Cluster install of Python libraries versus notebook install

[lmorrissey]

If a base set of libraries is installed on the cluster and pinned to a specific version, can/would this conflict with a notebook submitted to the cluster that defines a conflicting set of libraries for install?
Is there a way to override the cluster python env via modifying the PYTHONPATH or some other Databricks variable in these cases or some order of precedence?

[Alberto_Umana · Accepted solution]

When a base set of libraries is installed on a cluster, can indeed conflict with a notebook submitted to the cluster that defines a conflicting set of libraries for installation. This is because the libraries installed at the cluster level take precedence over those specified in the notebook. 

If you need to use custom Python libraries or modules, the recommended approach is to install the required libraries directly to the cluster using the cluster library installation feature. This ensures that the libraries are available to all notebooks running on the cluster.

About your pythonpath variable, please see;

https://kb.databricks.com/en_US/clusters/cannot-set-a-custom-pythonpath