Skip to main content

Vantage6 client

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.7221216. 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-client-3.7.0rc2.tar.gz (31.6 kB view details)

Uploaded Source

Built Distribution

vantage6_client-3.7.0rc2-py3-none-any.whl (36.3 kB view details)

Uploaded Python 3

File details

Details for the file vantage6-client-3.7.0rc2.tar.gz.

File metadata

  • Download URL: vantage6-client-3.7.0rc2.tar.gz
  • Upload date:
  • Size: 31.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.7.15

File hashes

Hashes for vantage6-client-3.7.0rc2.tar.gz
Algorithm Hash digest
SHA256 c43f7a7e69f4998cbc25b1b75df3f5804f1300dd66c9f7c19493d9cd11ec8e9f
MD5 5d9ea94d6d37809a316913d0a42a116b
BLAKE2b-256 df6d8e89b3e1d2d8f6036167e749c560eb05cdaa01b8ec25387749dd8cfa2f17

See more details on using hashes here.

File details

Details for the file vantage6_client-3.7.0rc2-py3-none-any.whl.

File metadata

File hashes

Hashes for vantage6_client-3.7.0rc2-py3-none-any.whl
Algorithm Hash digest
SHA256 22111cae90a568584533c4c37e10df6e9b1609fb2a4504890e9337e09a936570
MD5 f6daf044df1ed56646cb9d9caa9d2170
BLAKE2b-256 1936298729c8d12c73491a41b3837e229a7f17194ae0ec98e02a91d655cbb54a

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