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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 ploomber

Or with conda:

conda install ploomber -c conda-forge

Use Binder to try out Ploomber without setting up an environment:

Or run an example locally:

# list examples
ploomber examples

# ML pipeline example
ploomber examples -n templates/ml-basic -o ml-basic
cd ml-basic

# if using pip
pip install -r requirements.txt

# if using conda
conda env create --file environment.yml
conda activate ml-basic

# run pipeline (output will be available in the output directory)
ploomber build

Ready to migrate your project? Click here.

Do you want to learn more? Check out the introductory tutorial.

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

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

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

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.

• Documentation
• PyData Chicago talk (covers motivation and demo)
• Develop and deploy an ML pipeline in 30 minutes (EuroPython 2021)
• Guest blog post on the official Jupyter blog
• Examples (Machine Learning pipeline, ETL, among others)
• Blog
• Comparison with other tools
• More videos