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Guido van Rossum began working on Python in the late 1980s as a successor to theABC programming language. Python 3.0, released in 2008, was a major revision and not completelybackward-compatible with earlier versions. Beginning with Python 3.5,[34] capabilities and keywords for typing were added to the language, allowing optionalstatic typing.[35] Currently only versions in the 3.x series are supported.
Python has gained widespread use in themachine learning community.[36][37][38][39] It is widely taught as an introductory programming language.[40] Since 2003, Python has consistently ranked in the top ten of the most popular programming languages in theTIOBE Programming Community Index, which ranks based on searches in 24 platforms.[41]
Python was conceived in the late 1980s[42] byGuido van Rossum atCentrum Wiskunde & Informatica (CWI) in theNetherlands.[43] It was designed as a successor to theABC programming language, which was inspired bySETL,[44] capable ofexception handling and interfacing with theAmoeba operating system.[12] Python implementation began in December 1989.[43] Van Rossum first released it in 1991 as Python 0.9.0.[43] Van Rossum assumed sole responsibility for the project, as the lead developer, until 12 July 2018, when he announced his "permanent vacation" from responsibilities as Python's "benevolent dictator for life" (BDFL); this title was bestowed on him by the Python community to reflect his long-term commitment as the project's chief decision-maker.[45] (He has since come out of retirement and is self-titled "BDFL-emeritus".) In January 2019, active Python core developers elected a five-member Steering Council to lead the project.[46][47]
Python 2.0 was released on 16 October 2000, featuring many new features such aslist comprehensions,cycle-detecting garbage collection,reference counting, andUnicode support.[49] Python 2.7'send-of-life was initially set for 2015, and then postponed to 2020 out of concern that a large body of existing code could not easily be forward-ported to Python 3.[50][51] It no longer receives security patches or updates.[52][53] While Python 2.7 and older versions are officially unsupported, a different unofficial Python implementation,PyPy, continues to support Python 2, i.e., "2.7.18+" (plus 3.11), with the plus signifying (at least some) "backported security updates".[54]
Python 3.0 was released on 3 December 2008, and was a major revision and not completelybackward-compatible with earlier versions, with some new semantics and changed syntax. Python 2.7.18, released in 2020, was the last release of Python 2.[55] Several releases in the Python 3.x series have added new syntax to the language, and made a few (considered very minor) backward-incompatible changes.
As of November 2025[update], Python 3.14.0 is the latest stable release, and Python 3.13.9 was released a week later, all older 3.x versions had a security update down to Python 3.9.24 then again with 3.9.25, the final version in 3.9 series. Python 3.10 is, since November 2025, the oldest supported branch.[56] Python 3.15 has an alpha released, and Android has a official downloadable executable available for Python 3.14. Releases receive two years of full support followed by three years of security support.
Python's design offers some support for functional programming in the "Lisp tradition". It hasfilter,map, andreduce functions;list comprehensions,dictionaries,sets, andgenerator expressions.[64] The standard library has two modules (itertools andfunctools) that implement functional tools borrowed fromHaskell andStandard ML.[65]
Python's core philosophy is summarized in theZen of Python (PEP 20) written byTim Peters, which includes aphorisms such as these:[66]
Explicit is better than implicit.
Simple is better than complex.
Readability counts.
Special cases aren't special enough to break the rules.
Although practicality beats purity.
Errors should never pass silently.
Unless explicitly silenced.
There should be one-- and preferably only one --obvious way to do it.
