pggraph

A linear, one-concept-per-lesson path through pggraph, the Postgres extension that compiles graph traversal and GQL/Cypher pattern matching on top of ordinary Postgres tables, from registering your first table as a node to a relationship-aware context API for AI agents. 29 lessons · 3 tiers.

Prerequisites: Comfortable writing basic Python. Pairs naturally with pgvector (same 'add a superpower to Postgres' pattern) but doesn't depend on it, either order works.

No AI model calls in this course, it's pure Postgres and Python. Setup needs a local Postgres with the pggraph extension, run via `docker compose up -d` from the project root (a separate container from pgvector's, if you've also done that course), exposed on localhost:5434, database name fixed to `graph` (pggraph's own image requires it).

Built on pggraph, the Postgres extension this course teaches.