If you want to clone this repository to start your own project, you can choose the license you prefer and feel free to delete anything related to the license you are dropping.
As a one time setup, when starting a fresh project, dependencies need to be installed. This can be done with
The pipeline is then built with
npm run build
Running your pipeline in Python is as easy as running the build script file directly.
# You can run the script file directly. node dist/src/main.js # To run passing command line arguments. node dist/src/main.js --input_text="🎉" # To run the tests. npm test
This project already comes with automated testing via GitHub Actions.
To configure it, look at the
To run this pipeline on another runner, simply set the
--runner flag (along with any other parameters it requires). For example, to run on Flink you can execute the pipeline as
node dist/src/main.js --runner=flink [--flinkMaster=...]
or to run it on dataflow execute the pipeline as
node dist/src/main.js \ --runner=dataflow \ --project=[GCP_PROJECT] \ --tempLocation='gs://bucket/temp' \ --region=us-central1
Note that the first time this is run it may take a while to download the required jars/environment, but this will be cached for later use.
Thank you for your interest in contributing! All contributions are welcome! 🎉🎊
Please refer to the
CONTRIBUTING.md file for more information.
This software is distributed under the terms of both the MIT license and the Apache License (Version 2.0).
See LICENSE for details.