Glossary

>>>

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

...

Can refer to:

• The default Python prompt of the interactive shell when entering the 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.

• TheEllipsisbuilt-in constant.

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 aslib2to3;a standalone entry point is provided asTools/scripts/2to3.See 2to3 — Automated Python 2 to 3 code translation.

abstract base class

Abstract base classes complementduck-typingby providing a way to define interfaces when other techniques like hasattr()would be clumsy or subtly wrong (for example with magic methods). ABCs introduce virtual subclasses, which are classes that don’t inherit from a class but are still recognized byisinstance()andissubclass();see the abcmodule documentation. Python comes with many built-in ABCs for data structures (in thecollections.abcmodule), numbers (in the numbersmodule), streams (in theiomodule), import finders and loaders (in theimportlib.abcmodule). You can create your own ABCs with theabcmodule.

annotation

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

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

Seevariable annotation,function annotation,PEP 484 andPEP 526,which describe this functionality. Also seeAnnotations Best Practices for best practices on working with annotations.

argument

A value passed to afunction(ormethod) when calling the function. There are two kinds of argument:

• 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,3and5are both keyword arguments in the following calls tocomplex():

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

• 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 aniterablepreceded by*. For example,3and5are 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 theCallssection 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 theparameterglossary entry, the FAQ question on the difference between arguments and parameters,andPEP 362.

asynchronous context manager

An object which controls the environment seen in an asyncwithstatement by defining__aenter__()and __aexit__()methods. Introduced byPEP 492.

asynchronous generator

A function which returns anasynchronous generator iterator.It looks like a coroutine function defined withasyncdefexcept that it containsyieldexpressions for producing a series of values usable in anasyncforloop.

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

An asynchronous generator function may containawait expressions as well asasyncfor,andasyncwith statements.

asynchronous generator iterator

An object created by aasynchronous generatorfunction.

This is anasynchronous iteratorwhich when called using the __anext__()method returns an awaitable object which will execute the body of the asynchronous generator function until the next yieldexpression.

Eachyieldtemporarily suspends processing, remembering the location execution state (including local variables and pending try-statements). When theasynchronous generator iteratoreffectively resumes with another awaitable returned by__anext__(),it picks up where it left off. SeePEP 492andPEP 525.

asynchronous iterable

An object, that can be used in anasyncforstatement. Must return anasynchronous iteratorfrom its __aiter__()method. Introduced byPEP 492.

asynchronous iterator

An object that implements the__aiter__()and__anext__() methods.__anext__must return anawaitableobject. asyncforresolves the awaitables returned by an asynchronous iterator’s__anext__()method until it raises a StopAsyncIterationexception. Introduced byPEP 492.

attribute

A value associated with an object which is usually referenced by name using dotted expressions. For example, if an objectohas an attribute ait would be referenced aso.a.

It is possible to give an object an attribute whose name is not an identifier as defined byIdentifiers and keywords,for example using setattr(),if the object allows it. Such an attribute will not be accessible using a dotted expression, and would instead need to be retrieved withgetattr().

awaitable

An object that can be used in anawaitexpression. Can be acoroutineor an object with an__await__()method. See alsoPEP 492.

BDFL

Benevolent Dictator For Life, a.k.a.Guido van Rossum,Python’s creator.

binary file

Afile objectable to read and write bytes-like objects. Examples of binary files are files opened in binary mode ('rb', 'wb'or'rb+'),sys.stdin.buffer, sys.stdout.buffer,and instances ofio.BytesIOand gzip.GzipFile.

See alsotext filefor a file object able to read and write strobjects.

borrowed reference

In Python’s C API, a borrowed reference is a reference to an object, where the code using the object does not own the reference. It becomes a dangling pointer if the object is destroyed. For example, a garbage collection can remove the laststrong referenceto the object and so destroy it.

