https://github.com/americanexpress/mlflow-server-proxy

Jupyter server proxy extension for mlflow tracking server
https://github.com/americanexpress/mlflow-server-proxy

jupyter-notebook mlflow server-proxy

Last synced: 5 days ago
JSON representation

Jupyter server proxy extension for mlflow tracking server

• Host: GitHub
• URL: https://github.com/americanexpress/mlflow-server-proxy
• Owner: americanexpress
• License: apache-2.0
• Created: 2020-10-09T23:35:48.000Z (about 4 years ago)
• Default Branch: main
• Last Pushed: 2021-05-21T19:12:39.000Z (over 3 years ago)
• Last Synced: 2024-11-07T03:19:04.674Z (9 days ago)
• Topics: jupyter-notebook, mlflow, server-proxy
• Language: Python
• Homepage:
• Size: 26.4 KB
• Stars: 4
• Watchers: 7
• Forks: 3
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.txt
  • Code of conduct: CODE_OF_CONDUCT.md
  • Security: SECURITY.md

Awesome Lists containing this project

README

        
# MLFlow Server Proxy 

MLFlow Server Proxy lets you run arbitrary external MLFlow tracking server alongside your notebook server and provide authenticated web access to them using a path `/mlflow` next to others like `/lab`. 

Alongside the python package that provides the main functionality, the JupyterLab extension [@jupyterlab/server-proxy](https://github.com/jupyterhub/jupyter-server-proxy) provides buttons in the JupyterLab launcher window to get to MLFlow tracking server.

This package was built using the [`jupyter-server-proxy` cookiecutter template](https://github.com/jupyterhub/jupyter-server-proxy/tree/master/contrib/template).

##  🤹‍Installation

### Python package

You can currently install this package from PyPI.

```bash

pip install mlflow-server-proxy

```

To install with all the resources then use 

```bash

pip install 'mlflow-server-proxy[resources]'

```

The above command will install MLFlow as well.

##  🤹‍Setup 

The environment variable `MLFLOW_STORE` has to be set as backend storage for MLFlow to log models and artifacts. Default is `/tmp`

This environment variable is then used in setting server uri while using MLFlow in your code as below:

```python

import mlflow

server_uri = os.environ["MLFLOW_STORE"]

mlflow.set_tracking_uri(server_uri)

```

## Requirements

#### Install MLFlow 

This package's executes the standard `mlflow server` command. This command assumes the `mlflow` executable required to start the application is globally available.

```bash

pip install mlflow

```

### Install Jupyter Notebook

This extension relies on the Jupyter Notebook to run. [Refer to Jupyter's official documentaion](https://jupyter.org/install) for installation instructions.

## Release History

* Version 0.1.0

    * Initial release - File based backend

### Maintainer

 - [Gottam Sai Bharath](https://github.com/Gsbreddy)

##  🏆Contributing

We welcome Your interest in the American Express Open Source Community on Github. Any Contributor to

any Open Source Project managed by the American Express Open Source Community must accept and sign

an Agreement indicating agreement to the terms below. Except for the rights granted in this 

Agreement to American Express and to recipients of software distributed by American Express, You

reserve all right, title, and interest, if any, in and to Your Contributions. Please

[fill out the Agreement](https://cla-assistant.io/americanexpress/mlflow-server-proxy).

##  🗝️License

Any contributions made under this project will be governed by the

[Apache License 2.0](./LICENSE.txt).

##  🗣️Code of Conduct

This project adheres to the [American Express Community Guidelines](./CODE_OF_CONDUCT.md). By participating, you are expected to honor these

guidelines.