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PythonParadigmDesigned byDeveloperFirst appearedStable releasePreview releaseTyping disciplineOSLicenseFilename extensionsWebsiteMajor implementationsDialectsInfluenced byInfluenced

Multi-paradigm:object-oriented,[1] procedural(imperative), functional, structured,reflective
Guido van Rossum
Python Software Foundation
20 February 1991; 31 years ago[2]

3.10.7[3]  / 7 September 2022; 0 days ago

3.11.0rc1[4]  / 8 August 2022; 30 days ago

Duck, dynamic, strong typing;[5] gradual (since 3.5, but ignored in CPython)[6]
Windows, macOS, Linux/UNIX,Android[7][8] andmore[9]
Python Software Foundation License
.py, .pyi, .pyc, .pyd, .pyw, .pyz (since 3.5),[10] .pyo (prior to3.5)[11]
python.org
CPython, PyPy,Stackless Python, MicroPython, CircuitPython, IronPython,Jython
Cython, RPython,Starlark[12]
ABC,[13]Ada,[14] ALGOL68,[15] APL,[16]C,[17]C++,[18]CLU,[19]Dylan,[20]Haskell,[21][16]Icon,[22]Lisp,[23]Modula-3,[15][18]Perl,[24] Standard ML[16]
Apache Groovy, Boo, Cobra,CoffeeScript,[25] D, F#,Genie,[26] Go, JavaScript,[27][28]Julia,[29] Nim,Ring,[30]Ruby,[31]Swift[32]
  • Python Programming at Wikibooks

Python isdynamically-typed and garbage-collected. It supports multiple programming paradigms, includingstructured (particularly procedural), object-oriented andfunctional programming. It is often described as a “batteries included” language due to its comprehensive standardlibrary.[34][35]

Python was developed by Guido van Rossum as a replacement for the ABC programming language in the late 1980s, and it was first made available as Python0 in 1991. 9 0. Python2, at [36]. With the release of version 0 in 2000, new features including list comprehensions, cycle-detecting garbage collection, reference counting, and support for Unicode were added. Python3. 0 was a significant revision that wasn’t entirely backwards compatible with earlier versions when it was released in 2008. Python2 was replaced with version 2. 7. 18 in 2020. [37].

Python was conceived in the late 1980s[42] by Guido van Rossum at Centrum Wiskunde & Informatica (CWI) in theNetherlands as a successor to the ABC programming language, which was inspired bySETL,[43] capable of exception handling and interfacing with theAmoeba operating system.[13] 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 forlife”, a title the Python community bestowed upon him to reflect his long-term commitment as the project’s chief decision-maker.[45] In January 2019, active Python core developers elected a five-member Steering Council to lead theproject.[46][47]

Python 2.0 was released on 16 October 2000, with many major newfeatures.[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]

Python2. 7’s end-of-life was originally planned for 2015, but it was moved to 2020 due to worries that a sizable amount of existing code would be difficult to forward-port to Python3. No additional security updates or enhancements will be released for it in the future. With Python2’s end-of-life, only Python3 is left. 6. Later was supported up to x[55]. Subsequently, support for 3. 6 was also abandoned. Python 3 will debut in 2021. 9. 2 and 3. 8. 8 were expedited[56] as all Python versions (including 2. Web cache poisoning and potential remote code execution were caused by security flaws in version 7. [57] [59].

In 2022, Python 3.10.4 and 3.9.12 were expedited[60] and so were older releases including 3.8.13, and 3.7.13 because of many securityissues.[61] Python 3.9.13 is the latest 3.9 version, and from now on 3.9 (and older; 3.8 and 3.7) will only get security updates.[62]

Design philosophy andfeatures[edit]

Python is a multi-paradigm programming language Object-oriented programming and structured programming are fully supported, and many of its features support functional programming andaspect-oriented programming (including metaprogramming[63] andmetaobjects [magic methods] ) [64] Many other paradigms are supported via extensions, including design by contract[65][66] and logicprogramming [67]

A cycle-detecting garbage collector and dynamic typing are both used by Python for memory management. [68] It makes use of dynamic name resolution, also known as late binding, to bind method and variable names while the program is being run.

Its design offers some support for functional programming in the Lisp tradition. It has filter,mapandreduce functions;list comprehensions, dictionaries, sets, and generatorexpressions.[69] The standard library has two modules (itertools and functools) that implement functional tools borrowed from Haskell andStandard ML.[70]

Its core philosophy is summarized in the document The Zen of Python (PEP 20), which includesaphorisms such as:[71]

  • Beautiful is better than ugly.
  • Explicit is better than implicit.
  • Simple is better than complex.
  • Complex is better than complicated.
  • Readability counts.

Rather than building all of itsfunctionality 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 withABC, which espoused the opposite approach [42]

Python strives for a simpler, less-cluttered syntax and grammar while giving developers a choice in their coding methodology. In contrast toPerl’s “there is more than one way to do it” motto, Python embraces a “there should be one—and preferably only one—obvious way to do it”philosophy.[71] Alex Martelli, a Fellow at the PythonSoftware Foundation and Python book author, wrote: “To describe something as ‘clever’ is not considered a compliment in the Python culture.”[72]

Python’s developers strive to avoid premature optimization and rejectpatches to non-critical parts of the CPython reference implementation that would offer marginal increases in speed at the cost of clarity [73] When speed is important, a Python programmer can move time-critical functions to extension modules written in languagessuch as C; or use 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

The developers of Python want it to be enjoyable to use. This can be seen in the name, which pays homage to the British comedy group Monty Python[74], as well as in the occasionally lighthearted tone of the tutorials and reference materials. For instance, some examples refer to spam and eggs rather than the more common foo and bar. [75][76].