CallingPy_INCREF()on theborrowed referenceis recommended to convert it to astrong referencein-place, except when the object cannot be destroyed before the last usage of the borrowed reference. ThePy_NewRef()function can be used to create a new strong reference.

bytes-like object

An object that supports theBuffer Protocoland can export a C-contiguousbuffer. This includes allbytes, bytearray,andarray.arrayobjects, as well as many commonmemoryviewobjects. 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 includebytearrayand a memoryviewof abytearray. Other operations require the binary data to be stored in immutable objects ( “read-only bytes-like objects” ); examples of these includebytesand amemoryview of abytesobject.

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.pycfiles 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 virtual machinethat 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 the dis module.

callable

A callable is an object that can be called, possibly with a set of arguments (seeargument), with the following syntax:

callable(argument1,argument2,...)

Afunction,and by extension amethod,is a callable. An instance of a class that implements the__call__() method is also a callable.

callback

A subroutine function which is passed as an argument to be executed at some point in the future.

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 integer3,but in3+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 aTypeError.Without coercion, all arguments of even compatible types would have to be normalized to the same value by the programmer, e.g.,float(3)+4.5rather than just3+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 writteniin mathematics orjin engineering. Python has built-in support for complex numbers, which are written with this latter notation; the imaginary part is written with a jsuffix, e.g.,3+1j.To get access to complex equivalents of the mathmodule, usecmath.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 awith statement by defining__enter__()and__exit__()methods. SeePEP 343.

context variable

A variable which can have different values depending on its context. This is similar to Thread-Local Storage in which each execution thread may have a different value for a variable. However, with context variables, there may be several contexts in one execution thread and the main usage for context variables is to keep track of variables in concurrent asynchronous tasks. Seecontextvars.

contiguous

A buffer is considered contiguous exactly if it is either C-contiguousorFortran 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 are 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 theasyncdefstatement. See also PEP 492.

coroutine function

A function which returns acoroutineobject. A coroutine function may be defined with theasyncdefstatement, and may containawait,asyncfor,and asyncwithkeywords. These were introduced byPEP 492.

CPython

The canonical implementation of the Python programming language, as distributed onpython.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@wrappersyntax. Common examples for decorators areclassmethod()andstaticmethod().

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

deff(arg):
...
f=staticmethod(f)

@staticmethod
deff(arg):
...

The same concept exists for classes, but is less commonly used there. See the documentation forfunction definitionsand class definitionsfor more about decorators.

descriptor

Any object which defines the methods__get__(),__set__(),or __delete__().When a class attribute is a descriptor, its special binding behavior is triggered upon attribute lookup. Normally, using a.bto get, set or delete an attribute looks up the object namedbin the class dictionary fora,but ifbis 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, seeImplementing Descriptors or theDescriptor How To Guide.

dictionary

An associative array, where arbitrary keys are mapped to values. The keys can be any object with__hash__()and__eq__()methods. Called a hash in Perl.

dictionary comprehension

A compact way to process all or part of the elements in an iterable and return a dictionary with the results.results={n:n**2fornin range(10)}generates a dictionary containing keynmapped to valuen**2.SeeDisplays for lists, sets and dictionaries.

dictionary view

The objects returned fromdict.keys(),dict.values(),and 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 uselist(dictview).See Dictionary view objects.

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__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 usingtype()or isinstance().(Note, however, that duck-typing can be complemented withabstract base classes.) Instead, it typically employshasattr()tests orEAFPprogramming.

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 manytryandexcept statements. The technique contrasts with theLBYLstyle 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 alsostatements which cannot be used as expressions, such aswhile.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 formatted string literals.See alsoPEP 498.

file object

An object exposing a file-oriented API (with methods such as read()orwrite()) 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 calledfile-like objectsor streams.

There are actually three categories of file objects: raw binary files,buffered binary filesandtext files. Their interfaces are defined in theiomodule. The canonical way to create a file object is by using theopen()function.

file-like object

A synonym forfile object.

filesystem encoding and error handler

Encoding and error handler used by Python to decode bytes from the operating system and encode Unicode to the operating system.

