Customize or update environment

You can build a custom Docker image on top of the default one to customize your environment (install some package from apt to be available in your notebooks, or set up a custom Python environment by pre-installing the required libraries).

Generate indexes to ensure the editor's proper work

After you create a new custom environment or update one of our environments, run the following command in the same file:

RUN /opt/datalore/build_code_insight_data.sh /[environment_path]

where [environment_path] is the path to the environment you created or updated.

If not performed, these indexes will be updated every time the agent starts, which slows down the editor.

Add the created environment file to the main datalore pod

Add the file to following directory:

/opt/datalore/configs/environment_info

Make sure you follow these instructions:

• For a conda environment, specify the respective .yml file matching the envrionment name. For example, if you created a conda environment called somename, add an environment_somename.yml file.

• For a pip environment, specify the respective .txt file matching the envrionment name. For example, if you created a pip environment called somename, add an requirements_somename.txt file.