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Paradigm | multi-paradigm: object-oriented, imperative, functional, procedural, reflective |
---|---|
Designed by | Guido van Rossum |
Developer | Python Software Foundation |
First appeared | 20 February 1991[1] |
Stable release | 3.5.1 / 7 December 2015[2] 2.7.11 / 5 December 2015[3] |
Typing discipline | duck, dynamic, strong, gradual (as of Python 3.5)[4] |
OS | Cross-platform |
License | Python Software Foundation License |
Filename extensions | .py, .pyc, .pyd, .pyo,[5] pyw, .pyz[6] |
Website | www |
Major implementations | |
CPython, IronPython, Jython, PyPy | |
Dialects | |
Cython, RPython, Stackless Python | |
Influenced by | |
ABC,[7] ALGOL 68,[8] C,[9] C++,[10] Dylan,[11] Haskell,[12] Icon,[13] Java,[14] Lisp,[15] Modula‑3,[10] Perl | |
Influenced | |
Boo, Cobra, CoffeeScript,[16] D, F#, Falcon, Genie,[17] Go, Groovy, JavaScript,[18][19] Julia,[20] Nim, Ruby,[21] Swift,[22] | |
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Python is a widely used high-level, general-purpose, interpreted, dynamic programming language.[23][24] Its design philosophy emphasizes code readability, and its syntax allows programmers to express concepts in fewer lines of code than would be possible in languages such as C++ or Java.[25][26] The language provides constructs intended to enable clear programs on both a small and large scale.[27]
Python supports multiple programming paradigms, including object-oriented, imperative and functional programming or procedural styles. It features a dynamic type system and automatic memory management and has a large and comprehensive standard library.[28]
Python interpreters are available for installation on many operating systems, allowing Python code execution on a wide variety of systems. Using third-party tools, such as Py2exe or Pyinstaller,[29] Python code can be packaged into stand-alone executable programs for some of the most popular operating systems, allowing the distribution of Python-based software for use on those environments without requiring the installation of a Python interpreter.
CPython, the reference implementation of Python, is free and open-source software and has a community-based development model, as do nearly all of its alternative implementations. CPython is managed by the non-profit Python Software Foundation.
Contents
History
![](https://web.archive.org/web/20160324223148im_/https://upload.wikimedia.org/wikipedia/commons/thumb/6/66/Guido_van_Rossum_OSCON_2006.jpg/220px-Guido_van_Rossum_OSCON_2006.jpg)
Python was conceived in the late 1980s,[30] and its implementation was started in December 1989[31] by Guido van Rossum at CWI in the Netherlands as a successor to the ABC language (itself inspired by SETL)[32] capable of exception handling and interfacing with the Amoeba operating system.[7] Van Rossum is Python's principal author, and his continuing central role in deciding the direction of Python is reflected in the title given to him by the Python community, benevolent dictator for life (BDFL).
About the origin of Python, Van Rossum wrote in 1996:[33]
Over six years ago, in December 1989, I was looking for a "hobby" programming project that would keep me occupied during the week around Christmas. My office ... would be closed, but I had a home computer, and not much else on my hands. I decided to write an interpreter for the new scripting language I had been thinking about lately: a descendant of ABC that would appeal to Unix/C hackers. I chose Python as a working title for the project, being in a slightly irreverent mood (and a big fan of Monty Python's Flying Circus).
Python 2.0 was released on 16 October 2000 and had many major new features, including a cycle-detecting garbage collector and support for Unicode. With this release the development process was changed and became more transparent and community-backed.[34]
Python 3.0 (which early in its development was commonly referred to as Python 3000 or py3k), a major, backwards-incompatible release, was released on 3 December 2008[35] after a long period of testing. Many of its major features have been backported to the backwards-compatible Python 2.6 and 2.7.[36]
Features and philosophy
Python is a multi-paradigm programming language: object-oriented programming and structured programming are fully supported, and there are a number of language features which support functional programming and aspect-oriented programming (including by metaprogramming[37] and by magic methods).[38] Many other paradigms are supported using extensions, including design by contract[39][40] and logic programming.[41]
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.
The design of Python offers some support for functional programming in the Lisp tradition. The language has map(), reduce() and filter() functions; comprehensions for lists, dictionaries, and sets; and generator expressions.[42] The standard library has two modules (itertools and functools) that implement functional tools borrowed from Haskell and Standard ML.[43]
The core philosophy of the language is summarized by the document "PEP 20 (The Zen of Python)", which includes aphorisms such as:[44]
- Beautiful is better than ugly
- Explicit is better than implicit
- Simple is better than complex
- Complex is better than complicated
- Readability counts
Rather than requiring all desired functionality to be built into the language's core, Python was designed to be highly extensible. Python can also be embedded in existing 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).[30]
While offering choice in coding methodology, the Python philosophy rejects exuberant syntax, such as in Perl, in favor of a sparser, less-cluttered grammar. As Alex Martelli put it: "To describe something as clever is not considered a compliment in the Python culture."[45] 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".[44]
Python's developers strive to avoid premature optimization, and moreover, reject patches to non-critical parts of CPython that would offer a marginal increase in speed at the cost of clarity.[46] When speed is important, a Python programmer can move time-critical functions to extension modules written in languages such as C, or try using PyPy, a just-in-time compiler. Cython is also available, which translates a Python script into C and makes direct C-level API calls into the Python interpreter.
An important goal of the Python developers is making Python fun to use. This is reflected in the origin of the name, which comes from Monty Python,[47] and in an occasionally playful approach to tutorials and reference materials, such as using examples that refer to spam and eggs instead of the standard foo and bar.[48][49]
A common neologism in the Python community is pythonic, which can have a wide range of meanings related to program style. To say that code is pythonic is to say that it uses Python idioms well, that it is natural or shows fluency in the language, that it conforms with Python's minimalist philosophy and emphasis on readability. In contrast, code that is difficult to understand or reads like a rough transcription from another programming language is called unpythonic.