The filesystem encoding must guarantee to successfully decode all bytes below 128. If the file system encoding fails to provide this guarantee, API functions can raiseUnicodeError.

Thesys.getfilesystemencoding()and sys.getfilesystemencodeerrors()functions can be used to get the filesystem encoding and error handler.

Thefilesystem encoding and error handlerare configured at Python startup by thePyConfig_Read()function: see filesystem_encodingand filesystem_errorsmembers ofPyConfig.

See also thelocale encoding.

finder

An object that tries to find theloaderfor a module that is being imported.

Since Python 3.3, there are two types of finder:meta path findersfor use withsys.meta_path,andpath entry findersfor use withsys.path_hooks.

SeePEP 302,PEP 420andPEP 451for much more detail.

floor division

Mathematical division that rounds down to nearest integer. The floor division operator is//.For example, the expression11//4 evaluates to2in contrast to the2.75returned by float true division. Note that(-11)//4is-3because that is-2.75 roundeddownward.SeePEP 238.

function

A series of statements which returns some value to a caller. It can also be passed zero or moreargumentswhich may be used in the execution of the body. See alsoparameter,method, and theFunction definitionssection.

function annotation

Anannotationof a function parameter or return value.

Function annotations are usually used for type hints:for example, this function is expected to take two intarguments and is also expected to have anint return value:

defsum_two_numbers(a:int,b:int)->int:
returna+b

Function annotation syntax is explained in sectionFunction definitions.

Seevariable annotationandPEP 484, which describe this functionality. Also seeAnnotations Best Practices for best practices on working with annotations.

__future__

Afuture statement,from__future__import<feature>, directs the compiler to compile the current module using syntax or semantics that will become standard in a future release of Python. The__future__module documents the possible values of feature.By importing this module and evaluating its variables, you can see when a new feature was first added to the language and when it will (or did) become 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 thegcmodule.

generator

A function which returns agenerator iterator.It looks like a normal function except that it containsyieldexpressions for producing a series of values usable in a for-loop or that can be retrieved one at a time with thenext()function.

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

generator iterator

An object created by ageneratorfunction.

Eachyieldtemporarily suspends processing, remembering the location execution state (including local variables and pending try-statements). When thegenerator iteratorresumes, it picks up where it left off (in contrast to functions which start fresh on every invocation).

generator expression

An expression that returns an iterator. It looks like a normal expression followed by aforclause defining a loop variable, range, and an optionalifclause. The combined expression generates values for an enclosing function:

>>>sum(i*iforiinrange(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 thesingle dispatchglossary entry, the functools.singledispatch()decorator, andPEP 443.

generic type

Atypethat can be parameterized; typically a container classsuch aslistor dict.Used fortype hintsand annotations.

For more details, seegeneric alias types, PEP 483,PEP 484,PEP 585,and thetypingmodule.

GIL

Seeglobal interpreter lock.

global interpreter lock

The mechanism used by theCPythoninterpreter to assure that only one thread executes Pythonbytecodeat a time. This simplifies the CPython implementation by making the object model (including critical built-in types such asdict) 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 Cached bytecode invalidation.

hashable

An object ishashableif it has a hash value which never changes during its lifetime (it needs a__hash__()method), and can be compared to other objects (it needs an__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.

Most of Python’s immutable built-in objects are hashable; mutable containers (such as lists or dictionaries) are not; immutable containers (such as tuples and frozensets) are only hashable if their elements are hashable. 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 theirid().

IDLE

An Integrated Development and Learning Environment for Python. IDLEis 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 (orpath entries) that are searched by thepath based finderfor modules to import. During import, this list of locations usually comes fromsys.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 finderandloaderobject.

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 launchpythonwith 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 (rememberhelp(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 alsointeractive.

