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Python 3.0, released in 2008, was a major revision not completely backward-compatible with earlier versions. Python 2.7.18, released in 2020, was the last release of Python 2. [37] Python consistently ranks as one of the most popular programming languages, and has gained widespread use in the machine learning community. [38] [39] [40] [41]
IDLE (short for Integrated Development and Learning Environment) [2] [3] is an integrated development environment for Python, which has been bundled with the default implementation of the language since 1.5.2b1. [4] [5] It is packaged as an optional part of the Python packaging with many Linux distributions.
Python Package Index (formerly the Python Cheese Shop) is the official directory of Python software libraries and modules; Useful Modules in the Python.org wiki; Organizations Using Python – a list of projects that make use of Python; Python.org editors – Multi-platform table of various Python editors
The default can be overridden (e.g. in source code comment) to Python 3 (or 2) syntax. Since Python 3 syntax has changed in recent versions, Cython may not be up to date with the latest additions. Cython has "native support for most of the C++ language" and "compiles almost all existing Python code". [7] Cython 3.0.0 was released on 17 July ...
Anaconda is an open source [9] [10] data science and artificial intelligence distribution platform for Python and R programming languages.Developed by Anaconda, Inc., [11] an American company [1] founded in 2012, [11] the platform is used to develop and manage data science and AI projects. [9]
Python 2.6 was released to coincide with Python 3.0, and included some features from that release, as well as a "warnings" mode that highlighted the use of features that were removed in Python 3.0. [ 28 ] [ 10 ] Similarly, Python 2.7 coincided with and included features from Python 3.1, [ 29 ] which was released on June 26, 2009.
Written in C and Python, CPython is the default and most widely used implementation of the Python language. CPython can be defined as both an interpreter and a compiler as it compiles Python code into bytecode before interpreting it.
By default, a Pandas index is a series of integers ascending from 0, similar to the indices of Python arrays. However, indices can use any NumPy data type, including floating point, timestamps, or strings. [4]: 112 Pandas' syntax for mapping index values to relevant data is the same syntax Python uses to map dictionary keys to values.