Introducing the TM1py Universe

TM1py can greatly extend your TM1 applications by making it easier to connect to your cloud system of choice, build AI-infused planning solutions, and automate those tedious tasks that you complete on a regular basis.  TM1py can also be used to build utilities of various kinds that make sense for your organization.

In this article, we will present some of the most popular ones, and excitingly, every single one of them is completely free.

Are you ready to boost your TM1 applications? 

Let’s dive in.

RushTI is a Python script that enables the execution of TM1 processes in parallel using only one connection.  Instead of loading just one year of data within one process, you can run in parallel one process per month which will significantly speed up your loading time and lead to much better results.

But you can take things further.  If you want to run 1,000 different processes in parallel, that’s where RushTI really shines because it helps you manage all the threads, ensuring that your server still has enough memory to execute your users’ tasks.  For more detail, you can check out our guide to getting started with RushTI here.

1. It includes an optimized mode that specifies dependencies between processes.  For example, process B should only be executed once process A is finished.  This flexibility allows to you build complex logic into your processes that make the world of difference when you’re dealing with lots of different workflows.
2. You can group processes according to certain characteristics to make sure that all processes from group A are finished before executing processes from group B.
3. In the same list, you can execute processes into different TM1 instances, giving you full control over how things are processed.
4. A retry flag is available, meaning that if a process fails, you can ask RushTI to retry twice.

CubeCalc enables you to execute complex finance calculations which are not available natively in TM1 such as the most commonly used IRR (Internal Rate of Return) and NPV (Net Present Value).

Cubecalc currently includes the 15 most popular financial functions out of Microsoft Excel, meaning that there is no need to specifically code the functions in TM1 anymore.  These functions can be executed against your data with one simple command line.  You can read more about that here.

A new addition to the tool is a batch mode that allows you to execute multiple calculations with just one execution.  For example, CubeCalc can run the calculation for every element in any one subset.

MDXpy enables Python developers to create MDX queries programmatically without hacking raw MDX queries.  The benefits are vast and include:

• It’s faster to write MDX queries.
• It requires less MDX knowledge.
• Detailed error handling functionality.
• Eliminates syntax errors and those pesky brackets within queries.
• It makes code more robust and easier to refactor.
• It handles common pitfalls in MDX with aplomb.  (eg. escape ‘]’ in names and make ‘instr’ method case insensitive)

All of this combines into a really useful tool and if you want to explore it in more detail, check this out.

OptimusPy is a Python script that leverages TM1py to find the ideal dimension order for your cubes.  The tool will swap dimension orders until it finds the order with the best query speed and the smallest memory footprint.  This is ideal for traceability and custom analysis because it then visualizes the results in a CSV file and a scatter plot per cube, like the one you see below.  You can read more about it here.

The TM1py community is constantly growing and we can see more and more people contributing to TM1py and all the other utilities.  It’s a vibrant and exciting ecosystem that continues to push the boundaries on what is possible, delivering better results for a wide range of use cases.  You can see some of the testimonials here.

Check out the TM1py website to see how you push the limits of TM1 and unlock the next level of your planning and analytics journey.

• Dynamic TM1 queries with MDXpy
• Making sense of past events with Pulse
• Building Active Forms with hierarchies