However, Python has received criticism for violating these principles and adding unnecessary language bloat.[67] Responses to these criticisms note that the Zen of Python is a guideline rather than a rule.[68] The addition of some new features had been controversial: Guido van Rossum resigned asBenevolent Dictator for Life after conflict about adding the assignment expression operator inPython 3.8 .[69][70]
Nevertheless, rather than building all functionality into its core, Python was designed to be highlyextensible via modules. 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 represented the opposite approach.[42]
Python claims to strive for a simpler, less-cluttered syntax and grammar, while giving developers a choice in their coding methodology. Python lacks do while loops, whichRossum considered harmful.[71] In contrast toPerl's motto "there is more than one way to do it", Python advocates an approach where "there should be one – and preferably only one – obvious way to do it".[66] In practice, however, Python provides many ways to achieve a given goal. There are at least three ways to format a string literal, with no certainty as to which one a programmer should use.[72]Alex Martelli is aFellow at thePython Software Foundation and Python book author; he wrote that "To describe something as 'clever' isnot considered a compliment in the Python culture."[73]
Python's developers typically prioritise readability over performance. For example, they reject patches to non-critical parts of theCPython reference implementation that would offer increases in speed that do not justify the cost of clarity and readability.[74][failed verification] Execution speed can be improved by moving speed-critical functions to extension modules written in languages such asC, or by using ajust-in-time compiler likePyPy. Also, it is possible to transpile to other languages. However, this approach either fails to achieve the expected speed-up, since Python is a verydynamic language, or only a restricted subset of Python is compiled (with potential minor semantic changes).[75]
Python is meant to be a fun language to use. This goal is reflected in the name – a tribute to the British comedy groupMonty Python[76] – and in playful approaches to some tutorials and reference materials. For instance, some code examples use the terms "spam" and "eggs" (in reference toa Monty Python sketch), rather than the typical terms"foo" and "bar".[77][78]
A commonneologism in the Python community ispythonic, which has a broad range of meanings related to program style: Pythonic code may use Pythonidioms well; be natural or show fluency in the language; or conform with Python's minimalist philosophy and emphasis on readability.[79]
Python is meant to be an easily readable language. Its formatting is visually uncluttered and often uses English keywords where other languages use punctuation. Unlike many other languages, it does not usecurly brackets to delimit blocks, and semicolons after statements are allowed but rarely used. It has fewer syntactic exceptions and special cases thanC orPascal.[80]
Python useswhitespace indentation, rather than curly brackets or keywords, to delimitblocks. An increase in indentation comes after certain statements; a decrease in indentation signifies the end of the current block.[81] Thus, the program's visual structure accurately represents its semantic structure.[82] This feature is sometimes termed theoff-side rule. Some other languages use indentation this way; but in most, indentation has no semantic meaning. The recommended indent size is four spaces.[83]
Theassignment statement, using a single equals sign=
Theif statement, which conditionally executes a block of code, along withelse andelif (a contraction ofelse if)
Thefor statement, which iterates over aniterable object, capturing each element to a variable for use by the attached block; the variable is not deleted when the loop finishes
Thewhile statement, which executes a block of code as long as boolean condition is true
Thetry statement, which allows exceptions raised in its attached code block to be caught and handled byexcept clauses (or new syntaxexcept* in Python 3.11 for exception groups);[84] thetry statement also ensures that clean-up code in afinally block is always run regardless of how the block exits
Theraise statement, used to raise a specified exception or re-raise a caught exception
Theclass statement, which executes a block of code and attaches its local namespace to aclass, for use in object-oriented programming
Thewith statement, which encloses a code block within a context manager, allowingresource-acquisition-is-initialization (RAII)-like behavior and replacing a common try/finally idiom[85] Examples of a context include acquiring alock before some code is run, and then releasing the lock; or opening and then closing afile
Thecontinue statement, which skips the rest of the current iteration and continues with the next
Thedel statement, which removes a variable—deleting the reference from the name to the value, and producing an error if the variable is referred to before it is redefined[c]
Thepass statement, serving as aNOP (i.e., no operation), which is syntactically needed to create an empty code block
Theassert statement, used in debugging to check for conditions that should apply
Theyield statement, which returns a value from agenerator function (and also an operator); used to implementcoroutines
Thereturn statement, used to return a value from a function
Theimport andfrom statements, used to import modules whose functions or variables can be used in the current program
Thematch andcase statements, analogous to aswitch statement construct, which compares an expression against one or more cases as a control-flow measure
The assignment statement (=) binds a name as areference to a separate, dynamically allocatedobject. Variables may subsequently be rebound at any time to any object. In Python, a variable name is a generic reference holder without a fixeddata type; however, it always refers tosome object with a type. This is calleddynamic typing—in contrast tostatically-typed languages, where each variable may contain only a value of a certain type.
Python does not supporttail call optimization orfirst-class continuations; according to Van Rossum, the language never will.[86][87] However, better support forcoroutine-like functionality is provided by extending Python's generators.[88] Before 2.5, generators werelazyiterators; data was passed unidirectionally out of the generator. From Python 2.5 on, it is possible to pass data back into a generator function; and from version 3.3, data can be passed through multiple stack levels.[89]
The+,-, and* operators for mathematical addition, subtraction, and multiplication are similar to other languages, but the behavior of division differs. There are two types of division in Python:floor division (or integer division)//, and floating-point division/.[90] Python uses the** operator for exponentiation.
Python uses the+ operator for string concatenation. The language uses the* operator for duplicating a string a specified number of times.
The syntax:=, called the "walrus operator", was introduced in Python 3.8. This operator assigns values to variables as part of a larger expression.[93]
In Python,== compares two objects by value. Python'sis operator may be used to compare object identities (i.e., comparison by reference), and comparisons may be chained—for example,a<=b<=c.
Python usesand,or, andnot as Boolean operators.
Python has a type of expression called alist comprehension, and a more general expression called agenerator expression.[64]
Conditional expressions are written asxifcelsey.[94] (This is different in operand order from thec ? x : y operator common to many other languages.)
