Python (programming language)

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Python
Python logo and wordmark.svg
Paradigm Multi-paradigm: functional, imperative, object-oriented, structured, reflective
Designed by Guido van Rossum
Developer Python Software Foundation
First appeared1991;29 years ago (1991) [1]
Stable release
3.9.0 / 5 October 2020;46 days ago (2020-10-05) [2]
Preview release
3.10.0a2 / 3 November 2020;17 days ago (2020-11-03) [3]
Typing discipline Duck, dynamic, gradual (since 3.5) [4]
OS Linux, macOS, Windows
and more
License Python Software Foundation License
Filename extensions .py, .pyi, .pyc, .pyd, .pyo (prior to 3.5), [5] .pyw, .pyz (since 3.5) [6]
Website www.python.org
Major implementations
CPython, PyPy, Stackless Python, MicroPython, CircuitPython, IronPython, Jython, RustPython
Dialects
Cython, RPython, Starlark [7]
Influenced by
ABC, [8] Ada, [9] ALGOL 68, [10] APL, [11] C, [12] C++, [13] CLU, [14] Dylan, [15] Haskell, [16] Icon, [17] Java, [18] Lisp, [19] Modula-3, [13] Perl, Standard ML [11]
Influenced
Apache Groovy, Boo, Cobra, CoffeeScript, [20] D, F#, Genie, [21] Go, JavaScript, [22] [23] Julia, [24] Nim, Ring, [25] Ruby, [26] Swift [27]

Python is an interpreted, high-level and general-purpose programming language. Python's design philosophy emphasizes code readability with its notable use of significant whitespace. Its language constructs and object-oriented approach aim to help programmers write clear, logical code for small and large-scale projects. [28]

Contents

Python is dynamically typed and garbage-collected. It supports multiple programming paradigms, including structured (particularly, procedural), object-oriented, and functional programming. Python is often described as a "batteries included" language due to its comprehensive standard library. [29]

Python was created in the late 1980s, and first released in 1991, by Guido van Rossum as a successor to the ABC programming language. Python 2.0, released in 2000, introduced new features, such as list comprehensions, and a garbage collection system with reference counting, and was discontinued with version 2.7 in 2020. [30] Python 3.0, released in 2008, was a major revision of the language that is not completely backward-compatible and much Python 2 code does not run unmodified on Python 3.

Python interpreters are available for many operating systems. A global community of programmers develops and maintains CPython, a free and open-source [31] reference implementation. A non-profit organization, the Python Software Foundation, manages and directs resources for Python and CPython development.

History

Guido van Rossum at OSCON 2006 Guido van Rossum OSCON 2006 cropped.png
Guido van Rossum at OSCON 2006

Python was conceived in the late 1980s [32] by Guido van Rossum at Centrum Wiskunde & Informatica (CWI) in the Netherlands as a successor to the ABC programming language, which was inspired by SETL), [33] capable of exception handling and interfacing with the Amoeba operating system. [8] Its implementation began in December 1989. [34] Van Rossum shouldered sole responsibility for the project, as the lead developer, until 12 July 2018, when he announced his "permanent vacation" from his responsibilities as Python's Benevolent Dictator For Life , a title the Python community bestowed upon him to reflect his long-term commitment as the project's chief decision-maker. [35] He now shares his leadership as a member of a five-person steering council. [36] [37] [38] In January 2019, active Python core developers elected Brett Cannon, Nick Coghlan, Barry Warsaw, Carol Willing and Van Rossum to a five-member "Steering Council" to lead the project. [39] Guido van Rossum has since then withdrawn his nomination for the 2020 Steering council. [40]

Python 2.0 was released on 16 October 2000 with many major new features, including a cycle-detecting garbage collector and support for Unicode. [41]

Python 3.0 was released on 3 December 2008. It was a major revision of the language that is not completely backward-compatible. [42] Many of its major features were backported to Python 2.6.x [43] and 2.7.x version series. Releases of Python 3 include the 2to3 utility, which automates (at least partially) the translation of Python 2 code to Python 3. [44]

Python 2.7's end-of-life date was initially set at 2015 then postponed to 2020 out of concern that a large body of existing code could not easily be forward-ported to Python 3. [45] [46] No more security patches or other improvements will be released for it. [47] [48] With Python 2's end-of-life, only Python 3.6.x [49] and later are supported.