Users and admirers of Python—especially those considered knowledgeable or experienced—are often referred to as Pythonists, Pythonistas, and Pythoneers.[50][51]
Syntax and semantics
Python is intended to be a highly readable language. It is designed to have an uncluttered visual layout, frequently using English keywords where other languages use punctuation. Furthermore, Python has a smaller number of syntactic exceptions and special cases than C or Pascal.[52]
Indentation
Python uses whitespace indentation, rather than curly braces or keywords, to delimit blocks; this feature is also termed the off-side rule. An increase in indentation comes after certain statements; a decrease in indentation signifies the end of the current block.[53]
Statements and control flow
Python's statements include (among others):
- The assignment statement (token '=', the equals sign). This operates differently than in traditional imperative programming languages, and this fundamental mechanism (including the nature of Python's version of "variables") illuminates many other features of the language. Assignment in C, e.g., "x = 2", translates to "typed variable name x receives a copy of numeric value 2". The (right-hand) value is copied into an allocated storage location for which the (left-hand) variable name is the symbolic address. The memory allocated to the variable is large enough (potentially quite large) for the declared type. In the simplest case of Python assignment, using the same example, "x = 2", translates to "(generic) name x receives a reference to a separate, dynamically allocated object of numeric (int) type of value 2." This is referred to as "binding" the name to the object. Since the name's storage location doesn't "contain" the indicated value, it is not proper to refer to it as a "variable." Names may be subsequently re-bound at any time to objects of greatly varying types, including strings, procedures, complex objects with data and methods, etc. Successive assignments of a common value to multiple names, e.g., "x = 2"; "y = 2"; "z = 2" result in allocating storage to (at most) three names and a single numeric object, to which all three names are bound. Since a name is a generic reference holder it is not reasonable to associate a fixed data type with it. However at a given time a name will be bound to some object, which will have a type; thus there is dynamic typing.
- The
if
statement, which conditionally executes a block of code, along withelse
andelif
(a contraction of else-if). - The
for
statement, which iterates over an iterable object, capturing each element to a local variable for use by the attached block. - The
while
statement, which executes a block of code as long as its condition is true. - The
try
statement, which allows exceptions raised in its attached code block to be caught and handled byexcept
clauses; it also ensures that clean-up code in afinally
block will always be run regardless of how the block exits. - The
class
statement, which executes a block of code and attaches its local namespace to a class, for use in object-oriented programming. - The
def
statement, which defines a function or method. - The
with
statement (from Python 2.5), which encloses a code block within a context manager (for example, acquiring a lock before the block of code is run and releasing the lock afterwards, or opening a file and then closing it), allowing RAII-like behavior. - The
pass
statement, which serves as a NOP. It is syntactically needed to create an empty code block. - The
assert
statement, used during debugging to check for conditions that ought to apply. - The
yield
statement, which returns a value from a generator function. From Python 2.5,yield
is also an operator. This form is used to implement coroutines. - The
import
statement, which is used to import modules whose functions or variables can be used in the current program. - The
print
statement was changed to theprint()
function in Python 3.[54]
Python does not support tail-call optimization or first-class continuations, and, according to Guido van Rossum, it never will.[55][56] However, better support for coroutine-like functionality is provided in 2.5, by extending Python's generators.[57] Prior to 2.5, generators were lazy iterators; information was passed unidirectionally out of the generator. As of Python 2.5, it is possible to pass information back into a generator function, and as of Python 3.3, the information can be passed through multiple stack levels.[58]
Expressions
Some Python expressions are similar to languages such as C and Java, while some are not:
- Addition, subtraction, and multiplication are the same, but the behavior of division differs (see Mathematics for details). Python also added the
**
operator for exponentiation. - As of Python 3.5, it supports matrix multiplication directly with the
@
operator, as opposed to C and Java which implement these as library functions. Earlier versions of Python also used methods instead of an infix operator.[59][60] - In Python,
==
compares by value, in contrast to Java, which compares numerics by value[61] and objects by reference.[62] (Value comparisons in Java on objects can be performed with theequals()
method.) Python'sis
operator may be used to compare object identities (comparison by reference). In Python, comparisons may be chained, for examplea <= b <= c
. - Python uses the words
and
,or
,not
for its boolean operators rather than the symbolic&&
,||
,!
used in Java and C. - Python has a type of expression termed a list comprehension. Python 2.4 extended list comprehensions into a more general expression termed a generator expression.[42]
- Anonymous functions are implemented using lambda expressions; however, these are limited in that the body can only be a single expression.
- Conditional expressions in Python are written as
x if c else y
[63] (different in order of operands from the?:
operator common to many other languages). - Python makes a distinction between lists and tuples. Lists are written as
[1, 2, 3]
, are mutable, and cannot be used as the keys of dictionaries (dictionary keys must be immutable in Python). Tuples are written as(1, 2, 3)
, are immutable and thus can be used as the keys of dictionaries, provided all elements of the tuple are immutable. The parentheses around the tuple are optional in some contexts. Tuples can appear on the left side of an equal sign; hence a statement likex, y = y, x
can be used to swap two variables. - Python has a "string format" operator
%
. This functions analogous toprintf
format strings in C, e.g."spam=%s eggs=%d" % ("blah", 2)
evaluates to"spam=blah eggs=2"
. In Python 3 and 2.6+, this was supplemented by theformat()
method of thestr
class, e.g."spam={0} eggs={1}".format("blah", 2)
. - Python has various kinds of string literals:
- Strings delimited by single or double quotation marks. Unlike in Unix shells, Perl and Perl-influenced languages, single quotation marks and double quotation marks function identically. Both kinds of string use the backslash (
\
) as an escape character and there is no implicit string interpolation such as"$spam"
. - Triple-quoted strings, which begin and end with a series of three single or double quotation marks. They may span multiple lines and function like here documents in shells, Perl and Ruby.
- Raw string varieties, denoted by prefixing the string literal with an
r
. No escape sequences are interpreted; hence raw strings are useful where literal backslashes are common, such as regular expressions and Windows-style paths. Compare "@
-quoting" in C#.
- Strings delimited by single or double quotation marks. Unlike in Unix shells, Perl and Perl-influenced languages, single quotation marks and double quotation marks function identically. Both kinds of string use the backslash (
- Python has index and slice expressions on lists, denoted as
a[key]
,a[start:stop]
ora[start:stop:step]
. Indexes are zero-based, and negative indexes are relative to the end. Slices take elements from the start index up to, but not including, the stop index. The third slice parameter, called step or stride, allows elements to be skipped and reversed. Slice indexes may be omitted, for examplea[:]
returns a copy of the entire list. Each element of a slice is a shallow copy.