Python makes a distinction betweenlists andtuples. Lists are written as[1,2,3], are mutable, and cannot be used as the keys of dictionaries (since dictionary keys must beimmutable in Python). Tuples, written as(1,2,3), are immutable and thus can be used as the keys of dictionaries, provided that all of the tuple's elements are immutable. The+ operator can be used to concatenate two tuples, which does not directly modify their contents, but produces a new tuple containing the elements of both. For example, given the variablet initially equal to(1,2,3), executingt=t+(4,5) first evaluatest+(4,5), which yields(1,2,3,4,5); this result is then assigned back tot—thereby effectively "modifying the contents" oft while conforming to the immutable nature of tuple objects. Parentheses are optional for tuples in unambiguous contexts.[95]
Python featuressequence unpacking where multiple expressions, each evaluating to something assignable (e.g., a variable or a writable property) are associated just as in forming tuple literal; as a whole, the results are then put on the left-hand side of the equal sign in an assignment statement. This statement expects aniterable object on the right-hand side of the equal sign to produce the same number of values as the writable expressions on the left-hand side; while iterating, the statement assigns each of the values produced on the right to the corresponding expression on the left.[96]
Python has a "string format" operator% that functions analogously toprintf format strings in the C language—e.g."spam=%s eggs=%d"%("blah",2) evaluates to"spam=blah eggs=2". In Python 2.6+ and 3+, this operator was supplemented by theformat() method of thestr class, e.g.,"spam={0} eggs={1}".format("blah",2). Python 3.6 added "f-strings":spam="blah";eggs=2;f'spam={spam} eggs={eggs}'.[97]
Strings in Python can beconcatenated by "adding" them (using the same operator as for adding integers and floats); e.g.,"spam"+"eggs" returns"spameggs". If strings contain numbers, they are concatenated as strings rather than as integers, e.g."2"+"2" returns"22".
Delimited by single or double quotation marks; single and double quotation marks have equivalent functionality (unlike inUnix shells,Perl, and Perl-influenced languages). Both marks use the backslash (\) as anescape character.String interpolation became available in Python 3.6 as "formatted string literals".[97]
Triple-quoted, i.e., starting and ending with three single or double quotation marks; this may span multiple lines and function likehere documents in shells, Perl, andRuby.
Raw string varieties, denoted by prefixing the string literal withr. Escape sequences are not interpreted; hence raw strings are useful where literal backslashes are common, such as inregular expressions andWindows-style paths. (Compare "@-quoting" inC#.)
Python hasarray index andarray slicing expressions in lists, which are written asa[key],a[start:stop] ora[start:stop:step]. Indexes arezero-based, and negative indexes are relative to the end. Slices take elements from thestart index up to, but not including, thestop index. The (optional) third sliceparameter, calledstep orstride, allows elements to be skipped or reversed. Slice indexes may be omitted—for example,a[:] returns a copy of the entire list. Each element of a slice is ashallow copy.
In Python, a distinction between expressions and statements is rigidly enforced, in contrast to languages such asCommon Lisp,Scheme, orRuby. This distinction leads to duplicating some functionality, for example:
Theeval() vs.exec() built-in functions (in Python 2,exec is a statement); the former function is for expressions, while the latter is for statements
A statement cannot be part of an expression; because of this restriction, expressions such as list anddict comprehensions (and lambda expressions) cannot contain statements. As a particular case, an assignment statement such asa=1 cannot be part of the conditional expression of a conditional statement.
Python usesduck typing, and it has typed objects but untyped variable names. Type constraints are not checked at definition time; rather, operations on an object may fail at usage time, indicating that the object is not of an appropriate type. Despite beingdynamically typed, Python isstrongly typed, forbidding operations that are poorly defined (e.g., adding a number and a string) rather than quietly attempting to interpret them.
Python allows programmers to define their own types usingclasses, most often forobject-oriented programming. Newinstances of classes are constructed by calling the class, for example,SpamClass() orEggsClass()); the classes are instances of themetaclasstype (which is an instance of itself), thereby allowing metaprogramming andreflection.
Before version 3.0, Python had two kinds of classes, both using the same syntax:old-style andnew-style.[98] Current Python versions support the semantics of only the new style.
Python supportsoptional type annotations.[5][99] These annotations are not enforced by the language, but may be used by external tools such asmypy to catch errors. Python includes a moduletyping including several type names for type annotations.[100][101] Also, Mypy supports a Python compiler called mypyc, which leverages type annotations for optimization.[102]
Python includes conventional symbols for arithmetic operators (+,-,*,/), the floor-division operator//, and themodulo operator%. (With the modulo operator, a remainder can be negative, e.g.,4 % -3 == -2.) Also, Python offers the** symbol forexponentiation, e.g.5**3 == 125 and9**0.5 == 3.0. Also, it offers the matrix‑multiplication operator@ .[106] These operators work as in traditional mathematics; with the sameprecedence rules, theinfix operators+ and- can also beunary, to represent positive and negative numbers respectively.
