aiidalab/qe repository overview

⁠AiiDAlab Quantum ESPRESSO application

⁠About

This is a early-development implementation of an AiiDAlab application for Quantum ESPRESSO workflow. The app allows the execution of a workflow with Quantum ESPRESSO that includes the selection of an input structure, its relaxation, and the bands structure calculation.

The app is currently in an early development stage!

⁠For developers

The package uses pre-commit hooks to check the style consistency of all commits. To use those you need to first install the pre-commit package itself, e.g. with:

pip install .[dev]

and then install the pre-commit hooks with

pre-commit install

The pre-commit checks should now be automatically executed prior to each commit.

To run unit tests in the AiiDAlab container, you need to run pytest from within the aiida-core-services conda environment:

conda activate aiida-core-services
pytest -sv tests

To run the integration tests, you need to build the Docker image first:

cd docker/
docker buildx bake -f build.json -f docker-bake.hcl --set "*.platform=linux/amd64" --load

Then, you can run the integration tests with:

JUPYTER_TOKEN=max TAG=newly-baked pytest --driver Chrome tests_integration -sv

⁠For maintainers

To create a new release, clone the repository, install development dependencies with pip install '.[dev]', and then execute bumpver update. This will:

1. Create a tagged release with bumped version and push it to the repository.
2. Trigger a GitHub actions workflow that creates a GitHub release.

Additional notes:

• Use the --dry option to preview the release change.
• The release tag (e.g. a/b/rc) is determined from the last release. Use the --tag option to switch the release tag.

⁠Acknowledgements

This project has received funding from the European Union’s Horizon 2020 research and innovation programme⁠ under grant agreement No 957189⁠. The project is part of BATTERY 2030+, the large-scale European research initiative for inventing the sustainable batteries of the future. Also supported by the MARVEL National Centre for Competency in Research⁠ funded by the Swiss National Science Foundation⁠, the MARKETPLACE project funded by Horizon 2020⁠ under the H2020-NMBP-25-2017 call (Grant No. 760173), as well as by the MaX European Centre of Excellence⁠ funded by the Horizon 2020 EINFRA-5 program, Grant No. 676598.