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 some duplication of functionality. For example:
- List comprehensions vs.
for
-loops - Conditional expressions vs.
if
blocks - The
eval()
vs.exec()
built-in functions (in Python 2,exec
is a statement); the former is for expressions, the latter is for statements.
Statements cannot be a part of an expression, so list and other comprehensions or lambda expressions, all being expressions, cannot contain statements. A particular case of this is that an assignment statement such as a = 1
cannot form part of the conditional expression of a conditional statement. This has the advantage of avoiding a classic C error of mistaking an assignment operator =
for an equality operator ==
in conditions: if (c = 1) { ... }
is valid C code but if c = 1: ...
causes a syntax error in Python.
Methods
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, or Ruby).[64]
Typing
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 the given object 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, which are 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 themselves are instances of the metaclass type
(itself an instance of itself), allowing metaprogramming and reflection.
Prior to version 3.0, Python had two kinds of classes: "old-style" and "new-style".[65] Old-style classes were eliminated in Python 3.0, making all classes new-style. In versions between 2.2 and 3.0, both kinds of classes could be used. The syntax of both styles is the same, the difference being whether the class object
is inherited from, directly or indirectly (all new-style classes inherit from object
and are instances of type
).
Type | Mutable | Description | Syntax example |
---|---|---|---|
str |
Immutable | A character string: Sequence of Unicode codepoints. | 'Wikipedia' "Wikipedia" """Spanning |
bytearray |
Mutable | Sequence of bytes. | bytearray(b'Some ASCII') bytearray(b"Some ASCII") bytearray([119, 105, 107, 105]) |
bytes |
Immutable | Sequence of bytes. | b'Some ASCII' b"Some ASCII" bytes([119, 105, 107, 105]) |
list |
Mutable | List, can contain mixed types. | [4.0, 'string', True] |
tuple |
Immutable | Can contain mixed types. | (4.0, 'string', True) |
set |
Mutable | Unordered set, contains no duplicates. Can contain mixed types as long as they are hashable. | {4.0, 'string', True} |
frozenset |
Immutable | Unordered set, contains no duplicates. Can contain mixed types as long as they are hashable. | frozenset([4.0, 'string', True]) |
dict |
Mutable | Associative array (or dictionary) of key and value pairs. Can contain mixed types (keys and values). Keys must be a hashable type. |
{'key1': 1.0, 3: False} |
int |
Immutable | Integer of unlimited magnitude.[66] | 42 |
float |
Immutable | Floating point number (system-defined precision). | 3.1415927 |
complex |
Immutable | Complex number with real and imaginary parts. | 3+2.7j |
bool |
Immutable | Boolean value. | True False |
ellipsis |
An ellipsis placeholder to be used as an index in NumPy arrays. | ... |
Mathematics
Python has the usual C arithmetic operators (+
, -
, *
, /
, %
). It also has **
for exponentiation, e.g. 5**3 == 125
and 9**0.5 == 3.0
, and a new matrix multiply @
operator is included in version 3.5.[67]
The behavior of division has changed significantly over time:[68]
- Python 2.1 and earlier use the C division behavior. The
/
operator is integer division if both operands are integers, and floating-point division otherwise. Integer division rounds towards 0, e.g.7 / 3 == 2
and-7 / 3 == -2
. - Python 2.2 changes integer division to round towards negative infinity, e.g.
7 / 3 == 2
and-7 / 3 == -3
. The floor division//
operator is introduced. So7 // 3 == 2
,-7 // 3 == -3
,7.5 // 3 == 2.0
and-7.5 // 3 == -3.0
. Addingfrom __future__ import division
causes a module to use Python 3.0 rules for division (see next). - Python 3.0 changes
/
to always be floating-point division. In Python terms, the pre-3.0/
is "classic division", the version-3.0/
is "real division", and//
is "floor division".
Rounding towards negative infinity, though different from most languages, adds consistency. For instance, it means that the equation (a+b) // b == a // b + 1
is always true. It also means that the equation b * (a // b) + a % b == a
is valid for both positive and negative values of a
. However, maintaining the validity of this equation means that while the result of a % b
is, as expected, in the half-open interval [0, b), where b
is a positive integer, it has to lie in the interval (b, 0] when b
is negative.[69]
Python provides a round
function for rounding a float to the nearest integer. For tie-breaking, versions before 3 use round-away-from-zero: round(0.5)
is 1.0, round(-0.5)
is −1.0.[70] Python 3 uses round-to-even: round(1.5)
is 2, round(2.5)
is 2.[71]
Python allows boolean expressions with multiple equality relations in a manner that is consistent with general usage in mathematics. For example, the expression a < b < c
tests whether a
is less than b
and b
is less than c
. C-derived languages interpret this expression differently: in C, the expression would first evaluate a < b
, resulting in 0 or 1, and that result would then be compared with c
.[72][page needed]
Python has extensive built-in support for arbitrary precision arithmetic. Integers are transparently switched from the machine-supported maximum fixed-precision (usually 32 or 64 bits), belonging to the python type int
, to arbitrary precision, belonging to the python type long
, where needed. The latter have an "L" suffix in their textual representation.[73] The Decimal
type/class in module decimal
(since version 2.4) provides decimal floating point numbers to arbitrary precision and several rounding modes.[74] The Fraction
type in module fractions
(since version 2.6) provides arbitrary precision for rational numbers.[75]
Due to Python's extensive mathematics library, it is frequently used as a scientific scripting language to aid in problems such as numerical data processing and manipulation.
Libraries
Python has a large standard library, commonly cited as one of Python's greatest strengths,[76] providing tools suited to many tasks. This is deliberate and has been described as a "batteries included"[28] Python philosophy. For Internet-facing applications, a large number of standard formats and protocols (such as MIME and HTTP) are supported. Modules for creating graphical user interfaces, connecting to relational databases, pseudorandom number generators, arithmetic with arbitrary precision decimals,[77] manipulating regular expressions, and doing unit testing are also included.
