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1.. _glossary:
2
3********
4Glossary
5********
6
7.. if you add new entries, keep the alphabetical sorting!
8
9.. glossary::
10
11   ``>>>``
12      The default Python prompt of the interactive shell.  Often seen for code
13      examples which can be executed interactively in the interpreter.
14
15   ``...``
16      Can refer to:
17
18      * The default Python prompt of the interactive shell when entering the
19        code for an indented code block, when within a pair of matching left and
20        right delimiters (parentheses, square brackets, curly braces or triple
21        quotes), or after specifying a decorator.
22
23      * The :const:`Ellipsis` built-in constant.
24
25   2to3
26      A tool that tries to convert Python 2.x code to Python 3.x code by
27      handling most of the incompatibilities which can be detected by parsing the
28      source and traversing the parse tree.
29
30      2to3 is available in the standard library as :mod:`lib2to3`; a standalone
31      entry point is provided as :file:`Tools/scripts/2to3`.  See
32      :ref:`2to3-reference`.
33
34   abstract base class
35      Abstract base classes complement :term:`duck-typing` by
36      providing a way to define interfaces when other techniques like
37      :func:`hasattr` would be clumsy or subtly wrong (for example with
38      :ref:`magic methods <special-lookup>`).  ABCs introduce virtual
39      subclasses, which are classes that don't inherit from a class but are
40      still recognized by :func:`isinstance` and :func:`issubclass`; see the
41      :mod:`abc` module documentation.  Python comes with many built-in ABCs for
42      data structures (in the :mod:`collections.abc` module), numbers (in the
43      :mod:`numbers` module), streams (in the :mod:`io` module), import finders
44      and loaders (in the :mod:`importlib.abc` module).  You can create your own
45      ABCs with the :mod:`abc` module.
46
47   annotation
48      A label associated with a variable, a class
49      attribute or a function parameter or return value,
50      used by convention as a :term:`type hint`.
51
52      Annotations of local variables cannot be accessed at runtime, but
53      annotations of global variables, class attributes, and functions
54      are stored in the :attr:`__annotations__`
55      special attribute of modules, classes, and functions,
56      respectively.
57
58      See :term:`variable annotation`, :term:`function annotation`, :pep:`484`
59      and :pep:`526`, which describe this functionality.
60
61   argument
62      A value passed to a :term:`function` (or :term:`method`) when calling the
63      function.  There are two kinds of argument:
64
65      * :dfn:`keyword argument`: an argument preceded by an identifier (e.g.
66        ``name=``) in a function call or passed as a value in a dictionary
67        preceded by ``**``.  For example, ``3`` and ``5`` are both keyword
68        arguments in the following calls to :func:`complex`::
69
70           complex(real=3, imag=5)
71           complex(**{'real': 3, 'imag': 5})
72
73      * :dfn:`positional argument`: an argument that is not a keyword argument.
74        Positional arguments can appear at the beginning of an argument list
75        and/or be passed as elements of an :term:`iterable` preceded by ``*``.
76        For example, ``3`` and ``5`` are both positional arguments in the
77        following calls::
78
79           complex(3, 5)
80           complex(*(3, 5))
81
82      Arguments are assigned to the named local variables in a function body.
83      See the :ref:`calls` section for the rules governing this assignment.
84      Syntactically, any expression can be used to represent an argument; the
85      evaluated value is assigned to the local variable.
86
87      See also the :term:`parameter` glossary entry, the FAQ question on
88      :ref:`the difference between arguments and parameters
89      <faq-argument-vs-parameter>`, and :pep:`362`.
90
91   asynchronous context manager
92      An object which controls the environment seen in an
93      :keyword:`async with` statement by defining :meth:`__aenter__` and
94      :meth:`__aexit__` methods.  Introduced by :pep:`492`.
95
96   asynchronous generator
97      A function which returns an :term:`asynchronous generator iterator`.  It
98      looks like a coroutine function defined with :keyword:`async def` except
99      that it contains :keyword:`yield` expressions for producing a series of
100      values usable in an :keyword:`async for` loop.
101
102      Usually refers to an asynchronous generator function, but may refer to an
103      *asynchronous generator iterator* in some contexts.  In cases where the
104      intended meaning isn't clear, using the full terms avoids ambiguity.
105
106      An asynchronous generator function may contain :keyword:`await`
107      expressions as well as :keyword:`async for`, and :keyword:`async with`
108      statements.
109
110   asynchronous generator iterator
111      An object created by a :term:`asynchronous generator` function.
112
113      This is an :term:`asynchronous iterator` which when called using the
114      :meth:`__anext__` method returns an awaitable object which will execute
115      the body of the asynchronous generator function until the next
116      :keyword:`yield` expression.
117
118      Each :keyword:`yield` temporarily suspends processing, remembering the
119      location execution state (including local variables and pending
120      try-statements).  When the *asynchronous generator iterator* effectively
121      resumes with another awaitable returned by :meth:`__anext__`, it
122      picks up where it left off.  See :pep:`492` and :pep:`525`.
123
124   asynchronous iterable
125      An object, that can be used in an :keyword:`async for` statement.
126      Must return an :term:`asynchronous iterator` from its
127      :meth:`__aiter__` method.  Introduced by :pep:`492`.
128
129   asynchronous iterator
130      An object that implements the :meth:`__aiter__` and :meth:`__anext__`
131      methods.  ``__anext__`` must return an :term:`awaitable` object.
132      :keyword:`async for` resolves the awaitables returned by an asynchronous
133      iterator's :meth:`__anext__` method until it raises a
134      :exc:`StopAsyncIteration` exception.  Introduced by :pep:`492`.
135
136   attribute
137      A value associated with an object which is referenced by name using
138      dotted expressions.  For example, if an object *o* has an attribute
139      *a* it would be referenced as *o.a*.
140
141   awaitable
142      An object that can be used in an :keyword:`await` expression.  Can be
143      a :term:`coroutine` or an object with an :meth:`__await__` method.
