Glossary

.. _glossary:

Glossary

.. if you add new entries, keep the alphabetical sorting!

.. glossary::

>>> The default Python prompt of the interactive shell. Often seen for code examples which can be executed interactively in the interpreter.

... The default Python prompt of the interactive shell when entering code for an indented code block, when within a pair of matching left and right delimiters (parentheses, square brackets, curly braces or triple quotes), or after specifying a decorator.

2to3 A tool that tries to convert Python 2.x code to Python 3.x code by handling most of the incompatibilities which can be detected by parsing the source and traversing the parse tree.

  2to3 is available in the standard library as :mod:`lib2to3`; a standalone
  entry point is provided as :file:`Tools/scripts/2to3`.  See
  :ref:`2to3-reference`.

abstract base class Abstract base classes complement :term:duck-typing by providing a way to define interfaces when other techniques like :func:hasattr would be clumsy or subtly wrong (for example with :ref:magic methods <special-lookup>). ABCs introduce virtual subclasses, which are classes that don't inherit from a class but are still recognized by :func:isinstance and :func:issubclass; see the :mod:abc module documentation. Python comes with many built-in ABCs for data structures (in the :mod:collections.abc module), numbers (in the :mod:numbers module), streams (in the :mod:io module), import finders and loaders (in the :mod:importlib.abc module). You can create your own ABCs with the :mod:abc module.

annotation A label associated with a variable, a class attribute or a function parameter or return value, used by convention as a :term:type hint.

  Annotations of local variables cannot be accessed at runtime, but
  annotations of global variables, class attributes, and functions
  are stored in the :attr:`__annotations__`
  special attribute of modules, classes, and functions,
  respectively.

  See :term:`variable annotation`, :term:`function annotation`, :pep:`484`
  and :pep:`526`, which describe this functionality.

argument A value passed to a :term:function (or :term:method) when calling the function. There are two kinds of argument:

  * :dfn:`keyword argument`: an argument preceded by an identifier (e.g.
    ``name=``) in a function call or passed as a value in a dictionary
    preceded by ``**``.  For example, ``3`` and ``5`` are both keyword
    arguments in the following calls to :func:`complex`::

       complex(real=3, imag=5)
       complex(**{'real': 3, 'imag': 5})

  * :dfn:`positional argument`: an argument that is not a keyword argument.
    Positional arguments can appear at the beginning of an argument list
    and/or be passed as elements of an :term:`iterable` preceded by ``*``.
    For example, ``3`` and ``5`` are both positional arguments in the
    following calls::

       complex(3, 5)
       complex(*(3, 5))

  Arguments are assigned to the named local variables in a function body.
  See the :ref:`calls` section for the rules governing this assignment.
  Syntactically, any expression can be used to represent an argument; the
  evaluated value is assigned to the local variable.

  See also the :term:`parameter` glossary entry, the FAQ question on
  :ref:`the difference between arguments and parameters
  <faq-argument-vs-parameter>`, and :pep:`362`.

asynchronous context manager An object which controls the environment seen in an :keyword:async with statement by defining :meth:__aenter__ and :meth:__aexit__ methods. Introduced by :pep:492.

asynchronous generator A function which returns an :term:asynchronous generator iterator. It looks like a coroutine function defined with :keyword:async def except that it contains :keyword:yield expressions for producing a series of values usable in an :keyword:async for loop.

  Usually refers to an asynchronous generator function, but may refer to an
  *asynchronous generator iterator* in some contexts.  In cases where the
  intended meaning isn't clear, using the full terms avoids ambiguity.

  An asynchronous generator function may contain :keyword:`await`
  expressions as well as :keyword:`async for`, and :keyword:`async with`
  statements.

asynchronous generator iterator An object created by a :term:asynchronous generator function.

  This is an :term:`asynchronous iterator` which when called using the
  :meth:`__anext__` method returns an awaitable object which will execute
  the body of the asynchronous generator function until the next
  :keyword:`yield` expression.

  Each :keyword:`yield` temporarily suspends processing, remembering the
  location execution state (including local variables and pending
  try-statements).  When the *asynchronous generator iterator* effectively
  resumes with another awaitable returned by :meth:`__anext__`, it
  picks up where it left off.  See :pep:`492` and :pep:`525`.

asynchronous iterable An object, that can be used in an :keyword:async for statement. Must return an :term:asynchronous iterator from its :meth:__aiter__ method. Introduced by :pep:492.

asynchronous iterator An object that implements the :meth:__aiter__ and :meth:__anext__ methods. __anext__ must return an :term:awaitable object. :keyword:async for resolves the awaitables returned by an asynchronous iterator's :meth:__anext__ method until it raises a :exc:StopAsyncIteration exception. Introduced by :pep:492.

attribute A value associated with an object which is referenced by name using dotted expressions. For example, if an object o has an attribute a it would be referenced as o.a.

awaitable An object that can be used in an :keyword:await expression. Can be a :term:coroutine or an object with an :meth:__await__ method. See also :pep:492.

