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Pip's command-line interface allows the install of Python software packages by issuing a command: pip install some-package-name. Users can also remove the package by issuing a command: pip uninstall some-package-name. pip has a feature to manage full lists of packages and corresponding version numbers, possible through a "requirements" file. [14]
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.
Cython is a compiled language that is typically used to generate CPython extension modules. Annotated Python-like code is compiled to C and then automatically wrapped in interface code, producing extension modules that can be loaded and used by regular Python code using the import statement, but with significantly less computational overhead at ...
MicroPython consists of a Python compiler to bytecode and a runtime interpreter of that bytecode. The user is presented with an interactive prompt (the REPL) to execute supported commands immediately. Included are a selection of core Python libraries; MicroPython includes modules which give the programmer access to low-level hardware. [4]
Astropy is a collection of software packages written in the Python programming language and designed for use in astronomy. [2] The software is a single, free, core package for astronomical utilities due to the increasingly widespread usage of Python by astronomers, and to foster interoperability between various extant Python astronomy packages. [3]
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.
scikit-image (formerly scikits.image) is an open-source image processing library for the Python programming language. [2] It includes algorithms for segmentation, geometric transformations, color space manipulation, analysis, filtering, morphology, feature detection, and more. [3]
Moreover, complementary Python packages are available; SciPy is a library that adds more MATLAB-like functionality and Matplotlib is a plotting package that provides MATLAB-like plotting functionality. Although matlab can perform sparse matrix operations, numpy alone cannot perform such operations and requires the use of the scipy.sparse library.