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, incorporating theoretical lectures and practical exercises tailored to the needs of a programming scientist. New skills will be tested in a real programming project: we will team up to develop an entertaining scientific 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, C/C++, MATLAB, or Mathematica is absolutely required. Basic knowledge of Python is assumed. Participants without any prior experience with Python should work through the proposed introductory materials before the course.

Download the original announcement: pdf

Date & Location

September 8—13, 2014. Split, Croatia

Information about the venue, the city of Split, travel, and accommodation

Applications

~~You can apply on-line.~~ Here is a preview of the application form.

~~Applications must be submitted before 23:59 UTC, May 1, 2014. The application process is closed: We received 168 applications! Notifications of acceptance will be sent by June 1, 2014.~~ Participants have been selected. If you missed the deadline, write to python-info@g-node.org to be put on the announcement list for next year.

No fee is charged but participants should take care of travel, living, and accommodation expenses.

Candidates will be selected on the basis of their profile. Places are limited: acceptance rate is usually around 20%.

Prerequisites

You are supposed to know the basics of Python to participate in the lectures!

You are encouraged to go through the introductory material.

Students

Confirmed participants.

Preliminary Program

Day-by-day schedule with links to lecture and exercise materials

Day0 (Mon Sep 8): Best Programming Practices

Best Practices for Scientific Computing
Version control with git and how to contribute to Open Source with github
Object-oriented programming & design patterns

Day1 (Tue Sep 9): Software Carpentry

Test-driven development, unit testing & quality assurance
Debugging, profiling and benchmarking techniques
Advanced Python I: idioms, useful built-in data structures, generators

Day2 (Wed Sep 10): Scientific Tools for Python

Advanced NumPy
The Quest for Speed (intro): Interfacing to C with Cython
Programming in teams

Day3 (Thu Sep 11): The Quest for Speed

Writing parallel applications in Python
Python 3: why should I care
Programming project

Day4 (Fri Sep 12): Efficient Memory Management

When parallelization does not help: the starving CPUs problem
Advanced Python II: decorators and context managers
Programming project

Day5 (Sat Sep 13): Practical Software Development

Programming project
The Pelita Tournament

Lectures start at 8:30 sharp and finish around 18:30. During the day we will have short breaks (coffee & tea provided), and a long lunch break. The last half hour every evening is dedicated to tutors' consultation: Tutors will answer your questions and give suggestions for your own projects.

On Saturday, September 13, we are going to have a little closing party that you should not miss: book your return travel not before Sunday, September 14

Faculty

Francesc Alted, freelance developer, author of PyTables
Pietro Berkes, Enthought Inc.
Kathryn D. Huff, Department of Nuclear Engineering, University of California - Berkeley
Zbigniew Jędrzejewski-Szmek, Krasnow Institute, George Mason University
Eilif Muller, Blue Brain Project, École Polytechnique Fédérale de Lausanne
Rike-Benjamin Schuppner, Technologit GbR
Nelle Varoquaux, Centre for Computational Biology Mines ParisTech, Institut Curie, U900 INSERM, Paris
Stéfan van der Walt, Applied Mathematics, Stellenbosch University
Niko Wilbert, TNG Technology Consulting GmbH
Tiziano Zito, Institute for Theoretical Biology, Humboldt-Universität zu Berlin