Docs

Deeper chapters than the top-level README has room for. Each one is short and links back to the example code it describes.

Using DuckPipe

• why-duckpipe.md — the pain points this design responds to, mapped to the actual code that answers each one.
• triggers.md — cron, GitHub Actions, Lambda, webhook recipes.
• interop.md — embedding a pipeline inside Airflow/Dagster/Prefect.
• agent_authored.md — the agent writes you a pipeline, plain Python you can review, instead of operating an opaque one on your behalf.

Scaling out

• distributed_execution.md — syncing state to remote storage, and scoping a run to one task so many workers can share a DAG.
• ducklake.md — the opt-in DuckLake observability upgrade (time travel, schema evolution), including a shared Postgres catalog for multiple teams.
• serverless_executor.md — the same distributed-execution primitive, checked against two genuinely different invocation shapes.
• remote_execution.md — running unchanged on a bigger remote machine, for one big task instead of many small ones.
• browser.md — DuckPipe’s own source, unmodified, inside a browser tab via Pyodide.

Design

• ../DESIGN.md — the full design rationale, prior-art landscape check, and the reasoning behind every tenet.