Set of tools to process raw instrument data according to a dataschema into a standardised form called datagram, annotated with metadata, provenance information, timestamps, units, and uncertainties. Developed by the Materials for Energy Conversion lab at Empa (Dübendorf, CH) and by the ConCat lab at Technische Universität Berlin (Berlin, DE).

• Parsing tabulated data using CSV parsing functionality, including Bronkhorst and DryCal output formats.
• Parsing chromatography data from gas and liquid chromatography, including several Agilent, Masshunter, and Fusion formats.
• Parsing reflection coefficient traces from network analysers.
• Parsing potentiostat files for electrochemistry applications. Supports BioLogic file formats.
• Parsing spectroscopy files including common XPS, XRD and MS formats.

• timezone-aware timestamping using Unix timestamps
• automatic uncertainty determination using data contained in the raw files, instrument specification, or last significant digit
• uncertainty propagation to derived quantities
• tagging of data with units
• extensive dataschema and datagram validation using provided specifications
• mandatory metadata (such as provenance) is enforced

The full list of capabilities and features is listed in the project documentation.

The released versions of yadg are available on the Python Package Index (PyPI) under yadg. Those can be installed using:

    pip install yadg

If you wish to install the current development version as an editable installation, check out the master branch using git, and install yadg as an editable package using pip:

   git clone [email protected]:dgbowl/yadg.git
   cd yadg
   pip install -e .

Additional targets yadg[testing] and yadg[docs] are available and can be specified in the above commands, if testing and/or documentation capabilities are required.

• Peter Kraus
• Nicolas Vetsch

This project has received funding from the following sources:

• European Union’s Horizon 2020 programme under grant agreement No 957189.
• DFG's Emmy Noether Programme under grant number 490703766.

The project is also part of BATTERY 2030+, the large-scale European research initiative for inventing the sustainable batteries of the future.