Some parts of the standard library are covered by specifications (for example, the WSGI implementation wsgiref
follows PEP 333[78]), but the majority of the modules are not. They are specified by their code, internal documentation, and test suite (if supplied). However, because most of the standard library is cross-platform Python code, there are only a few modules that must be altered or completely rewritten by alternative implementations.
The standard library is not essential to run Python or embed Python within an application. Blender 2.49, for instance, omits most of the standard library.
As of January 2016, the Python Package Index, the official repository of third-party software for Python, contains more than 72,000 packages offering a wide range of functionality, including:
- graphical user interfaces, web frameworks, multimedia, databases, networking and communications
- test frameworks, automation and web scraping, documentation tools, system administration
- scientific computing, text processing, image processing
Development environments
Most Python implementations (including CPython) can function as a command line interpreter, for which the user enters statements sequentially and receives the results immediately (REPL). In short, Python acts as a shell.
Other shells add capabilities beyond those in the basic interpreter, including IDLE and IPython. While generally following the visual style of the Python shell, they implement features like auto-completion, retention of session state, and syntax highlighting.
In addition to standard desktop Python IDEs (integrated development environments), there are also browser-based IDEs, Sage (intended for developing science and math-related Python programs), and a browser-based IDE and hosting environment, PythonAnywhere.
Implementations
The main Python implementation, named CPython, is written in C meeting the C89 standard.[79] It compiles Python programs into intermediate bytecode,[80] which is executed by the virtual machine.[81] CPython is distributed with a large standard library written in a mixture of C and Python. It is available in versions for many platforms, including Windows and most modern Unix-like systems. CPython was intended from almost its very conception to be cross-platform.[82]
PyPy is a fast, compliant[83] interpreter of Python 2.7 and 3.2. Its just-in-time compiler brings a significant speed improvement over CPython.[84] A version taking advantage of multi-core processors using software transactional memory is being created.[85]
Stackless Python is a significant fork of CPython that implements microthreads; it does not use the C memory stack, thus allowing massively concurrent programs. PyPy also has a stackless version.[86]
Other just-in-time compilers have been developed in the past, but are now unsupported:
- Google started a project called Unladen Swallow in 2009 with the aims of increasing the speed of the Python interpreter by 5 times by using the LLVM and improving its multithreading ability to scale to thousands of cores.[87]
- Psyco is a specialising just in time compiler that integrates with CPython and transforms bytecode to machine code at runtime. The produced code is specialised for certain data types and is faster than standard Python code.
In 2005, Nokia released a Python interpreter for the Series 60 mobile phones called PyS60. It includes many of the modules from the CPython implementations and some additional modules for integration with the Symbian operating system. This project has been kept up to date to run on all variants of the S60 platform and there are several third party modules available. The Nokia N900 also supports Python with GTK widget libraries, with the feature that programs can be both written and run on the device itself.[88]
There are several compilers to high-level object languages, with either unrestricted Python, a restricted subset of Python, or a language similar to Python as the source language:
- Jython compiles into Java byte code, which can then be executed by every Java virtual machine implementation. This also enables the use of Java class library functions from the Python program.
- IronPython follows a similar approach in order to run Python programs on the .NET Common Language Runtime.
- The RPython language can be compiled to C, Java bytecode, or Common Intermediate Language, and is used to build the PyPy interpreter of Python.
- Pyjamas compiles Python to JavaScript.
- Shed Skin compiles Python to C++.
- Cython and Pyrex compile to C.
A performance comparison of various Python implementations on a non-numerical (combinatorial) workload was presented at EuroSciPy '13.[89]
Development
Python's development is conducted largely through the Python Enhancement Proposal (PEP) process. The PEP process is the primary mechanism for proposing major new features, for collecting community input on an issue, and for documenting the design decisions that have gone into Python.[90] Outstanding PEPs are reviewed and commented upon by the Python community and by Van Rossum, the Python project's benevolent dictator for life.[90]
Enhancement of the language goes along with development of the CPython reference implementation. The mailing list python-dev is the primary forum for discussion about the language's development; specific issues are discussed in the Roundup bug tracker maintained at python.org.[91] Development takes place on a self-hosted source code repository running Mercurial.[92]
CPython's public releases come in three types, distinguished by which part of the version number is incremented:
- Backwards-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—for example, version 3.0 was released 8 years after 2.0.
- Major or "feature" releases, which are largely compatible but introduce new features. The second part of the version number is incremented. These releases are scheduled to occur roughly every 18 months, and each major version is supported by bugfixes for several years after its release.[93]
- Bugfix releases, which introduce no new features but fix bugs. The third and final part of the version number is incremented. These releases are made whenever a sufficient number of bugs have been fixed upstream since the last release, or roughly every 3 months. Security vulnerabilities are also patched in bugfix releases.[94]
A number of alpha, beta, and release-candidates are also released as previews and for testing before the final release is made. Although there is a rough schedule for each release, this is often pushed back if the code is not ready. The development team monitor the state of the code by running the large unit test suite during development, and using the BuildBot continuous integration system.[95]
The community of Python developers has also contributed over 72,000 software modules (as of January 2016) to the Python Package Index (called PyPI), the official repository of third-party libraries for Python.
The major academic conference on Python is named PyCon. There are special mentoring programmes like the Pyladies.
Naming
Python's name is derived from the television series Monty Python's Flying Circus,[96] and it is common to use Monty Python references in example code.[97] For example, the metasyntactic variables often used in Python literature are spam and eggs, instead of the traditional foo and bar.[97][98] As well as this, the official Python documentation often contains various obscure Monty Python references.
The prefix Py- is used to show that something is related to Python. Examples of the use of this prefix in names of Python applications or libraries include Pygame, a binding of SDL to Python (commonly used to create games); PyS60, an implementation for the Symbian S60 operating system; PyQt and PyGTK, which bind Qt and GTK, respectively, to Python; and PyPy, a Python implementation originally written in Python.
Use
Since 2003, Python has consistently ranked in the top ten most popular programming languages as measured by the TIOBE Programming Community Index. As of January 2016, it is in the fifth position.[99] It was ranked as Programming Language of the Year for the year 2007 and 2010.[23] It is the third most popular language whose grammatical syntax is not predominantly based on C, e.g. C++, Objective-C (note, C# and Java only have partial syntactic similarity to C, such as the use of curly braces, and are closer in similarity to each other than C).
