A data-centric workflow orchestration framework.
- kiara user documentation: https://dharpa.org/kiara.documentation
- Code: https://github.com/DHARPA-Project/kiara
- Development documentation for this repo: https://dharpa.org/kiara
Kiara is the data orchestration engine developed by the DHARPA project. It uses a modular approach to let users re-use tried and tested data orchestration pipelines, as well as create new ones from existing building blocks. It also helps you manage your research data, and augment it with automatically-, semi-automatically-, and manually- created metadata. Most of this is not yet implemented.
- Python (version >=3.6 -- some make targets only work for Python >=3.7, but kiara itself should work on 3.6)
- pip, virtualenv
- git
- make
- direnv (optional)
git clone https://github.com/DHARPA-Project/kiara.git
cd kiara
python3 -m venv .venv
source .venv/bin/activate
make initIf you use direnv, you can alternatively do:
git clone https://github.com/DHARPA-Project/kiara.git
cd kiara
cp .envrc.disabled .envrc
direnv allow
make initNote: you might want to adjust the Python version in .envrc (should not be necessary in most cases though)
init: init development project (install project & dev dependencies into virtualenv, as well as pre-commit git hook)update-modules: update default kiara modules package from gitflake: run flake8 testsmypy: run mypy teststest: run unit testsdocs: create static documentation pages (underbuild/site)serve-docs: serve documentation pages (incl. auto-reload) for getting direct feedback when working on documentationclean: clean build directories
For details (and other, minor targets), check the Makefile.
> make test
# or
> make coverageThis project is MPL v2.0 licensed, for the license text please check the LICENSE file in this repository.
- Copyright (c) 2021, 2022 DHARPA project
- Copyright (c) 2021, 2022 Markus Binsteiner