Design philosophy and features

Python is a multi-paradigm programming language. Object-oriented programming and structured programming are fully supported, and many of its features support functional programming and aspect-oriented programming (including by metaprogramming [50] and metaobjects (magic methods)). [51] Many other paradigms are supported via extensions, including design by contract [52] [53] and logic programming. [54]

Python uses dynamic typing and a combination of reference counting and a cycle-detecting garbage collector for memory management. [55] It also features dynamic name resolution (late binding), which binds method and variable names during program execution.

Python's design offers some support for functional programming in the Lisp tradition. It has filter, map, and reduce functions; list comprehensions, dictionaries, sets, and generator expressions. [56] The standard library has two modules (itertools and functools) that implement functional tools borrowed from Haskell and Standard ML. [57]

The language's core philosophy is summarized in the document The Zen of Python (PEP 20), which includes aphorisms such as: [58]

Rather than having all of its functionality built into its core, Python was designed to be highly extensible. This compact modularity has made it particularly popular as a means of adding programmable interfaces to existing applications. Van Rossum's vision of a small core language with a large standard library and easily extensible interpreter stemmed from his frustrations with ABC, which espoused the opposite approach. [32]

Python strives for a simpler, less-cluttered syntax and grammar while giving developers a choice in their coding methodology. In contrast to Perl's "there is more than one way to do it" motto, Python embraces a "there should be one—and preferably only one—obvious way to do it" design philosophy. [58] Alex Martelli, a Fellow at the Python Software Foundation and Python book author, writes that "To describe something as 'clever' is not considered a compliment in the Python culture." [59]

Python's developers strive to avoid premature optimization, and reject patches to non-critical parts of the CPython reference implementation that would offer marginal increases in speed at the cost of clarity. [60] When speed is important, a Python programmer can move time-critical functions to extension modules written in languages such as C, or use PyPy, a just-in-time compiler. Cython is also available, which translates a Python script into C and makes direct C-level API calls into the Python interpreter.

An important goal of Python's developers is keeping it fun to use. This is reflected in the language's name—a tribute to the British comedy group Monty Python [61] —and in occasionally playful approaches to tutorials and reference materials, such as examples that refer to spam and eggs (from a famous Monty Python sketch) instead of the standard foo and bar. [62] [63]

A common neologism in the Python community is pythonic, which can have a wide range of meanings related to program style. To say that code is pythonic is to say that it uses Python idioms well, that it is natural or shows fluency in the language, that it conforms with Python's minimalist philosophy and emphasis on readability. In contrast, code that is difficult to understand or reads like a rough transcription from another programming language is called unpythonic.

Users and admirers of Python, especially those considered knowledgeable or experienced, are often referred to as Pythonistas. [64] [65]

Syntax and semantics

Python is meant to be an easily readable language. Its formatting is visually uncluttered, and it often uses English keywords where other languages use punctuation. Unlike many other languages, it does not use curly brackets to delimit blocks, and semicolons after statements are optional. It has fewer syntactic exceptions and special cases than C or Pascal. [66]

Indentation

Python uses whitespace indentation, rather than curly brackets or keywords, to delimit blocks. An increase in indentation comes after certain statements; a decrease in indentation signifies the end of the current block. [67] Thus, the program's visual structure accurately represents the program's semantic structure. [1] This feature is sometimes termed the off-side rule, which some other languages share, but in most languages indentation doesn't have any semantic meaning.

Statements and control flow

Python's statements include (among others):

Python does not support tail call optimization or first-class continuations, and, according to Guido van Rossum, it never will. [70] [71] However, better support for coroutine-like functionality is provided in 2.5, by extending Python's generators. [72] Before 2.5, generators were lazy iterators; information was passed unidirectionally out of the generator. From Python 2.5, it is possible to pass information back into a generator function, and from Python 3.3, the information can be passed through multiple stack levels. [73]

Expressions

Some Python expressions are similar to languages such as C and Java, while some are not:

In Python, a distinction between expressions and statements is rigidly enforced, in contrast to languages such as Common Lisp, Scheme, or Ruby. This leads to duplicating some functionality. For example:

Statements cannot be a part of an expression, so list and other comprehensions or lambda expressions, all being expressions, cannot contain statements. A particular case of this is that an assignment statement such as a = 1 cannot form part of the conditional expression of a conditional statement. This has the advantage of avoiding a classic C error of mistaking an assignment operator = for an equality operator == in conditions: if (c = 1) { ... } is syntactically valid (but probably unintended) C code but if c = 1: ... causes a syntax error in Python.

