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The Python Distribution Utilities (distutils) Python module was first added to the Python standard library in the 1.6.1 release, in September 2000, and in the 2.0 release, in October 2000, nine years after the first Python release in February 1991, with the goal of simplifying the process of installing third-party Python packages.
Python (programming language) scientific libraries (36 P) Pages in category "Python (programming language) libraries" The following 43 pages are in this category, out of 43 total.
DSatur is known to be exact for bipartite graphs, [1] as well as for cycle and wheel graphs. [2] In an empirical comparison by Lewis in 2021, DSatur produced significantly better vertex colourings than the greedy algorithm on random graphs with edge probability p = 0.5 {\displaystyle p=0.5} , while in turn producing significantly worse ...
CuPy is an open source library for GPU-accelerated computing with Python programming language, providing support for multi-dimensional arrays, sparse matrices, and a variety of numerical algorithms implemented on top of them. [3] CuPy shares the same API set as NumPy and SciPy, allowing it to be a drop-in replacement to run NumPy/SciPy code on GPU.
Requests is an HTTP client library for the Python programming language. [2] [3] Requests is one of the most downloaded Python libraries, [2] with over 300 million monthly downloads. [4] It maps the HTTP protocol onto Python's object-oriented semantics. Requests's design has inspired and been copied by HTTP client libraries for other programming ...
Pandas (styled as pandas) is a software library written for the Python programming language for data manipulation and analysis.In particular, it offers data structures and operations for manipulating numerical tables and time series.
Dask is an open-source Python library for parallel computing.Dask [1] scales Python code from multi-core local machines to large distributed clusters in the cloud. Dask provides a familiar user interface by mirroring the APIs of other libraries in the PyData ecosystem including: Pandas, scikit-learn and NumPy.
While evaluating free and commercial solutions, he ran across Python bindings on the wxWidgets toolkit webpage (known as wxWindows at the time). This was Dunn's introduction to Python. Together with Harri Pasanen and Edward Zimmerman he developed those initial bindings into wxPython 0.2. [2] In August 1998, version 0.3 of wxPython was released.