Find the ideal dimension order for your TM1 cubes

Install TM1py:

pip install TM1py

Clone or download the optimus-py Repository from GitHub

• Adjust config.ini to match your TM1 environment
• Create uniquely named views in the relevant cubes
• Execute the optimuspy.py
• provide 6 arguments: -i (name of the instance) -v (name of the cube view) -e (number of execution) -f (fast mode: True or False) -o (output: csv or xlsx) -u (update original order: True or False)

C:\Projects\optimus-py\optimuspy.py -i="tm1srv01" -v="Optimus" -e="10" -f="False" -o="csv" -u=True

C:\Projects\optimus-py\optimuspy.py --instance="tm1srv01" --view="Optimus" --executions="15" --fast="False" --output="csv" --update=True

OptimusPy determines the ideal dimension order for every cube, based on RAM and query speed. For traceability and custom analysis, Optimus visualizes the results in a csv report and a scatter plot per cube.

• Run on the same machine
• Use big and representative views
• Choose a sensible number of executions
• Provide enough spare memory on TM1 server
• Fast mode determines first and last position only

• TM1py - A python wrapper for the TM1 REST API
• matplotlib - A comprehensive library for crating visualizations in Python.

This project is licensed under the MIT License - see the LICENSE.md file for details