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Different Python versions can cause compatibility problems. For example, if your client code uses a library that requires Python 3.9, but the Databricks cluster is running Python 3.8, you might face issues. When you find the incompatibility, the primary step is to check the **library dependencies**. Determine the required Python versions and the dependencies of all libraries used in your code. Also, inspect the **Spark Connect client environment**. Ensure that the client environment has the necessary libraries. If the client environment is missing a library or uses an incompatible version, install the necessary packages using `pip` or `conda`.
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