https://github.com/cloudera/cml_amp_streamlit_on_cml

Demonstration of how to use Streamlit as a CML Application.
https://github.com/cloudera/cml_amp_streamlit_on_cml

applications data-visualization streamlit

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Demonstration of how to use Streamlit as a CML Application.

• Host: GitHub
• URL: https://github.com/cloudera/cml_amp_streamlit_on_cml
• Owner: cloudera
• License: apache-2.0
• Created: 2021-04-14T16:08:45.000Z (over 3 years ago)
• Default Branch: master
• Last Pushed: 2023-07-13T09:58:32.000Z (over 1 year ago)
• Last Synced: 2024-03-15T18:13:48.879Z (8 months ago)
• Topics: applications, data-visualization, streamlit
• Language: Python
• Homepage:
• Size: 434 KB
• Stars: 3
• Watchers: 8
• Forks: 7
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Streamlit as a CML Application

![The Streamlit logo](docs/images/streamlit-logo.png)

A minimal example of a [Streamlit](https://www.streamlit.io/) application running as a CML or CDSW Application.

We display and chart a small dataset with Seaborn.

## Repository Structure

```bash

.

├── cml                     # This folder contains scripts that facilitate the project launch on CML.

├── docs/images             # Storage for the images in this README.

├── .project-metadata.yaml  # Declarative specification of this project

├── app.py                  # The Streamlit app script.

├── LICENSE                 # This code has an Apache 2.0 License

├── README.md               # This file!

└── requirements.txt        # Python 3 package requirements.

```

## Launching the project on CML

There are three ways to launch this project on CML:

1. **From Prototype Catalog** - Navigate to the Prototype Catalog on a CML workspace, select the "Streamlit" tile, click "Launch as Project", click "Configure Project"

2. **As ML Prototype** - In a CML workspace, click "New Project", add a Project Name, select "ML Prototype" as the Initial Setup option, copy in the repo URL, click "Create Project", click "Configure Project"

3. **Manual Setup** - In a CML workspace, click "New Project", add a Project Name, select "Git" as the Initial Setup option, copy in the repo URL, click "Create Project". Launch a Python 3 Workbench Session and run `!pip3 install -r requirements.txt` to install requirements. Then create a CML Application as described in the [CML documentation](https://docs.cloudera.com/machine-learning/1.1/applications/topics/ml-applications.html), using `cml/launch_app.py` as the script.

## Using the app

Once the CML Application has been created (by any means), you can launch it from the Applications pane.

This should open a browser window, with a Streamlit application running at a URL

similar to `streamlit.cdsw-or-cml.your-organisation.com`.

If everything worked, you should see an application like this:

![An image of the Streamlit application](docs/images/streamlit-amp-screenshot.png)

To develop the Streamlit app, open a Python 3 workbench session and modify `app.py`.