The programming language’s name ‘Python’ came from the BBC Comedy series Monty Python’sFlying Circus Guido van Rossum thought he needed a name that was short, unique and slightly mysterious, And so, he decided to name the programming language ‘Python’ [74]

A commonneologism in the Python community is pythonic, which has a wide range of meanings related to program style. “Pythonic” code may use Python idioms well, be natural or 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 calledunpythonic.[77][78]

Python users and admirers, especially those considered knowledgeable or experienced, are often referred to asPythonistas.[79][80]

Syntax andsemantics[edit]

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 usecurly 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.[81]

Indentation[edit]

Python useswhitespace indentation, rather than curly brackets or keywords, to delimit blocks. An increase in indentation comes after certain statements; adecrease in indentation signifies the end of the current block.[82] Thus, the program’s visual structure accurately represents its semantic structure.[83] This feature is sometimes termed theoff-side rule. Some other languages use indentation this way; but in most, indentation has no semantic meaning. The recommended indent size is four spaces.[84]

Statements and controlflow[edit]

Python’s statements include:

  • Theassignment 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 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 by except clauses (or new syntax except* in Python 3.11 for exception groups[85]); it 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
  • The def statement, which defines afunction or method
  • The with statement, which encloses a code block within a context manager (for example, acquiring a lock before it is run, then releasingthe lock; or opening and closing a file), allowing resource-acquisition-is-initialization (RAII)-like behavior and replacing a common try/finallyidiom[86]
  • The break statement, which exits a loop
  • The continue statement, which skips the current iteration and continues with the next
  • The del statement, which removes a variable—deleting the reference from the name to the value, and producing an error if the variable is referred to before it is redefined
  • The passstatement, serving as a NOP, syntactically needed to create an empty code block
  • The assert statement, used in debugging to check for conditions that should apply
  • The yield statement, which returns a value from a generator function (and also anoperator); used to implement coroutines
  • The return statement, used to return a value from a function
  • The import statement, used to import modules whose functions or variables can be used in the current program

The assignment statement (=) binds a name as areference 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 fixeddata 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 neverwill.[87][88] However, better support for coroutine-like functionality is provided by extending Python’sgenerators.[89] Before 2.5, generators were lazyiterators; 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.[90]

Expressions[edit]

Some Python expressions are similar to those in languages such as C andJava, while some are not:

  • Addition, subtraction, and multiplication are the same, but the behavior of division differs. There are two types of divisions in Python: floor division (or integer division) // andfloating-point/division.[91] Python also uses the ** operator for exponentiation.
  • The @ infix operator. It is intended to be used by libraries such as NumPy formatrix multiplication.[92][93]
  • The syntax :=, called the”walrus operator”, was introduced in Python 3.8. It assigns values to variables as part of a larger expression.[94]
  • In Python, == compares by value, versus Java, which compares numerics byvalue[95] and objects by reference.[96] Python’s is operator may be used to compare object identities (comparison by reference), and comparisons may be chained—for example, a <= b <= c.
  • Python uses and, or, andnot as boolean operators rather than the symbolic &&, ||, ! in Java and C.
  • Python has a type of expression called a list comprehension, as well as a more general expression called a generatorexpression.[69]
  • Anonymous functions are implemented using lambda expressions; however, there may be only one expressionin each body.
  • Conditional expressions are written as x if c else y[97] (different in order of operands from the c ? x : y operator common to many other languages).
  • Python makes a distinction between lists andtuples. 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, written as (1, 2, 3), are immutable and thus can be used as keys of dictionaries, provided all of the tuple’s elements are immutable. The + operator can be used toconcatenate two tuples, which does not directly modify their contents, but produces a new tuple containing the elements of both. Thus, given the variable t initially equal to (1, 2, 3), executing t = t + (4, 5) first evaluates t + (4, 5), which yields (1, 2, 3, 4, 5), which is then assigned back to t—thereby effectively “modifying the contents” of t while conforming to the immutable nature of tuple objects. Parentheses are optional for tuples in unambiguouscontexts.[98]
  • Python features sequence unpacking where multiple expressions, each evaluating to anything that can be assigned (to a variable, writable property, etc.) are associated in an identical manner to that forming tuple literals—and, as a whole, are put on the left-hand side of the equal sign in an assignment statement. The statement expects aniterable object on the right-hand side of the equal sign that produces the same number of values as the provided writable expressions; when iterated through them, it assigns each of the produced values to the corresponding expression on the left.[99]
  • Python has a “string format” operator % that functions analogously to printf format strings inC—e.g. "spam=%s eggs=%d" % ("blah", 2) evaluates to "spam=blah eggs=2". In Python 2.6+ and 3+, this was supplemented by the format() method of the str class, e.g. "spam={0} eggs={1}".format("blah", 2). Python 3.6 added “f-strings”: spam = "blah"; eggs = 2; f'spam={spam} eggs={eggs}'.[100]
  • Strings in Python can be concatenated by”adding” them (with the same operator as for adding integers and floats), e.g. "spam" + "eggs" returns "spameggs". If strings contain numbers, they are added as strings rather than integers, e.g. "2" + "2" returns "22".
  • Python has various string literals:
    • Delimited by single or double quote marks. Unlike inUnix shells, Perl, and Perl-influenced languages, single and double quote marks function identically. Both use the backslash (\) as an escape character.String interpolation became available in Python 3.6 as “formatted string literals”.[100]
    • Triple-quoted (beginning and ending with three single or double quote marks), which may span multiple lines and function likehere documents in shells, Perl, and Ruby.
    • Raw string varieties, denoted by prefixing the string literal with r. Escape sequences are not interpreted; hence raw strings areuseful where literal backslashes are common, such as regular expressions and Windows-style paths. (Compare “@-quoting” in C#.)
  • Pythonhas array index and array slicing expressions in lists, denoted as a[key], a[start:stop] or a[start:stop:step]. Indexes are zero-based, and negative indexes are relative to the end. Slices take elements from thestart 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 example, a[:] 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, incontrast to languages such as Common Lisp, Scheme, or Ruby. This leads to duplicating some 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

Statementscannot be a part of an expression—so list and other comprehensions or lambda expressions, all being expressions, cannot contain statements. A particular case 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 anequality operator == in conditions: if (c = 1) { ... } is syntactically valid (but probably unintended) C code, but if c = 1: ... causes a syntax error in Python.

Methods[edit]

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 anexplicit 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).[101] 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 nativeoperations including length, comparison, in arithmetic operations and type conversion.[102]

Typing[edit]

The standard type hierarchy in Python 3

Python makes use of duck typing, has typed objects, but untyped variable names. Type restrictions are not checked at compile time; rather, operations on an object may fail, indicating that it is not a suitable type. Despite being dynamically typed, Python is strongly typed, prohibiting operations that are not clearly defined (such as adding a number to a string) rather than silently attempting to make sense of them.

Python allows programmers to define their owntypes using classes, most often used for object-oriented programming. New instances of classes are constructed by calling the class (forexample, SpamClass() or EggsClass()), and the classes are instances of the metaclass type (itself an instance of itself), allowing metaprogramming and reflection.

prior to version 3. Old-style and new-style classes were both available in Python 0 (both using the same syntax), but as of Python 3.0, only the new-style semantics are supported.

