I built snapconfig because loading large configs across AI worker processes was too slow.

Inspired by uv's use of rkyv, snapconfig compiles JSON/YAML/TOML/INI/env files to a binary cache, then memory-maps them for zero-copy reads. Cold loads are slower than Python's json module, but cached loads are 10-1000x faster. Benchmark results are available on github repo.

Perfect for Celery workers, serverless functions, AI workflows, or any setup where multiple processes read the same config.