An empirical study found scripting languages (such as Python) more productive than conventional languages (such as C and Java) for a programming problem involving string manipulation and search in a dictionary. Memory consumption was often "better than Java and not much worse than C or C++".[100]
Large organizations that make use of Python include Google,[101] Yahoo!,[102] CERN,[103] NASA,[104] and some smaller ones like ILM,[105] and ITA.[106]
Python can serve as a scripting language for web applications, e.g., via mod_wsgi for the Apache web server.[107] With Web Server Gateway Interface, a standard API has evolved to facilitate these applications. Web frameworks like Django, Pylons, Pyramid, TurboGears, web2py, Tornado, Flask, Bottle and Zope support developers in the design and maintenance of complex applications. Pyjamas and IronPython can be used to develop the client-side of Ajax-based applications. SQLAlchemy can be used as data mapper to a relational database. Twisted is a framework to program communications between computers, and is used (for example) by Dropbox.
Libraries like NumPy, SciPy and Matplotlib allow the effective use of Python in scientific computing,[108][109] with specialized libraries such as BioPython and Astropy providing domain-specific functionality. Sage is a mathematical software with a "notebook" programmable in Python: its library covers many aspects of mathematics, including algebra, combinatorics, numerical mathematics, number theory, and calculus.
Python has been successfully embedded in a number of software products as a scripting language, including in finite element method software such as Abaqus, 3D parametric modeler like FreeCAD, 3D animation packages such as 3ds Max, Blender, Cinema 4D, Lightwave, Houdini, Maya, modo, MotionBuilder, Softimage, the visual effects compositor Nuke, 2D imaging programs like GIMP,[110] Inkscape, Scribus and Paint Shop Pro,[111] and musical notation program or scorewriter capella. GNU Debugger uses Python as a pretty printer to show complex structures such as C++ containers. Esri promotes Python as the best choice for writing scripts in ArcGIS.[112] It has also been used in several video games,[113][114] and has been adopted as first of the three available programming languages in Google App Engine, the other two being Java and Go.[115]
Python has also been used in artificial intelligence tasks.[116][117][118][119] As a scripting language with module architecture, simple syntax and rich text processing tools, Python is often used for natural language processing tasks.[120]
Many operating systems include Python as a standard component; the language ships with most Linux distributions, AmigaOS 4, FreeBSD, NetBSD, OpenBSD and OS X, and can be used from the terminal. A number of Linux distributions use installers written in Python: Ubuntu uses the Ubiquity installer, while Red Hat Linux and Fedora use the Anaconda installer. Gentoo Linux uses Python in its package management system, Portage.
Python has also seen extensive use in the information security industry, including in exploit development.[121][122]
Most of the Sugar software for the One Laptop per Child XO, now developed at Sugar Labs, is written in Python.[123]
The Raspberry Pi single-board computer project has adopted Python as its principal user-programming language.
LibreOffice includes Python and intends to replace Java with Python. Python Scripting Provider is a core feature[124] since Version 4.0 from 7 February 2013.
Languages influenced by Python
Python's design and philosophy have influenced several programming languages, including:
- Boo uses indentation, a similar syntax, and a similar object model. However, Boo uses static typing (as well as optional duck typing) and is closely integrated with the .NET Framework.[125]
- Cobra uses indentation and a similar syntax. Cobra's "Acknowledgements" document lists Python first among languages that influenced it.[126] However, Cobra directly supports design-by-contract, unit tests, and optional static typing.[127]
- ECMAScript borrowed iterators, generators, and list comprehensions from Python.[128]
- Go is described as incorporating the "development speed of working in a dynamic language like Python".[129]
- Groovy was motivated by the desire to bring the Python design philosophy to Java.[130]
- Julia was designed "with true macros [.. and to be] as usable for general programming as Python [and] should be as fast as C".[20] Calling to or from Julia is possible; to with PyCall.jl and a Python package jyjulia allows calling, in the other direction, from Python.
- OCaml has an optional syntax, called twt (The Whitespace Thing), inspired by Python and Haskell.[131]
- Ruby's creator, Yukihiro Matsumoto, has said: "I wanted a scripting language that was more powerful than Perl, and more object-oriented than Python. That's why I decided to design my own language."[132]
- CoffeeScript is a programming language that cross-compiles to JavaScript; it has Python-inspired syntax.
- Swift is a programming language invented by Apple; it has some Python-inspired syntax.[133]
Python's development practices have also been emulated by other languages. The practice of requiring a document describing the rationale for, and issues surrounding, a change to the language (in Python's case, a PEP) is also used in Tcl[134] and Erlang[135] because of Python's influence.
Python has been awarded a TIOBE Programming Language of the Year award twice (in 2007 and 2010), which is given to the language with the greatest growth in popularity over the course of a year, as measured by the TIOBE index.[136]
See also
- IPython
- Comparison of integrated development environments for Python
- Comparison of programming languages
- List of programming languages
- Off-side rule languages, where blocks are expressed by indentation
- Python for S60
- Cython
- LAMP (software bundle)
- LEAP (software bundle)
References
- ^ "The History of Python: A Brief Timeline of Python". Blogger. 2009-01-20. Retrieved 2016-03-20.
- ^ Hastings, Larry (2015-12-07). "Python 3.5.1 and Python 3.4.4rc1 are now available". Python Insider. The Python Core Developers. Retrieved 2015-12-08.
- ^ "Python Release Python 2.7.11". Python Software Foundation. Retrieved 16 December 2015.
- ^ "Type hinting for Python". LWN.net. 24 December 2014. Retrieved 5 May 2015.
- ^ File extension .pyo will be removed in Python 3.5. See PEP 0488
- ^ Holth, Moore (30 March 2014). "PEP 0441 -- Improving Python ZIP Application Support". Retrieved 12 Nov 2015.
- ^ a b "Why was Python created in the first place?". General Python FAQ. Python Software Foundation. Retrieved 22 March 2007.
- ^ Kuchling, Andrew M. (22 December 2006). "Interview with Guido van Rossum (July 1998)". amk.ca. Retrieved 12 March 2012.
- ^ van Rossum, Guido (1993). "An Introduction to Python for UNIX/C Programmers". Proceedings of the NLUUG najaarsconferentie (Dutch UNIX users group).
even though the design of C is far from ideal, its influence on Python is considerable.
- ^ a b "Classes". The Python Tutorial. Python Software Foundation. Retrieved 20 February 2012.
It is a mixture of the class mechanisms found in C++ and Modula-3
- ^ Simionato, Michele. "The Python 2.3 Method Resolution Order". Python Software Foundation.
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. Retrieved 9 February 2012.
- ^ Schemenauer, Neil; Peters, Tim; Hetland, Magnus Lie (18 May 2001). "PEP 255 – Simple Generators". Python Enhancement Proposals. Python Software Foundation. Retrieved 9 February 2012.
- ^ Smith, Kevin D.; Jewett, Jim J.; Montanaro, Skip; Baxter, Anthony (2 September 2004). "PEP 318 – Decorators for Functions and Methods". Python Enhancement Proposals. Python Software Foundation. Retrieved 24 February 2012.
- ^ "More Control Flow Tools". Python 3 documentation. Python Software Foundation. Retrieved 24 July 2015.
- ^ "CoffeeScript borrows chained comparisons from Python".
- ^ "Genie Language - A brief guide". Retrieved 2015-12-28.
- ^ "Perl and Python influences in JavaScript". www.2ality.com. 24 February 2013. Retrieved 15 May 2015.
- ^ Rauschmayer, Axel. "Chapter 3: The Nature of JavaScript; Influences". O'Reilly, Speaking JavaScript. Retrieved 15 May 2015.
- ^ a b "Why We Created Julia". Julia website. February 2012. Retrieved 5 June 2014.
- ^ Bini, Ola (2007). Practical JRuby on Rails Web 2.0 Projects: bringing Ruby on Rails to the Java platform. Berkeley: APress. p. 3. ISBN 978-1-59059-881-8.
- ^ Lattner, Chris (3 June 2014). "Chris Lattner's Homepage". Chris Lattner. Retrieved 3 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.
- ^ a b TIOBE Software Index (2015). "TIOBE Programming Community Index Python". Retrieved 10 September 2015.
- ^ "The RedMonk Programming Language Rankings: June 2015 – tecosystems". Redmonk.com. 1 July 2015. Retrieved 10 September 2015.
- ^ Summerfield, Mark. Rapid GUI Programming with Python and Qt.
Python is a very expressive language, which means that we can usually write far fewer lines of Python code than would be required for an equivalent application written in, say, C++ or Java
- ^ McConnell, Steve (30 November 2009). Code Complete, p. 100. ISBN 9780735636972.
- ^ Kuhlman, Dave. "A Python Book: Beginning Python, Advanced Python, and Python Exercises".
- ^ a b "About Python". Python Software Foundation. Retrieved 24 April 2012., second section "Fans of Python use the phrase "batteries included" to describe the standard library, which covers everything from asynchronous processing to zip files."
- ^ "PyInstaller Home Page". Retrieved 27 January 2014.
- ^ a b Venners, Bill (13 January 2003). "The Making of Python". Artima Developer. Artima. Retrieved 22 March 2007.
- ^ van Rossum, Guido (20 January 2009). "A Brief Timeline of Python". The History of Python. Google. Retrieved 20 January 2009.
- ^ van Rossum, Guido (29 August 2000). "SETL (was: Lukewarm about range literals)". Python-Dev (Mailing list). Retrieved 13 March 2011.
- ^ van Rossum, Guido (1996). "Foreword for "Programming Python" (1st ed.)". Retrieved 10 July 2014.
- ^ Kuchling, A. M.; Zadka, Moshe (16 October 2000). "What's New in Python 2.0". Python Software Foundation. Retrieved 11 February 2012.
- ^ "Python 3.0 Release". Python Software Foundation. Retrieved 8 July 2009.
- ^ van Rossum, Guido (5 April 2006). "PEP 3000 – Python 3000". Python Enhancement Proposals. Python Software Foundation. Retrieved 27 June 2009.
- ^ The Cain Gang Ltd. "Python Metaclasses: Who? Why? When?". Archived from the original (PDF) on 10 December 2009. Retrieved 27 June 2009.
- ^ "3.3. Special method names". The Python Language Reference. Python Software Foundation. Retrieved 27 June 2009.
- ^ "PyDBC: method preconditions, method postconditions and class invariants for Python". Retrieved 24 September 2011.
- ^ "Contracts for Python". Retrieved 24 September 2011.
- ^ "PyDatalog". Retrieved 22 July 2012.
- ^ a b Hettinger, Raymond (30 January 2002). "PEP 289 – Generator Expressions". Python Enhancement Proposals. Python Software Foundation. Retrieved 19 February 2012.
- ^ "6.5 itertools – Functions creating iterators for efficient looping". Docs.python.org. Retrieved 24 November 2008.
- ^ a b Peters, Tim (19 August 2004). "PEP 20 – The Zen of Python". Python Enhancement Proposals. Python Software Foundation. Retrieved 24 November 2008.
- ^ Martelli, Alex; Ravenscroft, Anna; Ascher, David (2005). Python Cookbook, 2nd Edition. O'Reilly Media. p. 230. ISBN 978-0-596-00797-3.
- ^ "Python Culture".
- ^ "General Python FAQ - Why is it called Python?".
- ^ "15 Ways Python Is a Powerful Force on the Web".
- ^ "pprint - Data pretty printer - Python Documentation".
- ^ Goodger, David. "Code Like a Pythonista: Idiomatic Python".
- ^ "How to think like a Pythonista".
- ^ "Is Python a good language for beginning programmers?". General Python FAQ. Python Software Foundation. Retrieved 21 March 2007.
- ^ "Myths about indentation in Python". Secnetix.de. Retrieved 19 April 2011.
- ^ Sweigart, Al (2010). "Appendix A: Differences Between Python 2 and 3". Invent Your Own Computer Games with Python (2 ed.). ISBN 978-0-9821060-1-3. Retrieved 20 February 2014.
- ^ van Rossum, Guido (22 April 2009). "Tail Recursion Elimination". Neopythonic.blogspot.be. Retrieved 3 December 2012.
