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This year we will develop and release aimmspy, a Python library that will allow you to combine the power and convenience of Python with the well-known strengths of AIMMS. 

We already spent quite a lot of time designing the functionality of this library, but we are keen to hear your thoughts and ideas. And we are purposely not sharing our ideas to prevent directing your thinking 😎.

Can you please share your thoughts on what you would like to see in such a library, as reply to this post? And if you prefer to share your ideas in a live conversation, please email me at j.w.van.crevel@aimms.com. I will then reach out to make an appointment.

Looking forward to hearing your thoughts, needs, etcetera!

This is great - I’m really looking forward to this. To answer your question, it would be great to be able to access directly the AIMMS data tables (for both parameters and variables) as data frames in Pandas.

Thank you!

What I could see myself using this for would be:

  • Use python as a “conductor”:
    • Load/transform data, apply a (non-optimization) model to the data, then output my dataframes directly into AIMMS parameters
    • Execute the optimization model
    • Read AIMMS results back into dataframes for analysis
  • Alter sets programmatically (e.g., if I have a subset of AllConstraints, add or remove values)
  • Scenario analysis: flag a parameter, set a value range, then loop through executions and write results to a dataframe

Thanks John! Really nice ideas.

Another suggestion: it would be nice if in aimmspy, we can use the AIMMS modelling language directly in the Python IDE to define our model, so for us who prefer to use Python we don’t have to switch between different environments and can do everything in Python.

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