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Merge pull request #1581 from ChrisBarker-NOAA/conda_notes
Updated notes about conda
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source/conf.py

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# https://github.com/pypa/packaging.python.org/pull/1474
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"https://stackoverflow.com/*",
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"https://pyscaffold.org/*",
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"https://anaconda.org",
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]
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linkcheck_retries = 5
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# Ignore anchors for links to GitHub project pages -- GitHub adds anchors from

source/guides/installing-scientific-packages.rst

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for most of the software in the `scientific Python stack
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<https://scientific-python.org>`_ can be configured
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to interoperate with different FORTRAN libraries, and can take advantage
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of different levels of vectorised instructions available in modern CPUs.
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of different levels of vectorized instructions available in modern CPUs.
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Starting with version 1.10.4 of NumPy and version 1.0.0 of SciPy, pre-built
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32-bit and 64-bit binaries in the ``wheel`` format are available for all major
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operating systems (Windows, macOS, and Linux) on PyPI. Note, however, that on
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Windows, NumPy binaries are linked against the `ATLAS
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<http://www.netlib.org/atlas/>`__ BLAS/LAPACK library, restricted to SSE2
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<https://math-atlas.sourceforge.net/>`__ BLAS/LAPACK library, restricted to SSE2
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instructions, so they may not provide optimal linear algebra performance.
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There are a number of alternative options for obtaining scientific Python
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The conda cross-platform package manager
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----------------------------------------
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`Anaconda <https://www.anaconda.com/products/individual/>`_ is a Python distribution
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published by Anaconda, Inc. It is a stable collection of Open Source
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packages for big data and scientific use. As of the 5.0 release of Anaconda,
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about 200 packages are installed by default, and a total of 400-500 can be
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installed and updated from the Anaconda repository.
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``conda`` is an open source (BSD licensed) package management system and
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environment management system included in Anaconda that allows users to install
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environment management system that allows users to install
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multiple versions of binary software packages and their dependencies, and
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easily switch between them. It is a cross-platform tool working on Windows,
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macOS, and Linux. Conda can be used to package up and distribute all kinds of
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MacOS, and Linux. Conda can be used to package up and distribute all kinds of
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packages, it is not limited to just Python packages. It has full support for
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native virtual environments. Conda makes environments first-class citizens,
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making it easy to create independent environments even for C libraries. It is
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written in Python, but is Python-agnostic. Conda manages Python itself as a
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package, so that :command:`conda update python` is possible, in contrast to
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pip, which only manages Python packages. Conda is available in Anaconda and
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Miniconda (an easy-to-install download with just Python and conda).
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pip, which only manages Python packages.
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Anaconda `Anaconda <https://docs.anaconda.com/anaconda/>`_ is a Python distribution published by Anaconda, Inc. It is a stable collection of Open Source packages for big data and scientific use, and a collection of Graphical Interface utilities for managing conda environments.
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In addition to the full distribution provided by Anaconda, the conda package manager itself is available in `miniconda <https://docs.anaconda.com/miniconda/>`_, `miniforge <https://github.com/conda-forge/miniforge>`_, and `pixi <https://pixi.sh/>`_.
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Conda packages are available on multiple channels on Anaconda.org, including the
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default channel supported by Anaconda, Inc, the community supported conda-forge channel, which provides a wide variety of pre-built packages, and some domain-specific package collections.

source/key_projects.rst

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:doc:`Docs <conda:index>`
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conda is the package management tool for `Anaconda
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<https://docs.anaconda.com/anaconda/>`__ Python installations.
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Anaconda Python is a distribution from `Anaconda, Inc
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<https://www.anaconda.com/products/individual>`__ specifically aimed at the scientific
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community, and in particular on Windows where the installation of binary
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extensions is often difficult.
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Conda is a package, dependency, and environment management system for any language — Python, R,
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Ruby, C/C++, Fortran, and more. It is written in Python and
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widely used in the Python scientific computing community, due to its support for non-Python
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compiled libraries and extensions. It is used as the basis of the `Anaconda
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<https://docs.anaconda.com/anaconda/>`__ Python distribution from Anaconda, Inc. It was originally
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aimed at the scientific community, but can also be used on its own, or with the
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:doc:`miniconda <conda:miniconda>`, `miniforge <https://github.com/conda-forge/miniforge>`_ or
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`pixi <https://pixi.sh/>`_ systems. It is available for Windows, Mac and Linux systems.
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Conda is a completely separate tool from :ref:`pip`, virtualenv and wheel, but provides
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many of their combined features in terms of package management, virtual environment
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management and deployment of binary extensions.
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Conda does not install packages from PyPI and can install only from
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the official Anaconda repositories, or anaconda.org (a place for
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user-contributed *conda* packages), or a local (e.g. intranet) package
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server. However, note that :ref:`pip` can be installed into, and work
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side-by-side with conda for managing :term:`distributions
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<Distribution Package>` from PyPI. Also, `conda skeleton
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<https://docs.conda.io/projects/conda-build/en/latest/user-guide/tutorials/build-pkgs-skeleton.html>`__
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is a tool to make Python packages installable by conda by first
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fetching them from PyPI and modifying their metadata.
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many of their combined features, such as package management, virtual environment
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management and deployment of binary extensions and other binary code.
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Conda does not install packages from PyPI -- it can only manage packages built specifically
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for conda, which can be made available on a "conda channel", such as those hosted on
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`anaconda.org <https://anaconda.org>`__, or a local (e.g. intranet) package server.
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In addition to the "default" channels managed by `Anaconda, Inc. <https://www.anaconda.com/>`__, there are a wide variety of packages from the community supported
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`conda-forge project <https://conda-forge.org/>`__
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Note that :ref:`pip` can be installed into, and work side-by-side with conda
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for managing :term:`distributions <Distribution Package>` from PyPI. It is also possible
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to build conda packages from Python source packages using tools such as
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`conda skeleton
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<https://docs.conda.io/projects/conda-build/en/latest/user-guide/tutorials/build-pkgs-skeleton.html>`__: a tool to automatically make conda packages from Python packages available on PyPI.
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.. _devpi:
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