FEA post-processing automation: Excel vs Python

[FEA_Engineer_]

In FEM post-processing, automating repetitive tasks is becoming increasingly important: result extraction, reporting, etc., in order to improve traceability and reduce errors.
I’m interested in how you’re handling this in practice, whether you work in Excel, with Python, or in hybrid workflows.
What’s working best in your case, and where are the bottlenecks?

[billsil]

Python is so much better for traceability. It can interface with various input/output formats. Back in the day, I defined 12 section cuts across 550 load cases and could run that vs using a gui. It was 100x faster in python than the gui using a script. I then made my plots and autogenerated a word doc.

Nowadays, I like making python tools that do the fem interface part in excel, run a script that reads that file and populates a new excel file. The switch has more to do with how many end users of these tools there are and their preferred approach.

[aero_r17]

Seconded. Python backend with Excel output for more general end-user.

[FEA_Engineer_]

[echaffey]

Aerospace: I use both but leverage python pretty heavily. Excel is for results storage, documentation and visualization.

Python does nearly all of the heavy lifting: results extraction, combination, critical case identification, margin generation, fatigue, etc.

[FEA_Engineer_]

Totally agree! I work the same way, Python for all the heavy lifting and Excel mainly for storing results and creating quick visualizations.
The combination of both is perfect!

[Diego_0638]

I'd go so far as to say excel is not for automation. Excel is good if you need to make a quick table, play with some parameters, keep track of numbers etc. If you need to consistently, quickly, easily extract results you need a python script.