- ^ van Rossum, Guido (9 February 2006). "Language Design Is Not Just Solving Puzzles". Artima forums. Artima. Retrieved 21 March 2007.
- ^ van Rossum, Guido; Eby, Phillip J. (10 May 2005). "PEP 342 – Coroutines via Enhanced Generators". Python Enhancement Proposals. Python Software Foundation. Retrieved 19 February 2012.
- ^ "PEP 380". Python.org. Retrieved 3 December 2012.
- ^ "PEP 0465 -- A dedicated infix operator for matrix multiplication". python.org. Retrieved 1 January 2016.
- ^ "Python 3.5.1 Release and Changelog". python.org. Retrieved 1 January 2016.
- ^ http://docs.oracle.com/javase/specs/jls/se8/html/jls-15.html#jls-15.21.1
- ^ http://docs.oracle.com/javase/specs/jls/se8/html/jls-15.html#jls-15.21.3
- ^ van Rossum, Guido; Hettinger, Raymond (7 February 2003). "PEP 308 – Conditional Expressions". Python Enhancement Proposals. Python Software Foundation. Retrieved 13 July 2011.
- ^ "Why must 'self' be used explicitly in method definitions and calls?". Design and History FAQ. Python Software Foundation. Retrieved 19 February 2012.
- ^ "The Python Language Reference, section 3.3. New-style and classic classes, for release 2.7.1". Retrieved 12 January 2011.
- ^ Zadka, Moshe; van Rossum, Guido (11 March 2001). "PEP 237 – Unifying Long Integers and Integers". Python Enhancement Proposals. Python Software Foundation. Retrieved 24 September 2011.
- ^ "PEP 465 -- A dedicated infix operator for matrix multiplication". python.org.
- ^ Zadka, Moshe; van Rossum, Guido (11 March 2001). "PEP 238 – Changing the Division Operator". Python Enhancement Proposals. Python Software Foundation. Retrieved 23 October 2013.
- ^ "Why Python's Integer Division Floors". Retrieved 25 August 2010.
- ^ "round", The Python standard library, release 2.7, §2: Built-in functions, retrieved 14 August 2011
- ^ "round", The Python standard library, release 3.2, §2: Built-in functions, retrieved 14 August 2011
- ^ Python Essential Reference, David M Beazley
- ^ "Built-in Type". docs.python.org.
- ^ Batista, Facundo. "PEP 0327 -- Decimal Data Type". Python.org. Retrieved 2015-09-26.
- ^ "What’s New in Python 2.6 — Python v2.6.9 documentation". docs.python.org. Retrieved 2015-09-26.
- ^ Piotrowski, Przemyslaw (July 2006). "Build a Rapid Web Development Environment for Python Server Pages and Oracle". Oracle Technology Network. Oracle. Retrieved 12 March 2012.
- ^ Batista, Facundo (17 October 2003). "PEP 327 – Decimal Data Type". Python Enhancement Proposals. Python Software Foundation. Retrieved 24 November 2008.
- ^ Eby, Phillip J. (7 December 2003). "PEP 333 – Python Web Server Gateway Interface v1.0". Python Enhancement Proposals. Python Software Foundation. Retrieved 19 February 2012.
- ^ van Rossum, Guido (5 June 2001). "PEP 7 – Style Guide for C Code". Python Enhancement Proposals. Python Software Foundation. Retrieved 24 November 2008.
- ^ "CPython byte code". Docs.python.org. Retrieved 16 February 2016.
- ^ "Python 2.5 internals" (PDF). Retrieved 19 April 2011.
- ^ "An Interview with Guido van Rossum". Oreilly.com. Retrieved 24 November 2008.
- ^ "PyPy compatibility". Pypy.org. Retrieved 3 December 2012.
- ^ "speed comparison between CPython and Pypy". Speed.pypy.org. Retrieved 3 December 2012.
- ^ "STM with threads". Morepypy.blogspot.be. 10 June 2012. Retrieved 3 December 2012.
- ^ "Application-level Stackless features — PyPy 2.0.2 documentation". Doc.pypy.org. Retrieved 17 July 2013.
- ^ "Plans for optimizing Python". Google Project Hosting. Google. 15 December 2009. Retrieved 24 September 2011.
- ^ "Python on the Nokia N900". Stochastic Geometry.
- ^ Murri, Riccardo (2013). Performance of Python runtimes on a non-numeric scientific code. European Conference on Python in Science (EuroSciPy).
- ^ a b Warsaw, Barry; Hylton, Jeremy; Goodger, David (13 June 2000). "PEP 1 – PEP Purpose and Guidelines". Python Enhancement Proposals. Python Software Foundation. Retrieved 19 April 2011.
- ^ Cannon, Brett. "Guido, Some Guys, and a Mailing List: How Python is Developed". python.org. Python Software Foundation. Archived from the original on 1 June 2009. Retrieved 27 June 2009.
- ^ "Python Developer's Guide".
- ^ Norwitz, Neal (8 April 2002). "[Python-Dev] Release Schedules (was Stability & change)". Retrieved 27 June 2009.
- ^ Aahz; Baxter, Anthony (15 March 2001). "PEP 6 – Bug Fix Releases". Python Enhancement Proposals. Python Software Foundation. Retrieved 27 June 2009.
- ^ "Python Buildbot". Python Developer’s Guide. Python Software Foundation. Retrieved 24 September 2011.
- ^ "General Python FAQ". Python v2.7.3 documentation. Docs.python.org. Retrieved 3 December 2012.
- ^ a b "Whetting Your Appetite". The Python Tutorial. Python Software Foundation. Retrieved 20 February 2012.
- ^ "In Python, should I use else after a return in an if block?". Stack Overflow. Stack Exchange. 17 February 2011. Retrieved 6 May 2011.
- ^ http://www.tiobe.com/index.php/content/paperinfo/tpci/index.html
- ^ Prechelt, Lutz (14 March 2000). "An empirical comparison of C, C++, Java, Perl, Python, Rexx, and Tcl" (PDF). Retrieved 30 August 2013.
- ^ "Quotes about Python". Python Software Foundation. Retrieved 8 January 2012.
- ^ "Organizations Using Python". Python Software Foundation. Retrieved 15 January 2009.
