Mage is an open-source notebook for building and deploying data pipelines.

Table of contents

1. Quick start
2. Tutorials
3. Features
4. Contributing
5. Community

You can install Mage using Docker or pip:

git clone https://github.com/mage-ai/mage-ai.git && cd mage-ai

./scripts/init.sh [project_name]

./scripts/start.sh [project_name]

Open http://localhost:6789 in your browser and build a pipeline.

./scripts/run.sh [project_name] [pipeline]

pip install mage-ai

You may need to install development libraries for MIT Kerberos to use some Mage features. On Ubuntu, this can be installed as:

apt install libkrb5-dev

mage init [project_name]

mage start [project_name]

Open http://localhost:6789 in your browser and build a pipeline.

mage run [project_name] [pipeline]

• Train model on Titanic dataset
• Load data from API, transform it, and export it to PostgreSQL
• Integrate Mage into an existing Airflow project
• [Coming soon] How to visualize your data with charts

1. Data centric editor
2. Production ready code
3. Extensible

An interactive coding experience designed for preparing data to train ML models.

Visualize the impact of your code every time you load, clean, and transform data.

No more writing throw away code or trying to turn notebooks into scripts.

Each block (aka cell) in this editor is a modular file that can be tested, reused, and chained together to create an executable data pipeline locally or in any environment.

Read more about blocks and how they work.

Run your data pipeline end-to-end using the command line function: $ mage run [project] [pipeline]

You can run your pipeline in production environments with the orchestration tools

• Airflow
• Prefect
• Dagster (Tutorial coming soon)

Easily add new functionality directly in the source code or through plug-ins (coming soon).

Adding new API endpoints (Tornado), transformations (Python, PySpark, SQL), and charts (using React) is easy to do (tutorial coming soon).

Check out what’s new here.

We welcome all contributions to Mage; from small UI enhancements to brand new cleaning actions. We love seeing community members level up and give people power-ups!

Check out the 🎁 contributing guide to get started by setting up your development environment and exploring the code base.

Got questions? Live chat with us in Slack

Anything you contribute, the Mage team and community will maintain. We’re in it together!

We love the community of Magers (/ˈmājər/); a group of mages who help each other realize their full potential!

To live chat with the Mage team and community, please join the free Mage Slack channel.

For real-time news and fun memes, check out the Mage Twitter.

To report bugs or add your awesome code for others to enjoy, visit GitHub.

See the LICENSE file for licensing information.