You can create an environment for your Renku session based on a environment file in a code repository.

This guide will walk you through what kinds of files you can use to define environments in RenkuLab, and how to create a code-based environment for your project.

What kinds of environment definitions are supported?

RenkuLab’s code-based environments currently supports creating Python environments. Support for more languages is coming soon!

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Do you need to install R packages in your Renku session? See R.

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Defining a Python Environment

There are multiple ways you can define a python environment for your Renku session:

• Miniconda (environment.yml) (recommended)
• Pip (requirements.txt)
• Poetry (pyproject.toml)

See below for more details on how to use each of these systems.

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If you’d like to learn more about the system Renku uses to create python environments, check out https://paketo.io/docs/howto/python/#use-a-package-manager.

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Miniconda (environment.yml) (recommended)

Include an environment.yml file located at the root (top level) of the code repository.

• Here’s an example environment.yml:

Important usage notes:

• Regarding conda channels:
  • nodefaults must be included. See example above.
  • We recommend using the conda-forge channel or other non-anaconda channels.
  • The defaults channel is not recommended and often results in failed builds (due to rate limits imposed by Anaconda).
• Please note that miniconda can only be used at this time to create Python environments, not R environments.
• Environments defined with one of these files will be created via miniconda. Configuring a version of miniconda is not supported.