Skip to main content
Glama

Python Dependency Manager Companion

by KemingHe
create-custom-channels.rst2.31 kB
======================== Creating custom channels ======================== In this tutorial, we walk through how to create your own channel that can either be accessed via the local or network file system or served from a webserver. To create a custom channel: #. You will need to install conda-build to complete this tutorial. If you do not already have it, you can install it with the following command: .. code:: conda install conda-build #. Organize all the packages in subdirectories for the platforms you wish to serve. Below is an example of what this may look like: .. code:: channel ├── linux-64 │ └── package-1.0-0.tar.bz2 ├── osx-64 │ └── package-1.0-0.tar.bz2 └── win-64 └── package-1.0-0.tar.bz2 #. Run ``conda index`` on the channel root directory: .. code:: conda index channel/ The conda index command generates a file ``repodata.json``, saved to each repository directory, which conda uses to get the metadata for the packages in the channel. .. note:: Each time you add or modify a package in the channel, you must rerun ``conda index`` for conda to see the update. #. To test custom channels, serve the custom channel using a web server or using a ``file://`` URL to the channel directory. Test by sending a search command to the custom channel. **Example**: if you want a file in the custom channel location ``/opt/channel/linux-64/``, search for files in that location: .. code:: conda search -c file:///opt/channel/ --override-channels .. note:: * The channel URL does not include the platform, as conda automatically detects and adds the platform. * The option ``--override-channels`` ensures that conda searches only your specified channel and no other channels, such as default channels or any other channels you may have listed in your ``.condarc`` file. If you have set up your private repository correctly, you get the following output: .. code:: Fetching package metadata: . . . . This is followed by a list of the conda packages found. This verifies that you have set up and indexed your private repository successfully.

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/KemingHe/python-dependency-manager-companion-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server