It is dynamically typed and garbage-collected. It supports multiple programming paradigms, including structured (particularly procedural), object-oriented, and functional programming. It is often described as a "batteries included" language due to its comprehensive standard library.
Guido van Rossum began working on Python in the late 1980s as a successor to the ABC programming language and first released it in 1991 as Python 0.9.0. Python 2.0 was released in 2000 and subsequently in 2008, python 3.0 was released, which was also a major revision not completely backward compatible with earlier versions. Python 2.7.18, released in 2020, was the last release of Python 2.
Python consistently ranks as one of the most popular programming languages and has gained widespread use in the machine-learning community.
Python was invented in the late 1980s 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, capable of exception handling and interfacing with the Amoeba operating system. Its implementation began in December 1989. 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" (BDFL), a title the Python community bestowed upon him 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.
Python is a multi-paradigm programming language. Object-oriented and structured programming are fully supported, and many of their features support functional and aspect-oriented programming (including metaprogramming and metaobjects). Many other paradigms are supported via extensions, including design by contract and logic programming. Python is known as a glue language, and it can work very well with many other languages with ease of access.
Python uses dynamic typing, 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.
Its 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.
Its core philosophy is summarized in the Zen of Python (PEP 20), which includes aphorisms such as;
However, Python features regularly violate these principles and have received criticism for adding unnecessary language bloat. Responses to these criticisms are that the Zen of Python is a guideline rather than a rule. Adding some new features had been so controversial that Guido van Rossum resigned as Benevolent Dictator for Life following vitriol over the addition of the assignment expression operator in Python 3.8.
Nevertheless, rather than building all of its functionality into its core, Python was designed to be highly extensible via modules. The 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.
Python claims to strive 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 as "there should be one - and preferably only one - obvious way to do it" philosophy.
In practice, however, Python provides many ways to achieve the same task. There are, for example, at least three ways to format a string literal, with no certainty as to which one a programmer should use. Alex Martelli, a Fellow at the Python Software Foundation and Python book author, wrote: "To describe something as 'clever' is not considered a compliment in Python culture".
Python's developers usually 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. Execution speed can be improved by moving speed-critical functions to extension modules written in languages like C or using a just-in-time compiler like PyPy. It is also possible to cross-compile to other languages. Still, it either doesn't provide the full speed-up that might be expected, since Python is a very dynamic language, or a restricted subset of Python is compiled, and possibly semantics are slightly changed.
Python's developers aim for it to be fun to use. This is reflected in its name - a tribute to the British comedy group Monty Python - and occasionally playful approaches to tutorials and reference materials, such as the use of the terms "spams", and "eggs" (a reference to a Monty Python sketch) in examples, instead of the often-used "foo" and "bar". A common neologism in the Python community is pythonic; which has a wide range of meanings related to programming styles. "Pythonic" code may use Python idioms well, be natural to show fluency in the language, or conform with Python's minimalist philosophy and emphasis on readability. Code that is difficult to understand or reads like a rough transcription from another programming language is called unpythonic.
Python is meant to be an easily readable language. Its formatting is visually uncluttered and often uses English keywords whereas 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.
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.
Python's statements include;
The assignment statement (=) binds a name as a reference to a separate, dynamically allocated object. Variables may subsequently be rebound at any time to any object. In Python, a variable name is a generic reference holder without a fixed data type; however, it always refers to some object with a type. This is called dynamic typing - in contrast to statically typed languages, where each variable may contain only a value of a certain type.
Python does not support tail call optimization or first-class continuations, and according to Van Rossum, it never will. However, better support for coroutine-like functionality is provided by extending Python's generators. Before 2.5, generators were lazy iterators; data was passed unidirectionally out of the generator. From Python 2.5 onwards, it is possible to pass data back into a generator function, and from version 3.3, it can be passed through multiple stack levels.