Python Esp Hack

[Alacoque Whitchurch]

Pythonis 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.[34][35]

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.[36] Python 2.0 was released in 2000. Python 3.0, released in 2008, was a major revision not completely backward-compatible with earlier versions. Python 2.7.18, released in 2020, was the last release of Python 2.[37]

Python was invented in the late 1980s[42] 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,[43] capable of exception handling and interfacing with the Amoeba operating system.[12] Its implementation began in December 1989.[44] 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[45] (he's 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, with many major new features such as list comprehensions, cycle-detecting garbage collection, reference counting, and Unicode support.[48] Python 3.0, released on 3 December 2008, with many of its major features backported to Python 2.6.x[49] and 2.7.x. Releases of Python 3 include the 2to3 utility, which automates the translation of Python 2 code to Python 3.[50]

Python 2.7's end-of-life was initially set for 2015, then postponed to 2020 out of concern that a large body of existing code could not easily be forward-ported to Python 3.[51][52] No further security patches or other improvements will be released for it.[53][54] Currently only 3.8 and later are supported (2023 security issues were fixed in e.g. 3.7.17, the final 3.7.x release[55]). While Python 2.7 and older is officially unsupported, a different unofficial Python implementation, PyPy, continues to support Python 2, i.e. "2.7.18+" (plus 3.9 and 3.10), with the plus meaning (at least some) "backported security updates".[56]

In 2021 (and again twice in 2022), security updates were expedited, since all Python versions were insecure (including 2.7[57]) because of security issues leading to possible remote code execution[58] and web-cache poisoning.[59] In 2022, Python 3.10.4 and 3.9.12 were expedited[60] and 3.8.13, because of many security issues.[61] When Python 3.9.13 was released in May 2022, it was announced that the 3.9 series (joining the older series 3.8 and 3.7) would only receive security fixes in the future.[62] On 7 September 2022, four new releases were made due to a potential denial-of-service attack: 3.10.7, 3.9.14, 3.8.14, and 3.7.14.[63][64]

Every Python release since 3.5 has added some syntax to the language. 3.10 added the union type operator [65] and the match and case keywords (for structural pattern matching statements). 3.11 expanded exception handling functionality. Python 3.12 added the new keyword type.

Notable changes in 3.11 from 3.10 include increased program execution speed and improved error reporting.[66] Python 3.11 claims to be between 10 and 60% faster than Python 3.10, and Python 3.12 adds another 5% on top of that. It also has improved error messages, and many other changes.

Python 3.13 introduced an incremental garbage collector (producing shorter pauses for collection in programs with a lot of objects); an experimental JIT compiler;[68] and removals from the C API. Some standard library modules and many deprecated classes, functions and methods, will be removed in Python 3.15 and or 3.16.[69][70] Starting with 3.13, it and later versions have 2 years of full support (up from one and a half); followed by 3 years of security support (for same total support as before).

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[71] and metaobjects).[72] Many other paradigms are supported via extensions, including design by contract[73][74] and logic programming.[75]

Python uses dynamic typing and a combination of reference counting and a cycle-detecting garbage collector for memory management.[76] 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,mapandreduce functions; list comprehensions, dictionaries, sets, and generator expressions.[77] The standard library has two modules (itertools and functools) that implement functional tools borrowed from Haskell and Standard ML.[78]

However, Python features regularly violate these principles and have received criticism for adding unnecessary language bloat.[80] Responses to these criticisms are that the Zen of Python is a guideline rather than a rule.[81] The addition of 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.[82][83]

Nevertheless, rather than building all of its functionality into its core, Python was designed to be highly extensible 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 espoused the opposite approach.[42]

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.[86] Execution speed can be improved by moving speed-critical functions to extension modules written in languages such as C, or by using a just-in-time compiler like PyPy. It is also possible to cross-compile to other languages, but 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.[87]

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.[92]

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.[93] Thus, the program's visual structure accurately represents its semantic structure.[94] 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.[95]

Python does not support tail call optimization or first-class continuations, and, according to Van Rossum, it never will.[98][99] However, better support for coroutine-like functionality is provided by extending Python's generators.[100] Before 2.5, generators were lazy iterators; 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, it can be passed through multiple stack levels.[101]

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:

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, Ruby).[110] Python also provides methods, often called dunder methods (due to their names beginning and ending with double-underscores), to allow user-defined classes to modify how they are handled by native operations including length, comparison, in arithmetic operations and type conversion.[111]

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 it 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, 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.

Python supports optional type annotations.[4][113] These annotations are not enforced by the language, but may be used by external tools such as mypy to catch errors.[114][115] Mypy also supports a Python compiler called mypyc, which leverages type annotations for optimization.[116]

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