BDFL Benevolent Dictator For Life, a.k.a. Guido van Rossum <https://gvanrossum.github.io/>_, Python's creator.

binary file A :term:file object able to read and write :term:bytes-like objects <bytes-like object>. Examples of binary files are files opened in binary mode ('rb', 'wb' or 'rb+'), :data:sys.stdin.buffer, :data:sys.stdout.buffer, and instances of :class:io.BytesIO and :class:gzip.GzipFile.

  See also :term:`text file` for a file object able to read and write
  :class:`str` objects.

bytes-like object An object that supports the :ref:bufferobjects and can export a C-:term:contiguous buffer. This includes all :class:bytes, :class:bytearray, and :class:array.array objects, as well as many common :class:memoryview objects. Bytes-like objects can be used for various operations that work with binary data; these include compression, saving to a binary file, and sending over a socket.

  Some operations need the binary data to be mutable.  The documentation
  often refers to these as "read-write bytes-like objects".  Example
  mutable buffer objects include :class:`bytearray` and a
  :class:`memoryview` of a :class:`bytearray`.
  Other operations require the binary data to be stored in
  immutable objects ("read-only bytes-like objects"); examples
  of these include :class:`bytes` and a :class:`memoryview`
  of a :class:`bytes` object.

bytecode Python source code is compiled into bytecode, the internal representation of a Python program in the CPython interpreter. The bytecode is also cached in .pyc files so that executing the same file is faster the second time (recompilation from source to bytecode can be avoided). This "intermediate language" is said to run on a :term:virtual machine that executes the machine code corresponding to each bytecode. Do note that bytecodes are not expected to work between different Python virtual machines, nor to be stable between Python releases.

  A list of bytecode instructions can be found in the documentation for
  :ref:`the dis module <bytecodes>`.

class A template for creating user-defined objects. Class definitions normally contain method definitions which operate on instances of the class.

class variable A variable defined in a class and intended to be modified only at class level (i.e., not in an instance of the class).

coercion The implicit conversion of an instance of one type to another during an operation which involves two arguments of the same type. For example, int(3.15) converts the floating point number to the integer 3, but in 3+4.5, each argument is of a different type (one int, one float), and both must be converted to the same type before they can be added or it will raise a :exc:TypeError. Without coercion, all arguments of even compatible types would have to be normalized to the same value by the programmer, e.g., float(3)+4.5 rather than just 3+4.5.

complex number An extension of the familiar real number system in which all numbers are expressed as a sum of a real part and an imaginary part. Imaginary numbers are real multiples of the imaginary unit (the square root of -1), often written i in mathematics or j in engineering. Python has built-in support for complex numbers, which are written with this latter notation; the imaginary part is written with a j suffix, e.g., 3+1j. To get access to complex equivalents of the :mod:math module, use :mod:cmath. Use of complex numbers is a fairly advanced mathematical feature. If you're not aware of a need for them, it's almost certain you can safely ignore them.

context manager An object which controls the environment seen in a :keyword:with statement by defining :meth:__enter__ and :meth:__exit__ methods. See :pep:343.

contiguous .. index:: C-contiguous, Fortran contiguous

  A buffer is considered contiguous exactly if it is either
  *C-contiguous* or *Fortran contiguous*.  Zero-dimensional buffers are
  C and Fortran contiguous.  In one-dimensional arrays, the items
  must be laid out in memory next to each other, in order of
  increasing indexes starting from zero.  In multidimensional
  C-contiguous arrays, the last index varies the fastest when
  visiting items in order of memory address.  However, in
  Fortran contiguous arrays, the first index varies the fastest.

coroutine Coroutines is a more generalized form of subroutines. Subroutines are entered at one point and exited at another point. Coroutines can be entered, exited, and resumed at many different points. They can be implemented with the :keyword:async def statement. See also :pep:492.

coroutine function A function which returns a :term:coroutine object. A coroutine function may be defined with the :keyword:async def statement, and may contain :keyword:await, :keyword:async for, and :keyword:async with keywords. These were introduced by :pep:492.

CPython The canonical implementation of the Python programming language, as distributed on python.org <https://www.python.org>_. The term "CPython" is used when necessary to distinguish this implementation from others such as Jython or IronPython.

decorator A function returning another function, usually applied as a function transformation using the @wrapper syntax. Common examples for decorators are :func:classmethod and :func:staticmethod.

  The decorator syntax is merely syntactic sugar, the following two
  function definitions are semantically equivalent::

     def f(...):
         ...
     f = staticmethod(f)

     @staticmethod
     def f(...):
         ...

