# RULEBOOK: Python Performance

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## The Numbers
- Async overhead: **1,400x** (sync 20ns, async 28us)
- Set vs list membership: **200x** at 1000 items
- orjson vs stdlib json: **8x** faster
- Exception raise: **6.5x** (try/except is free)
- SQLite commit: **98%** of write latency

## Rules

**Collections**: Default to `set` for membership. Use `dict.get()` not check-then-access.

**Async**: Default sync. Only async for I/O >1ms. Use `gather()` not loops.

**JSON**: Default `orjson`. stdlib only for zero-deps requirement.

**Exceptions**: try/except is free. Use `.get()` for dicts. EAFP for <15% failure rate.

**Strings**: f-strings default. `%` for logging (deferred eval). `join()` for many parts.

**Memory**: `@dataclass(slots=True)` for 100+ instances.

**Imports**: `TYPE_CHECKING` for heavy types. Lazy imports in CLI tools.

**Database**: DiskCache for key-value. Batch SQLite writes. Reads cheap, writes expensive.

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*Source: python-numbers-everyone-should-know (Python 3.14.2, Apple Silicon)*