Ploomber is an open source Python framework for building reproducible data pipelines from notebooks and scripts.

Can Ploomber deploy pipelines?

Yes. Ploomber supports deployment to single-machine scripts, Kubernetes, Airflow, AWS Batch, and SLURM.

Is Ploomber still actively maintained?

The `ploomber/ploomber` repository is archived, so teams should verify maintenance expectations before adopting it for new production pipelines.

Ploomber: Open Source Alternative to Amazon SageMaker

Data science work often starts in notebooks, then gets rewritten for production orchestration. That rewrite creates duplicated logic, fragile handoffs, and slow iteration. Full workflow schedulers can be too much when the immediate problem is making analysis code reproducible, modular, cached, and deployable without forcing every notebook into a platform-specific operator model.

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Ploomber

Who Ploomber is for#

Data scientists productionizing notebooks

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ML engineers iterating on pipelines

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Teams migrating legacy notebooks

What it's built on#

FAQ#

Similar open-source tools#

GPT‑NeoX

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The problem it solves#

How it solves it#

Notebook and script pipelines

YAML and Python APIs

Incremental execution

Multiple deployment targets

Strengths and trade-offs#

Strengths

Trade-offs

Install and self-host#

LLM Foundry

Ollama

Unsloth

mTarsier

N8N2MCP