  The same concept exists for classes, but is less commonly used there.  See
  the documentation for :ref:`function definitions <function>` and
  :ref:`class definitions <class>` for more about decorators.

descriptor Any object which defines the methods :meth:__get__, :meth:__set__, or :meth:__delete__. When a class attribute is a descriptor, its special binding behavior is triggered upon attribute lookup. Normally, using a.b to get, set or delete an attribute looks up the object named b in the class dictionary for a, but if b is a descriptor, the respective descriptor method gets called. Understanding descriptors is a key to a deep understanding of Python because they are the basis for many features including functions, methods, properties, class methods, static methods, and reference to super classes.

  For more information about descriptors' methods, see :ref:`descriptors`.

dictionary An associative array, where arbitrary keys are mapped to values. The keys can be any object with :meth:__hash__ and :meth:__eq__ methods. Called a hash in Perl.

dictionary view The objects returned from :meth:dict.keys, :meth:dict.values, and :meth:dict.items are called dictionary views. They provide a dynamic view on the dictionary’s entries, which means that when the dictionary changes, the view reflects these changes. To force the dictionary view to become a full list use list(dictview). See :ref:dict-views.

docstring A string literal which appears as the first expression in a class, function or module. While ignored when the suite is executed, it is recognized by the compiler and put into the :attr:__doc__ attribute of the enclosing class, function or module. Since it is available via introspection, it is the canonical place for documentation of the object.

duck-typing A programming style which does not look at an object's type to determine if it has the right interface; instead, the method or attribute is simply called or used ("If it looks like a duck and quacks like a duck, it must be a duck.") By emphasizing interfaces rather than specific types, well-designed code improves its flexibility by allowing polymorphic substitution. Duck-typing avoids tests using :func:type or :func:isinstance. (Note, however, that duck-typing can be complemented with :term:abstract base classes <abstract base class>.) Instead, it typically employs :func:hasattr tests or :term:EAFP programming.

EAFP Easier to ask for forgiveness than permission. This common Python coding style assumes the existence of valid keys or attributes and catches exceptions if the assumption proves false. This clean and fast style is characterized by the presence of many :keyword:try and :keyword:except statements. The technique contrasts with the :term:LBYL style common to many other languages such as C.

expression A piece of syntax which can be evaluated to some value. In other words, an expression is an accumulation of expression elements like literals, names, attribute access, operators or function calls which all return a value. In contrast to many other languages, not all language constructs are expressions. There are also :term:statement\s which cannot be used as expressions, such as :keyword:while. Assignments are also statements, not expressions.

extension module A module written in C or C++, using Python's C API to interact with the core and with user code.

f-string String literals prefixed with 'f' or 'F' are commonly called "f-strings" which is short for :ref:formatted string literals <f-strings>. See also :pep:498.

file object An object exposing a file-oriented API (with methods such as :meth:read() or :meth:write()) to an underlying resource. Depending on the way it was created, a file object can mediate access to a real on-disk file or to another type of storage or communication device (for example standard input/output, in-memory buffers, sockets, pipes, etc.). File objects are also called :dfn:file-like objects or :dfn:streams.

  There are actually three categories of file objects: raw
  :term:`binary files <binary file>`, buffered
  :term:`binary files <binary file>` and :term:`text files <text file>`.
  Their interfaces are defined in the :mod:`io` module.  The canonical
  way to create a file object is by using the :func:`open` function.

file-like object A synonym for :term:file object.

finder An object that tries to find the :term:loader for a module that is being imported.

  Since Python 3.3, there are two types of finder: :term:`meta path finders
  <meta path finder>` for use with :data:`sys.meta_path`, and :term:`path
  entry finders <path entry finder>` for use with :data:`sys.path_hooks`.

  See :pep:`302`, :pep:`420` and :pep:`451` for much more detail.

floor division Mathematical division that rounds down to nearest integer. The floor division operator is //. For example, the expression 11 // 4 evaluates to 2 in contrast to the 2.75 returned by float true division. Note that (-11) // 4 is -3 because that is -2.75 rounded downward. See :pep:238.

function A series of statements which returns some value to a caller. It can also be passed zero or more :term:arguments <argument> which may be used in the execution of the body. See also :term:parameter, :term:method, and the :ref:function section.

function annotation An :term:annotation of a function parameter or return value.

  Function annotations are usually used for
  :term:`type hints <type hint>`: for example, this function is expected to take two
  :class:`int` arguments and is also expected to have an :class:`int`
  return value::

     def sum_two_numbers(a: int, b: int) -> int:
        return a + b

  Function annotation syntax is explained in section :ref:`function`.

  See :term:`variable annotation` and :pep:`484`,
  which describe this functionality.

future A pseudo-module which programmers can use to enable new language features which are not compatible with the current interpreter.