Methods

Methods on objects are functions attached to the object's class; the syntax instance.method(argument) is, for normal methods and functions, syntactic sugar for Class.method(instance, argument). Python methods have an explicit self parameter to access instance data, in contrast to the implicit self (or this) in some other object-oriented programming languages (e.g., C++, Java, Objective-C, or Ruby). [84]

Typing

The standard type hierarchy in Python 3 Python 3. The standard type hierarchy.png
The standard type hierarchy in Python 3

Python uses duck typing and has typed objects but untyped variable names. Type constraints are not checked at compile time; rather, operations on an object may fail, signifying that the given object is not of a suitable type. Despite being dynamically typed, Python is strongly typed, forbidding operations that are not well-defined (for example, adding a number to a string) rather than silently attempting to make sense of them.

Python allows programmers to define their own types using classes, which are most often used for object-oriented programming. New instances of classes are constructed by calling the class (for example, SpamClass() or EggsClass()), and the classes are instances of the metaclass type (itself an instance of itself), allowing metaprogramming and reflection.

Before version 3.0, Python had two kinds of classes: old-style and new-style. [85] The syntax of both styles is the same, the difference being whether the class object is inherited from, directly or indirectly (all new-style classes inherit from object and are instances of type). In versions of Python 2 from Python 2.2 onwards, both kinds of classes can be used. Old-style classes were eliminated in Python 3.0.

The long-term plan is to support gradual typing [86] and from Python 3.5, the syntax of the language allows specifying static types but they are not checked in the default implementation, CPython. An experimental optional static type checker named mypy supports compile-time type checking. [87]

Summary of Python 3's built-in types
Type Mutability DescriptionSyntax examples
boolimmutable Boolean value True
False
bytearraymutableSequence of bytes bytearray(b'Some ASCII')
bytearray(b"Some ASCII")
bytearray([119,105,107,105])
bytesimmutableSequence of bytesb'Some ASCII'
b"Some ASCII"
bytes([119,105,107,105])
compleximmutable Complex number with real and imaginary parts3+2.7j
dictmutable Associative array (or dictionary) of key and value pairs; can contain mixed types (keys and values), keys must be a hashable type{'key1':1.0,3:False}
{}
ellipsis a immutableAn ellipsis placeholder to be used as an index in NumPy arrays...
Ellipsis
floatimmutable Double precision floating point number. The precision is machine dependent but in practice is generally implemented as a 64-bit IEEE 754 number with 53 bits of precision [88]

1.414

frozensetimmutableUnordered set, contains no duplicates; can contain mixed types, if hashablefrozenset([4.0,'string',True])
intimmutable Integer of unlimited magnitude [89] 42
listmutable List, can contain mixed types[4.0,'string',True]
[]
NoneType a immutableAn object representing the absence of a value, often called null in other languagesNone
NotImplementedType a immutableA placeholder that can be returned from overloaded operators to indicate unsupported operand types.NotImplemented
rangeimmutableA Sequence of numbers commonly used for looping specific number of times in for loops [90] range(1,10)
range(10,-5,-2)
setmutableUnordered set, contains no duplicates; can contain mixed types, if hashable{4.0,'string',True}
set()
strimmutableA character string: sequence of Unicode codepoints'Wikipedia'
"Wikipedia"
"""Spanningmultiplelines"""
tupleimmutableCan contain mixed types(4.0,'string',True)
('single element',)
()

^a Not directly accessible by name

Arithmetic operations

Python has the usual symbols for arithmetic operators (+, -, *, /), the floor division operator // and the modulo operation % (where the remainder can be negative, e.g. 4 % -3 == -2). It also has ** for exponentiation, e.g. 5**3 == 125 and 9**0.5 == 3.0, and a matrix multiply operator @ . [91] These operators work like in traditional math; with the same precedence rules, the operators infix ( + and - can also be unary to represent positive and negative numbers respectively).

