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Implement a statistical sampling profiler that can profile external Python processes by PID. Uses the _remote_debugging module and converts the results to pstats-compatible format for analysis. Co-authored-by: Pablo Galindo <pablogsal@gmail.com>
81 lines
2.8 KiB
Python
81 lines
2.8 KiB
Python
import collections
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import marshal
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from .collector import Collector
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class PstatsCollector(Collector):
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def __init__(self, sample_interval_usec):
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self.result = collections.defaultdict(
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lambda: dict(total_rec_calls=0, direct_calls=0, cumulative_calls=0)
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)
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self.stats = {}
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self.sample_interval_usec = sample_interval_usec
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self.callers = collections.defaultdict(
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lambda: collections.defaultdict(int)
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)
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def collect(self, stack_frames):
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for thread_id, frames in stack_frames:
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if not frames:
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continue
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# Process each frame in the stack to track cumulative calls
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for frame in frames:
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location = (frame.filename, frame.lineno, frame.funcname)
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self.result[location]["cumulative_calls"] += 1
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# The top frame gets counted as an inline call (directly executing)
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top_frame = frames[0]
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top_location = (
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top_frame.filename,
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top_frame.lineno,
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top_frame.funcname,
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)
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self.result[top_location]["direct_calls"] += 1
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# Track caller-callee relationships for call graph
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for i in range(1, len(frames)):
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callee_frame = frames[i - 1]
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caller_frame = frames[i]
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callee = (
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callee_frame.filename,
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callee_frame.lineno,
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callee_frame.funcname,
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)
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caller = (
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caller_frame.filename,
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caller_frame.lineno,
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caller_frame.funcname,
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)
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self.callers[callee][caller] += 1
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def export(self, filename):
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self.create_stats()
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self._dump_stats(filename)
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def _dump_stats(self, file):
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stats_with_marker = dict(self.stats)
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stats_with_marker[("__sampled__",)] = True
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with open(file, "wb") as f:
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marshal.dump(stats_with_marker, f)
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# Needed for compatibility with pstats.Stats
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def create_stats(self):
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sample_interval_sec = self.sample_interval_usec / 1_000_000
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callers = {}
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for fname, call_counts in self.result.items():
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total = call_counts["direct_calls"] * sample_interval_sec
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cumulative_calls = call_counts["cumulative_calls"]
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cumulative = cumulative_calls * sample_interval_sec
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callers = dict(self.callers.get(fname, {}))
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self.stats[fname] = (
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call_counts["direct_calls"], # cc = direct calls for sample percentage
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cumulative_calls, # nc = cumulative calls for cumulative percentage
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total,
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cumulative,
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callers,
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)
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