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Conda is an open-source, [2] cross-platform, [3] language-agnostic package manager and environment management system. It was originally developed to solve package management challenges faced by Python data scientists, and today is a popular package manager for Python and R.
pvlib python's documentation is online and includes many theory topics, an intro tutorial, an example gallery, and an API reference. The software is broken down by the steps shown in the PVPMC modeling diagram.
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.
Anaconda Cloud is a package management service by Anaconda where users can find, access, store and share public and private notebooks, environments, and Conda and PyPI packages. [52] Cloud hosts useful Python packages, notebooks and environments for a wide variety of applications.
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]
A software package development process is a system for developing software packages.Such packages are used to reuse and share code, e.g., via a software repository.A package development process includes a formal system for package checking that usually exposes bugs, thereby potentially making it easier to produce trustworthy software (Chambers' prime directive). [1]
It is an open-source cross-platform integrated development environment (IDE) for scientific programming in the Python language.Spyder integrates with a number of prominent packages in the scientific Python stack, including NumPy, SciPy, Matplotlib, pandas, IPython, SymPy and Cython, as well as other open-source software.
Such repositories may provide additional functionality, like access control, versioning, security checks for uploaded software, cluster functionality etc. and typically support a variety of formats in one package, so as to cater for all the needs in an enterprise, and thus aiming to provide a single point of truth.