144      See also :pep:`492`.
145
146   BDFL
147      Benevolent Dictator For Life, a.k.a. `Guido van Rossum
148      <https://gvanrossum.github.io/>`_, Python's creator.
149
150   binary file
151      A :term:`file object` able to read and write
152      :term:`bytes-like objects <bytes-like object>`.
153      Examples of binary files are files opened in binary mode (``'rb'``,
154      ``'wb'`` or ``'rb+'``), :data:`sys.stdin.buffer`,
155      :data:`sys.stdout.buffer`, and instances of :class:`io.BytesIO` and
156      :class:`gzip.GzipFile`.
157
158      See also :term:`text file` for a file object able to read and write
159      :class:`str` objects.
160
161   bytes-like object
162      An object that supports the :ref:`bufferobjects` and can
163      export a C-:term:`contiguous` buffer. This includes all :class:`bytes`,
164      :class:`bytearray`, and :class:`array.array` objects, as well as many
165      common :class:`memoryview` objects.  Bytes-like objects can
166      be used for various operations that work with binary data; these include
167      compression, saving to a binary file, and sending over a socket.
168
169      Some operations need the binary data to be mutable.  The documentation
170      often refers to these as "read-write bytes-like objects".  Example
171      mutable buffer objects include :class:`bytearray` and a
172      :class:`memoryview` of a :class:`bytearray`.
173      Other operations require the binary data to be stored in
174      immutable objects ("read-only bytes-like objects"); examples
175      of these include :class:`bytes` and a :class:`memoryview`
176      of a :class:`bytes` object.
177
178   bytecode
179      Python source code is compiled into bytecode, the internal representation
180      of a Python program in the CPython interpreter.  The bytecode is also
181      cached in ``.pyc`` files so that executing the same file is
182      faster the second time (recompilation from source to bytecode can be
183      avoided).  This "intermediate language" is said to run on a
184      :term:`virtual machine` that executes the machine code corresponding to
185      each bytecode. Do note that bytecodes are not expected to work between
186      different Python virtual machines, nor to be stable between Python
187      releases.
188
189      A list of bytecode instructions can be found in the documentation for
190      :ref:`the dis module <bytecodes>`.
191
192   class
193      A template for creating user-defined objects. Class definitions
194      normally contain method definitions which operate on instances of the
195      class.
196
197   class variable
198      A variable defined in a class and intended to be modified only at
199      class level (i.e., not in an instance of the class).
200
201   coercion
202      The implicit conversion of an instance of one type to another during an
203      operation which involves two arguments of the same type.  For example,
204      ``int(3.15)`` converts the floating point number to the integer ``3``, but
205      in ``3+4.5``, each argument is of a different type (one int, one float),
206      and both must be converted to the same type before they can be added or it
207      will raise a :exc:`TypeError`.  Without coercion, all arguments of even
208      compatible types would have to be normalized to the same value by the
209      programmer, e.g., ``float(3)+4.5`` rather than just ``3+4.5``.
210
211   complex number
212      An extension of the familiar real number system in which all numbers are
213      expressed as a sum of a real part and an imaginary part.  Imaginary
214      numbers are real multiples of the imaginary unit (the square root of
215      ``-1``), often written ``i`` in mathematics or ``j`` in
216      engineering.  Python has built-in support for complex numbers, which are
217      written with this latter notation; the imaginary part is written with a
218      ``j`` suffix, e.g., ``3+1j``.  To get access to complex equivalents of the
219      :mod:`math` module, use :mod:`cmath`.  Use of complex numbers is a fairly
220      advanced mathematical feature.  If you're not aware of a need for them,
221      it's almost certain you can safely ignore them.
222
223   context manager
224      An object which controls the environment seen in a :keyword:`with`
225      statement by defining :meth:`__enter__` and :meth:`__exit__` methods.
226      See :pep:`343`.
227
228   context variable
229      A variable which can have different values depending on its context.
230      This is similar to Thread-Local Storage in which each execution
231      thread may have a different value for a variable. However, with context
232      variables, there may be several contexts in one execution thread and the
233      main usage for context variables is to keep track of variables in
234      concurrent asynchronous tasks.
235      See :mod:`contextvars`.
236
237   contiguous
238      .. index:: C-contiguous, Fortran contiguous
239
240      A buffer is considered contiguous exactly if it is either
241      *C-contiguous* or *Fortran contiguous*.  Zero-dimensional buffers are
242      C and Fortran contiguous.  In one-dimensional arrays, the items
243      must be laid out in memory next to each other, in order of
244      increasing indexes starting from zero.  In multidimensional
245      C-contiguous arrays, the last index varies the fastest when
246      visiting items in order of memory address.  However, in
247      Fortran contiguous arrays, the first index varies the fastest.
248
249   coroutine
250      Coroutines are a more generalized form of subroutines. Subroutines are
251      entered at one point and exited at another point.  Coroutines can be
252      entered, exited, and resumed at many different points.  They can be
253      implemented with the :keyword:`async def` statement.  See also
254      :pep:`492`.
255
256   coroutine function
257      A function which returns a :term:`coroutine` object.  A coroutine
258      function may be defined with the :keyword:`async def` statement,
259      and may contain :keyword:`await`, :keyword:`async for`, and
260      :keyword:`async with` keywords.  These were introduced
261      by :pep:`492`.
262
263   CPython
264      The canonical implementation of the Python programming language, as
265      distributed on `python.org <https://www.python.org>`_.  The term "CPython"
266      is used when necessary to distinguish this implementation from others
267      such as Jython or IronPython.
268
269   decorator
270      A function returning another function, usually applied as a function
271      transformation using the ``@wrapper`` syntax.  Common examples for
272      decorators are :func:`classmethod` and :func:`staticmethod`.
273
274      The decorator syntax is merely syntactic sugar, the following two
275      function definitions are semantically equivalent::
276
277         def f(...):
278             ...
