pp-print-hot — print in loop vs join once (stdout discarded)
Claim
Measured on this machine: primary hot case print_in_loop ratio before/after ~2.10× (faster after). Default severity stays off. Do not escalate to error from this fill alone.
How measured
- Harness:
packages/pyperf/examples/bench/evidence_pp.py - Protocol: warm=3; median of 9 rounds; GC/collect where applicable
- Raw lines:
pp-print-hot.jsonl
Runtime (this evidence file)
| Field | Value |
|---|---|
| When | 2026-10-23 Asia/Shanghai (machine clock; JSONL ts is UTC) |
| Toolchain | CPython 3.15.1 |
Median after (print_join_once) | 1.073375 ms (ops=20000, ratio=1.000000) |
Median before (print_in_loop) | 2.258042 ms (ops=20000, ratio=2.103684) |
| Primary ratio before/after | ~2.10× (print_in_loop) |
Direction and absolute ms are N/machine/opt-sensitive. Re-run the harness after toolchain or machine changes.
Lint mapping
pyperf-lint pp-print-hot default stays off. Escalate recommended: no.
Limits
- Microbench; not an app profile.
- Small-N rows may sit near timer noise; prefer hot (non-small) cases for ratio claims.
- I/O rules (print/echo/puts/writeln) discard to
/dev/null— env-dependent.