Section author: Axel Huebl

If you are new to python, get your hands on the tutorials of the following important libraries to get started.


Numpy is the universal swiss army knife for working on ND arrays in python.


Access, share, modify, run and interact with your python scripts from your browser:


An exploratory framework that visualizes and analyzes data in our HDF5 files thanks to their openPMD markup. Automatically converts units to SI, interprets iteration steps as time series, annotates axes and provides some domain specific analysis, e.g. for LWFA. Also provides an interactive GUI for fast exploration via Jupyter notebooks.


A data library that reads (and writes) data in our openPMD files (HDF5 and ADIOS) to and from Numpy data structures. Provides an API to correctly convert units to SI, interprets iteration steps correctly, etc.


With yt 3.4 or newer, our HDF5 output, which uses the openPMD markup, can be read, processed and visualized with yt.

pyDive (experimental)

pyDive provides numpy-style array and file processing on distributed memory systems (“numpy on MPI” for data sets that are much larger than your local RAM). pyDive is currently not ready to interpret openPMD directly, but can work on generated raw ADIOS and HDF5 files.