Learning Python as a practising geotechnical engineer is hard. A task that takes ten minutes in Excel can take two hours to script. You debug more than you build, online documentation feels abstract, and nobody senior is pushing you to do it.
That frustration is normal. GeotechPython was built for exactly that phase. Every post here is written by a practising UK geotechnical engineer who decided to share the process openly, because the return on effort is real.
this is not about becoming a software developer.
it is about becoming a more efficient, defensible, and structured engineer.
Code that a reviewer can sign off on
Every workflow on this site is designed around three non-negotiables.
Transparent assumptions
Every variable has a name. Every partial factor is explicit. No hidden formula chains — just readable Python that traces directly back to the code clause.
Reviewable by non-coders
Scripts are structured so a senior engineer can follow the logic line by line, check against hand calculations, and sign off with confidence.
Built for real projects
Every post comes from genuine project experience. No toy examples — just the patterns that appear in foundation design, GI interpretation, and FEM automation.
Choose where to start
Four structured tracks, each focused on a real part of geotechnical practice. Follow one or mix as your work demands.
AGS Data & GI Interpretation
Read, validate, and summarise ground investigation data. Build traceable pipelines from raw AGS files to clean design model inputs.
Auditable Geotechnical Calculations
Settlement, bearing capacity, retaining walls — coded with explicit assumptions and structured logs a senior engineer can sign off.
PLAXIS Automation
Script your FEM models, automate input and output, and run batch parameter studies directly from Python with QA built in from day one.
AI & Low-Code Tools
How AI-powered apps are starting to transform how geotechnical teams build, share, and check tools — without writing a line of backend code.