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When your Python libraries don't work the way they should in Python tool, restoring the tool to it's original state could be the solution. This article walks through how to restore Python libraries and the virtual environment associated with the Python tool.
Making a copy of a workflow that contains a Python tool will cause the JupyterGuidDir to be duplicated. Because of this reason, both copies will point to the same Jupyter Notebook document. If the user makes changes on one copy, the other will be changed too which is not desirable.
With the Python Tool, Alteryx can manipulate your data using everyone’s favorite programming language - Python! Included with the tool are a few of pre-built libraries that extend past even the native Python download.
Alteryx Designer comes with tools (based on both R and Python) to create and use predictive models without needing to write any code. But what if you've got custom models written in R or Python outside of Designer that you want to use in Designer, or vice versa?
The Python tool interface is based on a Jupyter Notebook. As of Alteryx Designer 2018.4, the Python tool can create logs for its web configuration. The frequency of these logs can be increased by switching on the debugging log level. Note that output file will be bigger and that it will impact Python tool performance in Designer.\n