LPP dev guide

Efficient scientific coding

You will find here material to help you get started with your coding. Depending on whether you mostly do data analysis or numerical modeling, you'll need slightly different tools and methods. the advice we give you will help to be efficient, rigorous and to write code than you'll be able to use, maintain and share in the long run. Now remember, If you're a PhD or a post-doc, following these advice will not only help you improving the quality and reproducibility of your science, but also will make all your coding efforts reusable for your future you and by people in the lab once you're gone. More importantly, it will give you the basic knowledge you need to legitimately claim for a data science / computing science position in the private sector.

Now, what are you doing?

Code review and analysis


Code Review for Teams Too Busy to Review Code (youtube video)
Nice tutorial on code review with Rhodecode


CPP Check



Modern C++


Instruction tables

Setting up a clean Python environment

C++ development


These are useful links to check out regularly

PRACE training:

Catalogue of courses:

Formation IDRIS:

Code Design and Architecture

Writing code


  • [[hyb-par: Documentationtools| Documentation Tools]]

Dev Dej games

1 - show me your snippet
2 - explique à ton voisin
3 - montre nous ton blog préféré
4 - pull me quizz
5 - sell me (some features of ) your editor
6 - critic my code
7 - show me a youtube video
8 - optimize my snippet
9 - translate my code
10 - Ze lib of Ze Week

Updated by Nicolas Aunai over 6 years ago · 19 revisions

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