[Alek99]

Mapping type inference samples only 100 keys and values, but currently materializes every key and value before taking that sample. Use bounded iteration so inference keeps the same sample and resulting types without copying or retrieving the rest of a large mapping.

On a local CPython 3.14.5 / Apple M5 Pro benchmark, inference for a one-million-entry dict fell from 5.62 ms to 0.026 ms, with peak traced temporary allocation falling from 8 MB to 360 B. This measures the inference helper, not whole-app compilation. Added a CodSpeed benchmark across mapping sizes and regressions covering empty mappings, the exact sample boundary, and custom Mapping iteration/value access. The bounded-iteration regression fails on the unchanged base.

Validation:

• Full unit suite: 8,303 passed, 18 skipped; 75.95% coverage.
• Focused Var tests and new benchmark: 260 passed.
• Repository-wide Ruff check and format check passed.
• pyright reflex tests and changed-file type checks passed.

Independent of the other performance changes; based directly on main.

[greptile-apps]

Confidence Score: 5/5

[Medium impact] The PR appears safe to merge.

Summary

figure_out_type now samples mappings without first copying every key and value.

• Mapping type inference reads only the first 100 keys and values.

No actionable issues were found. Tests were inspected, not run.

_{Reviews (3) · Last reviewed commit: "Merge branch 'main' into codex/perf-boun..." · Reviewed by Greptile}

[codspeed]

Merging this PR will degrade performance by 0.44%

2 warnings

⚠️ 19 benchmarks are dominated by system calls

System calls cannot be simulated consistently and are left out of the measure. The reported value understates the real cost. Switch to the Walltime instrument to measure them.

Learn more about system calls

See affected benchmarks

⚠️ 2 benchmarks with a significant change ran on different hardware

Their base and head results were measured on machines with a different CPU, core count or memory, so the changes might not come from the code. Run base and head on the same runner type.

Learn more about Macro Runners

See affected benchmarks

⚡ 1 improved benchmark
❌ 1 regressed benchmark
✅ 146 untouched benchmarks
🆕 3 new benchmarks

Warning

Please fix the performance issues or acknowledge them on CodSpeed.

Performance Changes

	Benchmark	BASE	HEAD	Efficiency
❌	test_state_collection_assignment[1000]	11.4 ms	12.1 ms	-5.05%
⚡	test_process_event_burst_independent_tokens[1]	2.8 ms	2.7 ms	+4.39%
🆕	test_mapping_type_inference[100]	N/A	1.4 ms	N/A
🆕	test_mapping_type_inference[10000]	N/A	1.4 ms	N/A
🆕	test_mapping_type_inference[100000]	N/A	1.4 ms	N/A

Tip

Investigate this regression by commenting @codspeedbot fix this regression on this PR, or directly use the CodSpeed MCP with your agent.

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_{Comparing codex/perf-bounded-mapping-inference (bbc1920) with main (982a6fb)}

[cubic-dev-ai]

No issues found across 4 files

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