The long-term plan is to support gradualtyping.[104] Python’s syntax allows specifying static types, but they are not checked in the default implementation, CPython. An experimental optional static type-checker, mypy, supports compile-time typechecking.[105]

Summary of Python 3’s built-in types Type MutabilityDescription Syntax examples

bool immutable Boolean value TrueFalse
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])
complex immutable Complex number with real and imaginary parts 3+2.7j3 + 2.7j
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}{}
types.EllipsisType immutable An ellipsis placeholder to be used as an index in NumPy arrays ...Ellipsis
float immutable Double-precision floating-point number. The precision is machine-dependent but in practice is generally implemented as a 64-bit IEEE 754number with 53 bits of precision.[106]

1.33333

frozenset immutable Unordered set, contains no duplicates; can contain mixed types, if hashable frozenset([4.0, 'string', True])
int immutable Integer of unlimited magnitude[107] 42
list mutable List, can contain mixed types [4.0, 'string', True][]
types.NoneType immutable An object representing the absence of a value, often called null in other languages None
types.NotImplementedType immutable A placeholder that can be returned from overloaded operators to indicate unsupported operand types. NotImplemented
range immutable A Sequence of numbers commonly used for looping specific number of times in for loops[108] range(-1, 10)range(10, -5, -2)
set mutable Unordered set, contains no duplicates; can contain mixed types, if hashable {4.0, 'string', True}set()
str immutable A character string: sequence of Unicode codepoints 'Wikipedia'"Wikipedia"

"""Spanningmultiplelines"""
'''Spanningmultiplelines'''
tuple immutable Can contain mixed types (4.0, 'string', True)('single element',)()

Arithmetic operations[edit]

Python has the usual symbols for arithmetic operators (+, -, *, /), the floor division operator // and themodulo operation % (where the remainder can be negative, e.g. 4 % -3 == -2). It also has ** for exponentiation, e.g. 5**3 == 125 and 9**0.5 == 3.0, and a matrix‑multiplication operator @.[109] These operators work like in traditional math; with the same precedence rules, the operators infix (+ and - can also be unary to represent positive and negative numbers respectively).

The division between integers produces floating-point results. The behavior of division has changed significantly over time:[110]

  • Current Python (i.e. since 3.0) changed / toalways be floating-point division, e.g. 5/2 == 2.5.
  • The floor division // operator was introduced. So 7//3 == 2, -7//3 == -3, 7.5//3 == 2.0 and -7.5//3 == -3.0. Adding from __future__ import division causes a module used in Python 2.7 to use Python 3.0 rules for division (see above).

In Python terms, / is true division (or simply division), and // is floor division. / before version 3.0 is classic division.[110]

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 thehalf-open interval [0, b), where b is a positive integer, it has to lie in the interval (b, 0] when b is negative.[111]

Python provides a round function forrounding a float to the nearest integer. For tie-breaking, Python 3 uses round to even: round(1.5) and round(2.5) both produce2.[112] Versions before 3 used round-away-from-zero: round(0.5) is 1.0, round(-0.5) is−1.0.[113]

Python allows boolean expressions with multiple equality relations in a manner that is consistent with general use in mathematics. For example, the expression a < b < c tests whether a is less than b and b is less thanc.[114] 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 withc.[115]

Python uses arbitrary-precision arithmetic for all integer operations. The Decimal type/class in the decimal module providesdecimal floating-point numbers to a pre-defined arbitrary precision and several rounding modes.[116] The Fraction class in the fractions module provides arbitrary precision forrational numbers.[117]

Due to Python’s extensive mathematics library, and the third-party library NumPy that further extends the native capabilities, it is frequently used as ascientific scripting language to aid in problems such as numerical data processing and manipulation.[118][119]

Programmingexamples[edit]

Hello world program:

Program to calculate thefactorial of a positive integer:

n = int(input('Type a number, and its factorial will be printed: '))if n < :    raise ValueError('You must enter a non-negative integer')factorial = 1for i in range(2, n + 1):    factorial *= iprint(factorial)

Libraries[edit]

Python’s large standard library[120] provides tools suited to many tasks, and is commonly cited as one of its greatest strengths. For Internet-facing applications, many standard formats and protocols such as MIME andHTTP are supported. It includes modules for creating graphical user interfaces, connecting to relational databases,generating pseudorandom numbers, arithmetic with arbitrary-precision decimals,[121] manipulating regularexpressions, and unit testing.

Some parts of the standard library are covered by specifications—for example, the Web Server Gateway Interface (WSGI) implementation wsgiref follows PEP333[122]—but most 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 need altering or rewriting for variant implementations.

As ofJune 2022, the Python Package Index (PyPI), the official repository for third-party Python software, contains over 380,000[123] packages with a wide range of functionality, including:

  • Automation
  • Data analytics
  • Databases
  • Documentation
  • Graphical user interfaces
  • Image processing
  • Machine learning
  • Mobileapps
  • Multimedia
  • Computer networking
  • Scientific computing
  • System administration
  • Test frameworks
  • Text processing
  • Web frameworks
  • Web scraping

Development environments[edit]

The majority of Python implementations, including CPython, have a readevalprint loop (REPL), which enables them to work as command line interpreters for which users enter statements sequentially and instantly receive results.

Python also comes with anIntegrated development environment (IDE) called IDLE, which is more beginner-oriented

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Other shells, including IDLE andIPython, add further abilities such as improved auto-completion, session state retention and syntax highlighting.

As well as standard desktop integrated developmentenvironments, there are Web browser-based IDEs, including SageMath, for developing science- and math-related programs; PythonAnywhere, a browser-based IDE and hosting environment; and Canopy IDE, a commercial IDEemphasizing scientific computing.[124]

Implementations[edit]

Referenceimplementation[edit]

CPython is the reference implementation of Python.It is written in C, meeting the C89 standard (Python 3.11 uses C11[125]) with several selectC99 features (With later C versions out, it is considered outdated.[126][127] CPython includes its own C extensions, but third-party extensions are notlimited to older C versions—e.g. they can be implemented with C11 or C++.[128][129]) Itcompiles Python programs into an intermediate bytecode[130] which is then executed by its virtualmachine.[131] CPython is distributed with a large standard library written in a mixture of C and native Python, and is available for many platforms, including Windows (starting with Python 3.9, the Python installer deliberately fails to install onWindows 7 and 8;[132][133] Windows XP was supporteduntil Python 3.5) and most modern Unix-like systems, including macOS (and Apple M1 Macs, since Python 3.9.1, with experimental installer) and unofficial support for e.g.VMS.[134] Platform portability was one of its earliest priorities.[135] (During Python 1 and 2 development, evenOS/2 and Solaris were supported,[136] but support has since been dropped for many platforms.)