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 thegarbage collector.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 aslist,str, andtuple) and some non-sequence types likedict, file objects,and objects of any classes you define with an__iter__()method or with a__getitem__()method that implementsSequencesemantics.

Iterables can be used in aforloop and in many other places where a sequence is needed (zip(),map(),…). When an iterable object is passed as an argument to the built-in functioniter(),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 iter()or deal with iterator objects yourself. Thefor statement does that automatically for you, creating a temporary unnamed variable to hold the iterator for the duration of the loop. See also iterator,sequence,andgenerator.

iterator

An object representing a stream of data. Repeated calls to the iterator’s __next__()method (or passing it to the built-in function next()) return successive items in the stream. When no more data are available aStopIterationexception is raised instead. At this point, the iterator object is exhausted and any further calls to its __next__()method just raiseStopIterationagain. Iterators are required to have an__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 list) produces a fresh new iterator each time you pass it to the iter()function or use it in aforloop. 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 inIterator Types.

CPython implementation detail:CPython does not consistently apply the requirement that an iterator define__iter__().

key function

A key function or collation function is a callable that returns a value used for sorting or ordering. For example,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 includemin(),max(), sorted(),list.sort(),heapq.merge(), heapq.nsmallest(),heapq.nlargest(),and itertools.groupby().

There are several ways to create a key function. For example. the str.lower()method can serve as a key function for case insensitive sorts. Alternatively, a key function can be built from a lambdaexpression such aslambdar:(r[0],r[2]).Also, theoperatormodule provides three key function constructors: attrgetter(),itemgetter(),and methodcaller().See theSorting HOW TOfor examples of how to create and use key functions.

keyword argument

Seeargument.

lambda

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

LBYL

Look before you leap. This coding style explicitly tests for pre-conditions before making calls or lookups. This style contrasts with theEAFPapproach and is characterized by the presence of many ifstatements.

In a multi-threaded environment, the LBYL approach can risk introducing a race condition between “the looking” and “the leaping”. For example, the code,ifkeyinmapping:returnmapping[key]can fail if another thread removeskeyfrommappingafter the test, but before the lookup. This issue can be solved with locks or by using the EAFP approach.

locale encoding

On Unix, it is the encoding of the LC_CTYPE locale. It can be set with locale.setlocale(locale.LC_CTYPE,new_locale).

On Windows, it is the ANSI code page (ex:cp1252).

locale.getpreferredencoding(False)can be used to get the locale encoding.

Python uses thefilesystem encoding and error handlerto convert between Unicode filenames and bytes filenames.

list

A built-in Pythonsequence.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)forxin range(256)ifx%2==0]generates a list of strings containing even hex numbers (0x..) in the range from 0 to 255. Theif clause is optional. If omitted, all elements inrange(256)are processed.

loader

An object that loads a module. It must define a method named load_module().A loader is typically returned by a finder.SeePEP 302for details and importlib.abc.Loaderfor anabstract base class.

magic method

An informal synonym forspecial method.

mapping

A container object that supports arbitrary key lookups and implements the methods specified in theMappingor MutableMapping abstract base classes.Examples includedict,collections.defaultdict, collections.OrderedDictandcollections.Counter.

meta path finder

Afinderreturned by a search ofsys.meta_path.Meta path finders are related to, but different frompath entry finders.

Seeimportlib.abc.MetaPathFinderfor 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 inMetaclasses.

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 firstargument(which is usually calledself). Seefunctionandnested scope.

method resolution order

Method Resolution Order is the order in which base classes are searched for a member during lookup. SeeThe Python 2.3 Method Resolution Orderfor 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 ofimporting.

See alsopackage.

module spec

A namespace containing the import-related information used to load a module. An instance ofimportlib.machinery.ModuleSpec.

