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Write maintainable, production-ready pipelines using Jupyter or your favorite text editor. Develop locally, deploy to the cloud.

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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.

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Get Started


Compatible with Python 3.6 and higher.

Install with pip:

pip install ploomber

Or with conda:

conda install ploomber -c conda-forge

Getting started

Open 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 build

You 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.


Main Features

⚡️ Get started quickly

A simple YAML API to get started quickly, a powerful Python API for total flexibility.

⏱ Shorter development cycles

Automatically cache your pipeline’s previous results and only re-compute tasks that have changed since your last execution.

☁️ Deploy anywhere

Run as a shell script in a single machine or distributively in Kubernetes, Airflow, AWS Batch, or SLURM.

📙 Automated migration from legacy notebooks

Bring your old monolithic notebooks, and we’ll automatically convert them into maintainable, modular pipelines.

I want to migrate my notebook.

Show me a demo.


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