Division between integers produces floating-point results. The behavior of division has changed significantly over time:[107]
The current version of Python (i.e., since 3.0) changed the/ operator to always represent floating-point division, e.g.,5/2==2.5.
The floor division// operator was introduced, meaning that7//3 == 2,-7//3 == -3,7.5//3 == 2.0, and-7.5//3 == -3.0. For Python 2.7, adding thefrom__future__importdivision statement allows a module in Python 2.7 to use Python 3.x rules for division (see above).
In Python terms, the/ operator representstrue division (or simplydivision), while the// operator representsfloor division. Before version 3.0, the/ operator representsclassic division.[107]
Rounding towards negative infinity, though a different method than in most languages, adds consistency to Python. For instance, this rounding implies that the equation(a+b)//b==a//b+1 is always true. Also, the rounding implies that the equationb*(a//b)+a%b==a is valid for both positive and negative values ofa. As expected, the result ofa%b lies in thehalf-open interval [0,b), whereb is a positive integer; however, maintaining the validity of the equation requires that the result must lie in the interval (b, 0] whenb is negative.[108]
Python provides around function for rounding a float to the nearest integer. Fortie-breaking, Python 3 uses theround to even method:round(1.5) andround(2.5) both produce2.[109] Python versions before 3 used theround-away-from-zero method:round(0.5) is1.0, andround(-0.5) is−1.0.[110]
Python allows Boolean expressions that contain multiple equality relations to be consistent with general usage in mathematics. For example, the expressiona < b < c tests whethera is less thanb andb is less thanc.[111] C-derived languages interpret this expression differently: in C, the expression would first evaluatea < b, resulting in 0 or 1, and that result would then be compared withc.[112]
Due to Python's extensive mathematics library and the third-party libraryNumPy, the language is frequently used for scientific scripting in tasks such as numerical data processing and manipulation.[115][116]
Functions are created in Python by using thedef keyword. A function is defined similarly to how it is called, by first providing the function name and then the required parameters. Here is an example of a function that prints its inputs:
defprinter(input1,input2="already there"):print(input1)print(input2)printer("hello")# Example output:# hello# already there
To assign a default value to a function parameter in case no actual value is provided at run time, variable-definition syntax can be used inside the function header.
Program to calculate thefactorial of a non-negative integer:
text=input('Type a number, and its factorial will be printed: ')n=int(text)ifn<0:raiseValueError('You must enter a non-negative integer')factorial=1foriinrange(2,n+1):factorial*=iprint(factorial)
Some parts of the standard library are covered by specifications—for example, theWeb Server Gateway Interface (WSGI) implementationwsgiref follows PEP 333[118]—but most parts are specified by their code, internal documentation, andtest suites. However, because most of the standard library is cross-platform Python code, only a few modules must be altered or rewritten for variant implementations.
As of 13 March 2025,[update] thePython Package Index (PyPI), the official repository for third-party Python software, contains over 614,339[119] packages.
Most[which?] Python implementations (including CPython) include aread–eval–print loop (REPL); this permits the environment to function as acommand line interpreter, with which users enter statements sequentially and receive results immediately.[120]
Other shells, includingIDLE andIPython, add additional capabilities such as improved auto-completion, session-state retention, andsyntax highlighting.[121][122]
CPython is thereference implementation of Python. This implementation is written in C, meeting theC11 standard[126] since version 3.11. Older versions use theC89 standard with several selectC99 features, but third-party extensions are not limited to older C versions—e.g., they can be implemented using C11 or C++.[127][128] CPythoncompiles Python programs into an intermediatebytecode,[129] which is then executed by avirtual machine.[130] CPython is distributed with a large standard library written in a combination of C and native Python.
CPython is available for many platforms, including Windows and most modernUnix-like systems, including macOS (andApple M1 Macs, since Python 3.9.1, using an experimental installer). Starting with Python 3.9, the Python installer intentionally fails to install onWindows 7 and 8;[131][132]Windows XP was supported until Python 3.5, with unofficial support forVMS.[133] Platform portability was one of Python's earliest priorities.[134] During development of Python 1 and 2, evenOS/2 andSolaris were supported;[7] since that time, support has been dropped for many platforms.
All current Python versions (since 3.7) support only operating systems that feature multithreading, by now supporting not nearly as many operating systems (dropping many outdated) than in the past.