  By importing the :mod:`__future__` module and evaluating its variables,
  you can see when a new feature was first added to the language and when it
  becomes the default::

     >>> import __future__
     >>> __future__.division
     _Feature((2, 2, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0), 8192)

garbage collection The process of freeing memory when it is not used anymore. Python performs garbage collection via reference counting and a cyclic garbage collector that is able to detect and break reference cycles. The garbage collector can be controlled using the :mod:gc module.

  .. index:: single: generator

generator A function which returns a :term:generator iterator. It looks like a normal function except that it contains :keyword:yield expressions for producing a series of values usable in a for-loop or that can be retrieved one at a time with the :func:next function.

  Usually refers to a generator function, but may refer to a
  *generator iterator* in some contexts.  In cases where the intended
  meaning isn't clear, using the full terms avoids ambiguity.

generator iterator An object created by a :term:generator function.

  Each :keyword:`yield` temporarily suspends processing, remembering the
  location execution state (including local variables and pending
  try-statements).  When the *generator iterator* resumes, it picks up where
  it left off (in contrast to functions which start fresh on every
  invocation).

  .. index:: single: generator expression

generator expression An expression that returns an iterator. It looks like a normal expression followed by a :keyword:!for clause defining a loop variable, range, and an optional :keyword:!if clause. The combined expression generates values for an enclosing function::

     >>> sum(i*i for i in range(10))         # sum of squares 0, 1, 4, ... 81
     285

generic function A function composed of multiple functions implementing the same operation for different types. Which implementation should be used during a call is determined by the dispatch algorithm.

  See also the :term:`single dispatch` glossary entry, the
  :func:`functools.singledispatch` decorator, and :pep:`443`.

GIL See :term:global interpreter lock.

global interpreter lock The mechanism used by the :term:CPython interpreter to assure that only one thread executes Python :term:bytecode at a time. This simplifies the CPython implementation by making the object model (including critical built-in types such as :class:dict) implicitly safe against concurrent access. Locking the entire interpreter makes it easier for the interpreter to be multi-threaded, at the expense of much of the parallelism afforded by multi-processor machines.

  However, some extension modules, either standard or third-party,
  are designed so as to release the GIL when doing computationally-intensive
  tasks such as compression or hashing.  Also, the GIL is always released
  when doing I/O.

  Past efforts to create a "free-threaded" interpreter (one which locks
  shared data at a much finer granularity) have not been successful
  because performance suffered in the common single-processor case. It
  is believed that overcoming this performance issue would make the
  implementation much more complicated and therefore costlier to maintain.

hash-based pyc A bytecode cache file that uses the hash rather than the last-modified time of the corresponding source file to determine its validity. See :ref:pyc-invalidation.

hashable An object is hashable if it has a hash value which never changes during its lifetime (it needs a :meth:__hash__ method), and can be compared to other objects (it needs an :meth:__eq__ method). Hashable objects which compare equal must have the same hash value.

  Hashability makes an object usable as a dictionary key and a set member,
  because these data structures use the hash value internally.

  All of Python's immutable built-in objects are hashable; mutable
  containers (such as lists or dictionaries) are not.  Objects which are
  instances of user-defined classes are hashable by default.  They all
  compare unequal (except with themselves), and their hash value is derived
  from their :func:`id`.

IDLE An Integrated Development Environment for Python. IDLE is a basic editor and interpreter environment which ships with the standard distribution of Python.

immutable An object with a fixed value. Immutable objects include numbers, strings and tuples. Such an object cannot be altered. A new object has to be created if a different value has to be stored. They play an important role in places where a constant hash value is needed, for example as a key in a dictionary.

import path A list of locations (or :term:path entries <path entry>) that are searched by the :term:path based finder for modules to import. During import, this list of locations usually comes from :data:sys.path, but for subpackages it may also come from the parent package's __path__ attribute.

importing The process by which Python code in one module is made available to Python code in another module.

importer An object that both finds and loads a module; both a :term:finder and :term:loader object.

interactive Python has an interactive interpreter which means you can enter statements and expressions at the interpreter prompt, immediately execute them and see their results. Just launch python with no arguments (possibly by selecting it from your computer's main menu). It is a very powerful way to test out new ideas or inspect modules and packages (remember help(x)).

interpreted Python is an interpreted language, as opposed to a compiled one, though the distinction can be blurry because of the presence of the bytecode compiler. This means that source files can be run directly without explicitly creating an executable which is then run. Interpreted languages typically have a shorter development/debug cycle than compiled ones, though their programs generally also run more slowly. See also :term:interactive.

interpreter shutdown When asked to shut down, the Python interpreter enters a special phase where it gradually releases all allocated resources, such as modules and various critical internal structures. It also makes several calls to the :term:garbage collector <garbage collection>. This can trigger the execution of code in user-defined destructors or weakref callbacks. Code executed during the shutdown phase can encounter various exceptions as the resources it relies on may not function anymore (common examples are library modules or the warnings machinery).