Division between integers produces floating point results. The behavior of division has changed significantly over time: [92]

In Python terms, / is true division (or simply division), and // is floor division./ before version 3.0 is classic division. [92]

Rounding towards negative infinity, though different from most languages, adds consistency. For instance, it means that the equation (a + b)//b == a//b + 1 is always true. It also means that the equation b*(a//b) + a%b == a is valid for both positive and negative values of a. However, maintaining the validity of this equation means that while the result of a%b is, as expected, in the half-open interval [0, b), where b is a positive integer, it has to lie in the interval (b, 0] when b is negative. [93]

Python provides a round function for rounding a float to the nearest integer. For tie-breaking, Python 3 uses round to even: round(1.5) and round(2.5) both produce 2. [94] Versions before 3 used round-away-from-zero: round(0.5) is 1.0, round(-0.5) is −1.0. [95]

Python allows boolean expressions with multiple equality relations in a manner that is consistent with general use in mathematics. For example, the expression a < b < c tests whether a is less than b and b is less than c. [96] C-derived languages interpret this expression differently: in C, the expression would first evaluate a < b, resulting in 0 or 1, and that result would then be compared with c. [97]

Python uses arbitrary-precision arithmetic for all integer operations. The Decimal type/class in the decimal module provides decimal floating point numbers to a pre-defined arbitrary precision and several rounding modes. [98] The Fraction class in the fractions module provides arbitrary precision for rational numbers. [99]

Due to Python's extensive mathematics library, and the third-party library NumPy that further extends the native capabilities, it is frequently used as a scientific scripting language to aid in problems such as numerical data processing and manipulation. [100] [101]

Programming examples

Hello world program:

print('Hello, world!')

Program to calculate the factorial of a positive integer:

n=int(input('Type a number, and its factorial will be printed: '))ifn<0:raiseValueError('You must enter a non negative integer')fact=1foriinrange(2,n+1):fact*=iprint(fact)

Libraries

Python's large standard library, commonly cited as one of its greatest strengths, [102] provides tools suited to many tasks. For Internet-facing applications, many standard formats and protocols such as MIME and HTTP are supported. It includes modules for creating graphical user interfaces, connecting to relational databases, generating pseudorandom numbers, arithmetic with arbitrary-precision decimals, [103] manipulating regular expressions, and unit testing.

Some parts of the standard library are covered by specifications (for example, the Web Server Gateway Interface (WSGI) implementation wsgiref follows PEP 333 [104] ), but most modules are not. They are specified by their code, internal documentation, and test suites. However, because most of the standard library is cross-platform Python code, only a few modules need altering or rewriting for variant implementations.

As of November 2019, the Python Package Index (PyPI), the official repository for third-party Python software, contains over 200,000 [105] packages with a wide range of functionality, including:

Development environments

Most Python implementations (including CPython) include a read–eval–print loop (REPL), permitting them to function as a command line interpreter for which the user enters statements sequentially and receives results immediately.

Other shells, including IDLE and IPython, add further abilities such as improved auto-completion, session state retention and syntax highlighting.

As well as standard desktop integrated development environments, there are Web browser-based IDEs; SageMath (intended for developing science and math-related Python programs); PythonAnywhere, a browser-based IDE and hosting environment; and Canopy IDE, a commercial Python IDE emphasizing scientific computing. [107]

Implementations

Reference implementation

CPython is the reference implementation of Python. It is written in C, meeting the C89 standard with several select C99 features. [108] It compiles Python programs into an intermediate bytecode [109] which is then executed by its virtual machine. [110] CPython is distributed with a large standard library written in a mixture of C and native Python. It is available for many platforms, including Windows (Vista and later; supported Windows XP and older, with by now unsupported Python 2.7) and most modern Unix-like systems. Platform portability was one of its earliest priorities, [111] in Python 1 and 2 time-frame, even supporting VMS and OS/2; support has since been dropped for a lot of platforms.