279         f = staticmethod(f)
280
281         @staticmethod
282         def f(...):
283             ...
284
285      The same concept exists for classes, but is less commonly used there.  See
286      the documentation for :ref:`function definitions <function>` and
287      :ref:`class definitions <class>` for more about decorators.
288
289   descriptor
290      Any object which defines the methods :meth:`__get__`, :meth:`__set__`, or
291      :meth:`__delete__`.  When a class attribute is a descriptor, its special
292      binding behavior is triggered upon attribute lookup.  Normally, using
293      *a.b* to get, set or delete an attribute looks up the object named *b* in
294      the class dictionary for *a*, but if *b* is a descriptor, the respective
295      descriptor method gets called.  Understanding descriptors is a key to a
296      deep understanding of Python because they are the basis for many features
297      including functions, methods, properties, class methods, static methods,
298      and reference to super classes.
299
300      For more information about descriptors' methods, see :ref:`descriptors`.
301
302   dictionary
303      An associative array, where arbitrary keys are mapped to values.  The
304      keys can be any object with :meth:`__hash__` and :meth:`__eq__` methods.
305      Called a hash in Perl.
306
307   dictionary view
308      The objects returned from :meth:`dict.keys`, :meth:`dict.values`, and
309      :meth:`dict.items` are called dictionary views. They provide a dynamic
310      view on the dictionary’s entries, which means that when the dictionary
311      changes, the view reflects these changes. To force the
312      dictionary view to become a full list use ``list(dictview)``.  See
313      :ref:`dict-views`.
314
315   docstring
316      A string literal which appears as the first expression in a class,
317      function or module.  While ignored when the suite is executed, it is
318      recognized by the compiler and put into the :attr:`__doc__` attribute
319      of the enclosing class, function or module.  Since it is available via
320      introspection, it is the canonical place for documentation of the
321      object.
322
323   duck-typing
324      A programming style which does not look at an object's type to determine
325      if it has the right interface; instead, the method or attribute is simply
326      called or used ("If it looks like a duck and quacks like a duck, it
327      must be a duck.")  By emphasizing interfaces rather than specific types,
328      well-designed code improves its flexibility by allowing polymorphic
329      substitution.  Duck-typing avoids tests using :func:`type` or
330      :func:`isinstance`.  (Note, however, that duck-typing can be complemented
331      with :term:`abstract base classes <abstract base class>`.)  Instead, it
332      typically employs :func:`hasattr` tests or :term:`EAFP` programming.
333
334   EAFP
335      Easier to ask for forgiveness than permission.  This common Python coding
336      style assumes the existence of valid keys or attributes and catches
337      exceptions if the assumption proves false.  This clean and fast style is
338      characterized by the presence of many :keyword:`try` and :keyword:`except`
339      statements.  The technique contrasts with the :term:`LBYL` style
340      common to many other languages such as C.
341
342   expression
343      A piece of syntax which can be evaluated to some value.  In other words,
344      an expression is an accumulation of expression elements like literals,
345      names, attribute access, operators or function calls which all return a
346      value.  In contrast to many other languages, not all language constructs
347      are expressions.  There are also :term:`statement`\s which cannot be used
348      as expressions, such as :keyword:`while`.  Assignments are also statements,
349      not expressions.
350
351   extension module
352      A module written in C or C++, using Python's C API to interact with the
353      core and with user code.
354
355   f-string
356      String literals prefixed with ``'f'`` or ``'F'`` are commonly called
357      "f-strings" which is short for
358      :ref:`formatted string literals <f-strings>`.  See also :pep:`498`.
359
360   file object
361      An object exposing a file-oriented API (with methods such as
362      :meth:`read()` or :meth:`write()`) to an underlying resource.  Depending
363      on the way it was created, a file object can mediate access to a real
364      on-disk file or to another type of storage or communication device
365      (for example standard input/output, in-memory buffers, sockets, pipes,
366      etc.).  File objects are also called :dfn:`file-like objects` or
367      :dfn:`streams`.
368
369      There are actually three categories of file objects: raw
370      :term:`binary files <binary file>`, buffered
371      :term:`binary files <binary file>` and :term:`text files <text file>`.
372      Their interfaces are defined in the :mod:`io` module.  The canonical
373      way to create a file object is by using the :func:`open` function.
374
375   file-like object
376      A synonym for :term:`file object`.
377
378   finder
379      An object that tries to find the :term:`loader` for a module that is
380      being imported.
381
382      Since Python 3.3, there are two types of finder: :term:`meta path finders
383      <meta path finder>` for use with :data:`sys.meta_path`, and :term:`path
384      entry finders <path entry finder>` for use with :data:`sys.path_hooks`.
385
386      See :pep:`302`, :pep:`420` and :pep:`451` for much more detail.
387
388   floor division
389      Mathematical division that rounds down to nearest integer.  The floor
390      division operator is ``//``.  For example, the expression ``11 // 4``
391      evaluates to ``2`` in contrast to the ``2.75`` returned by float true
392      division.  Note that ``(-11) // 4`` is ``-3`` because that is ``-2.75``
393      rounded *downward*. See :pep:`238`.
394
395   function
396      A series of statements which returns some value to a caller. It can also
397      be passed zero or more :term:`arguments <argument>` which may be used in
398      the execution of the body. See also :term:`parameter`, :term:`method`,
399      and the :ref:`function` section.
400
401   function annotation
402      An :term:`annotation` of a function parameter or return value.
403
404      Function annotations are usually used for
405      :term:`type hints <type hint>`: for example, this function is expected to take two
406      :class:`int` arguments and is also expected to have an :class:`int`
407      return value::
408
409         def sum_two_numbers(a: int, b: int) -> int:
410            return a + b
411
412      Function annotation syntax is explained in section :ref:`function`.
413
414      See :term:`variable annotation` and :pep:`484`,
415      which describe this functionality.
416
417   __future__
418      A pseudo-module which programmers can use to enable new language features
419      which are not compatible with the current interpreter.
420
421      By importing the :mod:`__future__` module and evaluating its variables,
422      you can see when a new feature was first added to the language and when it
423      becomes the default::
424
425         >>> import __future__
426         >>> __future__.division
427         _Feature((2, 2, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0), 8192)
428
429   garbage collection
430      The process of freeing memory when it is not used anymore.  Python
431      performs garbage collection via reference counting and a cyclic garbage
432      collector that is able to detect and break reference cycles.  The
433      garbage collector can be controlled using the :mod:`gc` module.
434
435      .. index:: single: generator
436
437   generator
438      A function which returns a :term:`generator iterator`.  It looks like a
439      normal function except that it contains :keyword:`yield` expressions
440      for producing a series of values usable in a for-loop or that can be
441      retrieved one at a time with the :func:`next` function.
442
443      Usually refers to a generator function, but may refer to a
444      *generator iterator* in some contexts.  In cases where the intended
445      meaning isn't clear, using the full terms avoids ambiguity.
446
447   generator iterator
448      An object created by a :term:`generator` function.
449
450      Each :keyword:`yield` temporarily suspends processing, remembering the
451      location execution state (including local variables and pending
452      try-statements).  When the *generator iterator* resumes, it picks up where
453      it left off (in contrast to functions which start fresh on every
454      invocation).
455
456      .. index:: single: generator expression
457
458   generator expression
459      An expression that returns an iterator.  It looks like a normal expression
460      followed by a :keyword:`!for` clause defining a loop variable, range,
461      and an optional :keyword:`!if` clause.  The combined expression
462      generates values for an enclosing function::
463
464         >>> sum(i*i for i in range(10))         # sum of squares 0, 1, 4, ... 81
465         285
466
467   generic function
468      A function composed of multiple functions implementing the same operation
469      for different types. Which implementation should be used during a call is
470      determined by the dispatch algorithm.
471
472      See also the :term:`single dispatch` glossary entry, the
473      :func:`functools.singledispatch` decorator, and :pep:`443`.
474
475
476   GIL
477      See :term:`global interpreter lock`.
478
479   global interpreter lock
480      The mechanism used by the :term:`CPython` interpreter to assure that
481      only one thread executes Python :term:`bytecode` at a time.
482      This simplifies the CPython implementation by making the object model
483      (including critical built-in types such as :class:`dict`) implicitly
484      safe against concurrent access.  Locking the entire interpreter
485      makes it easier for the interpreter to be multi-threaded, at the
486      expense of much of the parallelism afforded by multi-processor
487      machines.
488
489      However, some extension modules, either standard or third-party,
490      are designed so as to release the GIL when doing computationally-intensive
491      tasks such as compression or hashing.  Also, the GIL is always released
492      when doing I/O.
493
494      Past efforts to create a "free-threaded" interpreter (one which locks
495      shared data at a much finer granularity) have not been successful
496      because performance suffered in the common single-processor case. It
497      is believed that overcoming this performance issue would make the
498      implementation much more complicated and therefore costlier to maintain.
499
500
501   hash-based pyc
502      A bytecode cache file that uses the hash rather than the last-modified
503      time of the corresponding source file to determine its validity. See
504      :ref:`pyc-invalidation`.
505
506   hashable
507      An object is *hashable* if it has a hash value which never changes during
508      its lifetime (it needs a :meth:`__hash__` method), and can be compared to
509      other objects (it needs an :meth:`__eq__` method).  Hashable objects which
510      compare equal must have the same hash value.
511
512      Hashability makes an object usable as a dictionary key and a set member,
513      because these data structures use the hash value internally.
514
515      Most of Python's immutable built-in objects are hashable; mutable
516      containers (such as lists or dictionaries) are not; immutable
517      containers (such as tuples and frozensets) are only hashable if
518      their elements are hashable.  Objects which are
519      instances of user-defined classes are hashable by default.  They all
520      compare unequal (except with themselves), and their hash value is derived
521      from their :func:`id`.
522
523   IDLE
524      An Integrated Development Environment for Python.  IDLE is a basic editor
525      and interpreter environment which ships with the standard distribution of
526      Python.
527
528   immutable
529      An object with a fixed value.  Immutable objects include numbers, strings and
530      tuples.  Such an object cannot be altered.  A new object has to
531      be created if a different value has to be stored.  They play an important
532      role in places where a constant hash value is needed, for example as a key
533      in a dictionary.
534
535   import path
536      A list of locations (or :term:`path entries <path entry>`) that are
537      searched by the :term:`path based finder` for modules to import. During
538      import, this list of locations usually comes from :data:`sys.path`, but
539      for subpackages it may also come from the parent package's ``__path__``
540      attribute.
541
542   importing
543      The process by which Python code in one module is made available to
544      Python code in another module.
545
546   importer
547      An object that both finds and loads a module; both a
548      :term:`finder` and :term:`loader` object.
549
550   interactive
551      Python has an interactive interpreter which means you can enter
552      statements and expressions at the interpreter prompt, immediately
553      execute them and see their results.  Just launch ``python`` with no
554      arguments (possibly by selecting it from your computer's main
555      menu). It is a very powerful way to test out new ideas or inspect
556      modules and packages (remember ``help(x)``).
557
558   interpreted
559      Python is an interpreted language, as opposed to a compiled one,
560      though the distinction can be blurry because of the presence of the
561      bytecode compiler.  This means that source files can be run directly
562      without explicitly creating an executable which is then run.
563      Interpreted languages typically have a shorter development/debug cycle
564      than compiled ones, though their programs generally also run more
565      slowly.  See also :term:`interactive`.
566
567   interpreter shutdown
568      When asked to shut down, the Python interpreter enters a special phase
569      where it gradually releases all allocated resources, such as modules
570      and various critical internal structures.  It also makes several calls
571      to the :term:`garbage collector <garbage collection>`. This can trigger
572      the execution of code in user-defined destructors or weakref callbacks.
573      Code executed during the shutdown phase can encounter various
574      exceptions as the resources it relies on may not function anymore
575      (common examples are library modules or the warnings machinery).
576
577      The main reason for interpreter shutdown is that the ``__main__`` module
578      or the script being run has finished executing.
579
580   iterable
581      An object capable of returning its members one at a time. Examples of
582      iterables include all sequence types (such as :class:`list`, :class:`str`,
583      and :class:`tuple`) and some non-sequence types like :class:`dict`,
584      :term:`file objects <file object>`, and objects of any classes you define
585      with an :meth:`__iter__` method or with a :meth:`__getitem__` method
586      that implements :term:`Sequence` semantics.
587
588      Iterables can be
589      used in a :keyword:`for` loop and in many other places where a sequence is
590      needed (:func:`zip`, :func:`map`, ...).  When an iterable object is passed
591      as an argument to the built-in function :func:`iter`, it returns an
592      iterator for the object.  This iterator is good for one pass over the set
593      of values.  When using iterables, it is usually not necessary to call
594      :func:`iter` or deal with iterator objects yourself.  The ``for``
595      statement does that automatically for you, creating a temporary unnamed
596      variable to hold the iterator for the duration of the loop.  See also
597      :term:`iterator`, :term:`sequence`, and :term:`generator`.
598
599   iterator
600      An object representing a stream of data.  Repeated calls to the iterator's
601      :meth:`~iterator.__next__` method (or passing it to the built-in function
602      :func:`next`) return successive items in the stream.  When no more data
603      are available a :exc:`StopIteration` exception is raised instead.  At this
604      point, the iterator object is exhausted and any further calls to its
605      :meth:`__next__` method just raise :exc:`StopIteration` again.  Iterators
606      are required to have an :meth:`__iter__` method that returns the iterator
607      object itself so every iterator is also iterable and may be used in most
608      places where other iterables are accepted.  One notable exception is code
609      which attempts multiple iteration passes.  A container object (such as a
610      :class:`list`) produces a fresh new iterator each time you pass it to the
611      :func:`iter` function or use it in a :keyword:`for` loop.  Attempting this
612      with an iterator will just return the same exhausted iterator object used
613      in the previous iteration pass, making it appear like an empty container.
614
615      More information can be found in :ref:`typeiter`.
616
617   key function
618      A key function or collation function is a callable that returns a value
619      used for sorting or ordering.  For example, :func:`locale.strxfrm` is
620      used to produce a sort key that is aware of locale specific sort
621      conventions.
622
623      A number of tools in Python accept key functions to control how elements
624      are ordered or grouped.  They include :func:`min`, :func:`max`,
625      :func:`sorted`, :meth:`list.sort`, :func:`heapq.merge`,
626      :func:`heapq.nsmallest`, :func:`heapq.nlargest`, and
627      :func:`itertools.groupby`.
628
629      There are several ways to create a key function.  For example. the
630      :meth:`str.lower` method can serve as a key function for case insensitive
631      sorts.  Alternatively, a key function can be built from a
632      :keyword:`lambda` expression such as ``lambda r: (r[0], r[2])``.  Also,
633      the :mod:`operator` module provides three key function constructors:
634      :func:`~operator.attrgetter`, :func:`~operator.itemgetter`, and
635      :func:`~operator.methodcaller`.  See the :ref:`Sorting HOW TO
636      <sortinghowto>` for examples of how to create and use key functions.
637
638   keyword argument
639      See :term:`argument`.
640
641   lambda
642      An anonymous inline function consisting of a single :term:`expression`
643      which is evaluated when the function is called.  The syntax to create
644      a lambda function is ``lambda [parameters]: expression``
645
646   LBYL
647      Look before you leap.  This coding style explicitly tests for
648      pre-conditions before making calls or lookups.  This style contrasts with
649      the :term:`EAFP` approach and is characterized by the presence of many
650      :keyword:`if` statements.
651
652      In a multi-threaded environment, the LBYL approach can risk introducing a
653      race condition between "the looking" and "the leaping".  For example, the
654      code, ``if key in mapping: return mapping[key]`` can fail if another
655      thread removes *key* from *mapping* after the test, but before the lookup.
656      This issue can be solved with locks or by using the EAFP approach.
657
658   list
659      A built-in Python :term:`sequence`.  Despite its name it is more akin
660      to an array in other languages than to a linked list since access to
661      elements is O(1).
662
663   list comprehension
664      A compact way to process all or part of the elements in a sequence and
665      return a list with the results.  ``result = ['{:#04x}'.format(x) for x in
666      range(256) if x % 2 == 0]`` generates a list of strings containing
667      even hex numbers (0x..) in the range from 0 to 255. The :keyword:`if`
668      clause is optional.  If omitted, all elements in ``range(256)`` are
669      processed.
670
671   loader
672      An object that loads a module. It must define a method named
673      :meth:`load_module`. A loader is typically returned by a
674      :term:`finder`. See :pep:`302` for details and
675      :class:`importlib.abc.Loader` for an :term:`abstract base class`.
676
677   magic method
678      .. index:: pair: magic; method
679
680      An informal synonym for :term:`special method`.
681
682   mapping
683      A container object that supports arbitrary key lookups and implements the
684      methods specified in the :class:`~collections.abc.Mapping` or
685      :class:`~collections.abc.MutableMapping`
686      :ref:`abstract base classes <collections-abstract-base-classes>`.  Examples
687      include :class:`dict`, :class:`collections.defaultdict`,
688      :class:`collections.OrderedDict` and :class:`collections.Counter`.
689
690   meta path finder
691      A :term:`finder` returned by a search of :data:`sys.meta_path`.  Meta path
692      finders are related to, but different from :term:`path entry finders
693      <path entry finder>`.
694
695      See :class:`importlib.abc.MetaPathFinder` for the methods that meta path
696      finders implement.
697
698   metaclass
699      The class of a class.  Class definitions create a class name, a class
700      dictionary, and a list of base classes.  The metaclass is responsible for
701      taking those three arguments and creating the class.  Most object oriented
702      programming languages provide a default implementation.  What makes Python
703      special is that it is possible to create custom metaclasses.  Most users
704      never need this tool, but when the need arises, metaclasses can provide
705      powerful, elegant solutions.  They have been used for logging attribute
706      access, adding thread-safety, tracking object creation, implementing
707      singletons, and many other tasks.
708
709      More information can be found in :ref:`metaclasses`.
710
711   method
712      A function which is defined inside a class body.  If called as an attribute
713      of an instance of that class, the method will get the instance object as
714      its first :term:`argument` (which is usually called ``self``).
715      See :term:`function` and :term:`nested scope`.
716
717   method resolution order
718      Method Resolution Order is the order in which base classes are searched
719      for a member during lookup. See `The Python 2.3 Method Resolution Order
720      <https://www.python.org/download/releases/2.3/mro/>`_ for details of the
721      algorithm used by the Python interpreter since the 2.3 release.
722
723   module
724      An object that serves as an organizational unit of Python code.  Modules
725      have a namespace containing arbitrary Python objects.  Modules are loaded
726      into Python by the process of :term:`importing`.
727
728      See also :term:`package`.
729
730   module spec
731      A namespace containing the import-related information used to load a
732      module. An instance of :class:`importlib.machinery.ModuleSpec`.
733
734   MRO
735      See :term:`method resolution order`.
736
737   mutable
738      Mutable objects can change their value but keep their :func:`id`.  See
739      also :term:`immutable`.
740
741   named tuple
742      The term "named tuple" applies to any type or class that inherits from
743      tuple and whose indexable elements are also accessible using named
744      attributes.  The type or class may have other features as well.
745
746      Several built-in types are named tuples, including the values returned
747      by :func:`time.localtime` and :func:`os.stat`.  Another example is
748      :data:`sys.float_info`::
749
750           >>> sys.float_info[1]                   # indexed access
751           1024
752           >>> sys.float_info.max_exp              # named field access
753           1024
754           >>> isinstance(sys.float_info, tuple)   # kind of tuple
755           True
756
757      Some named tuples are built-in types (such as the above examples).
758      Alternatively, a named tuple can be created from a regular class
759      definition that inherits from :class:`tuple` and that defines named
760      fields.  Such a class can be written by hand or it can be created with
761      the factory function :func:`collections.namedtuple`.  The latter
762      technique also adds some extra methods that may not be found in
763      hand-written or built-in named tuples.
764
765   namespace
766      The place where a variable is stored.  Namespaces are implemented as
767      dictionaries.  There are the local, global and built-in namespaces as well
768      as nested namespaces in objects (in methods).  Namespaces support
769      modularity by preventing naming conflicts.  For instance, the functions
770      :func:`builtins.open <.open>` and :func:`os.open` are distinguished by
771      their namespaces.  Namespaces also aid readability and maintainability by
772      making it clear which module implements a function.  For instance, writing
773      :func:`random.seed` or :func:`itertools.islice` makes it clear that those
774      functions are implemented by the :mod:`random` and :mod:`itertools`
775      modules, respectively.
776
777   namespace package
778      A :pep:`420` :term:`package` which serves only as a container for
779      subpackages.  Namespace packages may have no physical representation,
780      and specifically are not like a :term:`regular package` because they
781      have no ``__init__.py`` file.
782
783      See also :term:`module`.
784
785   nested scope
786      The ability to refer to a variable in an enclosing definition.  For
787      instance, a function defined inside another function can refer to
788      variables in the outer function.  Note that nested scopes by default work
789      only for reference and not for assignment.  Local variables both read and
790      write in the innermost scope.  Likewise, global variables read and write
791      to the global namespace.  The :keyword:`nonlocal` allows writing to outer
792      scopes.
793
794   new-style class
795      Old name for the flavor of classes now used for all class objects.  In
796      earlier Python versions, only new-style classes could use Python's newer,
797      versatile features like :attr:`~object.__slots__`, descriptors,
798      properties, :meth:`__getattribute__`, class methods, and static methods.
799
800   object
801      Any data with state (attributes or value) and defined behavior
802      (methods).  Also the ultimate base class of any :term:`new-style
803      class`.
804
805   package
806      A Python :term:`module` which can contain submodules or recursively,
807      subpackages.  Technically, a package is a Python module with an
808      ``__path__`` attribute.
809
810      See also :term:`regular package` and :term:`namespace package`.
811
812   parameter
813      A named entity in a :term:`function` (or method) definition that
814      specifies an :term:`argument` (or in some cases, arguments) that the
815      function can accept.  There are five kinds of parameter:
816
817      * :dfn:`positional-or-keyword`: specifies an argument that can be passed
818        either :term:`positionally <argument>` or as a :term:`keyword argument
819        <argument>`.  This is the default kind of parameter, for example *foo*
820        and *bar* in the following::
821
822           def func(foo, bar=None): ...
823
824      .. _positional-only_parameter:
825
826      * :dfn:`positional-only`: specifies an argument that can be supplied only
827        by position.  Python has no syntax for defining positional-only
828        parameters.  However, some built-in functions have positional-only
829        parameters (e.g. :func:`abs`).
830
831      .. _keyword-only_parameter:
832
833      * :dfn:`keyword-only`: specifies an argument that can be supplied only
834        by keyword.  Keyword-only parameters can be defined by including a
835        single var-positional parameter or bare ``*`` in the parameter list
836        of the function definition before them, for example *kw_only1* and
837        *kw_only2* in the following::
838
839           def func(arg, *, kw_only1, kw_only2): ...
840
841      * :dfn:`var-positional`: specifies that an arbitrary sequence of
842        positional arguments can be provided (in addition to any positional
843        arguments already accepted by other parameters).  Such a parameter can
844        be defined by prepending the parameter name with ``*``, for example
845        *args* in the following::
846
847           def func(*args, **kwargs): ...
848
849      * :dfn:`var-keyword`: specifies that arbitrarily many keyword arguments
850        can be provided (in addition to any keyword arguments already accepted
851        by other parameters).  Such a parameter can be defined by prepending
852        the parameter name with ``**``, for example *kwargs* in the example
853        above.
854
855      Parameters can specify both optional and required arguments, as well as
856      default values for some optional arguments.
857
858      See also the :term:`argument` glossary entry, the FAQ question on
859      :ref:`the difference between arguments and parameters
860      <faq-argument-vs-parameter>`, the :class:`inspect.Parameter` class, the
861      :ref:`function` section, and :pep:`362`.
862
863   path entry
864      A single location on the :term:`import path` which the :term:`path
865      based finder` consults to find modules for importing.
866
867   path entry finder
868      A :term:`finder` returned by a callable on :data:`sys.path_hooks`
869      (i.e. a :term:`path entry hook`) which knows how to locate modules given
870      a :term:`path entry`.
871
872      See :class:`importlib.abc.PathEntryFinder` for the methods that path entry
873      finders implement.
874
875   path entry hook
876      A callable on the :data:`sys.path_hook` list which returns a :term:`path
877      entry finder` if it knows how to find modules on a specific :term:`path
878      entry`.
879
880   path based finder
881      One of the default :term:`meta path finders <meta path finder>` which
882      searches an :term:`import path` for modules.
883
884   path-like object
885      An object representing a file system path. A path-like object is either
886      a :class:`str` or :class:`bytes` object representing a path, or an object
887      implementing the :class:`os.PathLike` protocol. An object that supports
888      the :class:`os.PathLike` protocol can be converted to a :class:`str` or
889      :class:`bytes` file system path by calling the :func:`os.fspath` function;
890      :func:`os.fsdecode` and :func:`os.fsencode` can be used to guarantee a
891      :class:`str` or :class:`bytes` result instead, respectively. Introduced
892      by :pep:`519`.
893
894   PEP
895      Python Enhancement Proposal. A PEP is a design document
896      providing information to the Python community, or describing a new
897      feature for Python or its processes or environment. PEPs should
898      provide a concise technical specification and a rationale for proposed
899      features.
900
901      PEPs are intended to be the primary mechanisms for proposing major new
902      features, for collecting community input on an issue, and for documenting
903      the design decisions that have gone into Python. The PEP author is
904      responsible for building consensus within the community and documenting
905      dissenting opinions.
906
907      See :pep:`1`.
908
909   portion
910      A set of files in a single directory (possibly stored in a zip file)
911      that contribute to a namespace package, as defined in :pep:`420`.
912
913   positional argument
914      See :term:`argument`.
915
916   provisional API
917      A provisional API is one which has been deliberately excluded from
918      the standard library's backwards compatibility guarantees.  While major
919      changes to such interfaces are not expected, as long as they are marked
920      provisional, backwards incompatible changes (up to and including removal
921      of the interface) may occur if deemed necessary by core developers.  Such
922      changes will not be made gratuitously -- they will occur only if serious
923      fundamental flaws are uncovered that were missed prior to the inclusion
924      of the API.
925
926      Even for provisional APIs, backwards incompatible changes are seen as
927      a "solution of last resort" - every attempt will still be made to find
928      a backwards compatible resolution to any identified problems.
929
930      This process allows the standard library to continue to evolve over
931      time, without locking in problematic design errors for extended periods
932      of time.  See :pep:`411` for more details.
933
934   provisional package
935      See :term:`provisional API`.
936
937   Python 3000
938      Nickname for the Python 3.x release line (coined long ago when the
939      release of version 3 was something in the distant future.)  This is also
940      abbreviated "Py3k".
941
942   Pythonic
943      An idea or piece of code which closely follows the most common idioms
944      of the Python language, rather than implementing code using concepts
945      common to other languages.  For example, a common idiom in Python is
946      to loop over all elements of an iterable using a :keyword:`for`
947      statement.  Many other languages don't have this type of construct, so
948      people unfamiliar with Python sometimes use a numerical counter instead::
949
950          for i in range(len(food)):
951              print(food[i])
952
953      As opposed to the cleaner, Pythonic method::
954
955         for piece in food:
956             print(piece)
957
958   qualified name
959      A dotted name showing the "path" from a module's global scope to a
960      class, function or method defined in that module, as defined in
961      :pep:`3155`.  For top-level functions and classes, the qualified name
962      is the same as the object's name::
963
964         >>> class C:
965         ...     class D:
966         ...         def meth(self):
967         ...             pass
968         ...
969         >>> C.__qualname__
970         'C'
971         >>> C.D.__qualname__
972         'C.D'
973         >>> C.D.meth.__qualname__
974         'C.D.meth'
975
976      When used to refer to modules, the *fully qualified name* means the
977      entire dotted path to the module, including any parent packages,
978      e.g. ``email.mime.text``::
979
980         >>> import email.mime.text
981         >>> email.mime.text.__name__
982         'email.mime.text'
983
984   reference count
985      The number of references to an object.  When the reference count of an
986      object drops to zero, it is deallocated.  Reference counting is
987      generally not visible to Python code, but it is a key element of the
988      :term:`CPython` implementation.  The :mod:`sys` module defines a
989      :func:`~sys.getrefcount` function that programmers can call to return the
990      reference count for a particular object.
991
992   regular package
993      A traditional :term:`package`, such as a directory containing an
994      ``__init__.py`` file.
995
996      See also :term:`namespace package`.
997
998   __slots__
999      A declaration inside a class that saves memory by pre-declaring space for
1000      instance attributes and eliminating instance dictionaries.  Though
1001      popular, the technique is somewhat tricky to get right and is best
1002      reserved for rare cases where there are large numbers of instances in a
1003      memory-critical application.