Otherimplementations[edit]

  • PyPy is a fast, compliant interpreter of Python 2.7 and3.8.[137] [138] Its just-in-time compiler brings a significant speed improvement over CPythonbut some libraries written in C cannot be used with it.[139]
  • Stackless Python is a significant fork of CPython that implements microthreads; itdoes not use the call stack in the same way, thus allowing massively concurrent programs. PyPy also has a stackless version.[140]
  • MicroPython andCircuitPython are Python 3 variants optimized for microcontrollers, including Lego MindstormsEV3.[141]
  • Pyston is a variant of the Python runtime that uses just-in-time compilation to speed up the execution of Python programs.[142]
  • Cinder is a performance-oriented fork of CPython 3.8 that contains a numberof optimizations including bytecode inline caching, eager evaluation of coroutines, a method-at-a-time JIT and an experimental bytecode compiler.[143]

Unsupportedimplementations[edit]

Other just-in-time Python compilers have been developed, but are now unsupported:

  • Google began a project named Unladen Swallow in 2009,with the aim of speeding up the Python interpreter fivefold by using the LLVM, and of improving its multithreading ability to scale to thousands of cores,[144] while ordinary implementations suffer from theglobal interpreter lock.
  • Psyco is a discontinued just-in-time specializing compiler that integrates with CPython and transforms bytecode to machine code at runtime. The emitted code is specialized for certain data types and is faster than the standard Python code. Psyco does not support Python 2.7 or later.
  • PyS60 was a Python 2 interpreter forSeries 60 mobile phones released by Nokia in 2005. It implemented many of the modules from the standard library and some additional modules for integrating with the Symbian operating system. The NokiaN900 also supports Python with GTK widget libraries, enabling programs to be written and run on the target device.[145]

Cross-compilers to otherlanguages[edit]

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:

  • Brython,[146] Transcrypt[147][148] andPyjs (latest release in 2012) compile Python to JavaScript.
  • Cython compiles (a superset of) Python 2.7 to C (while the resulting code is also usable with Python 3 and also e.g. C++).
  • Nuitka compiles Python into C.[149]
  • Numba uses LLVM to compile a subset of Python to machine code.
  • Pythran compiles a subset of Python 3 to C++(C++11).[150][151][152]
  • RPython can be compiled to C, and is used to build the PyPy interpreter of Python.
  • The Python → 11l → C++ transpiler[153] compiles a subset of Python 3 to C++ (C++17).

Specialized:

  • MyHDL is a Python-based hardware description language (HDL), that converts MyHDL code to Verilog or VHDL code.

Older projects (or not to be used with Python 3.x and latest syntax):

  • Google’s Grumpy (latest release in 2017) transpiles Python 2 toGo.[154][155][156]
  • IronPython allows running Python 2.7 programs (and analpha, released in 2021, is also available for “Python 3.4, although features and behaviors from later versions may be included”[157]) on the .NETCommon Language Runtime.[158]
  • Jython compiles Python 2.7 to Java bytecode, allowing the use of the Java libraries from a Pythonprogram.[159]
  • Pyrex (latest release in 2010) and Shed Skin (latest release in 2013) compile to C and C++ respectively.

Performance[edit]

Performance comparison of various Python implementations on a non-numerical (combinatorial) workload was presented at EuroSciPy’13.[160] Python’s performance compared to other programming languages is also benchmarked by The Computer Language BenchmarksGame.[161]

Development[edit]

Python’s development is conducted largely through the Python Enhancement Proposal(PEP) process, the primary mechanism for proposing major new features, collecting community input on issues, and documenting Python design decisions [162] Python coding style is covered in PEP8 [163]Outstanding PEPs are reviewed and commented on by the Python community and the steering council [162]

Enhancement of the language corresponds with the development of the CPython reference implementation The mailing list python-dev is the primary forum for the language’s development Specific issues are discussed in theRoundup bug tracker hosted at bugs python org [164] Developmentoriginally took place on a self-hosted source-code repository running Mercurial, until Python moved to GitHub in January2017 [165]

CPython’s public releases come in three types, distinguished by which part of the version number is incremented:

  • Backward-incompatible versions, where code is expected to break and needs to be manually ported. The first part ofthe 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 is very unlikely to ever happen.[166]
  • 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 happen annually.[167][168] Each major version is supported by bug fixes for several years after itsrelease.[169]
  • Bugfix releases,[170] which introduce no new features, occur about every 3 months and are made when a sufficient number of bugs have been fixed upstreamsince the last release. Security vulnerabilities are also patched in these releases. The third and final part of the version number is incremented.[170]

Numerous alpha, beta, and release candidates are also made available as previews and for testing prior to their official releases. Although each release has a general schedule, if the code is not ready, releases frequently get pushed back. By running the extensive unit test suite while developing, the Python development team keeps track of the state of the code. [171].

Themajor academic conference on Python is PyCon. There are also special Python mentoring programmes, such as Pyladies.

Python 3.10 deprecated wstr (to be removed in Python 3.12; meaning Python extensions[172] need to be modified by then),[173] and added pattern matching to thelanguage.[174]

API documentation generators[edit]

Tools that can generate documentationfor Python API include pydoc (available as part of the standard library), Sphinx, Pdoc and its forks, Doxygen andGraphviz, among others.[175]

Naming[edit]

The name Python is derived from the British comedy troupe Monty Python, whose work Guido van Rossum was inspired by while creating the language. Python code and culture frequently make references to Monty Python;[176] for instance, the metasyntactic variables that are frequently used in Python literature are spam and eggs rather than the conventional foo and bar. The official Python documentation also makes numerous references to Monty Python routines [176][177]. [178][179].

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 includePygame, a binding of SDL to Python (commonly used to create games); PyQt andPyGTK, which bind Qt and GTK to Python respectively; and PyPy, a Python implementation originally written in Python.

