Skip to main content

Vantage6 common

Project description


vantage6

A privacy preserving federated learning solution

Release PyPI vantage6 Unittests Coverage Status Codacy Badge DOI

DocumentationContributingReferences


This repository is part of vantage6, our privacy preserving federated learning infrastructure for secure insight exchange, and contains all the vantage6 infrastructure source/ code. Please visit our website (vantage6.ai) to learn more!

:books: Documentation

This repository is home to 4 PyPi packages:

Note that when using vantage6 you do not install the server and node packages. These are delivered to you in Docker images.

Two docker images are published which contain the Node and Server applications:

  • harbor2.vantage6.ai/infrastructure/node:VERSION
  • harbor2.vantage6.ai/infrastructure/server:VERSION

These docker images are used by the vantage6 CLI package, which can be installed by running:

pip install vantage6

This will install the CLI which enables you to use the commands:

  • vnode CMD [OPTIONS]
  • vserver CMD [OPTIONS]

You can find more (user) documentation at Gitbook (docs.vantage6.ai). If you have any questions, suggestions or just want to chat about federated learning: join our Dircord (https://discord.gg/yAyFf6Y) channel.

:gift_heart: Contributing

We hope to continue developing, improving, and supporting vantage6 with the help of the federated learning community. If you are interested in contributing, first of all, thank you! Second, please take a look at our contributing guidelines

:black_nib: References

If you are using vantage6, please cite this repository as well as the accompanying papers as follows:

  • F. Martin, M. Sieswerda, H. Alradhi, et al. vantage6. Available at https://doi.org/10.5281/zenodo.3686944. Accessed on MONTH, 20XX.
  • A. Moncada-Torres, F. Martin, M. Sieswerda, J. van Soest, G. Gelijnse. VANTAGE6: an open source priVAcy preserviNg federaTed leArninG infrastructurE for Secure Insight eXchange. AMIA Annual Symposium Proceedings, 2020, p. 870-877. [BibTeX, PDF]
  • D. Smits*, B. van Beusekom*, F. Martin, L. Veen, G. Geleijnse, A. Moncada-Torres, An Improved Infrastructure for Privacy-Preserving Analysis of Patient Data, Proceedings of the International Conference of Informatics, Management, and Technology in Healthcare (ICIMTH), vol. 25, 2022, p. 144-147. [BibTeX, PDF]

vantage6.aiDiscordDiscourseUser documentation

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

vantage6-common-3.5.0.tar.gz (18.6 kB view details)

Uploaded Source

Built Distribution

vantage6_common-3.5.0-py3-none-any.whl (20.0 kB view details)

Uploaded Python 3

File details

Details for the file vantage6-common-3.5.0.tar.gz.

File metadata

  • Download URL: vantage6-common-3.5.0.tar.gz
  • Upload date:
  • Size: 18.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.7.15

File hashes

Hashes for vantage6-common-3.5.0.tar.gz
Algorithm Hash digest
SHA256 c0bd2337e6cf98c61b7b29a8ce0b1bdf3c03aa9f2de5cf2e64b24275a6a0afb0
MD5 4b3a1d332b5ff5470deee67892bd499c
BLAKE2b-256 98f9eb84b985d6af92daf485a6f87a3beb88340dd33ec0bf139b4653d0e9540a

See more details on using hashes here.

File details

Details for the file vantage6_common-3.5.0-py3-none-any.whl.

File metadata

File hashes

Hashes for vantage6_common-3.5.0-py3-none-any.whl
Algorithm Hash digest
SHA256 da441f117095417b8f614c7d335db28e96ae55ed7efff2d25d333f052ed02065
MD5 53ef9f52d8c2836e5e024b3ee476e450
BLAKE2b-256 e17f961e52492b6586ab597c31f151834968fcac6e7ffda27e5603ad210edfbe

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page