1004
1005   sequence
1006      An :term:`iterable` which supports efficient element access using integer
1007      indices via the :meth:`__getitem__` special method and defines a
1008      :meth:`__len__` method that returns the length of the sequence.
1009      Some built-in sequence types are :class:`list`, :class:`str`,
1010      :class:`tuple`, and :class:`bytes`. Note that :class:`dict` also
1011      supports :meth:`__getitem__` and :meth:`__len__`, but is considered a
1012      mapping rather than a sequence because the lookups use arbitrary
1013      :term:`immutable` keys rather than integers.
1014
1015      The :class:`collections.abc.Sequence` abstract base class
1016      defines a much richer interface that goes beyond just
1017      :meth:`__getitem__` and :meth:`__len__`, adding :meth:`count`,
1018      :meth:`index`, :meth:`__contains__`, and
1019      :meth:`__reversed__`. Types that implement this expanded
1020      interface can be registered explicitly using
1021      :func:`~abc.register`.
1022
1023   single dispatch
1024      A form of :term:`generic function` dispatch where the implementation is
1025      chosen based on the type of a single argument.
1026
1027   slice
1028      An object usually containing a portion of a :term:`sequence`.  A slice is
1029      created using the subscript notation, ``[]`` with colons between numbers
1030      when several are given, such as in ``variable_name[1:3:5]``.  The bracket
1031      (subscript) notation uses :class:`slice` objects internally.
1032
1033   special method
1034      .. index:: pair: special; method
1035
1036      A method that is called implicitly by Python to execute a certain
1037      operation on a type, such as addition.  Such methods have names starting
1038      and ending with double underscores.  Special methods are documented in
1039      :ref:`specialnames`.
1040
1041   statement
1042      A statement is part of a suite (a "block" of code).  A statement is either
1043      an :term:`expression` or one of several constructs with a keyword, such
1044      as :keyword:`if`, :keyword:`while` or :keyword:`for`.
1045
1046   text encoding
1047      A codec which encodes Unicode strings to bytes.
1048
1049   text file
1050      A :term:`file object` able to read and write :class:`str` objects.
1051      Often, a text file actually accesses a byte-oriented datastream
1052      and handles the :term:`text encoding` automatically.
1053      Examples of text files are files opened in text mode (``'r'`` or ``'w'``),
1054      :data:`sys.stdin`, :data:`sys.stdout`, and instances of
1055      :class:`io.StringIO`.
1056
1057      See also :term:`binary file` for a file object able to read and write
1058      :term:`bytes-like objects <bytes-like object>`.
1059
1060   triple-quoted string
1061      A string which is bound by three instances of either a quotation mark
1062      (") or an apostrophe (').  While they don't provide any functionality
1063      not available with single-quoted strings, they are useful for a number
1064      of reasons.  They allow you to include unescaped single and double
1065      quotes within a string and they can span multiple lines without the
1066      use of the continuation character, making them especially useful when
1067      writing docstrings.
1068
1069   type
1070      The type of a Python object determines what kind of object it is; every
1071      object has a type.  An object's type is accessible as its
1072      :attr:`~instance.__class__` attribute or can be retrieved with
1073      ``type(obj)``.
1074
1075   type alias
1076      A synonym for a type, created by assigning the type to an identifier.
1077
1078      Type aliases are useful for simplifying :term:`type hints <type hint>`.
1079      For example::
1080
1081         from typing import List, Tuple
1082
1083         def remove_gray_shades(
1084                 colors: List[Tuple[int, int, int]]) -> List[Tuple[int, int, int]]:
1085             pass
1086
1087      could be made more readable like this::
1088
1089         from typing import List, Tuple
1090
1091         Color = Tuple[int, int, int]
1092
1093         def remove_gray_shades(colors: List[Color]) -> List[Color]:
1094             pass
1095
1096      See :mod:`typing` and :pep:`484`, which describe this functionality.
1097
1098   type hint
1099      An :term:`annotation` that specifies the expected type for a variable, a class
1100      attribute, or a function parameter or return value.
1101
1102      Type hints are optional and are not enforced by Python but
1103      they are useful to static type analysis tools, and aid IDEs with code
1104      completion and refactoring.
1105
1106      Type hints of global variables, class attributes, and functions,
1107      but not local variables, can be accessed using
1108      :func:`typing.get_type_hints`.
1109
1110      See :mod:`typing` and :pep:`484`, which describe this functionality.
1111
1112   universal newlines
1113      A manner of interpreting text streams in which all of the following are
1114      recognized as ending a line: the Unix end-of-line convention ``'\n'``,
1115      the Windows convention ``'\r\n'``, and the old Macintosh convention
1116      ``'\r'``.  See :pep:`278` and :pep:`3116`, as well as
1117      :func:`bytes.splitlines` for an additional use.
1118
1119   variable annotation
1120      An :term:`annotation` of a variable or a class attribute.
1121
1122      When annotating a variable or a class attribute, assignment is optional::
1123
1124         class C:
1125             field: 'annotation'
1126
1127      Variable annotations are usually used for
1128      :term:`type hints <type hint>`: for example this variable is expected to take
1129      :class:`int` values::
1130
1131         count: int = 0
1132
1133      Variable annotation syntax is explained in section :ref:`annassign`.
1134
1135      See :term:`function annotation`, :pep:`484`
1136      and :pep:`526`, which describe this functionality.
1137
1138   virtual environment
1139      A cooperatively isolated runtime environment that allows Python users
1140      and applications to install and upgrade Python distribution packages
1141      without interfering with the behaviour of other Python applications
1142      running on the same system.
1143
1144      See also :mod:`venv`.
1145
1146   virtual machine
1147      A computer defined entirely in software.  Python's virtual machine
1148      executes the :term:`bytecode` emitted by the bytecode compiler.
1149
1150   Zen of Python
1151      Listing of Python design principles and philosophies that are helpful in
1152      understanding and using the language.  The listing can be found by typing
1153      "``import this``" at the interactive prompt.
1154