  The main reason for interpreter shutdown is that the ``__main__`` module
  or the script being run has finished executing.

iterable An object capable of returning its members one at a time. Examples of iterables include all sequence types (such as :class:list, :class:str, and :class:tuple) and some non-sequence types like :class:dict, :term:file objects <file object>, and objects of any classes you define with an :meth:__iter__ method or with a :meth:__getitem__ method that implements :term:Sequence semantics.

  Iterables can be
  used in a :keyword:`for` loop and in many other places where a sequence is
  needed (:func:`zip`, :func:`map`, ...).  When an iterable object is passed
  as an argument to the built-in function :func:`iter`, it returns an
  iterator for the object.  This iterator is good for one pass over the set
  of values.  When using iterables, it is usually not necessary to call
  :func:`iter` or deal with iterator objects yourself.  The ``for``
  statement does that automatically for you, creating a temporary unnamed
  variable to hold the iterator for the duration of the loop.  See also
  :term:`iterator`, :term:`sequence`, and :term:`generator`.

iterator An object representing a stream of data. Repeated calls to the iterator's :meth:~iterator.__next__ method (or passing it to the built-in function :func:next) return successive items in the stream. When no more data are available a :exc:StopIteration exception is raised instead. At this point, the iterator object is exhausted and any further calls to its :meth:__next__ method just raise :exc:StopIteration again. Iterators are required to have an :meth:__iter__ method that returns the iterator object itself so every iterator is also iterable and may be used in most places where other iterables are accepted. One notable exception is code which attempts multiple iteration passes. A container object (such as a :class:list) produces a fresh new iterator each time you pass it to the :func:iter function or use it in a :keyword:for loop. Attempting this with an iterator will just return the same exhausted iterator object used in the previous iteration pass, making it appear like an empty container.

  More information can be found in :ref:`typeiter`.

key function A key function or collation function is a callable that returns a value used for sorting or ordering. For example, :func:locale.strxfrm is used to produce a sort key that is aware of locale specific sort conventions.

  A number of tools in Python accept key functions to control how elements
  are ordered or grouped.  They include :func:`min`, :func:`max`,
  :func:`sorted`, :meth:`list.sort`, :func:`heapq.merge`,
  :func:`heapq.nsmallest`, :func:`heapq.nlargest`, and
  :func:`itertools.groupby`.

  There are several ways to create a key function.  For example. the
  :meth:`str.lower` method can serve as a key function for case insensitive
  sorts.  Alternatively, a key function can be built from a
  :keyword:`lambda` expression such as ``lambda r: (r[0], r[2])``.  Also,
  the :mod:`operator` module provides three key function constructors:
  :func:`~operator.attrgetter`, :func:`~operator.itemgetter`, and
  :func:`~operator.methodcaller`.  See the :ref:`Sorting HOW TO
  <sortinghowto>` for examples of how to create and use key functions.

keyword argument See :term:argument.

lambda An anonymous inline function consisting of a single :term:expression which is evaluated when the function is called. The syntax to create a lambda function is lambda [parameters]: expression

LBYL Look before you leap. This coding style explicitly tests for pre-conditions before making calls or lookups. This style contrasts with the :term:EAFP approach and is characterized by the presence of many :keyword:if statements.

  In a multi-threaded environment, the LBYL approach can risk introducing a
  race condition between "the looking" and "the leaping".  For example, the
  code, ``if key in mapping: return mapping[key]`` can fail if another
  thread removes *key* from *mapping* after the test, but before the lookup.
  This issue can be solved with locks or by using the EAFP approach.

list A built-in Python :term:sequence. Despite its name it is more akin to an array in other languages than to a linked list since access to elements is O(1).

list comprehension A compact way to process all or part of the elements in a sequence and return a list with the results. result = ['{:#04x}'.format(x) for x in range(256) if x % 2 == 0] generates a list of strings containing even hex numbers (0x..) in the range from 0 to 255. The :keyword:if clause is optional. If omitted, all elements in range(256) are processed.

loader An object that loads a module. It must define a method named :meth:load_module. A loader is typically returned by a :term:finder. See :pep:302 for details and :class:importlib.abc.Loader for an :term:abstract base class.

mapping A container object that supports arbitrary key lookups and implements the methods specified in the :class:~collections.abc.Mapping or :class:~collections.abc.MutableMapping :ref:abstract base classes <collections-abstract-base-classes>. Examples include :class:dict, :class:collections.defaultdict, :class:collections.OrderedDict and :class:collections.Counter.

meta path finder A :term:finder returned by a search of :data:sys.meta_path. Meta path finders are related to, but different from :term:path entry finders <path entry finder>.

  See :class:`importlib.abc.MetaPathFinder` for the methods that meta path
  finders implement.

metaclass The class of a class. Class definitions create a class name, a class dictionary, and a list of base classes. The metaclass is responsible for taking those three arguments and creating the class. Most object oriented programming languages provide a default implementation. What makes Python special is that it is possible to create custom metaclasses. Most users never need this tool, but when the need arises, metaclasses can provide powerful, elegant solutions. They have been used for logging attribute access, adding thread-safety, tracking object creation, implementing singletons, and many other tasks.

  More information can be found in :ref:`metaclasses`.

method A function which is defined inside a class body. If called as an attribute of an instance of that class, the method will get the instance object as its first :term:argument (which is usually called self). See :term:function and :term:nested scope.

method resolution order Method Resolution Order is the order in which base classes are searched for a member during lookup. See The Python 2.3 Method Resolution Order <https://www.python.org/download/releases/2.3/mro/>_ for details of the algorithm used by the Python interpreter since the 2.3 release.

module An object that serves as an organizational unit of Python code. Modules have a namespace containing arbitrary Python objects. Modules are loaded into Python by the process of :term:importing.

  See also :term:`package`.

module spec A namespace containing the import-related information used to load a module. An instance of :class:importlib.machinery.ModuleSpec.

MRO See :term:method resolution order.

mutable Mutable objects can change their value but keep their :func:id. See also :term:immutable.

named tuple Any tuple-like class whose indexable elements are also accessible using named attributes (for example, :func:time.localtime returns a tuple-like object where the year is accessible either with an index such as t[0] or with a named attribute like t.tm_year).

  A named tuple can be a built-in type such as :class:`time.struct_time`,
  or it can be created with a regular class definition.  A full featured
  named tuple can also be created with the factory function
  :func:`collections.namedtuple`.  The latter approach automatically
  provides extra features such as a self-documenting representation like
  ``Employee(name='jones', title='programmer')``.

namespace The place where a variable is stored. Namespaces are implemented as dictionaries. There are the local, global and built-in namespaces as well as nested namespaces in objects (in methods). Namespaces support modularity by preventing naming conflicts. For instance, the functions :func:builtins.open <.open> and :func:os.open are distinguished by their namespaces. Namespaces also aid readability and maintainability by making it clear which module implements a function. For instance, writing :func:random.seed or :func:itertools.islice makes it clear that those functions are implemented by the :mod:random and :mod:itertools modules, respectively.

namespace package A :pep:420 :term:package which serves only as a container for subpackages. Namespace packages may have no physical representation, and specifically are not like a :term:regular package because they have no __init__.py file.

  See also :term:`module`.

nested scope The ability to refer to a variable in an enclosing definition. For instance, a function defined inside another function can refer to variables in the outer function. Note that nested scopes by default work only for reference and not for assignment. Local variables both read and write in the innermost scope. Likewise, global variables read and write to the global namespace. The :keyword:nonlocal allows writing to outer scopes.

new-style class Old name for the flavor of classes now used for all class objects. In earlier Python versions, only new-style classes could use Python's newer, versatile features like :attr:~object.__slots__, descriptors, properties, :meth:__getattribute__, class methods, and static methods.

object Any data with state (attributes or value) and defined behavior (methods). Also the ultimate base class of any :term:new-style class.

package A Python :term:module which can contain submodules or recursively, subpackages. Technically, a package is a Python module with an __path__ attribute.

  See also :term:`regular package` and :term:`namespace package`.

parameter A named entity in a :term:function (or method) definition that specifies an :term:argument (or in some cases, arguments) that the function can accept. There are five kinds of parameter:

  * :dfn:`positional-or-keyword`: specifies an argument that can be passed
    either :term:`positionally <argument>` or as a :term:`keyword argument
    <argument>`.  This is the default kind of parameter, for example *foo*
    and *bar* in the following::

       def func(foo, bar=None): ...

  .. _positional-only_parameter:

  * :dfn:`positional-only`: specifies an argument that can be supplied only
    by position.  Python has no syntax for defining positional-only
    parameters.  However, some built-in functions have positional-only
    parameters (e.g. :func:`abs`).

  .. _keyword-only_parameter:

  * :dfn:`keyword-only`: specifies an argument that can be supplied only
    by keyword.  Keyword-only parameters can be defined by including a
    single var-positional parameter or bare ``*`` in the parameter list
    of the function definition before them, for example *kw_only1* and
    *kw_only2* in the following::

       def func(arg, *, kw_only1, kw_only2): ...

  * :dfn:`var-positional`: specifies that an arbitrary sequence of
    positional arguments can be provided (in addition to any positional
    arguments already accepted by other parameters).  Such a parameter can
    be defined by prepending the parameter name with ``*``, for example
    *args* in the following::

       def func(*args, **kwargs): ...