Other implementations

PyPy is a fast, compliant interpreter of Python 2.7 and 3.6. [112] Its just-in-time compiler brings a significant speed improvement over CPython but several libraries written in C cannot be used with it. [113] [114]

Stackless Python is a significant fork of CPython that implements microthreads; it does not use the C memory stack, thus allowing massively concurrent programs. PyPy also has a stackless version. [115]

MicroPython and CircuitPython are Python 3 variants optimized for microcontrollers. This includes Lego Mindstorms EV3. [116]

Unsupported implementations

Other just-in-time Python compilers have been developed, but are now unsupported:

In 2005, Nokia released a Python interpreter for the Series 60 mobile phones named PyS60. It includes many of the modules from the CPython implementations and some additional modules to integrate with the Symbian operating system. The project has been kept up-to-date to run on all variants of the S60 platform, and several third-party modules are available. The Nokia N900 also supports Python with GTK widget libraries, enabling programs to be written and run on the target device. [118]

Cross-compilers to other languages

There are several compilers to high-level object languages, with either unrestricted Python, a restricted subset of Python, or a language similar to Python as the source language:

Performance

A performance comparison of various Python implementations on a non-numerical (combinatorial) workload was presented at EuroSciPy '13. [124] Python's performance compared to other programming languages has also been benchmarked by The Computer Language Benchmarks Game. [125]

Development

Python's development is conducted largely through the Python Enhancement Proposal (PEP) process, the primary mechanism for proposing major new features, collecting community input on issues and documenting Python design decisions. [126] Python coding style is covered in PEP 8. [127] Outstanding PEPs are reviewed and commented on by the Python community and the steering council. [126]

Enhancement of the language corresponds with development of the CPython reference implementation. The mailing list python-dev is the primary forum for the language's development. Specific issues are discussed in the Roundup bug tracker hosted at bugs.python.org. [128] Development originally took place on a self-hosted source-code repository running Mercurial, until Python moved to GitHub in January 2017. [129]

CPython's public releases come in three types, distinguished by which part of the version number is incremented:

Python 3.9 alpha1 was announced in November 2019 [132] and with the adoption of a new yearly release cadence, [133] [134] the first release of 3.9 is slated for November 2020. [135]

Many alpha, beta, and release-candidates are also released as previews and for testing before final releases. Although there is a rough schedule for each release, they are often delayed if the code is not ready. Python's development team monitors the state of the code by running the large unit test suite during development, and using the BuildBot continuous integration system. [136]

The major academic conference on Python is PyCon. There are also special Python mentoring programmes, such as Pyladies.

API documentation generators

Python API documentation generators include:

Naming

Python's name is derived from the British comedy group Monty Python, whom Python creator Guido van Rossum enjoyed while developing the language. Monty Python references appear frequently in Python code and culture; [137] for example, the metasyntactic variables often used in Python literature are spam and eggs instead of the traditional foo and bar. [137] [138] The official Python documentation also contains various references to Monty Python routines. [139] [140]

The prefix Py- is used to show that something is related to Python. Examples of the use of this prefix in names of Python applications or libraries include Pygame, a binding of SDL to Python (commonly used to create games); PyQt and PyGTK, which bind Qt and GTK to Python respectively; and PyPy, a Python implementation originally written in Python.

Uses

Since 2003, Python has consistently ranked in the top ten most popular programming languages in the TIOBE Programming Community Index where, as of February 2020, it is the third most popular language (behind Java, and C). [141] It was selected Programming Language of the Year in 2007, 2010, and 2018. [142]

An empirical study found that scripting languages, such as Python, are more productive than conventional languages, such as C and Java, for programming problems involving string manipulation and search in a dictionary, and determined that memory consumption was often "better than Java and not much worse than C or C++". [143]

Large organizations that use Python include Wikipedia, Google, [144] Yahoo!, [145] CERN, [146] NASA, [147] Facebook, [148] Amazon, Instagram, [149] Spotify [150] and some smaller entities like ILM [151] and ITA. [152] The social news networking site Reddit is written entirely in Python. [153]

Python can serve as a scripting language for web applications, e.g., via mod_wsgi for the Apache web server. [154] With Web Server Gateway Interface, a standard API has evolved to facilitate these applications. Web frameworks like Django, Pylons, Pyramid, TurboGears, web2py, Tornado, Flask, Bottle and Zope support developers in the design and maintenance of complex applications. Pyjs and IronPython can be used to develop the client-side of Ajax-based applications. SQLAlchemy can be used as a data mapper to a relational database. Twisted is a framework to program communications between computers, and is used (for example) by Dropbox.

