hamilton

Hamilton UI and SDK patterns for tracking, monitoring, and debugging dataflows. Use for observability, lineage tracking, and production monitoring.

Core Hamilton patterns for creating DAGs, applying decorators, testing, and debugging dataflows. Use for basic Hamilton development tasks.

Systematic 5-step workflow for building Hamilton DAGs - DOT graphs, signatures, validation, TDD implementation. Use this workflow when creating new Hamilton modules from scratch.

Hamilton integration patterns for Airflow, Dagster, FastAPI, Streamlit, Jupyter notebooks, and other frameworks. Use when integrating Hamilton with other tools.

LLM and AI workflow patterns for Hamilton including RAG pipelines, embeddings, vector databases, and prompt engineering. Use for building AI applications with Hamilton.

Interactive Hamilton DAG development via MCP tools. Validate, visualize, scaffold, and execute Hamilton pipelines without leaving the conversation. Use when building or debugging Hamilton dataflows interactively.

Performance and parallelization patterns for Hamilton including async I/O, Spark, Ray, Dask, caching, and multithreading. Use for scaling Hamilton workflows.