MRO

Seemethod resolution order.

mutable

Mutable objects can change their value but keep theirid().See alsoimmutable.

named tuple

The term “named tuple” applies to any type or class that inherits from tuple and whose indexable elements are also accessible using named attributes. The type or class may have other features as well.

Several built-in types are named tuples, including the values returned bytime.localtime()andos.stat().Another example is sys.float_info:

>>>sys.float_info[1]# indexed access
1024
>>>sys.float_info.max_exp# named field access
1024
>>>isinstance(sys.float_info,tuple)# kind of tuple
True

Some named tuples are built-in types (such as the above examples). Alternatively, a named tuple can be created from a regular class definition that inherits fromtupleand that defines named fields. Such a class can be written by hand or it can be created with the factory functioncollections.namedtuple().The latter technique also adds some extra methods that may not be found in hand-written or built-in named tuples.

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 builtins.openandos.open()are distinguished by their namespaces. Namespaces also aid readability and maintainability by making it clear which module implements a function. For instance, writing random.seed()oritertools.islice()makes it clear that those functions are implemented by therandomanditertools modules, respectively.

namespace package

APEP 420packagewhich serves only as a container for subpackages. Namespace packages may have no physical representation, and specifically are not like aregular packagebecause they have no__init__.pyfile.

See alsomodule.

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. Thenonlocalallows 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__slots__,descriptors, properties,__getattribute__(),class methods, and static methods.

object

Any data with state (attributes or value) and defined behavior (methods). Also the ultimate base class of anynew-style class.

package

A Pythonmodulewhich can contain submodules or recursively, subpackages. Technically, a package is a Python module with a __path__attribute.

See alsoregular packageandnamespace package.

parameter

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

• positional-or-keyword:specifies an argument that can be passed eitherpositionallyor as akeyword argument.This is the default kind of parameter, for examplefoo andbarin the following:

  deffunc(foo,bar=None):...
  

• positional-only:specifies an argument that can be supplied only by position. Positional-only parameters can be defined by including a /character in the parameter list of the function definition after them, for exampleposonly1andposonly2in the following:

  deffunc(posonly1,posonly2,/,positional_or_keyword):...
  

• 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 examplekw_only1and kw_only2in the following:

  deffunc(arg,*,kw_only1,kw_only2):...
  

• 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 argsin the following:

  deffunc(*args,**kwargs):...
  

• 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 examplekwargsin the example above.

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

See also theargumentglossary entry, the FAQ question on the difference between arguments and parameters,theinspect.Parameterclass, the Function definitionssection, andPEP 362.

path entry

A single location on theimport pathwhich thepath based finderconsults to find modules for importing.

path entry finder

Afinderreturned by a callable onsys.path_hooks (i.e. apath entry hook) which knows how to locate modules given apath entry.

Seeimportlib.abc.PathEntryFinderfor the methods that path entry finders implement.

path entry hook

A callable on thesys.path_hooklist which returns apath entry finderif it knows how to find modules on a specificpath entry.

path based finder

One of the defaultmeta path finderswhich searches animport pathfor modules.

path-like object

An object representing a file system path. A path-like object is either astrorbytesobject representing a path, or an object implementing theos.PathLikeprotocol. An object that supports theos.PathLikeprotocol can be converted to astror bytesfile system path by calling theos.fspath()function; os.fsdecode()andos.fsencode()can be used to guarantee a strorbytesresult instead, respectively. Introduced byPEP 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.

SeePEP 1.

portion

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

positional argument

Seeargument.

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. SeePEP 411for more details.

provisional package

Seeprovisional 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 afor statement. Many other languages don’t have this type of construct, so people unfamiliar with Python sometimes use a numerical counter instead:

foriinrange(len(food)):
print(food[i])

As opposed to the cleaner, Pythonic method:

forpieceinfood:
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:

>>>classC:
...classD:
...defmeth(self):
...pass
...
>>>C.__qualname__
'C'
>>>C.D.__qualname__
'C.D'
>>>C.D.meth.__qualname__
'C.D.meth'

When used to refer to modules, thefully qualified namemeans the entire dotted path to the module, including any parent packages, e.g.email.mime.text:

>>>importemail.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 CPythonimplementation. Thesysmodule defines a getrefcount()function that programmers can call to return the reference count for a particular object.

regular package

A traditionalpackage,such as a directory containing an __init__.pyfile.

