Compressed graph

A compact and highly-efficient representation of the graph dataset, suited for scale-up analysis on high-end machines with large amounts of memory. The graph is compressed in Boldi-Vigna representation, designed to be loaded by the WebGraph framework, specifically using our swh-graph library.

Comments

This graph changed the MPH from GOV/Cmph to PTHash; Rust code hardcoding GOVMPH needs to replace it with DynMph or SwhidPthash. Java is no longer supported to read this graph.

Dataset size
11 TiB
Export date
Teaser dataset
Popular 500 python compressed graph (15 GB)
Popular 500 python provenance (all releases and revisions) (46 GB)
S3 URL
s3://softwareheritage/graph/2024-08-23/compressed/
Deprecated
False

Referencing Software Heritage

If you use any of the datasets indexed on this website for research purposes, please acknowledge Software Heritage as recommended in the publications page, that is:

  1. Add a footnote on the title page of your paper, formatted as: “This work was made possible by Software Heritage, the universal source code archive: https://www.softwareheritage.org”; and
  2. cite at least one of the following papers:

Specific datasets might recommend additional citations, to credit their creators.

Specific citation instructions

If you use this dataset for research purposes, please cite the following paper: Antoine Pietri, Diomidis Spinellis, Stefano Zacchiroli. The Software Heritage Graph Dataset: Public software development under one roof. In proceedings of MSR 2019: The 16th International Conference on Mining Software Repositories, May 2019, Montreal, Canada. Co-located with ICSE 2019 (Preprint), (BibTeX).

Download the dataset

For Amazon S3 links, you'll need to install either awscli or swh.datasets.

aws s3 cp --recursive --no-sign-request s3://softwareheritage/graph/2024-08-23/compressed/ 2024-08-23-compressed
# OR
swh datasets download-graph 2024-08-23

By accessing the datasets, you agree with the Software Heritage Ethical Charter for using the archive data, the terms of use for bulk access, and the Software Heritage principles for large language models.

To learn how to use the datasets read the documentation.