Metadata-Version: 2.1
Name: mage-ai
Version: 0.3.4
Summary: Mage is a tool for building and deploying data pipelines.
Home-page: https://github.com/mage-ai/mage-ai
Author: Mage
Author-email: eng@mage.ai
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Provides-Extra: bigquery
Provides-Extra: hdf5
Provides-Extra: postgres
Provides-Extra: redshift
Provides-Extra: s3
Provides-Extra: spark
Provides-Extra: snowflake
Provides-Extra: all
License-File: LICENSE

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# Intro

<img alt="Fire mage" height="160" src="media/mage-fire-charging-up.svg" />

Mage is an open-source tool for <b>building</b> and <b>deploying</b> data pipelines.

<br />

<b>Here is a sample data pipeline defined across 3 files:</b>

```python
# data_loaders/load_data_from_file.py
import pandas as pd


@data_loader
def load_data():
    return pd.read_csv('default_repo/titanic.csv')
```

```python
# transformers/select_columns.py
@transformer
def transform_df(df, *args):
    return df[['Age', 'Fare', 'Survived']]
```

```python
# data_exporters/export_to_file.py
@data_exporter
def export_data(df) -> None:
    df.to_csv('default_repo/titanic_transformed.csv')
```

<br />

<b>What the data pipeline looks like in the UI:</b>

<img
  alt="data pipeline overview"
  src="media/data-pipeline-overview.jpg"
/>

New? We recommend reading about [blocks](docs/blocks/README.md) and
learning from a [hands-on tutorial](docs/tutorials/quick_start/etl_restaurant/README.md).

<br />

[![Join us on Slack](https://img.shields.io/badge/%20-Join%20us%20on%20Slack-black?style=for-the-badge&logo=slack&labelColor=6B50D7)](https://www.mage.ai/chat)

## Table of contents

1. [Quick start](#%EF%B8%8F-quick-start)
1. [Demo](#-demo)
1. [Tutorials](#-tutorials)
1. [Features](#-features)
1. [Documentation](#-documentation)
1. [Contributing](#%EF%B8%8F-contributing)
1. [Community](#-community)

# 🏃‍♀️ Quick start

Install Mage using Docker or `pip`:

### Using Docker

Create a new project and launch tool (change `demo_project` to any other name if you want):

```bash
docker run -it -p 6789:6789 -v $(pwd):/home/src \
  mageai/mageai mage start demo_project
```

Open [http://localhost:6789](http://localhost:6789) in your browser and build a pipeline.

<sub>Follow the [guide](docs/kernels/README.md#pyspark-kernel-) if you want to use PySpark kernel in your notebook.</sub>

### Using pip

##### 1. Install Mage
```bash
pip install mage-ai
```

<sub>For additional packages (e.g. `spark`, `postgres`, etc), please see [Installing extra packages](docs/README.md#installing-extra-packages).</sub>

<sub>If you run into errors, please see [Install errors](docs/README.md#install-errors).</sub>

##### 2. Create new project and launch tool (change `demo_project` to any other name if you want):

```bash
mage start demo_project
```

Open [http://localhost:6789](http://localhost:6789) in your browser and build a pipeline.

<br />

# 🎮 Demo

## Live demo

Try a hosted version of the tool here: [http://demo.mage.ai](http://demo.mage.ai/).

> WARNING
>
> The live demo is public, please don’t save anything sensitive.

## Demo video (2 min)

[![Mage quick start demo](media/mage-youtube-preview.jpg)](https://www.youtube.com/watch?v=hrsErfPDits "Mage quick start demo")

<sub><i>Click the image to play video</i></sub>

<br />

# 👩‍🏫 Tutorials

- [Train model on Titanic dataset](docs/tutorials/quick_start/train_titanic_model/README.md)
- [Load data from API, transform it, and export it to PostgreSQL](docs/tutorials/quick_start/etl_restaurant/README.md)
- [Integrate Mage into an existing Airflow project](docs/tutorials/airflow/integrate_into_existing_project/README.md)

<br />

# 🔮 Features

- [Overview](docs/features/README.md)
- [Roadmap](https://airtable.com/shrJS0cDOmQywb8vp)
- [Changelog](https://mageai.notion.site/What-s-new-7cc355e38e9c42839d23fdbef2dabd2c)

<img
  alt="Mage"
  src="media/tool-overview.png"
/>

<br />

# 📚 Documentation

Read more docs [here](docs/README.md).

<br />

# 🙋‍♀️ Contributing
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](/docs/contributing/README.md) to get started
by setting up your development environment and
exploring the code base.

Got questions? Live chat with us in
[<img alt="Slack" height="20" src="https://thepostsportsbar.com/wp-content/uploads/2017/02/Slack-Logo.png" style="position: relative; top: 4px;" /> Slack](https://www.mage.ai/chat)

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

<br />

# 🧙 Community
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 [<img alt="Slack" height="20" src="https://thepostsportsbar.com/wp-content/uploads/2017/02/Slack-Logo.png" style="position: relative; top: 4px;" /> Slack](https://www.mage.ai/chat)
channel.

[![Join us on Slack](https://img.shields.io/badge/%20-Join%20us%20on%20Slack-black?style=for-the-badge&logo=slack&labelColor=6B50D7)](https://www.mage.ai/chat)

For real-time news and fun memes, check out the Mage
[<img alt="Twitter" height="20" src="https://upload.wikimedia.org/wikipedia/commons/thumb/4/4f/Twitter-logo.svg/2491px-Twitter-logo.svg.png" style="position: relative; top: 4px;" /> Twitter](https://twitter.com/mage_ai).

To report bugs or add your awesome code for others to enjoy,
visit [GitHub](https://github.com/mage-ai/mage-ai).

<br />

# 🪪 License
See the [LICENSE](LICENSE) file for licensing information.

[<img alt="Water mage casting spell" height="300" src="media/mage-water-charging-up.svg" />](https://www.mage.ai/)
