apache/hamilton

Health v2 · maintenance only

Adoption not part of the score

2575 stars · 212 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Apache Hamilton is a lightweight Python library for defining directed acyclic graphs (DAGs) of data transformations as plain, testable Python functions. It encodes lineage, tracing, and metadata automatically and integrates with tools like pandas, Polars, Spark, Airflow, FastAPI, and Streamlit.

Use cases

• build modular etl pipelines in python
• define testable data transformation dags
• track data lineage for pandas dataframes
• feature engineering pipelines for machine learning
• orchestrate llm and rag workflows
• visualize and document dataflows
• add data quality checks to pipelines

When to choose

• you want declarative, function-based dataflows with automatic lineage in pure Python
• you need testable, reusable transformation logic across notebooks, ETL jobs, and services
• you want a lightweight alternative to heavyweight orchestrators for dataflow definition

When to avoid

• you need full-fledged workflow scheduling and cron-style orchestration like Airflow provides
• your team prefers SQL-first or notebook-first transformation tools like dbt
• you only need simple one-off scripts with no reuse or lineage requirements

Facets

library · maturity active

etl data-science machine-learning rag workflow-automation testing monitoring data-science machine-learning developer-tools python cross-platform dag dataflow lineage dataframe pandas feature-engineering mlops llmops orchestration data-quality data-engineering automation

Member repositories

For agents

markdown · JSON · MCP: product_card(name="apache/hamilton")