:`classmethod`. The
namespace returned by ``__prepare__`` is passed in to ``__new__``, but when
the final class object is created the namespace is copied into a new ``dict``.

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.

.. _class-object-creation:

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,
   class)``.

.. 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,
   class)``.

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

.. _callable-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, ...)`` roughly translates to ``type(x).__call__(x, arg1, ...)``.

.. _sequence-types:

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:`collections.abc` module provides a
:class:`~collections.abc.MutableMapping`
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 iterate
through the object's 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. The return value may also be
   :const:`NotImplemented`, which is treated the same as if the
   ``__length_hint__`` method didn't exist at all. This method is purely an
   optimization and is never required for correctness.

.. versionadded:: 3.4

.. index:: object: slice

.. note::

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 container. However, container objects can
supply the following special method with a more efficient implementation, which
also does not require the object be iterable.

.. 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>`.

.. _numeric-types:

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[, modulo])
            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 a different implementation of 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.

.. note::

Due to a bug in the dispatching mechanism for ``**=``, a class that
      defines :meth:`__ipow__` but returns ``NotImplemented`` would fail to
      fall back to ``x.__pow__(y)`` and ``y.__rpow__(x)``. This bug is fixed
      in Python 3.10.

.. method:: object.__neg__(self)
            object.__pos__(self)
            object.__abs__(self)
            object.__invert__(self)

.. index:: builtin: abs

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

.. method:: object.__complex__(self)
            object.__int__(self)
            object.__float__(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.

If :meth:`__int__`, :meth:`__float__` and :meth:`__complex__` are not
   defined then corresponding built-in functions :func:`int`, :func:`float`
   and :func:`complex` fall back to :meth:`__index__`.

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

.. 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__`.

.. _context-managers:

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`
      statement.

.. _special-lookup:

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

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
   10
   >>> type(c).__len__(c)          # Explicit lookup via type
   Metaclass getattribute invoked
   10
   >>> len(c)                      # Implicit lookup
   10

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

Coroutines
==========

Awaitable Objects
-----------------

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

.. note::

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:

Coroutine Objects
-----------------

:term:`Coroutine objects <coroutine>` 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.

.. _async-iterators:

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.

.. _async-context-managers:

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)

Semantically similar to :meth:`__enter__`, the only
   difference being that it must return an *awaitable*.

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

Semantically similar to :meth:`__exit__`, the only
   difference being 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

.. rubric:: Footnotes

.. [#] 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.

.. [#] 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.

.. [#] "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.

.. [#] For operands of the same type, it is assumed that if the non-reflected
   method -- such as :meth:`__add__` -- fails then the overall operation is not
   supported, which is why the reflected method is not called.

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