Skip to main content

neptune.ai MLflow integration library

Project description

neptune-mlflow

Note

This integration is still being updated for the main Neptune client library. It is currently only available for the Neptune legacy API.


mlflow neptune.ai integration

Overview

neptune-mflow integrates MLflow with Neptune to let you get the best of both worlds. Enjoy tracking and reproducibility of MLflow with the organization and collaboration of Neptune.

With neptune-mlflow you can have your MLflow experiment runs hosted in a beautiful knowledge repo that lets you invite and manage project contributors.

All you need to do is go to your MLflow project and run:

neptune mlflow --project USER_NAME/PROJECT_NAME

and you have your experiments organized and easily shareable with the world.

Documentation

See neptune-mlflow docs for more info.

Get started

Register

Go to neptune.ai and sign up.

It is completely free for individuals and non-organizations, and you can invite others to join your team!

Get your API token

In the bottom-left corner, click your user menu and select Get your API token.

Set NEPTUNE_API_TOKEN environment variable

Go to your console and run:

export NEPTUNE_API_TOKEN='your_long_api_token'

Create your first project

Click All projectsNew project. Choose a name for it and whether you want it public or private.

Install lib

pip install neptune-mlflow

Sync your mlruns with Neptune

neptune mlflow --project USER_NAME/PROJECT_NAME

Explore and Share

You can now explore and organize your experiments in Neptune, and share it with anyone:

  • by sending a link to your project, experiment or chart if it is public
  • or invite people to your project if you want to keep it private!

Getting help

If you get stuck, don't worry. We are here to help.

The best order of communication is:

Contributing

If you see something that you don't like, you are more than welcome to contribute!

There are many options:

  • Submit a feature request or a bug here, on Github
  • Submit a pull request that deals with an open feature request or bug
  • Spread the word about Neptune in your community

Project details


Download files

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

Source Distribution

neptune_mlflow-1.0.0rc1.tar.gz (12.7 kB view details)

Uploaded Source

Built Distribution

neptune_mlflow-1.0.0rc1-py3-none-any.whl (18.8 kB view details)

Uploaded Python 3

File details

Details for the file neptune_mlflow-1.0.0rc1.tar.gz.

File metadata

  • Download URL: neptune_mlflow-1.0.0rc1.tar.gz
  • Upload date:
  • Size: 12.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.17

File hashes

Hashes for neptune_mlflow-1.0.0rc1.tar.gz
Algorithm Hash digest
SHA256 4b70e4008d1ba724ecd98a3433aac9b3a80761683dec3cf153affb5a873123fc
MD5 f22e29c7f6871597540be60dd1d8e600
BLAKE2b-256 c18ce6e37b1f0d8fa664425d1f3eac7473dad30ac5c5c32143cc6443b607ac89

See more details on using hashes here.

File details

Details for the file neptune_mlflow-1.0.0rc1-py3-none-any.whl.

File metadata

File hashes

Hashes for neptune_mlflow-1.0.0rc1-py3-none-any.whl
Algorithm Hash digest
SHA256 ba7a0e24903dcfa47c601b0f9ebb5033fdacfc133a9f22ddedc97836c07907a5
MD5 059ddaa1f693a091f9526e5a19e8a451
BLAKE2b-256 c0f4ea2e0159169f8b30cbfbee3fa6a64cfcbb72557dfb971146782b85620a69

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