Popularity[edit]

Since 2003, Python has consistently ranked in the top ten most popular programming languages in the TIOBE ProgrammingCommunity Index where, as of October 2021, it is the most popular language (ahead of Java, and C).[180] It was selected Programming Language of the Year (for “the highest rise in ratings in a year”) in 2007, 2010, 2018, and 2020 (theonly language to do so four times[181]).[182]

An empirical study found that scripting languages, such as Python, are more productive than conventional languages, such as C and Java, for programming problemsinvolving string manipulation and search in a dictionary, and determined that memory consumption was often “better than Java and not much worse than C or C++”.[183]

Large organizations that use Python include Wikipedia,Google,[184]Yahoo!,[185] CERN,[186]NASA,[187] Facebook,[188]Amazon, Instagram,[189]Spotify,[190] and some smaller entities likeILM[191] andITA.[192] The social news networking site Reddit was written mostly inPython.[193]

Uses[edit]

Python can serve as a scripting language forweb applications, e g , via mod_wsgi for the Apachewebserver [194] With Web Server Gateway Interface, a standard API has evolved to facilitate these applications Webframeworks like Django, Pylons, Pyramid, TurboGears,web2py, Tornado, Flask, Bottle, and Zope support developers in the design and maintenance of complex applications Pyjs and IronPython can be used to develop the client-side of Ajax-based applications SQLAlchemy can be used as a data mapper to a relational database Twisted is a framework to program communications between computers, and is used (for example) by Dropbox

Python can be used effectively for scientific computing thanks to libraries like NumPy, SciPy, and Matplotlib[195][196], with Biopython and Astropy providing functionality that is specific to the biological and statistical domains. SageMath is a computer algebra system with a notebook interface that can be programmed in Python. Its library includes topics in algebra, combinatorics, numerical mathematics, number theory, and calculus. [197] Python bindings for OpenCV are available, and they offer a wide range of features for computer vision and image processing. [198].

Python is frequently employed in artificial intelligence and machine learning projects with the aid of libraries like TensorFlow, Keras, Pytorch, and Scikit-learn. [199][200][201][202] Python is a popular scripting language for natural language processing because of its modular architecture, straightforward syntax, and rich text processing tools. [203].

Python has libraries like Pygame that can be used to create 2D games, so it can also be used to make games.

As a scripting language, Python has been successfully integrated into a wide range of software products, including infinite element method software like Abaqus, 3D parametric modelers like FreeCAD, 3D animation packages like 3ds Max,Blender, Cinema 4D, Lightwave, Houdini, Maya, modo, MotionBuilder, Softimage, the visual effects compositor Nuke, 2D imaging programs like GIMP,[204] Inkscape,Scribus and Paint Shop To display intricate structures like C containers, GNU Debugger uses Python as a pretty printer. Python is recommended by Esri as the best language for creating scripts for ArcGIS. In addition, it has been adopted as the first of the three programming languages offered by Google App Engine, the other two being Java and Go. [206] It has also been used in a number of videogames. [209].

Many operating systems include Python as a standard component It ships with most Linuxdistributions,[210] AmigaOS 4 (using Python2 7), FreeBSD (as a package), NetBSD, andOpenBSD (as a package) and can be used from the command line (terminal) Many Linux distributions use installers written in Python: Ubuntu uses the Ubiquity installer, whileRed Hat Linux and Fedora Linux use the Anaconda installer Gentoo Linux uses Python in itspackage management system, Portage

In the field of information security, including in the creation of exploits, Python is widely used. [211][212].

Most of the Sugar software for theOne Laptop per Child XO, now[when?] developed atSugar Labs, is written in Python.[213] The Raspberry Pisingle-board computer project has adopted Python as its main user-programming language.

LibreOffice includes Python and intends to replace Java with Python. Its Python Scripting Provider is a corefeature[214] since Version 4.0 from 7 February 2013.

Languages influenced by Python[edit]

Python’s design and philosophy have influenced many other programming languages:

  • Boo uses indentation, a similar syntax, and a similar object model.[215]
  • Cobra uses indentation and a similar syntax, and its Acknowledgements document lists Python first among languages that influenced it.[216]
  • CoffeeScript, a programming language that cross-compiles to JavaScript, has Python-inspired syntax.
  • ECMAScript/JavaScript borrowed iterators andgenerators from Python.[217]
  • GDScript, a scripting language very similar to Python, built-in to theGodot game engine.[218]
  • Go is designed for the “speed of working in a dynamic language likePython”[219] and shares the same syntax for slicing arrays.
  • Groovy was motivated by the desire to bring the Python design philosophy toJava.[220]
  • Julia was designed to be “as usable for general programming as Python”.[29]
  • Nim uses indentation and similar syntax.[221]
  • 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 ownlanguage.”[222]
  • Swift, a programming language developed by Apple, has some Python-inspiredsyntax.[223]

Python’s development practices have also been emulated by other languages. For example, the practice of requiring a document describing the rationale for, and issues surrounding, a change to the language (in Python, a PEP) is also used inTcl,[224]Erlang,[225] and Swift.[226]

Seealso[edit]

  • Python syntax and semantics
  • pip(package manager)
  • List of programming languages
  • History of programming languages
  • Comparison of programming languages

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  • READ More:  What is software integration example?

    Sources[edit]

    • “Python for Artificial Intelligence”. Wiki.python.org. 19 July 2012. Archived fromthe original on 1 November 2012. Retrieved 3 December2012.
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    • Russell, Stuart J. & Norvig, Peter (2009). Artificial Intelligence: A Modern Approach (3rd ed.). Upper Saddle River, NJ: Prentice Hall. ISBN 978-0-13-604259-4.

    Further reading[edit]

    • 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. Archived from the original on 29 December 2008. Retrieved 31 March2010.
    • 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[edit]

    • Official website

    .

    What is the duration of Python course? : In general, it takes around two to six months to learn the fundamentals of Python But you can learn enough to write your first short program in a matter of minutes Developing mastery of Python’s vast array of libraries can take months or years
    Read Detail Answer On What is the duration of Python course?

    You’ve probably come across at least one blog post where the writer claims to have learned Python in a short period of time and to have moved on to a high-paying position. While some of these tales may be true, they won’t help you get ready for a steady learning marathon. Therefore, how long does it actually take to learn Python, and is it time well spent?

    In this article, you’ll learn:

    • What “learning Python” means and how you can measure yourprogress
    • What different reasons there are for learning Python
    • What background factors affect your learning approach and outcome
    • How much time you’ll want to invest in learning Python at different skill levels
    • Which resources you can use to improve your learning process

    To get started, you’ll go over some different reasons people want to learn to program inPython. Keep your personal motivations in mind and identify where you place yourself. Your reasons for learning Python will impact both your approach and the amount of time you’ll need to set aside.

    Why Would You Learn Python?