All alternative implementations have at least slightly different semantics. For example, an alternative may include unordered dictionaries, in contrast to other current Python versions. As another example in the larger Python ecosystem, PyPy does not support the full C Python API.
Creating an executable with Python often is done by bundling an entire Python interpreter into the executable, which causes binary sizes to be massive for small programs,[136] yet there exist implementations that are capable of truly compiling Python. Alternative implementations include the following:
PyPy is a faster, compliant interpreter of Python 2.7 and 3.10.[137][138] PyPy'sjust-in-time compiler often improves speed significantly relative to CPython, but PyPy does not support some libraries written in C.[139] PyPy offers support for theRISC-V instruction-set architecture.
Codon is an implementation with anahead-of-time (AOT) compiler, which compiles a statically-typed Python-like language whose "syntax and semantics are nearly identical to Python's, there are some notable differences"[140] For example, Codon uses 64-bit machine integers for speed, not arbitrarily as with Python; Codon developers claim that speedups over CPython are usually on the order of ten to a hundred times. Codon compiles to machine code (viaLLVM) and supports native multithreading.[141] Codon can also compile to Python extension modules that can be imported and used from Python.
Pyston is a variant of the Python runtime that uses just-in-time compilation to speed up execution of Python programs.[143]
Cinder is a performance-oriented fork of CPython 3.8 that features a number of optimizations, including bytecode inline caching, eager evaluation of coroutines, a method-at-a-timeJIT, and an experimental bytecode compiler.[144]
The Snek[145][146][147] embedded computing language "is Python-inspired, but it is not Python. It is possible to write Snek programs that run under a full Python system, but most Python programs will not run under Snek."[148] Snek is compatible with 8-bitAVR microcontrollers such asATmega 328P-based Arduino, as well as larger microcontrollers that are compatible withMicroPython. Snek is an imperative language that (unlike Python) omitsobject-oriented programming. Snek supports only one numeric data type, which features 32-bitsingle precision (resemblingJavaScript numbers, though smaller).
Stackless Python is a significant fork of CPython that implementsmicrothreads. This implementation uses thecall stack differently, thus allowing massively concurrent programs. PyPy also offers a stackless version.[149]
Just-in-time Python compilers have been developed, but are now unsupported:
Google began a project namedUnladen Swallow in 2009: this project aimed to speed up the Python interpreter five-fold by usingLLVM, and improvemultithreading capability for scaling to thousands of cores,[150] while typical implementations are limited by theglobal interpreter lock.
Psyco is a discontinuedjust-in-timespecializing compiler, which integrates with CPython and transforms bytecode to machine code at runtime. The emitted code is specialized for certaindata types and is faster than standard Python code. Psyco does not support Python 2.7 or later.
PyS60 was a Python 2 interpreter forSeries 60 mobile phones, which was released byNokia in 2005. The interpreter implemented many modules from Python's standard library, as well as additional modules for integration with theSymbian operating system. The NokiaN900 also supports Python through theGTK widget library, allowing programs to be written and run on the target device.[151]
There are several compilers/transpilers to high-level object languages; the source language is unrestricted Python, a subset of Python, or a language similar to Python:
Cython compiles a superset of Python to C. The resulting code can be used with Python via direct C-level API calls into the Python interpreter.
PyJL compiles/transpiles a subset of Python to "human-readable, maintainable, and high-performance Julia source code".[75] Despite the developers' performance claims, this is not possible forarbitrary Python code; that is, compiling to a faster language or machine code is known to be impossible in the general case. The semantics of Python might potentially be changed, but in many cases speedup is possible with few or no changes in the Python code. The faster Julia source code can then be used from Python or compiled to machine code.
Nuitka compiles Python into C.[155] This compiler works with Python 3.4 to 3.13 (and 2.6 and 2.7) for Python's main supported platforms (and Windows 7 or even Windows XP) and for Android. The compiler developers claim full support for Python 3.10, partial support for Python 3.11 and 3.12, and experimental support for Python 3.13. Nuitka supports macOS including Apple Silicon-based versions. The compiler is free of cost, though it has commercial add-ons (e.g., for hiding source code).
Numba is a JIT compiler that is used from Python; the compiler translates a subset of Python and NumPy code into fast machine code. This tool is enabled by adding a decorator to the relevant Python code.
Pythran compiles a subset of Python 3 to C++ (C++11).[156]
RPython can be compiled to C, and it is used to build the PyPy interpreter for Python.
The Python → 11l → C++ transpiler[157] compiles a subset of Python 3 to C++ (C++17).
IronPython allows running Python 2.7 programs with the .NETCommon Language Runtime.[161] Analpha version (released in 2021), is available for "Python 3.4, although features and behaviors from later versions may be included."[162]
Jython compiles Python 2.7 to Java bytecode, allowing the use of Java libraries from a Python program.[163]
Pyrex (last released in 2010) andShed Skin (last released in 2013) compile to C and C++ respectively.
