Python (programming language) — A Video Map Guide

of Python The designer of Python, Guido van Rossum, at PyCon US 2024 Python was conceived in the late 1980s by Guido van Rossum at Centrum Wiskunde & Informatica (CWI) in the Netherlands. It was designed as a successor to the ABC programming language, which was inspired by SETL, capable of exception handling and interfacing with the Amoeba operating system. Python implementation began in December 1989. Van Rossum first released it in 1991 as Python 0.9.0. 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. (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. The name Python derives from the British comedy series Monty Python's Flying Circus. (See § Naming.) Python 2.0 was released on 16 October 2000, featuring many new features such as list comprehensions, cycle-detecting garbage collection, reference counting, and Unicode support. Python 2.7's end-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. It no longer receives security patches or updates. 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". Python 3.0 was released on 3 December 2008, and was a major revision and not completely backward-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. Several

Python is a multi-paradigm programming language. Object-oriented programming and structured programming are fully supported, and many of their features support functional programming and aspect-oriented programming – including metaprogramming and metaobjects. Many other paradigms are supported via extensions, including design by contract and logic programming. Python is often referred to as a 'glue language' because it is purposely designed to be able to integrate components written in other languages. Python uses dynamic typing and a combination of reference counting and a cycle-detecting garbage collector for memory management. It uses 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. The standard library has two modules (itertools and functools) that implement functional tools borrowed from Haskell and Standard ML. Python's core philosophy is summarized in the Zen of Python (PEP 20) written by Tim Peters, which includes aphorisms such as these: 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. Responses to these criticisms note that the Zen of Python is a guideline rather than a rule. The addition of some new features had been controversial: Guido van Rossum resigned as Benevolent Dictator for Life after conflict about adding the assignment expression operator in Python 3.8. Nevertheless, rather than building all functional

Python syntax and semantics 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 use curly brackets to delimit blocks, and semicolons after statements are allowed but rarely used. It has fewer syntactic exceptions and special cases than C or Pascal. Indentation Python syntax and semantics § 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. Thus, the program's visual structure accurately represents its semantic structure. This feature is sometimes termed the off-side rule. Some other languages use indentation this way; but in most, indentation has no semantic meaning. The recommended indent size is four spaces. Statements and control flow Python's statements include the following: The assignment statement, using a single equals sign = The if statement, which conditionally executes a block of code, along with else and elif (a contraction of else if) The for statement, which iterates over an iterable object, capturing each element to a variable for use by the attached block; the variable is not deleted when the loop finishes The while statement, which executes a block of code as long as boolean condition is true The try statement, which allows exceptions raised in its attached code block to be caught and handled by except clauses (or new syntax except* in Python 3.11 for exception groups); the try statement also ensures that clean-up code in a finally block is always run regardless of how the block exits The raise statement, used to raise a specified exception or re-raise a caught exception The class statement, which executes a block of code and attaches its local namespace to a class, for use in object-oriented programming

"Hello, World!" program: print('Hello, World!') Program to calculate the factorial of a non-negative integer: text = input('Type a number, and its factorial will be printed: ') n = int(text) if n

Python's large standard library is commonly cited as one of its greatest strengths. For Internet-facing applications, many standard formats and protocols such as MIME and HTTP are supported. The language includes modules for creating graphical user interfaces, connecting to relational databases, generating pseudorandom numbers, arithmetic with arbitrary-precision decimals, 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—but most parts 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 must be altered or rewritten for variant implementations. As of 13 March 2025,[update] the Python Package Index (PyPI), the official repository for third-party Python software, contains over 614,339 packages.

