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Mirroring Alternate Channels

Last Updated: Dec 01, 2017 12:59PM CST

You can mirror any channel from Anaconda Cloud using Anaconda Enterprise Repository.

In addition to the default Anaconda channel, some common channels are the Conda-Forge and R channels.

You can mirror these or any other channel into their own channels on your Anaconda Enterprise Repository installation.


  1. Create a yaml file for the channel to be mirrored, r.yaml and conda-forge.yaml.

    Add the channels and URL to the channel in each file. This configuration will mirror everything from the channel including all platforms and all python versions.

          - https://conda.anaconda.org/conda-forge

          - https://conda.anaconda.org/r

    To start the mirroring process, run the following commands:
    anaconda-server-sync-conda --mirror-config r.yaml --account=r-channel
    anaconda-server-sync-conda --mirror-config conda-forge.yaml --account=conda-forge

    --mirror-config : points to the path of the yaml file. If this file is not in the current working directory you will need to specify the full path.

    --account: create the channel on your installation of Anaconda Repository. The name is specified after the = symbol.

  2. Edit the yaml file to configure your mirror for specific packages, python versions, operating system platforms, architectures, and licenses.

    platforms : specify what operating systems and architectures you want to mirror packages for: win-32, win-64, linux-32, linux-64, osx-32, osx-64.

    python_versions: specify the python version of the packages being mirrored in the format of X.Y: 2.6, 2.7, 3.4, 3.5, etc.

    pkg_list: specify the exact package names you want to mirror from the channel. Packages named here will be mirrored.

    Example yaml file:

    This configuration mirrors Linux 64-bit and Windows 64-bit platform versions of the Numpy and Scipy packages for Python-2.7 from the Conda-Forge channels:

          - https://conda.anaconda.org/conda-forge

          - win-64
          - linux-64

          - 2.7

          - numpy
          - scipy

MORE INFO: For other options like blacklisting, whitelisting, and license filtering, see the documentation.
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