A performance comparison among various Python implementations, using a non-numerical (combinatorial) workload, was presented at EuroSciPy '13.[164] In addition, Python's performance relative to other programming languages is benchmarked byThe Computer Language Benchmarks Game.[165]
There are several approaches to optimizing Python performance, despite the inherent slowness of aninterpreted language. These approaches include the following strategies or tools:
Just-in-time compilation: Dynamically compiling parts of a Python program during the execution of the program. This technique is used in libraries such asNumba andPyPy.
Static compilation: Sometimes, Python code can be compiled into machine code sometime before execution. An example of this approach isCython, which compiles Python into C.
Concurrency andparallelism: Multiple tasks can be run simultaneously. Python contains modules such as `multiprocessing` to support this form of parallelism. Moreover, this approach helps to overcome limitations of theGlobal Interpreter Lock (GIL) in CPU tasks.
Efficientdata structures: Performance can also be improved by using data types such asSet for membership tests, ordeque fromcollections forqueue operations.
Performance gains can be observed by utilizing libraries such asNumPy. Most high performance Python libraries useC orFortran under the hood instead of the Python interpreter.[166]
Python's development is conducted mostly through thePython Enhancement Proposal (PEP) process; this process is the primary mechanism for proposing major new features, collecting community input on issues, and documenting Python design decisions.[167] Python coding style is covered in PEP 8.[83] Outstanding PEPs are reviewed and commented on by the Python community and the steering council.[167]
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 were originally discussed in theRoundupbug tracker hosted by the foundation.[168] In 2022, all issues and discussions were migrated toGitHub.[169] Development originally took place on aself-hosted source-code repository runningMercurial, until Python moved toGitHub in January 2017.[170]
CPython's public releases have three types, distinguished by which part of the version number is incremented:
Backward-incompatible versions, where code is expected to break and must be manuallyported. The first part of the version number is incremented. These releases happen infrequently—version 3.0 was released 8 years after 2.0. According to Guido van Rossum, a version 4.0 will probably never exist.[171]
Major or "feature" releases are largely compatible with the previous version but introduce new features. The second part of the version number is incremented. Starting with Python 3.9, these releases are expected to occur annually.[172][173] Each major version is supported by bug fixes for several years after its release.[174]
Bug fix releases,[175] which introduce no new features, occur approximately every three months; these releases are made when a sufficient number of bugs have been fixedupstream since the last release. Security vulnerabilities are also patched in these releases. The third and final part of the version number is incremented.[175]
Manyalpha, beta, and release-candidates are also released as previews and for testing before final releases. Although there is a rough schedule for releases, they are often delayed if the code is not ready yet. Python's development team monitors the state of the code by running a largeunit test suite during development.[176]
Python's name is inspired by the British comedy groupMonty Python, whom Python creator Guido van Rossum enjoyed while developing the language. Monty Python references appear frequently in Python code and culture;[177] for example, themetasyntactic variables often used in Python literature arespam andeggs, rather than the traditionalfoo andbar.[177][178] Also, the official Python documentation contains various references to Monty Python routines.[179][180] Python users are sometimes referred to as "Pythonistas".[181]
^del in Python does not behave the same waydelete in languages such asC++ does, where such a word is used to call thedestructor and deallocate heap memory.
^ab"Why was Python created in the first place?".General Python FAQ. Python Software Foundation.Archived from the original on 24 October 2012. Retrieved22 March 2007.I had extensive experience with implementing an interpreted language in the ABC group at CWI, and from working with this group I had learned a lot about language design. This is the origin of many Python features, including the use of indentation for statement grouping and the inclusion of very high-level data types (although the details are all different in Python).
^abKuchling, Andrew M. (22 December 2006)."Interview with Guido van Rossum (July 1998)".amk.ca. Archived fromthe original on 1 May 2007. Retrieved12 March 2012.I'd spent a summer at DEC's Systems Research Center, which introduced me to Modula-2+; the Modula-3 final report was being written there at about the same time. What I learned there later showed up in Python's exception handling, modules, and the fact that methods explicitly contain 'self' in their parameter list. String slicing came from Algol-68 and Icon.
^van Rossum, Guido (1993). "An Introduction to Python for UNIX/C Programmers".Proceedings of the NLUUG Najaarsconferentie (Dutch UNIX Users Group).CiteSeerX10.1.1.38.2023.even though the design of C is far from ideal, its influence on Python is considerable.
