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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]
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.
In 2009, a Google sponsored branch named Unladen Swallow was created to incorporate a just-in-time compiler into CPython. [7] [8] Development ended in 2011 without it being merged into the main implementation, [9] though some of its code, such as improvements to the cPickle module, made it in. [10] [7]
Python Imaging Library is a free and open-source additional library for the Python programming language that adds support for opening, manipulating, and saving many different image file formats. It is available for Windows, Mac OS X and Linux. The latest version of PIL is 1.1.7, was released in September 2009 and supports Python 1.5.2–2.7. [3]
The Zen of Python is a collection of 19 "guiding principles" for writing computer programs that influence the design of the Python programming language. [1] Python code that aligns with these principles is often referred to as "Pythonic". [2] Software engineer Tim Peters wrote this set of principles and posted it on the Python mailing list in ...
Since its inception, Firefox for Linux supported the 32-bit memory architecture of the IA-32 instruction set. 64-bit builds were introduced in the 4.0 release. [186] The 46.0 release replaced GTK 2.18 with 3.4 as a system requirement on Linux and other systems running X.Org. [198] Starting with 53.0, the 32-bit builds require the SSE2 ...
In computing, CUDA (Compute Unified Device Architecture) is a proprietary [2] parallel computing platform and application programming interface (API) that allows software to use certain types of graphics processing units (GPUs) for accelerated general-purpose processing, an approach called general-purpose computing on GPUs.