Scientists spend more and more time writing, maintaining, and debugging software. While techniques for doing this efficiently have evolved, only few scientists have been trained to use them. As a result, instead of doing their research, they spend far too much time writing deficient code and reinventing the wheel. In this course we will present a selection of advanced programming techniques and best practices which are standard in the industry, but especially tailored to the needs of a programming scientist. Lectures are devised to be interactive and to give the students enough time to acquire direct hands-on experience with the materials. Students will work in pairs throughout the school and will team up to practice the newly learned skills in a real programming project — an entertaining computer game.

We use the Python programming language for the entire course. Python works as a simple programming language for beginners, but more importantly, it also works great in scientific simulations and data analysis. We show how clean language design, ease of extensibility, and the great wealth of open source libraries for scientific computing and data visualization are driving Python to become a standard tool for the programming scientist.

This school is targeted at Master or PhD students and Post-docs from all areas of science. Competence in Python or in another language such as Java, JavaScript, C/C++, MATLAB, or R is absolutely required. Basic knowledge of Python and git or another version control system is assumed. Participants without any prior experience with Python or git should work through the proposed introductory material before the course.

We are striving hard to get a pool of students which is international and gender-balanced: see how far we got in previous years!

students faculty organizers archives

Date & Location

5–11 September, 2022. Bilbao, Spain Spain

Application process

The deadline for application has expired. If you missed it, write to to be put on the announcement list for ASPP2023.

Participation is for free, i.e. no fee is charged! Participants however should take care of travel, living, and accommodation expenses by themselves. We are in the process of securing some funds for supporting students with accommodation and living costs.


  • Version control with git and how to contribute to open source projects with GitHub
  • Best practices in data visualization
  • Testing and debugging scientific code
  • Advanced NumPy
  • Organizing, documenting, and distributing scientific code
  • Advanced scientific Python: context managers and generators
  • Writing parallel applications in Python
  • Profiling and speeding up scientific code with Cython and numba
  • Programming in teams

schedule venue & travel


We are able to hold this year's ASPP school thanks to the help by Nicolas Rougier at Inria Bordeaux Sud-Ouest, Institute of Neurodegenerative Diseases, University of Bordeaux France, and with the generous financial and organizational support of several sponsors: