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:
-
Create a
run_ui.pyfile to serve as the entry point for the Streamlit application:from datarush.ui import run_ui if __name__ == "__main__": run_ui()
-
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
foowith version0.0.1: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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