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Ploomber is the fastest way to build data pipelines ⚡️. Use your favorite editor (Jupyter, VSCode, PyCharm) to develop interactively and deploy ☁️ without code changes (Kubernetes, Airflow, AWS Batch, and SLURM). Do you have legacy notebooks? Refactor them into modular pipelines with a single command.
Compatible with Python 3.6 and higher.
Install with pip:
pip install ploomberOr with conda:
conda install ploomber -c conda-forgeOpen a hosted JupyterLab instance:
Run an example locally:
# ML pipeline example
ploomber examples -n templates/ml-basic -o ml-basic
cd ml-basic
# install dependencies
pip install -r requirements.txt
# run pipeline
ploomber buildYou just ran a Ploomber pipeline! 🎉
Check out the output/nb.html report with model results!
The pipeline.yaml contains the pipeline declaration. Feel free to modify any of the tasks, then call ploomber build again to update the results (Note: if using VSCode or PyCharm, execute ploomber nb -i before editing the files).
What's next?
Ready to migrate your project? Click here.
Do you want to learn more? Check out the introductory tutorial.
Run more examples.
A simple YAML API to get started quickly, a powerful Python API for total flexibility.
get-started.mp4
Automatically cache your pipeline’s previous results and only re-compute tasks that have changed since your last execution.
shorter-cycles.mp4
Run as a shell script in a single machine or distributively in Kubernetes, Airflow, AWS Batch, or SLURM.
deploy.mp4
Bring your old monolithic notebooks, and we’ll automatically convert them into maintainable, modular pipelines.