  * :dfn:`var-keyword`: specifies that arbitrarily many keyword arguments
    can be provided (in addition to any keyword arguments already accepted
    by other parameters).  Such a parameter can be defined by prepending
    the parameter name with ``**``, for example *kwargs* in the example
    above.

  Parameters can specify both optional and required arguments, as well as
  default values for some optional arguments.

  See also the :term:`argument` glossary entry, the FAQ question on
  :ref:`the difference between arguments and parameters
  <faq-argument-vs-parameter>`, the :class:`inspect.Parameter` class, the
  :ref:`function` section, and :pep:`362`.

path entry A single location on the :term:import path which the :term:path based finder consults to find modules for importing.

path entry finder A :term:finder returned by a callable on :data:sys.path_hooks (i.e. a :term:path entry hook) which knows how to locate modules given a :term:path entry.

  See :class:`importlib.abc.PathEntryFinder` for the methods that path entry
  finders implement.

path entry hook A callable on the :data:sys.path_hook list which returns a :term:path entry finder if it knows how to find modules on a specific :term:path entry.

path based finder One of the default :term:meta path finders <meta path finder> which searches an :term:import path for modules.

path-like object An object representing a file system path. A path-like object is either a :class:str or :class:bytes object representing a path, or an object implementing the :class:os.PathLike protocol. An object that supports the :class:os.PathLike protocol can be converted to a :class:str or :class:bytes file system path by calling the :func:os.fspath function; :func:os.fsdecode and :func:os.fsencode can be used to guarantee a :class:str or :class:bytes result instead, respectively. Introduced by :pep:519.

PEP Python Enhancement Proposal. A PEP is a design document providing information to the Python community, or describing a new feature for Python or its processes or environment. PEPs should provide a concise technical specification and a rationale for proposed features.

  PEPs are intended to be the primary mechanisms for proposing major new
  features, for collecting community input on an issue, and for documenting
  the design decisions that have gone into Python. The PEP author is
  responsible for building consensus within the community and documenting
  dissenting opinions.

  See :pep:`1`.

portion A set of files in a single directory (possibly stored in a zip file) that contribute to a namespace package, as defined in :pep:420.

positional argument See :term:argument.

provisional API A provisional API is one which has been deliberately excluded from the standard library's backwards compatibility guarantees. While major changes to such interfaces are not expected, as long as they are marked provisional, backwards incompatible changes (up to and including removal of the interface) may occur if deemed necessary by core developers. Such changes will not be made gratuitously -- they will occur only if serious fundamental flaws are uncovered that were missed prior to the inclusion of the API.

  Even for provisional APIs, backwards incompatible changes are seen as
  a "solution of last resort" - every attempt will still be made to find
  a backwards compatible resolution to any identified problems.

  This process allows the standard library to continue to evolve over
  time, without locking in problematic design errors for extended periods
  of time.  See :pep:`411` for more details.

provisional package See :term:provisional API.

Python 3000 Nickname for the Python 3.x release line (coined long ago when the release of version 3 was something in the distant future.) This is also abbreviated "Py3k".

Pythonic An idea or piece of code which closely follows the most common idioms of the Python language, rather than implementing code using concepts common to other languages. For example, a common idiom in Python is to loop over all elements of an iterable using a :keyword:for statement. Many other languages don't have this type of construct, so people unfamiliar with Python sometimes use a numerical counter instead::

      for i in range(len(food)):
          print(food[i])

  As opposed to the cleaner, Pythonic method::

     for piece in food:
         print(piece)

qualified name A dotted name showing the "path" from a module's global scope to a class, function or method defined in that module, as defined in :pep:3155. For top-level functions and classes, the qualified name is the same as the object's name::

     >>> class C:
     ...     class D:
     ...         def meth(self):
     ...             pass
     ...
     >>> C.__qualname__
     'C'
     >>> C.D.__qualname__
     'C.D'
     >>> C.D.meth.__qualname__
     'C.D.meth'

  When used to refer to modules, the *fully qualified name* means the
  entire dotted path to the module, including any parent packages,
  e.g. ``email.mime.text``::

     >>> import email.mime.text
     >>> email.mime.text.__name__
     'email.mime.text'

reference count The number of references to an object. When the reference count of an object drops to zero, it is deallocated. Reference counting is generally not visible to Python code, but it is a key element of the :term:CPython implementation. The :mod:sys module defines a :func:~sys.getrefcount function that programmers can call to return the reference count for a particular object.

regular package A traditional :term:package, such as a directory containing an __init__.py file.

  See also :term:`namespace package`.

slots A declaration inside a class that saves memory by pre-declaring space for instance attributes and eliminating instance dictionaries. Though popular, the technique is somewhat tricky to get right and is best reserved for rare cases where there are large numbers of instances in a memory-critical application.

sequence An :term:iterable which supports efficient element access using integer indices via the :meth:__getitem__ special method and defines a :meth:__len__ method that returns the length of the sequence. Some built-in sequence types are :class:list, :class:str, :class:tuple, and :class:bytes. Note that :class:dict also supports :meth:__getitem__ and :meth:__len__, but is considered a mapping rather than a sequence because the lookups use arbitrary :term:immutable keys rather than integers.

