Scientists from all disciplines are nowadays confronted with the necessity of diving into the world of scientific programming, whether to interpret basic data or make more advanced computation. However, developed code is often found to be sloppy and even buggy, leading to irreproducible research as well as making it difficult to collaborate and share resources.
Therefore, this workshop organized by the Paris-Saclay Center for Data Science aims at presenting, on the one hand, the PyData ecosystem widely used in scientific programming and, on the other hand, the software engineering best practises to achieve efficient and reusable code.
Loïc Esteve, Alexandre Boucaud, Alexandre Gramfort, Balazs Kegl, Guillaume Lemaitre, Bartosz Telenczuk, Joris Van den Bossche, Gaël Varoquaux.
Day 1 – Scientific programming with Python
Goal: introducing the most important packages for scientific computing and data analysis in Python. The main topics presented will be:
- Introduction to the basics of numpy, pandas, and matplotlib;
- Introduction to scientific computing toolbox: scipy, statsmodels, and scikit-learn.
Day 2 – Software engineering best practices for scientists
Goal: moving from standalone scripts to efficient and reusable code with tutorial on writing modular, documented, tested, and shareable code.
- Migrating from scripts to modular code;
- Best practices through PEP8 and well documented code;
- Test and continuous integration in a nutshell
Contact Email: firstname.lastname@example.org