Python is a general-purpose, high-level programming language[5] whose design philosophy emphasizes code readability.[6] Python claims to "[combine] remarkable power with very clear syntax",[7]and its standard library is large and comprehensive. Its use of indentation for block delimiters is unique among popular programming languages.
Python supports multiple programming paradigms, primarily but not limited to object-oriented, imperative and, to a lesser extent, functional programming styles. It features a fully dynamic typesystem and automatic memory management, similar to that of Scheme, Ruby, Perl, and Tcl. Like other dynamic languages, Python is often used as a scripting language, but is also used in a wide range of non-scripting contexts. Using third-party tools, Python code can be packaged into standalone executable programs. Python interpreters are available for many operating systems.
The reference implementation of Python (CPython) is free and open source software and has a community-based development model, as do all or nearly all of its alternative implementations. CPython is managed by the non-profit Python Software Foundation.
Python is a multi-paradigm programming language. Rather than forcing programmers to adopt a particular style of programming, it permits several styles: object-oriented programming and structured programmingare fully supported, and there are a number of language features which support functional programming and aspect-oriented programming (including by metaprogramming[15] and by magic methods).[16] Many other paradigms are supported using extensions, such as pyDBC[17] and Contracts for Python[18] which allow Design by Contract.
Python uses dynamic typing and a combination of reference counting and a cycle-detecting garbage collector for memory management. An important feature of Python is dynamic name resolution (late binding), which binds method and variable names during program execution.
Rather than requiring all desired functionality to be built into the language's core, Python was designed to be highly extensible. New built-in modules can be easily written in C, C++ or Cython. Python can also be used as an extension language for existing modules and applications that need a programmable interface. This design of a small core language with a large standard library and an easily extensible interpreter was intended by Van Rossum from the very start because of his frustrations with ABC (which espoused the opposite mindset).[8]
The design of Python offers only limited support for functional programming in the Lisp tradition. However, Python's design philosophy exhibits significant similarities to those of minimalistic Lisp-family languages, such asScheme.[citation needed] The language has map(), reduce() and filter() functions, and the list comprehensions added in Python 2.0 have since been extended with comprehensions for dictionaries and sets, as well as generator expressions. The standard library has two modules (itertools and functools) that implement functional tools borrowed from Haskell and Standard ML.[19]
While offering choice in coding methodology, the Python philosophy rejects exuberant syntax, such as in Perl, in favor of a sparser, less-cluttered grammar. Python's developers expressly promote a particular "culture" or ideology based on what they want the language to be, favoring language forms they see as "beautiful", "explicit" and "simple". As Alex Martelli put it in his Python Cookbook (2nd ed., p. 230): "To describe something as clever is NOT considered a compliment in the Python culture." Python's philosophy rejects the Perl "there is more than one way to do it" approach to language design in favor of "there should be one—and preferably only one—obvious way to do it".[20]
Python's developers eschew premature optimization, and moreover, reject patches to non-critical parts of CPython which would offer a marginal increase in speed at the cost of clarity.[21] Python is sometimes described as "slow".[22]However, by the Pareto principle, most problems and sections of programs are not speed critical. When speed is important, Python programmers tend to try using a JIT compiler such as Psyco or using an alternative language implementation such as PyPy. When pure Python code isn't fast enough, time-critical functions can be rewritten in "closer to the metal" languages such as C, or by translating (a dialect of) Python code to C code using tools like Cython.[23]
The core philosophy of the language is summarized by the document "PEP 20 (The Zen of Python)".[20
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