Configure an agent with PyPI access: visualizations

In order for Moderne to retrieve your visualization artifacts from PyPI, you will need to configure the agent and run it in a specific environment. This guide will walk you through how to configure the agent to get visualization artifacts from your PyPI package index.

Note: This feature is experimental. Running the agent in a different environment (read: os, python version) may break deployed visualizations.

Publishing visualizations

Visualization artifacts published to the configured PyPI index can be deployed to moderne if there is an agent configured with access.

Configuring the Moderne agent

The following table contains all of the variables/arguments you need to add to your Moderne agent run command in order for it to get visualization artifacts from your PyPI package index. Please note that these variables/arguments must be combined with ones found in other steps in the Configuring the Moderne agent guide.

You can configure multiple PyPI indexes by including multiple entries, each with a different {index}.


  • MODERNE_AGENT_VISUALIZATIONS_USEONLYCONFIGURED(Optional) Only use the visualization sources configured in the agent. Default is false.

  • MODERNE_AGENT_PYPI_{index}_URLThe URL of your PyPI package index.

  • MODERNE_AGENT_PYPI_{index}_USERNAME(Optional) The username used to access the index. Defaults to null.

  • MODERNE_AGENT_PYPI_{index}_PASSWORD(Optional) The password used to access the index. Defaults to null.

  • MODERNE_AGENT_PYPI_{index}_SKIPSSL(Optional) Whether or not to skip SSL/TLS verification for calls from the agent to this PyPI package index. This must be set to true if you use a self-signed SSL/TLS certificate. Defaults to false.


docker run \
# ... Existing variables
# ... Additional variables

The agent environment

To install pip packages from the secure environment the agent runs in we need to install and move the packages on the agent and to the SaaS. To achieve this the enviroments that the agent and the SaaS run in must be in sync. The easiest way to achieve this is to run the agent using the OCI container, but if you do run it using your own container or using the executable jar directly you will need to ensure that the enviroment is setup up in a way that the python packages downloaded on the agent will also work on the SaaS. This means:

  • Linux (ubuntu:22.04 is tested)

  • /bin/sh shell with

    • Python version 3.11 available under the python3 command

    • Pip and virtualenv (venv) installed. Alias not required (called via python3 -m pip/venv)

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