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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 folder, you'll see an 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.