    You might be completely new to programming and on the fence about whether ornot you should invest your time into learning Python. In this first section, you’ll think about the different reasons people want to learn this programming language. Take note of the one you identify with the most:

    • Career and job opportunities: Maybe you want to start a new career as a software developer. Maybe you want to keep working at your current company and transition into a more technical role, such as data analysis. Programming proficiency is an excellentaddition to any skill set you already have. Once you have the Python skills you need, you can ace your Python coding interview to get your dream job.

    • Automation: Python can help you automate repetitive tasks that you regularly do in your job and private life. You could learn to automate your work withExcel spreadsheets, build a web scraper to access public data from the Internet, create command-line interfaces, or build bots for Twitter orDiscord that take work off your plate.

    • Curiosity: Digital products are everywhere, and you probably use them daily. You might want to know how your digital thermometer works, how a popular website is built, or how your favorite computer game would look if you digitally took it apart.

    • Creativity: You might have some fantastic ideas for your owngames, and you could build them with Arcade, Pygame, or another game engine. Or you may want to get started with programming hardware for home automation, Internet of Things (IoT), orembedded game development.

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    All of these are great reasons to get into programming! Your personal motivation for starting on this journey will affect how fast and how deeply you’ll learn Python. It’ll also influence which aspects of the language will require your focus. If you’re looking for inspiration on topics to tackle, then you can read aboutwhat you can do with Python.

    What Does “Learning Python” Mean?

    Learning Python means more than just learning the Python programming language. You’ll need to know more than just the specifics of a singleprogramming language to do something useful with your programming skills. At the same time, you don’t need to understand every single aspect of Python to be productive.

    Learning Python is about learning how to accomplish practical tasks with Python programming. It’s about a skill set that you can use to build projects for yourself or an employer.

    How Can You Measure Your LearningProgress?

    Its often hard to say at what point youve fully learned something Do you know Python when you know its syntax? Have you learned it when you know how to use a popular library without looking it up online? Or do you need to know all the ins and outs of the Python ecosystem to be able to say that youve learned Python?

    Realistically, youll probably never learn all there is to know about the Python ecosystem Theres too much to know! Therefore, its helpful to separate your journey into different segments This approach makes it easier for you to keep moving in the right direction

    When you think about different skill levels, you might think of three traditional categories:

  • Beginner
  • Intermediate
  • Expert
  • However, it’s hard to define when someone stops being abeginner, and even experienced programmers often don’t consider themselves experts. On the other hand, some programmers with low ability may think of themselves as experts, a cognitive bias known as the Dunning-Kruger effect. With that in mind, mapping out your progress following this type of traditional classification might not be that useful for you.

    TheFour Stages of Competence

    To evaluate your progress in learning, you will instead employ a different framework that is based on the four stages of competence:

    To make the four stages of competence more accessible, you’ll see the following short names to refer to each of the four stages:

  • Unawareness for unconscious incompetence
  • Awareness for conscious incompetence
  • Ability forconscious competence
  • Expertise for unconscious competence
  • You can read about what each of the stages stands for further down in this section. When you learn about time estimates for learning Python later on in this article, you’ll use the four stages of competence as a framework. But there’s a twist! You’ll shift your focus to the learning process that takes place in between the different stages and concentrate onthe mind shift that takes you from one phase to the next. You’ll read about how to get from:

  • Unawareness to awareness
  • Awareness to ability
  • Ability to expertise
  • Youll see that each of the four stages of competence covers similar grounds as the classic beginner-intermediate-expert model However, this alternate framework makes it easier for you to find your spot on the progression right now, which can give you actionable insight about how to keep moving from unawareness towards expertise:

    You should primarily rely on your own assessment of your progress to determine when you’ve transitioned from one phase to the next. Although time estimates can help you with that, you shouldn’t use them as strict guidelines. You’ll learn about some of these factors later on in this article. Many factors affect each person’s learning progress.

    You’ll discover an additional gauge of progress based on the number of projects you’ve finished, which should help the time estimates a little. Consider gauging your progress from one learning phase to the next by adding up the amount of time you invested and the number of projects you finished.

    Remember that these are only estimates. You’ll likely see yourself going faster or slower than described. As your ultimate self-assessment, focus on keeping track of transitions in your state of mind, which can indicate a switch from one phase to another. In the end, it’s essential that you keep working on projects, keep track of your progress, and enjoy yourself while you do. You’ll see your skills grow over time.

    Stage1: Unconscious Incompetence (Unawareness)

    For every skill that’s new to you, you’ll start at the stage of unconscious incompetence. That term probably doesn’t sound very encouraging. However, once you read Wikipedia’s definition of this stage, you see that it’s just a practical term to describe a familiar state of mind:

    The individual does not understand or know how to do something and does not necessarily recognize the deficit. They may deny the usefulness of the skill. The individual must recognize their own incompetence, and the value of the new skill, before moving on to the next stage. The length of time an individual spends in this stage depends on the strength of the stimulus to learn. (Source)

    You don’t know what you don’t know. You won’t learn something if you don’t accept that you don’t know it, and you also probably won’t understand what you don’t want to learn.

    Graduating from this first stage might take only a couple of moments. Nevertheless, it’s a crucial step for learning anything new and it often doesn’t get enough attention.

    Stage 2: Conscious Incompetence(Awareness)

    Once you’re aware that Python is a programming language that you want to learn more about, your active time investment begins. At this point, you’re at the stage of conscious incompetence:

    Though the individual does not understand or know how to do something, they recognize the deficit, as well as thevalue of a new skill in addressing the deficit. The making of mistakes can be integral to the learning process at this stage. (Source)

    It’ll take time and effort to progress through this stage. This investment is what people often think about when they talk about learning something new.

    Stage 3: Conscious Competence(Ability)

    If you think that you’ve successfully graduated from the previous phase of the four stages of competence, then you’ve achieved conscious competence:

    The individual understands or knows how to do something. However, demonstrating the skill or knowledge requires concentration. It may be broken down into steps, andthere is heavy conscious involvement in executing the new skill. (Source)

    At this point, you will be able to work with Python, which may be sufficient for your purposes. Programming skills can be put to use to create your own projects or to enhance workflows at your current job. You most likely know Python well enough to land a job as a software developer at the entry level. Python programming still requires a lot of conscious effort, but you can make things work.

    During this stage, however, you don’t have enough practice to be fluent and proficient. Moving to unconscious competence in Python will require even more time and effort from your side.

