pytest_park.models.results

source module pytest_park.models.results

Classes

• MethodImprovement — Aggregated improvement metrics for a method within a group.

• OverviewStatistics — Accumulated comparison statistics across all benchmark deltas.

• MethodHistoryPoint — A single mean observation for a method in one run.

• MethodHistoryComparison — A method mean observation compared against a reference run baseline.

• PriorRunComparison — Comparison of a candidate method mean against one prior reference run.

• ImprovementSummary — Aggregated improvement metrics across all methods.

• SplitBarRow — Original vs new mean pair for one argument combination.

source dataclass MethodImprovement(group: str, method: str, current_benchmark_name: str | None = None, comparison_benchmark_name: str | None = None, original_benchmark_name: str | None = None, orig_arg_count: int = 0, ref_arg_count: int = 0, avg_vs_orig_time: float | None = None, avg_vs_orig_pct: float | None = None, med_vs_orig_time: float | None = None, med_vs_orig_pct: float | None = None, min_vs_orig_time: float | None = None, min_vs_orig_pct: float | None = None, max_vs_orig_time: float | None = None, max_vs_orig_pct: float | None = None, avg_vs_prev_time: float | None = None, avg_vs_prev_pct: float | None = None, med_vs_prev_time: float | None = None, med_vs_prev_pct: float | None = None, min_vs_prev_time: float | None = None, min_vs_prev_pct: float | None = None, max_vs_prev_time: float | None = None, max_vs_prev_pct: float | None = None)

Aggregated improvement metrics for a method within a group.

source dataclass OverviewStatistics(count: int, avg_delta_pct: float, median_delta_pct: float, avg_speedup: float, improved: int, regressed: int, unchanged: int)

Accumulated comparison statistics across all benchmark deltas.

source dataclass MethodHistoryPoint(run_id: str, timestamp: str | None, method: str, distinct: str, mean: float)

A single mean observation for a method in one run.

source dataclass MethodHistoryComparison(run_id: str, timestamp: str | None, method: str, distinct: str, mean: float, reference_mean: float, delta_pct: float, speedup: float)

A method mean observation compared against a reference run baseline.

source dataclass PriorRunComparison(method: str, candidate_run_id: str, reference_run_id: str, distinct: str, mean: float, reference_mean: float, delta_pct: float, speedup: float, reference_timestamp: str | None)

Comparison of a candidate method mean against one prior reference run.

source dataclass ImprovementSummary(count: int, avg_vs_orig_time: float | None = None, avg_vs_orig_pct: float | None = None, med_vs_orig_time: float | None = None, med_vs_orig_pct: float | None = None, min_vs_orig_time: float | None = None, min_vs_orig_pct: float | None = None, max_vs_orig_time: float | None = None, max_vs_orig_pct: float | None = None, avg_vs_prev_time: float | None = None, avg_vs_prev_pct: float | None = None, med_vs_prev_time: float | None = None, med_vs_prev_pct: float | None = None, min_vs_prev_time: float | None = None, min_vs_prev_pct: float | None = None, max_vs_prev_time: float | None = None, max_vs_prev_pct: float | None = None)

Aggregated improvement metrics across all methods.

source dataclass SplitBarRow(argument: str, original: float, new: float, delta_pct: float, speedup: float)

Original vs new mean pair for one argument combination.