FLPQ_Data is a Python package for the creation, manipulation, and study of the structure, dynamics, and functions of complex Graphs and Grammars used for experimental analysis of Formal Language constrained Path Querying algorithms.
- Website: https://formallanguageconstrainedpathquerying.github.io/FLPQ_Data
- Tutorial: https://formallanguageconstrainedpathquerying.github.io/FLPQ_Data/tutorial.html
- Documentation: https://formallanguageconstrainedpathquerying.github.io/FLPQ_Data/reference/index.html
- Source Code: https://github.com/formallanguageconstrainedpathquerying/FLPQ_Data
- Bug Tracker: https://github.com/formallanguageconstrainedpathquerying/FLPQ_Data/issues
- Changelog: https://github.com/FormalLanguageConstrainedPathQuerying/FLPQ_Data/blob/master/CHANGELOG.md
Install from PyPI with pip:
pip install flpq-data
Requires Python 3.11–3.13; see the Install page for details.
FLPQ_Data bundles 113 labeled directed graphs across eight families — C alias analysis, RDF/OWL datasets, Java points-to, field-sensitive aliasing, context-sensitive data-flow, data provenance, name resolution (stack graphs), and biological graphs from UniProt — together with the context-free grammars used to query them. Each graph ships as a per-label MatrixMarket archive; see the Graphs page for statistics and download links.
>>> import flpq_data
>>> flpq_data.GRAPHS[:3]
['skos', 'wc', 'generations']The full list of graphs, with statistics and download links, is on the Graphs page.
>>> bzip_path = flpq_data.download_graph("bzip")
>>> bzip = flpq_data.graph_from_mtx_dir(bzip_path / "graph")To work on FLPQ_Data itself, set up the development environment (uv):
uv sync --all-groups
and run the main local checks that CI enforces — tests, quality checks, and the docs build:
uv run pytest uv run pre-commit run --all-files uv run make -C docs html
The full developer guide — development setup, quality checks, the test pipeline, docs build and deployment, the package release process, and contribution guidelines — is on the Developer page.
Create an Issue corresponding to the "CONTRIBUTE NEW DATA" issue template — one or more validated archives (one graph each), links to them, and the motivation. The maintainers upload and merge the data into the dataset; the full contribution guide is on the Contributing data page.
If you use FLPQ_Data in your work, please cite it — see the Citation section on the About page for BibTeX entries.
The code (package source, documentation, and tooling) is licensed under Apache-2.0 (LICENSE.txt). The dataset (graphs, grammars, and benchmarks) is licensed under CC-BY 4.0 (LICENSE-DATA.txt).