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Python for lunch!

PFL is a space where researchers and students at IMAU exchange ideas and expertise on Python & discuss best practices in open science.

Every two weeks we host seminar-style meetings at IMAU (room 607) where anybody can present a particular Python package or workflow. Following the presentation there is room for general discussion, and we encourage users to help each other out with specific problems. Everybody can be a teacher!

Agenda

# date topic speaker(s)
10 2019.05.01 Defensive programming Erik
9 2019.04.17 General discussion -
8 2019.04.03 Matplotlib + cartopy Anne, Leo
7 2019.03.27 Matplotlib basics Mikael, Leo
6 2019.03.06 Advanced OO programming Tjebbe, Philippe
5 2019.02.20 Object oriented programming Tjebbe, Philippe
4 2019.02.06 Xarray Leo, André
3 2019.01.23 Example workflows using Jupyter Anneke, Leo
2 2018.12.12 Jupyter notebooks André
1 2018.12.28 virtual environments Daniele
0 2018.11.14 introduction PFL team

Overview of possible topics

Category Package or topic
NetCDF Xarray, Iris, HDF5, netCDF4 (Aarnout)
Regridding xesmf
Data analysis pandas, aospy, xgcm, salem, ESMValTool
Plotting Matplotlib, Cartopy, basemap (André)
Science SciPy, machine learning (Mikael)
Computing Fast code / vectorization, cython / Fortran (Leo), Numba, dask, parallel computing
Programming readability / PEP / best practices, defensive programming and testing (Erik), OO programming (Tjebbe)
Workflow Jupyter Lab, git, virtual environments
Education nbgrader, Sympy

Background

Many IMAU folks currently use Python for parts of their workflow or have expressed interest in doing so. Yet the suite of packages available for geophysical science is quite extensive and therefore it can be hard to pick the right one. On top of that, learning a new language or developing a new workflow from scratch can be quite time-consuming. It makes you wonder, if only there was a fun and efficient way of mastering new Python skills… Enter Python for Lunch!.

Python for lunch! is an informal seminar series held every two weeks centered around Python. Each session has a focus which can be a package, a workflow, an aspect of programming... you name it. Next to that we intend to make room for a users-helping-users kind of thing, both online and offline, so we can maximally benefit from each others knowledge. The overall goal being to spend less time on re-inventing the wheel and more on doing cool science!

External links

Open science communities

  • Pangeo is a community promoting open, reproducible, and scalable science.
  • NumFocus is a nonprofit dedicated to supporting the open source scientific computing community.
  • EDU-SIG, Python in Education

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  • Jupyter Notebook 98.9%
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