    Stage 4: Unconscious Competence(Expertise)

    When you reach unconscious competence, using your tools appears to be effortless. Python can be used in this stage in a similar manner to how a master musician would play their instrument. A skilled guitarist focuses on their music rather than how they hold their guitar. They have the skill to playfully and precisely use their instrument.

    Once you can move the tools you’re using into the background and you realize that your focus is primarily on creating, you’ve achieved unconscious competence:

    The individual has had so much practice with a skill that it has become “second nature” and can be performed easily. As a result, the skill can be performed while executing another task. The individual may be able to teach it to others, depending upon how and when it waslearned. (Source)

    Python programming proficiency may seem far away from where you are right now. Thats completely normal and okay! No musician starts as an expert handler of their instrument Years of diligent training are needed to achieve expertise. Many people go back to the first stage of the four stages of competence to advance their skills in another area, even after they have mastered one subject.

    When some programmers talk about how they never stop learning, they’re describing their progress from ability towards expertise in just one area of their work. While you might eventually gain expertise in one field where Python is used, there are many more where you’ll keep working and slowly progress from ability onwards.

    What Factors Influence Your LearningJourney?

    Now that you know how to break down your learning path into different steps, you might want to hear a specific number of hours it’ll take you to move between the four stages. You’ll find some time estimates below, but remember that learning is a personal process. Multiple factors determine how much time and effort learningPython will take for you. Here are some individual factors to consider:

  • Background: What previous experience do you have? If you know English well, if you have programmed in another language before, or if you have experience with mathematical logic and language learning, then you might progress more quickly.

  • Motivation: What do you want to usePython for, and how urgently do you want to learn it? If you have a clearly defined aim, such as a specific challenge you want to tackle, then it’ll be more straightforward to stay focused and motivated, and you might progress more quickly.

  • Aim: What skill level are you aiming for, and what goal do you hope to achieve by learning Python? Suppose you’re planning to get a full-time position as a Python developer. You’ll probably have to dive deeper into more aspectsof the language than you would if you were planning to complete a personal project as a hobby.

  • Availability: How much time can you invest in learning Python? Are you a student or in between jobs? Can you dedicate a significant amount of each day to study programming? Do you have a full-time job, meaning you can only study outside of work? Do you take care of kids or other people? If you have more time to invest, then you’ll progress faster.

  • Mentorship:Do you have someone who can teach you? You’ll learn faster with a knowledgeable friend or mentor who’s been through the process themselves and is ready to share their knowledge with you. You can get your mentorship support from a dedicated mentor at your job or online. If you don’t have a mentor in mind, try to get involved in a learning community.

  • Learning Resources: Do you have access to qualitylearning resources? They can help you decide what to learn first and how to continue. If your learning resources have high didactic quality as well as accuracy, then you’ll learn the right things more quickly.

  • This list isn’t exhaustive, and there may be other factors that’ll influence your learning journey. However, if you thoroughly consider these additional factors and think about your personal situation, you’re in a better position to assess the time you’ll needaccurately.

    How Long Does It Take to Learn Python?

    You now know what “learning Python” means andwhat learning framework you can use to split the learning process into stages. You also learned about background factors that can influence your learning journey. In this section, you’ll get familiar with guidelines that canhelp you plan how long it might take you to learn Python at different skill levels.

    From Unawareness to Awareness

    To step from unawareness into awareness, you’ll need to accept that you don’t know Python yet and that you want to know it. You’ll need to be ready to invest your time andeffort into studying the Python ecosystem:

      

    Goal Accept you don’t know Python and that you want to learn it
    Time Requirement Probably a few seconds or minutes
    Workload Common curiosity

    The good news is that you’ve already taken this step. You already know Python exists and that you want to invest in learning it, and you know why you should learn Python. Therefore, you’ll most likely find yourself somewhere in the next step of your progression through the four stages of competence.

    From Awareness to Ability

    You must engage with numerous new ideas, work through online tutorials and courses, and become familiar with the Python ecosystem in order to advance from awareness to ability. Included in that are activities like contemplation, reading, listening, building, and creating, as well as laboriously tapping away at a keyboard without much apparent payoff. You must be focused and determined to improve your Python skills.

    Although Python is a beginner-friendly language that reads similarly to English, it can still assist you in getting up to speed relatively quickly. If you are proficient in English, you can start writing simple Python code logic in a matter of days.

    You won’t build fully-fledged programs in only a few days, but you might be able to run small scripts that you wroteyourself. At this point, however, you haven’t reached the stage of ability yet. For this, you’ll need to build an understanding of at least the following Python programming concepts:

    • Python’s syntax
    • Data types
    • Flow control structures, such as thefor loop, the while loop, and conditional statements
    • Functions and scopes
    • Decorators, generators, and iterators
    • Classes and object-oriented programming
    • Best practices for writing Pythoniccode
    • Popular packages in the standard library, such as pathlib and collections

    Youll also need to learn more than just Python if you want to build functioning programs or apply for a job Youll need to understand some fundamental software development principles and howto use them in Python

    You should know how to:

    • Set up your Python development environment
    • Manage Python dependencies
    • Debug your code to find and fix errors
    • Write and handleexceptions
    • Test your Python apps
    • Understand modules and packages and how to use popular packages in Python’s extensive third-party ecosystem

    Tackling all ofthese topics and understanding these concepts requires a lot of training and time investment. How much exactly is hard to say and will be different for everyone. As a guideline, you can likely get there in about four months of consistent and focused study of at least four hours each day:

      

    Goal Learn Python’s syntax and fundamental programming and software development concepts
    Time Requirement Approximately four months of four hours each day
    Workload Approximately ten large projects

    Start by learning Pythons syntax and fundamental programming concepts, then focus on a specific library that you need to solve your challenge Having a particular task to tackle can help you keep your direction, consistently practice what youre learning, and move faster from awareness towards ability in Python

    If you read online that someone learned Python quickly, then they were probably talking about this phase. Depending on your prior experience,you can learn enough Python relatively quickly that you’ll have the ability to work with the language. After you’ve gained this ability, you’ll step into the next phase, which is where most programmers spend most of their time.

    From Ability to Expertise

    Moving from ability to expertise takes alot of time and practice, and the idea of becoming a “Python expert” is a little misleading. You’ll probably never be an expert in all of Python, and that’s okay! Most seasoned Python developers are only experts in a specific field:

    • Web development
    • REST API programming
    • Data science
    • Machine learning
    • GUI programming
    • Pygame game development
    • DevOps
    • Embedded programming

    There is much to learn in each field, and this list is not all-inclusive. It will take you a different amount of time for each area to advance you from skill to expertise. You can be an expert in any of these topics while still being a complete beginner in another area

    You can develop into a specialist in that field by consistently practicing the concepts and libraries required for it.