^ab"Classes".The Python Tutorial. Python Software Foundation.Archived from the original on 23 October 2012. Retrieved20 February 2012.It is a mixture of the class mechanisms found in C++ and Modula-3
^Lundh, Fredrik."Call By Object".effbot.org.Archived from the original on 23 November 2019. Retrieved21 November 2017.replace "CLU" with "Python", "record" with "instance", and "procedure" with "function or method", and you get a pretty accurate description of Python's object model.
^Simionato, Michele."The Python 2.3 Method Resolution Order". Python Software Foundation.Archived from the original on 20 August 2020. Retrieved29 July 2014.The C3 method itself has nothing to do with Python, since it was invented by people working on Dylan and it is described in a paper intended for lispers
^Kuchling, A. M."Functional Programming HOWTO".Python v2.7.2 documentation. Python Software Foundation.Archived from the original on 24 October 2012. Retrieved9 February 2012.List comprehensions and generator expressions [...] are a concise notation for such operations, borrowed from the functional programming language Haskell.
^Schemenauer, Neil; Peters, Tim; Hetland, Magnus Lie (18 May 2001)."PEP 255 – Simple Generators".Python Enhancement Proposals. Python Software Foundation.Archived from the original on 5 June 2020. Retrieved9 February 2012.
^"More Control Flow Tools".Python 3 documentation. Python Software Foundation.Archived from the original on 4 June 2016. Retrieved24 July 2015.By popular demand, a few features commonly found in functional programming languages like Lisp have been added to Python. With the lambda keyword, small anonymous functions can be created.
^"re – Regular expression operations".Python 3.10.6 documentation.Archived from the original on 18 July 2018. Retrieved6 September 2022.This module provides regular expression matching operations similar to those found in Perl.
^"CoffeeScript".coffeescript.org.Archived from the original on 12 June 2020. Retrieved3 July 2018.
^Bezanson, Jeff; Karpinski, Stefan; Shah, Viral B.; Edelman, Alan (February 2012)."Why We Created Julia".Julia website.Archived from the original on 2 May 2020. Retrieved5 June 2014.We want something as usable for general programming as Python [...]
^abLattner, Chris (3 June 2014)."Chris Lattner's Homepage". Chris Lattner.Archived from the original on 25 December 2018. Retrieved3 June 2014.The Swift language is the product of tireless effort from a team of language experts, documentation gurus, compiler optimization ninjas, and an incredibly important internal dogfooding group who provided feedback to help refine and battle-test ideas. Of course, it also greatly benefited from the experiences hard-won by many other languages in the field, drawing ideas from Objective-C, Rust, Haskell, Ruby, Python, C#, CLU, and far too many others to list.
^"TIOBE Index". TIOBE.Archived from the original on 25 February 2018. Retrieved3 January 2023.The TIOBE Programming Community index is an indicator of the popularity of programming languages Updated as required.
^Healy, John; McInnes, Leland; Weir, Colin (2017). "Bridging the Cyber-Analysis Gap: The Democratization of Data Science".The Cyber Defense Review.2 (1):109–118.ISSN2474-2120.JSTOR26267404.Python is the lingua franca of data science and machine learning.
^Sultana, Simon G.; Reed, Philip A. (2017). "Curriculum for an Introductory Computer Science Course: Identifying Recommendations from Academia and Industry".The Journal of Technology Studies.43 (2):80–92.doi:10.21061/jots.v43i2.a.3.ISSN1071-6084.JSTOR90023144.
^"TIOBE Index". TIOBE.Archived from the original on 25 February 2018. Retrieved3 January 2023.The TIOBE Programming Community index is an indicator of the popularity of programming languages
^abVenners, Bill (13 January 2003)."The Making of Python".Artima Developer. Artima.Archived from the original on 1 September 2016. Retrieved22 March 2007.
^abcvan Rossum, Guido (20 January 2009)."A Brief Timeline of Python".The History of Python.Archived from the original on 5 June 2020. Retrieved20 January 2009.
^Kuchling, A. M.; Zadka, Moshe (16 October 2000)."What's New in Python 2.0". Python Software Foundation.Archived from the original on 23 October 2012. Retrieved11 February 2012.
^"3.3. Special method names".The Python Language Reference. Python Software Foundation.Archived from the original on 15 December 2018. Retrieved27 June 2009.
^"Reference counts". Extending and embedding the Python interpreter.Docs.python.org.Archived from the original on 18 October 2012. Retrieved5 June 2020.Since Python makes heavy use ofmalloc() andfree()}, it needs a strategy to avoid memory leaks as well as the re‑use of freed memory. The method chosen is calledreference counting.
^abHettinger, Raymond (30 January 2002)."PEP 289 – Generator Expressions".Python Enhancement Proposals. Python Software Foundation.Archived from the original on 14 June 2020. Retrieved19 February 2012.
