Since its official first release in 2016, the TM1py project evolved from a framework created and maintained by one person to a community project that is currently powering many TM1 applications.

This could not have been achieved without the growing and active TM1py community on Github.

With two major releases, 2020 has been a very busy year for TM1py with contributions coming from developers all around the world (@rkvinoth, @scrambldchannel, @rclapp, @ykud and @zPat to name a few):

The TM1py project is hosted on GitHub (github.com/cubewise-code/tm1py). If you have a question, just create a new issue there. The community is very active with members all around the world, it is very likely that you will get an answer within the hour.

Click the Watch button on the top right corner to not miss discussions from various topics such as TM1, TM1py, Python, MDX…. You will learn a lot by watching the TM1py project. Do not forget to give a Star to show your support to the project.

TM1py makes it easy for TM1 developers to go beyond the limits of TM1 such as:

• “Decreasing development time by handling some of the more tedious tasks automatically.” Matt Schlinz (Jabil)
• “We have been using it for process optimizations and parallel processing.” Vinoth Kumar(AWS)
• “Another great addition to TM1py is OptimusPy to find the optimal dimension order in terms of RAM usage and Query time.” Herman Teeuwen (Canon)