Joe Bylund

pyparsing’s backtracking was the latency ceiling (~3.2k parses/sec). How we identified it, built a hand-written recursive-descent parser with pyparsing as a live parity check, and caught 22 edge cases along the way.

The Rust card store held 96k printings, each owning its own heap-allocated strings — even though ‘Forest’ appears 130 times with the same set name and ‘Shock’ has the same oracle text across every printing. Replacing each unique string with a u32 ID cut the archived card data from 107 MB to 47 MB and the build-time heap from 205 MB to 145 MB.

Swapping cachetools for cachebox (a Rust-backed Python cache) required only a thin key-hashing compatibility wrapper. TTLCache operations went from 537 ns/op to 90 ns/op — a 6× gain for a one-line dependency change.

Why id:gruul was doing a full table scan and how encoding color identity as a 5-bit integer—twice, once in SQL and once in the Rust engine—fixed it with arithmetic that fits in a single CPU instruction.

Card search moved from PostgreSQL into a Rust extension via PyO3. The 76× speedup came not from clever SQL tuning but from eliminating the database round-trip entirely — and from hitting a ceiling that Python itself could not clear.