^abPeters, Tim (19 August 2004)."PEP 20 – The Zen of Python".Python Enhancement Proposals. Python Software Foundation.Archived from the original on 26 December 2018. Retrieved24 November 2008.
^Lutz, Mark (January 2022)."Python changes 2014+".Learning Python.Archived from the original on 15 March 2024. Retrieved25 February 2024.
^ab"Transpiling Python to Julia using PyJL"(PDF).Archived(PDF) from the original on 19 November 2023. Retrieved20 September 2023.After manually modifying one line of code by specifying the necessary type information, we obtained a speedup of 52.6×, making the translated Julia code 19.5× faster than the original Python code.
^Guttag, John V. (12 August 2016).Introduction to Computation and Programming Using Python: With Application to Understanding Data. MIT Press.ISBN978-0-262-52962-4.
^van Rossum, Guido (22 April 2009)."Tail Recursion Elimination". Neopythonic.blogspot.be.Archived from the original on 19 May 2018. Retrieved3 December 2012.
^van Rossum, Guido; Eby, Phillip J. (10 May 2005)."PEP 342 – Coroutines via Enhanced Generators".Python Enhancement Proposals. Python Software Foundation.Archived from the original on 29 May 2020. Retrieved19 February 2012.
^"PEP 380". Python.org.Archived from the original on 4 June 2020. Retrieved3 December 2012.
^"division".python.org.Archived from the original on 20 July 2006. Retrieved30 July 2014.
^van Rossum, Guido; Hettinger, Raymond (7 February 2003)."PEP 308 – Conditional Expressions".Python Enhancement Proposals. Python Software Foundation.Archived from the original on 13 March 2016. Retrieved13 July 2011.
^Zadka, Moshe; van Rossum, Guido (11 March 2001)."PEP 237 – Unifying Long Integers and Integers".Python Enhancement Proposals. Python Software Foundation.Archived from the original on 28 May 2020. Retrieved24 September 2011.
^abZadka, Moshe; van Rossum, Guido (11 March 2001)."PEP 238 – Changing the Division Operator".Python Enhancement Proposals. Python Software Foundation.Archived from the original on 28 May 2020. Retrieved23 October 2013.
^abBatista, Facundo (17 October 2003)."PEP 327 – Decimal Data Type".Python Enhancement Proposals. Python Software Foundation.Archived from the original on 4 June 2020. Retrieved24 November 2008.
^"What's New in Python 2.6".Python v2.6.9 documentation. 29 October 2013.Archived from the original on 23 December 2019. Retrieved26 September 2015.
^ab"IDLE — Python editor and shell".Python documentation. v3.13.7. Retrieved31 August 2025.IDLE is Python's Integrated Development and Learning Environment.
^van Rossum, Guido (5 June 2001)."PEP 7 – Style Guide for C Code".Python Enhancement Proposals. Python Software Foundation.Archived from the original on 1 June 2020. Retrieved24 November 2008.
^"Jython FAQ".www.jython.org.Archived from the original on 22 April 2021. Retrieved22 April 2021.
^Murri, Riccardo (2013).Performance of Python runtimes on a non-numeric scientific code. European Conference on Python in Science (EuroSciPy).arXiv:1404.6388.Bibcode:2014arXiv1404.6388M.
^abWarsaw, Barry; Hylton, Jeremy; Goodger, David (13 June 2000)."PEP 1 – PEP Purpose and Guidelines".Python Enhancement Proposals. Python Software Foundation.Archived from the original on 6 June 2020. Retrieved19 April 2011.
^abAahz; Baxter, Anthony (15 March 2001)."PEP 6 – Bug Fix Releases".Python Enhancement Proposals. Python Software Foundation.Archived from the original on 5 June 2020. Retrieved27 June 2009.
^"Python Buildbot".Python Developer's Guide. Python Software Foundation.Archived from the original on 5 June 2020. Retrieved24 September 2011.
^ab"Whetting Your Appetite".The Python Tutorial. Python Software Foundation.Archived from the original on 26 October 2012. Retrieved20 February 2012.
^"Why We Created Julia".Julia website. February 2012.Archived from the original on 2 May 2020. Retrieved5 June 2014.We want something as usable for general programming as Python [...]
^"Modular Docs – Why Mojo".docs.modular.com.Archived from the original on 5 May 2023. Retrieved5 May 2023.Mojo as a member of the Python family [..] Embracing Python massively simplifies our design efforts, because most of the syntax is already specified. [..] we decided that the right long-term goal for Mojo is to provide a superset of Python (i.e. be compatible with existing programs) and to embrace the CPython immediately for long-tail ecosystem enablement. To a Python programmer, we expect and hope that Mojo will be immediately familiar, while also providing new tools for developing systems-level code that enable you to do things that Python falls back to C and C++ for.
