⚡ Bolt: Cache JSON parsing for Pokemon types#267
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Optimizes the `parse_pokemon_types` function by introducing an LRU cache (`functools.lru_cache`) for the JSON decoding step. Because Pokémon type combinations are highly repetitive, caching the parsed JSON string prevents redundant and relatively expensive string parsing operations (`json.loads()`).
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💡 What: Extracted JSON string parsing into a private helper
_parse_types_jsonwrapped with@functools.lru_cacheinsrc/app/schemas/pokemon.py. The public validator converts the cached immutable tuple back to a fresh list.🎯 Why: When loading a large list of Pokémon from the database, the string representation of their types (e.g.
["electric"]) was redundantly parsed viajson.loadsfor every object. Since the combinations of Pokémon types are very small, caching the deserialization of these specific strings avoids thousands of unnecessary JSON parse operations.📊 Impact: Reduces CPU time spent on JSON decoding when fetching large collections or the full Pokédex, eliminating a deserialization bottleneck in the Pydantic schema validation pipeline.
🔬 Measurement: Verified by running
pytest tests/test_pokemon_schemas.pyand the full suite to ensure that list instantiations, type conversions, and exception handling still operate identically.PR created automatically by Jules for task 1894298109124350128 started by @edsonesf