Libraries such as NumPy, SciPy and Matplotlib allow the effective use of Python in scientific computing, [155] [156] with specialized libraries such as Biopython and Astropy providing domain-specific functionality. SageMath is a mathematical software with a notebook interface programmable in Python: its library covers many aspects of mathematics, including algebra, combinatorics, numerical mathematics, number theory, and calculus. [157] OpenCV has python bindings with a rich set of features for computer vision and image processing. [158]

Python has been successfully embedded in many software products as a scripting language, including in finite element method software such as Abaqus, 3D parametric modeler like FreeCAD, 3D animation packages such as 3ds Max, Blender, Cinema 4D, Lightwave, Houdini, Maya, modo, MotionBuilder, Softimage, the visual effects compositor Nuke, 2D imaging programs like GIMP, [159] Inkscape, Scribus and Paint Shop Pro, [160] and musical notation programs like scorewriter and capella. GNU Debugger uses Python as a pretty printer to show complex structures such as C++ containers. Esri promotes Python as the best choice for writing scripts in ArcGIS. [161] It has also been used in several video games, [162] [163] and has been adopted as first of the three available programming languages in Google App Engine, the other two being Java and Go. [164]

Python is commonly used in artificial intelligence projects and machine learning projects with the help of libraries like TensorFlow, Keras, Pytorch and Scikit-learn. [165] [166] [167] [168] As a scripting language with modular architecture, simple syntax and rich text processing tools, Python is often used for natural language processing. [169]

Many operating systems include Python as a standard component. It ships with most Linux distributions, [170] AmigaOS 4 (using Python 2.7), FreeBSD (as a package), NetBSD, OpenBSD (as a package) and macOS and can be used from the command line (terminal). Many Linux distributions use installers written in Python: Ubuntu uses the Ubiquity installer, while Red Hat Linux and Fedora use the Anaconda installer. Gentoo Linux uses Python in its package management system, Portage.

Python is used extensively in the information security industry, including in exploit development. [171] [172]

Most of the Sugar software for the One Laptop per Child XO, now developed at Sugar Labs, is written in Python. [173] The Raspberry Pi single-board computer project has adopted Python as its main user-programming language.

LibreOffice includes Python, and intends to replace Java with Python. Its Python Scripting Provider is a core feature [174] since Version 4.0 from 7 February 2013.

Languages influenced by Python

Python's design and philosophy have influenced many other programming languages:

Python's development practices have also been emulated by other languages. For example, the practice of requiring a document describing the rationale for, and issues surrounding, a change to the language (in Python, a PEP) is also used in Tcl, [184] Erlang, [185] and Swift. [186]

See also

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Nim (programming language)

Nim is an imperative, general-purpose, multi-paradigm, statically typed, systems, compiled programming language designed and developed by Andreas Rumpf. It is designed to be "efficient, expressive, and elegant", supporting metaprogramming, functional, message passing, procedural, and object-oriented programming styles by providing several features such as compile time code generation, algebraic data types, a foreign function interface (FFI) with C, C++, Objective-C, and JavaScript, and compiling to C, C++, Objective-C, and JavaScript.

Nuitka is a source to source compiler which compiles Python code to C source code, applying some compile-time optimizations in the process such as constant folding and propagation, built-in call prediction, type inference, and conditional statement execution. Nuitka initially was designed to produce C++ code, but current versions produce C source code using only those features of C11 that are shared by C++03, enabling further compilation to a binary executable format by modern C and C++ compilers including gcc, clang, MinGW, or Microsoft Visual C++. It accepts Python code compatible with several different Python versions and optionally allows for the creation of standalone programs that do not require Python to be installed on the target computer.

Tim Peters is an American software developer who created the Timsort hybrid sorting algorithm, and a major contributor to the Python programming language and its original CPython implementation. A pre-1.0 CPython user, he was among the group of early adopters who contributed to the detailed design of the language in its early stages.

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Sources

Further reading