- ^ "Python : the holy grail of programming". CERN Bulletin (CERN Publications) (31/2006). 31 July 2006. Retrieved 11 February 2012.
- ^ Shafer, Daniel G. (17 January 2003). "Python Streamlines Space Shuttle Mission Design". Python Software Foundation. Retrieved 24 November 2008.
- ^ Fortenberry, Tim (17 January 2003). "Industrial Light & Magic Runs on Python". Python Software Foundation. Retrieved 11 February 2012.
- ^ Taft, Darryl K. (5 March 2007). "Python Slithers into Systems". eWeek.com. Ziff Davis Holdings. Retrieved 24 September 2011.
- ^ "Usage statistics and market share of Python for websites". 2012. Retrieved 18 December 2012.
- ^ Oliphant, Travis (2007). "Python for Scientific Computing". Computing in Science and Engineering.
- ^ Millman, K. Jarrod; Aivazis, Michael (2011). "Python for Scientists and Engineers". Computing in Science and Engineering 13 (2): 9–12.
- ^ "Installers for GIMP for Windows - Frequently Asked Questions". 26 July 2013. Retrieved 26 July 2013.
- ^ "jasc psp9components". Archived from the original on 23 April 2014.
- ^ "About getting started with writing geoprocessing scripts". ArcGIS Desktop Help 9.2. Environmental Systems Research Institute. 17 November 2006. Retrieved 11 February 2012.
- ^ CCP porkbelly (24 August 2010). "Stackless Python 2.7". EVE Community Dev Blogs. CCP Games.
As you may know, EVE has at its core the programming language known as Stackless Python.
- ^ Caudill, Barry (20 September 2005). "Modding Sid Meier's Civilization IV". Sid Meier's Civilization IV Developer Blog. Firaxis Games. Archived from the original on 10 August 2010.
we created three levels of tools ... The next level offers Python and XML support, letting modders with more experience manipulate the game world and everything in it.
- ^ "Python Language Guide (v1.0)". Google Documents List Data API v1.0. Google. Archived from the original on 10 August 2010.
- ^ "Python for Artificial Intelligence". Wiki.python.org. 19 July 2012. Archived from the original on 1 November 2012. Retrieved 3 December 2012.
- ^ Paine, Jocelyn, ed. (August 2005). "AI in Python". AI Expert Newsletter (Amzi!). Retrieved 11 February 2012.
- ^ "PyAIML 0.8.5 : Python Package Index". Pypi.python.org. Retrieved 17 July 2013.
- ^ Russell, Stuart J. & Norvig, Peter (2009). Artificial Intelligence: A Modern Approach (3rd ed.). Upper Saddle River, NJ: Prentice Hall. p. 1062. ISBN 978-0-13-604259-4. Retrieved 11 February 2012.
- ^ "Natural Language Toolkit".
- ^ "Immunity: Knowing You're Secure".
- ^ "Corelabs site".
- ^ "What is Sugar?". Sugar Labs. Retrieved 11 February 2012.
- ^ "4.0 New Features and Fixes". LibreOffice.org. The Document Foundation. 2013. Retrieved 25 February 2013.
- ^ "Gotchas for Python Users". boo.codehaus.org. Codehaus Foundation. Retrieved 24 November 2008.
- ^ Esterbrook, Charles. "Acknowledgements". cobra-language.com. Cobra Language. Retrieved 7 April 2010.
- ^ Esterbrook, Charles. "Comparison to Python". cobra-language.com. Cobra Language. Retrieved 7 April 2010.
- ^ "Proposals: iterators and generators [ES4 Wiki]". wiki.ecmascript.org. Retrieved 24 November 2008.
- ^ Kincaid, Jason (10 November 2009). "Google’s Go: A New Programming Language That’s Python Meets C++". TechCrunch. Retrieved 29 January 2010.
- ^ Strachan, James (29 August 2003). "Groovy – the birth of a new dynamic language for the Java platform".
- ^ Lin, Mike. "The Whitespace Thing for OCaml". Massachusetts Institute of Technology. Retrieved 12 April 2009.
- ^ "An Interview with the Creator of Ruby". Linuxdevcenter.com. Retrieved 3 December 2012.
- ^ Lattner, Chris (3 June 2014). "Chris Lattner's Homepage". Chris Lattner. Retrieved 3 June 2014.
I started work on the Swift Programming Language in July of 2010. I implemented much of the basic language structure, with only a few people knowing of its existence. A few other (amazing) people started contributing in earnest late in 2011, and it became a major focus for the Apple Developer Tools group in July 2013 [...] drawing ideas from Objective-C, Rust, Haskell, Ruby, Python, C#, CLU, and far too many others to list.
- ^ Kupries, Andreas; Fellows, Donal K. (14 September 2000). "TIP #3: TIP Format". tcl.tk. Tcl Developer Xchange. Retrieved 24 November 2008.
- ^ Gustafsson, Per; Niskanen, Raimo (29 January 2007). "EEP 1: EEP Purpose and Guidelines". erlang.org. Retrieved 19 April 2011.
- ^ "TIOBE Programming Community Index for March 2012". TIOBE Software. March 2012. Retrieved 25 March 2012.
Further reading
- Downey, Allen B (May 2012). Think Python: How to Think Like a Computer Scientist (Version 1.6.6 ed.). ISBN 978-0-521-72596-5.
- Hamilton, Naomi (5 August 2008). "The A-Z of Programming Languages: Python". Computerworld. Retrieved 31 March 2010.
- Lutz, Mark (2013). Learning Python (5th ed.). O'Reilly Media. ISBN 978-0-596-15806-4.
- Pilgrim, Mark (2004). Dive Into Python. Apress. ISBN 978-1-59059-356-1.
- Pilgrim, Mark (2009). Dive Into Python 3. Apress. ISBN 978-1-4302-2415-0.
- Summerfield, Mark (2009). Programming in Python 3 (2nd ed.). Addison-Wesley Professional. ISBN 978-0-321-68056-3.
External links
- Official website
- Python (programming language) newsgroup on Usenet (alternative free web access using Google Groups)
- The History of Python (blog by Guido van Rossum)
- Python development list
- Python at DMOZ
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