See alsonamespace 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

Aniterablewhich supports efficient element access using integer indices via the__getitem__()special method and defines a __len__()method that returns the length of the sequence. Some built-in sequence types arelist,str, tuple,andbytes.Note thatdictalso supports__getitem__()and__len__(),but is considered a mapping rather than a sequence because the lookups use arbitrary immutablekeys rather than integers.

Thecollections.abc.Sequenceabstract base class defines a much richer interface that goes beyond just __getitem__()and__len__(),addingcount(), index(),__contains__(),and __reversed__().Types that implement this expanded interface can be registered explicitly using register().

set comprehension

A compact way to process all or part of the elements in an iterable and return a set with the results.results={cforcin'abracadabra'if cnotin'abc'}generates the set of strings{'r','d'}.See Displays for lists, sets and dictionaries.

single dispatch

A form ofgeneric functiondispatch where the implementation is chosen based on the type of a single argument.

slice

An object usually containing a portion of asequence.A slice is created using the subscript notation,[]with colons between numbers when several are given, such as invariable_name[1:3:5].The bracket (subscript) notation usessliceobjects 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 Special method names.

statement

A statement is part of a suite (a “block” of code). A statement is either anexpressionor one of several constructs with a keyword, such asif,whileorfor.

strong reference

In Python’s C API, a strong reference is a reference to an object which is owned by the code holding the reference. The strong reference is taken by callingPy_INCREF()when the reference is created and released withPy_DECREF() when the reference is deleted.

ThePy_NewRef()function can be used to create a strong reference to an object. Usually, thePy_DECREF()function must be called on the strong reference before exiting the scope of the strong reference, to avoid leaking one reference.

See alsoborrowed reference.

text encoding

A string in Python is a sequence of Unicode code points (in range U+0000–U+10FFFF). To store or transfer a string, it needs to be serialized as a sequence of bytes.

Serializing a string into a sequence of bytes is known as “encoding”, and recreating the string from the sequence of bytes is known as “decoding”.

There are a variety of different text serialization codecs,which are collectively referred to as “text encodings”.

text file

Afile objectable to read and writestrobjects. Often, a text file actually accesses a byte-oriented datastream and handles thetext encodingautomatically. Examples of text files are files opened in text mode ('r'or'w'), sys.stdin,sys.stdout,and instances of io.StringIO.

See alsobinary filefor a file object able to read and write bytes-like objects.

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 __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 simplifyingtype hints. For example:

defremove_gray_shades(
colors:list[tuple[int,int,int]])->list[tuple[int,int,int]]:
pass

could be made more readable like this:

Color=tuple[int,int,int]

defremove_gray_shades(colors:list[Color])->list[Color]:
pass

SeetypingandPEP 484,which describe this functionality.

type hint

Anannotationthat 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 typing.get_type_hints().

SeetypingandPEP 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'.SeePEP 278andPEP 3116,as well as bytes.splitlines()for an additional use.

variable annotation

Anannotationof a variable or a class attribute.

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

classC:
field:'annotation'

Variable annotations are usually used for type hints:for example this variable is expected to take intvalues:

count:int=0

Variable annotation syntax is explained in sectionAnnotated assignment statements.

Seefunction annotation,PEP 484 andPEP 526,which describe this functionality. Also seeAnnotations Best Practices for best practices on working with annotations.

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 alsovenv.

virtual machine

A computer defined entirely in software. Python’s virtual machine executes thebytecodeemitted 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 “importthis”at the interactive prompt.