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No-code data pipelines

Project description

DataRush

No-Code Data Pipelines

Installation

pip install datarush

Settings

Before running the application, ensure the following environment variables are configured. The use of a .env file is supported.

Name Description Default Value
TEMPLATE_STORE_TYPE Specifies the template store type: S3 or FILESYSTEM.
TEMPLATE_STORE_S3_BUCKET The S3 bucket to store templates when using the S3 store type.
TEMPLATE_STORE_S3_PREFIX The S3 prefix for templates when using the S3 store type. datarush
TEMPLATE_STORE_FILESYSTEM_PATH The filesystem path for templates when using the filesystem store. .
S3_ENDPOINT The endpoint URL for the S3 service.
S3_ACCESS_KEY The access key for the S3 service.
S3_SECRET_KEY The secret key for the S3 service.
S3_DEFAULT_BUCKET The default bucket suggested in the operations UI.

Running UI

To launch the DataRush user interface, follow these steps:

  1. Create a run_ui.py file to serve as the entry point for the Streamlit application:

    from datarush import run_ui
    
    if __name__ == "__main__":
        run_ui()
    
  2. Start the application using the Streamlit command:

    streamlit run run_ui.py
    

Running Templates

To execute a DataRush template, use the following commands:

  • For a template named foo with version 0.0.1:

    python -m datarush --template "foo" --version "0.0.1"
    
  • To pass additional input arguments supported by the template:

    python -m datarush --template "foo" --version "0.0.1" --other_argument "value"
    

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