  The :class:`collections.abc.Sequence` abstract base class
  defines a much richer interface that goes beyond just
  :meth:`__getitem__` and :meth:`__len__`, adding :meth:`count`,
  :meth:`index`, :meth:`__contains__`, and
  :meth:`__reversed__`. Types that implement this expanded
  interface can be registered explicitly using
  :func:`~abc.register`.

single dispatch A form of :term:generic function dispatch where the implementation is chosen based on the type of a single argument.

slice An object usually containing a portion of a :term:sequence. A slice is created using the subscript notation, [] with colons between numbers when several are given, such as in variable_name[1:3:5]. The bracket (subscript) notation uses :class:slice objects internally.

special method A method that is called implicitly by Python to execute a certain operation on a type, such as addition. Such methods have names starting and ending with double underscores. Special methods are documented in :ref:specialnames.

statement A statement is part of a suite (a "block" of code). A statement is either an :term:expression or one of several constructs with a keyword, such as :keyword:if, :keyword:while or :keyword:for.

struct sequence A tuple with named elements. Struct sequences expose an interface similar to :term:named tuple in that elements can be accessed either by index or as an attribute. However, they do not have any of the named tuple methods like :meth:~collections.somenamedtuple._make or :meth:~collections.somenamedtuple._asdict. Examples of struct sequences include :data:sys.float_info and the return value of :func:os.stat.

text encoding A codec which encodes Unicode strings to bytes.

text file A :term:file object able to read and write :class:str objects. Often, a text file actually accesses a byte-oriented datastream and handles the :term:text encoding automatically. Examples of text files are files opened in text mode ('r' or 'w'), :data:sys.stdin, :data:sys.stdout, and instances of :class:io.StringIO.

  See also :term:`binary file` for a file object able to read and write
  :term:`bytes-like objects <bytes-like object>`.

triple-quoted string A string which is bound by three instances of either a quotation mark (") or an apostrophe ('). While they don't provide any functionality not available with single-quoted strings, they are useful for a number of reasons. They allow you to include unescaped single and double quotes within a string and they can span multiple lines without the use of the continuation character, making them especially useful when writing docstrings.

type The type of a Python object determines what kind of object it is; every object has a type. An object's type is accessible as its :attr:~instance.__class__ attribute or can be retrieved with type(obj).

type alias A synonym for a type, created by assigning the type to an identifier.

  Type aliases are useful for simplifying :term:`type hints <type hint>`.
  For example::

     from typing import List, Tuple

     def remove_gray_shades(
             colors: List[Tuple[int, int, int]]) -> List[Tuple[int, int, int]]:
         pass

  could be made more readable like this::

     from typing import List, Tuple

     Color = Tuple[int, int, int]

     def remove_gray_shades(colors: List[Color]) -> List[Color]:
         pass

  See :mod:`typing` and :pep:`484`, which describe this functionality.

type hint An :term:annotation that specifies the expected type for a variable, a class attribute, or a function parameter or return value.

  Type hints are optional and are not enforced by Python but
  they are useful to static type analysis tools, and aid IDEs with code
  completion and refactoring.

  Type hints of global variables, class attributes, and functions,
  but not local variables, can be accessed using
  :func:`typing.get_type_hints`.

  See :mod:`typing` and :pep:`484`, which describe this functionality.

universal newlines A manner of interpreting text streams in which all of the following are recognized as ending a line: the Unix end-of-line convention '\n', the Windows convention '\r\n', and the old Macintosh convention '\r'. See :pep:278 and :pep:3116, as well as :func:bytes.splitlines for an additional use.

variable annotation An :term:annotation of a variable or a class attribute.

  When annotating a variable or a class attribute, assignment is optional::

     class C:
         field: 'annotation'

  Variable annotations are usually used for
  :term:`type hints <type hint>`: for example this variable is expected to take
  :class:`int` values::

     count: int = 0

  Variable annotation syntax is explained in section :ref:`annassign`.

  See :term:`function annotation`, :pep:`484`
  and :pep:`526`, which describe this functionality.

virtual environment A cooperatively isolated runtime environment that allows Python users and applications to install and upgrade Python distribution packages without interfering with the behaviour of other Python applications running on the same system.

  See also :mod:`venv`.

virtual machine A computer defined entirely in software. Python's virtual machine executes the :term:bytecode emitted by the bytecode compiler.

Zen of Python Listing of Python design principles and philosophies that are helpful in understanding and using the language. The listing can be found by typing "import this" at the interactive prompt.