    A Django expert, for example, will have enough proficiency with the framework to code an application without consulting the documentation, or perhaps theyll just need to search for particular topics Itll be similar for any other field

    It takes a lot of practice to code at this level of fluency. The skill becomes second nature with practice, and the libraries you’re using, the syntax, and the logic of the Python code will become less noticeable. Once you get there, you can solve the problems at hand while not having to think about the methods you’re using.

    Keep practicing what you’re most interested in and train the programming concepts and Python libraries that you find the most helpful for your tasks. Adopt a mindset of working towards expertise in one field for which Python is used, and stay comfortable with the idea that there’s always more tolearn:

      

    Goal Become really good at one field for which Python is used
    Time Requirement Continuous practice over years
    Workload Approximately twenty large projects

    There’s no end to your learning journey when studying with Python. You may want to make yourself comfortable in this phase of the four stages of competence because you’ll likely spend a good amount of your time here.

    Which Resources Can Help You Learn PythonFaster?

    You can think about enhancing the fun and effectiveness of your learning once you are clear on why you want to learn Python, what skill level you are aiming for, and how to account for your personal background.

    The good news is that you have a lot of help at your disposal! Below, you’ll find a list of the types oflearning aids that you can try out:

    • Learning Resources: You can learn from online content ranging from tutorials, video courses, quizzes, and projects. Online content is most helpful if you have a specific project inmind for which you can find existing tutorials or if you follow a learning path about a topic that interests you. You’ll find Real Python content labeled as basics, intermediate, andadvanced to help you find the best learning resource for your skill level.

    • Books: There are many great Python books that can help you learn the language at different levels of depth and complexity. If you’re just getting started, check out thePython Basics Book. If you’re already writing Python programs and looking to improve your language skills, then you might enjoy Python Tricks.

    • Challenges: You might enjoy challenging yourself with code examples and competing on leaderboards. Complete puzzles and keep training your coding skills atCodingBat, HackerRank, LeetCode, Advent Of Code, or CodinGame.

    • Communities: Many people learn better with social interactions. A good learning community can keep you engagedand accountable. You can join a friendly community of experts at Real Python or PythonistaCafe. You can also follow Real Python on Twitter and use the platform to stay in touch with other developers. Listen to the Real Pythonpodcast and sign up for the newsletter to keep yourself up-to-date with developments in the Python world.

    All of these different types of resources are available to you online. It’s worth spending some time picking and choosing which ones are most engaging and effective for you personally. That said, when learning anything new, there’s no way around two essential factors:

  • Time investment
  • Consistentpractice
  • The most important aspect is to keep showing up and make programming part of a consistent routine. To learn Python at any level, you’ll need to invest time and effort.

    Conclusion

    You learned about the different phases of learning Python You considered reasons why you might want to learn to program, aswell as what stages youre likely to go through during that process

    While you can start to write small scripts in Python after just a few days of study, youll probably spend around four months gaining an essential ability in programming with Python Youll have to spend years andbuild many projects to become a Python expert in even just one field

    In this article, you learned:

    • What “learning Python” means and how you can measure your progress
    • What different reasons there are for learning Python
    • What external factors influence how fast you’ll learn Python
    • Why learning Python atdifferent skill levels takes different amounts of time and effort
    • Which resources you can use to improve your learning process

    Learning to program in Python can be an excellent investment of your time If you keep showing up and make it exciting and fun for yourself, then youre more likely to find ways to integrate it into your regular habits If youre looking for more advice on your first steps, check out11 Beginner Tips for Learning Python Programming

    Additional Question — Which YouTube channel is best for learning Python Telugu?

    What is Python course fees?

    Popular Python Certification coursesCourseOffered byFeesPython DeveloperManipal ProlearnRs 3,700/-Foundational Level Course Programming in PythonIIT MadrasRs 4,000/-Certified Python Programmer CourseWileynxtRs 9,999/-Python Programming for BeginnersAcadglidRs 5,898/-

    What is qualification for Python?

    Prerequisite: 10+2 with knowledge of mathematical aptitude Objective: The course is designed to provide Basic knowledge of Python

    Can I learn Python in 1 month?

    Data scientists need to learn programming and are interested in the fastest way to do so. Python is therefore favored by the majority of data scientists. Relating to the original query in the article’s title, the solution is indeed. Python can be learned in one month.

    Can I learn Python in 3 days?

    Python is so simple to learn that you can do it in 3 days. You won’t become an expert in it, but you will feel at ease. The only thing left to learn after mastering the fundamentals is how to use the libraries appropriately for your work. For various tasks, there are various libraries.

    Is it difficult to learn Python?

    No, Python isn’t hard to learn for most people In fact, Python is considered one of the easiest programming languages to learn While anyone can learn Python programming even if you’ve never written a line of Python code before you should expect that it will take time, and you should expect moments of frustration

    Is Python enough to get a job?

    No, Python isn’t enough by itself to land a job, but having a solid educational foundation, some familiarity with Python’s fundamentals, and other soft skills will undoubtedly help.

    Can I learn Python at 45 and get a job?

    Certainly, provided you possess the necessary abilities and knowledge. There are many jobs in the python field, so nobody will ever care what age you are. In addition to this, you have the option of freelancing.

    Which coding language is the future?

    Python. Python can be regarded as the future of programming languages. As per the latest statistics, Python is the main coding language for around 80% of developers. The presence of extensive libraries in Python facilitates artificial intelligence, data science, and machine learning processes.

    What Python skills are in demand?

    Analysis and visualisation of data Data wrangling Python packages such as NumPy, MatPlotib, and Scikit learn SQL Proficiency in core pythonException handling File handling concepts Variables and data types OOPs concepts Data structures Generators Iterators

    Which pays more Java or Python?

    Jobs and Salary In the US, the median annual salary for Python developers is about $96,000, while for Java developers it is approximately $97,000 Both are very popular so if you become skilled in either, you can start working as a software developer or intern to start your career

    What kind of jobs use Python?

    Though there are many jobs in tech that use Python extensively including Software Engineer, Web Developer, Data Scientist, and Business Analyst a dedicated Python Developer will be expected to understand the language at a higher level and be capable of using Python to accomplish any number of tasks, including but

    Dannie Jarrod

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