What is the purpose of channels in Anaconda?

Anaconda is a widely appreciated platform for solving scientific computing problems. It is Python/R platform that simplifies package management and deployment. If you are new to Anaconda then you must be wondering what is the need of conda channels in Anaconda Platform? What are their uses in anaconda platform? Read along to know more about channels in Anaconda.

Conda Channels are basically the locations where packages are stored. If there is a need of a package that is other than the defaults, the developers can also create their own channels as there is a method available in the Anaconda. The channels Anaconda Channel and the R channel are two of the 10 official repositories present in Anaconda. You can understand its purpose with the fact that conda channels serve as the base for hosting and managing packages. Anaconda Navigator is a phenomenal platform for developers to launch multiple applications and manage them with ease.

Conda finds these locations by the channel name. The channels must be active whenever in use otherwise the condo will not be able to use the package that you desire in your code. There is a default channel when no channel is added. Channels also play the role of hosting the packages. Sometimes a channel might not be needed or may have some irresolvable issues with it. In this case the channel can be archived by using the archive property.

 Conda Forge

 Conda Forge is a Github led community based repository organization. The members of this organization can provide their own repositories, distributions and condo environment codes. Conda-Forge can also be installed along with conda, which is an open source package management system for any programming language. It can also be included in the Anaconda Navigator.

Steps to create your own channels in Anaconda Navigator

1. Go to Environments
2. Click on Channel
3. Click on add
4. Add the Channel name and the channel URL
5. Click on Save

Final Words…

So, go ahead. Use the channels in Anaconda to manage your packages and simplify the complex problems of data science programming with Python and R.