This node ensures the existence of a specific configurable Conda environment and propagates the environment to downstream Python nodes. This is useful to make workflows that contain Python nodes more portable by allowing to recreate the Conda environment used on the source machine (for example your personal computer) on the target machine (for example a KNIME Server instance). The node is intended to be used as follows:
- On your local machine, you need to have Conda set up and configured in the Preferences of the KNIME Python Integration as described in the corresponding installation guide.
- Configure this node by selecting the Conda environment to propagate and selecting the packages to include in the environment in case it needs to be recreated.
- Connect the output port of the node to the variable input port of any Python node.
- Successively open the configuration dialogues of the Python node and all subsequent Python nodes in the flow that you want to make portable. Upon opening their dialogues for the very first time, they will automatically pick up the environment by setting their respective Python 2 and/or Python 3 entries on the Flow Variables tab to the propagated conda.environment variable. Otherwise, you have to perform this step manually.
- Deploy the workflow by uploading it to the KNIME Server, sharing it via the KNIME Hub, or exporting it. Make sure that this node is reset before or during the deployment process.
- On the target machine, Conda must also be set up and configured in the Preferences of the KNIME Python Integration. If the target machine runs a KNIME Server, you may need to contact your server administrator and/or refer to the server administration guides in order to do this.
- During execution (on either machine), the node will check whether a local Conda environment exists that matches its configured environment. The node will recreate the environment if necessary, ensuring its availability to the connected and properly configured downstream Python nodes.