Comparison of integrated development environments § Python Most Python implementations (including CPython) include a read–eval–print loop (REPL); this permits the environment to function as a command line interpreter, with which users enter statements sequentially and receive results immediately. Also, CPython is bundled with an integrated development environment (IDE) called IDLE, which is oriented toward beginners. Other shells, including IDLE and IPython, add additional capabilities such as improved auto-completion, session-state retention, and syntax highlighting. Standard desktop IDEs include PyCharm, Spyder, and Visual Studio Code; there are web browser-based IDEs, such as the following environments: Jupyter Notebooks, an open-source interactive computing platform; PythonAnywhere, a browser-based IDE and hosting environment; and Canopy, a commercial IDE from Enthought that emphasizes scientific computing.

List of Python software § Python implementations Reference implementation CPython is the reference implementation of Python. This implementation is written in C, meeting the C11 standard since version 3.11. Older versions use the C89 standard with several select C99 features, but third-party extensions are not limited to older C versions—e.g., they can be implemented using C11 or C++. CPython compiles Python programs into an intermediate bytecode, which is then executed by a virtual machine. 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 modern Unix-like systems, including macOS (and Apple M1 Macs, since Python 3.9.1, using an experimental installer). Starting with Python 3.9, the Python installer intentionally fails to install on Windows 7 and 8; Windows XP was supported until Python 3.5, with unofficial support for VMS. Platform portability was one of Python's earliest priorities. During development of Python 1 and 2, even OS/2 and Solaris were supported; 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. Limitations of the reference implementation The energy usage of Python with CPython for typically written code is much worse than C by a factor of 75.88. The throughput of Python with CPython for typically written code is worse than C by a factor of 71.9. The average memory usage of CPython for typically written code is worse than C by a factor of 2.4. Other implementations 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 s

Python's development is conducted mostly through the Python 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. Python coding style is covered in PEP 8. Outstanding PEPs are reviewed and commented on by the Python community and the steering council. 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 the Roundup bug tracker hosted by the foundation. In 2022, all issues and discussions were migrated to GitHub. Development originally took place on a self-hosted source-code repository running Mercurial, until Python moved to GitHub in January 2017. 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 manually ported. 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. 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. Each major version is supported by bug fixes for several years after its release. Bug fix releases, which introduce no new features, occur approximately every three months; these releases are made when a sufficient number of bugs have been fixed upstream since the last release. Security vulnerabilities are also patched in these releases. The third and final part of the version number is incremented. Many alpha, beta, and release-candidates are also released as previews and for

Python's name is inspired by 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; for example, the metasyntactic variables often used in Python literature are spam and eggs, rather than the traditional foo and bar. Also, the official Python documentation contains various references to Monty Python routines. Python users are sometimes referred to as "Pythonistas".

Cobra has an Acknowledgements document that lists Python first among influencing languages. ECMAScript and JavaScript borrowed iterators and generators from Python. Go is designed for "speed of working in a dynamic language like Python". Julia was designed to be "as usable for general programming as Python". Mojo is almost a superset of Python. GDScript is strongly influenced by Python. Groovy, Boo, CoffeeScript, F#, Nim, Ruby, Swift, and V have been influenced, as well. See also @media(min-width:720px){} Computer programming portalFree and open-source software portal List of Python programming books pip (package manager) (see also uv) Pydoc NumPy SciPy Jupyter PyTorch Cython CPython Mojo Pygame PyQt PyGTK PyPy PyCon Google Colab – zero setup online IDE that runs Python Ren'Py Notes .skin-vector-2022 .skin-vector-2022 div .referencesdiv .referencesdiv .referencesdiv .referencesdiv .references ^ since 3.5, but those hints are ignored, except with unofficial tools ^ * Tier 1: 64-bit Linux, macOS; 64- and 32-bit Windows Tier 2: E.g. 32-bit WebAssembly (WASI) Tier 3: 64-bit Android, iOS, FreeBSD, and (32-bit) Raspberry Pi OSUnofficial (or has been known to work): Other Unix-like/BSD variants) and a few other platforms ^ del in Python does not behave the same way delete in languages such as C++ does, where such a word is used to call the destructor and deallocate heap memory.