Source code for bundle.perf_report.extractor.cprofile

# Copyright 2026 HorusElohim

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"""cProfile .prof file extraction."""

from __future__ import annotations

import os
import pstats
from dataclasses import dataclass, field
from pathlib import Path


[docs] @dataclass class CProfileRecord: """A single function entry from a .prof file.""" file: str line_number: int function: str call_count: int total_time: float cumulative_time: float
[docs] @dataclass class CProfileData: """All records extracted from one .prof file.""" prof_path: Path records: list[CProfileRecord] = field(default_factory=list) @property def name(self) -> str: return self.prof_path.stem @property def total_calls(self) -> int: return sum(r.call_count for r in self.records)
[docs] class CProfileExtractor: """Extract profiling data from .prof files produced by cProfile."""
[docs] @staticmethod def extract(prof_path: Path) -> CProfileData: """Parse a single .prof file and return structured data.""" stats = pstats.Stats(str(prof_path)) stats.strip_dirs().sort_stats("cumulative") profile = CProfileData(prof_path=prof_path) for (file, line, func_name), (cc, _nc, tt, ct, _callers) in stats.stats.items(): profile.records.append( CProfileRecord( file=file, line_number=line, function=func_name, call_count=cc, total_time=tt, cumulative_time=ct, ) ) profile.records.sort(key=lambda r: r.cumulative_time, reverse=True) return profile
[docs] @staticmethod def extract_all(directory: Path) -> list[CProfileData]: """Recursively find and extract all .prof files in a directory.""" profiles = [] for root, _, files in os.walk(directory): for f in files: if f.endswith(".prof"): prof_path = Path(root) / f profiles.append(CProfileExtractor.extract(prof_path)) return profiles