pytest_park.core.analysis

source module pytest_park.core.analysis

Functions

• attach_profiler_data — Attach profiler records to matching benchmark runs.

• select_reference_run — Select a run by explicit run_id or tag.

• select_latest_and_previous_runs — Select previous and latest run as reference/candidate pair.

• select_candidate_run — Select candidate run or default to latest non-reference run.

• list_methods — List unique benchmark methods seen across runs.

• compare_runs — Compare two runs and calculate per-case deltas.

• summarize_groups — Build group-level summary from case-level deltas.

• build_overview_statistics — Compute accumulated comparison statistics.

• build_method_statistics — Compute statistics for one benchmark method.

• build_trends — Build time-series means per case across run history.

• build_method_history — Build method mean history across runs.

• compare_method_history_to_reference — Compare method mean over runs against reference run mean.

• compare_method_to_all_prior_runs — Compare candidate method means against all prior runs.

• build_method_group_split_bars — Build split-bar chart rows per method base name for original/new roles.

• build_group_label — Create a logical group label for a benchmark case.

source attach_profiler_data(runs: list[BenchmarkRun], profiler_by_run: dict[str, dict[str, dict[str, object]]]) → list[BenchmarkRun]

Attach profiler records to matching benchmark runs.

source select_reference_run(runs: list[BenchmarkRun], reference_id_or_tag: str) → BenchmarkRun

Select a run by explicit run_id or tag.

Raises

• ValueError

source select_latest_and_previous_runs(runs: list[BenchmarkRun]) → tuple[BenchmarkRun, BenchmarkRun]

Select previous and latest run as reference/candidate pair.

Raises

• ValueError

source select_candidate_run(runs: list[BenchmarkRun], candidate_id_or_tag: str | None, reference_run: BenchmarkRun) → BenchmarkRun

Select candidate run or default to latest non-reference run.

Raises

• ValueError

source list_methods(runs: list[BenchmarkRun]) → list[str]

List unique benchmark methods seen across runs.

source compare_runs(reference_run: BenchmarkRun, candidate_run: BenchmarkRun, group_by: list[str] | None = None, distinct_params: list[str] | None = None) → list[BenchmarkDelta]

Compare two runs and calculate per-case deltas.

source summarize_groups(deltas: list[BenchmarkDelta]) → list[GroupSummary]

Build group-level summary from case-level deltas.

source build_overview_statistics(deltas: list[BenchmarkDelta]) → dict[str, float | int]

Compute accumulated comparison statistics.

source build_method_statistics(deltas: list[BenchmarkDelta], method: str) → dict[str, float | int] | None

Compute statistics for one benchmark method.

source build_trends(runs: list[BenchmarkRun]) → dict[str, list[TrendPoint]]

Build time-series means per case across run history.

source build_method_history(runs: list[BenchmarkRun], method: str, distinct_params: list[str] | None = None) → list[dict[str, float | str | None]]

Build method mean history across runs.

source compare_method_history_to_reference(runs: list[BenchmarkRun], reference_run: BenchmarkRun, method: str, distinct_params: list[str] | None = None) → list[dict[str, float | str | None]]

Compare method mean over runs against reference run mean.

source compare_method_to_all_prior_runs(runs: list[BenchmarkRun], candidate_run: BenchmarkRun, method: str, distinct_params: list[str] | None = None) → list[dict[str, float | str | None]]

Compare candidate method means against all prior runs.

source build_method_group_split_bars(run: BenchmarkRun) → dict[str, list[dict[str, float | str]]]

Build split-bar chart rows per method base name for original/new roles.

source build_group_label(case: BenchmarkCase, group_by: list[str] | None = None) → str

Create a logical group label for a benchmark case.