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Mage is a hybrid framework for transforming and integrating data. It combines the best of both worlds: the flexibility of notebooks with the rigor of modular code.
Plus hundreds of enterprise-class features, infrastructure innovations, and magical surprises.
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For documentation on getting started, how to develop, and how to deploy to production check out the live
Developer documentation portal.
The recommended way to install the latest version of Mage is through Docker with the following command:
docker pull mageai/mageai:latest
You can also install Mage using pip or conda, though this may cause dependency issues without the proper environment.
pip install mage-ai
conda install -c conda-forge mage-ai
Looking for help? The fastest way to get started is by checking out our documentation here.
Looking for quick examples? Open a demo project right in your browser or check out our guides.
Build and run a data pipeline with our demo app.
WARNING
The live demo is public to everyone, please donโt save anything sensitive (e.g. passwords, secrets, etc).
Click the image to play video
๐ถ | Orchestration | Schedule and manage data pipelines with observability. |
๐ | Notebook | Interactive Python, SQL, & R editor for coding data pipelines. |
๐๏ธ | Data integrations | Synchronize data from 3rd party sources to your internal destinations. |
๐ฐ | Streaming pipelines | Ingest and transform real-time data. |
โ | dbt | Build, run, and manage your dbt models with Mage. |
A sample data pipeline defined across 3 files โ
@data_loader
def load_csv_from_file() -> pl.DataFrame:
return pl.read_csv('default_repo/titanic.csv')
@transformer
def select_columns_from_df(df: pl.DataFrame, *args) -> pl.DataFrame:
return df[['Age', 'Fare', 'Survived']]
@data_exporter
def export_titanic_data_to_disk(df: pl.DataFrame) -> None:
df.to_csv('default_repo/titanic_transformed.csv')
FAQs
Mage is a tool for building and deploying data pipelines.
We found that mage-ai demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago.ย It has 2 open source maintainers collaborating on the project.
Did you know?
Socket for GitHub automatically highlights issues in each pull request and monitors the health of all your open source dependencies. Discover the contents of your packages and block harmful activity before you install or update your dependencies.
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