blob: c70e1eefe276cc83c95a2df727c8d2005bb94588 [file] [log] [blame]
from abc import ABC, abstractmethod
from .constants import (
DEFAULT_LOCATION,
THREAD_STATUS_HAS_GIL,
THREAD_STATUS_ON_CPU,
THREAD_STATUS_GIL_REQUESTED,
THREAD_STATUS_UNKNOWN,
THREAD_STATUS_HAS_EXCEPTION,
)
try:
from _remote_debugging import FrameInfo
except ImportError:
# Fallback definition if _remote_debugging is not available
FrameInfo = None
def normalize_location(location):
"""Normalize location to a 4-tuple format.
Args:
location: tuple (lineno, end_lineno, col_offset, end_col_offset) or None
Returns:
tuple: (lineno, end_lineno, col_offset, end_col_offset)
"""
if location is None:
return DEFAULT_LOCATION
return location
def extract_lineno(location):
"""Extract lineno from location.
Args:
location: tuple (lineno, end_lineno, col_offset, end_col_offset) or None
Returns:
int: The line number (0 for synthetic frames)
"""
if location is None:
return 0
return location[0]
class Collector(ABC):
@abstractmethod
def collect(self, stack_frames, timestamps_us=None):
"""Collect profiling data from stack frames.
Args:
stack_frames: List of InterpreterInfo objects
timestamps_us: Optional list of timestamps in microseconds. If provided
(from binary replay with RLE batching), use these instead of current
time. If None, collectors should use time.monotonic() or similar.
The list may contain multiple timestamps when samples are batched
together (same stack, different times).
"""
def collect_failed_sample(self):
"""Collect data about a failed sample attempt."""
@abstractmethod
def export(self, filename):
"""Export collected data to a file."""
def _iter_all_frames(self, stack_frames, skip_idle=False):
for interpreter_info in stack_frames:
for thread_info in interpreter_info.threads:
# skip_idle now means: skip if thread is not actively running
# A thread is "active" if it has the GIL OR is on CPU
if skip_idle:
status_flags = thread_info.status
has_gil = bool(status_flags & THREAD_STATUS_HAS_GIL)
on_cpu = bool(status_flags & THREAD_STATUS_ON_CPU)
if not (has_gil or on_cpu):
continue
frames = thread_info.frame_info
if frames:
yield frames, thread_info.thread_id
def _iter_async_frames(self, awaited_info_list):
# Phase 1: Index tasks and build parent relationships with pre-computed selection
task_map, child_to_parent, all_task_ids, all_parent_ids = self._build_task_graph(awaited_info_list)
# Phase 2: Find leaf tasks (tasks not awaited by anyone)
leaf_task_ids = self._find_leaf_tasks(all_task_ids, all_parent_ids)
# Phase 3: Build linear stacks from each leaf to root (optimized - no sorting!)
yield from self._build_linear_stacks(leaf_task_ids, task_map, child_to_parent)
def _iter_stacks(self, stack_frames, skip_idle=False):
"""Yield (frames, thread_id) for all stacks, handling both sync and async modes."""
if stack_frames and hasattr(stack_frames[0], "awaited_by"):
for frames, thread_id, _ in self._iter_async_frames(stack_frames):
if frames:
yield frames, thread_id
else:
for frames, thread_id in self._iter_all_frames(stack_frames, skip_idle=skip_idle):
if frames:
yield frames, thread_id
def _build_task_graph(self, awaited_info_list):
task_map = {}
child_to_parent = {} # Maps child_id -> (selected_parent_id, parent_count)
all_task_ids = set()
all_parent_ids = set() # Track ALL parent IDs for leaf detection
for awaited_info in awaited_info_list:
thread_id = awaited_info.thread_id
for task_info in awaited_info.awaited_by:
task_id = task_info.task_id
task_map[task_id] = (task_info, thread_id)
all_task_ids.add(task_id)
# Pre-compute selected parent and count for optimization
if task_info.awaited_by:
parent_ids = [p.task_name for p in task_info.awaited_by]
parent_count = len(parent_ids)
# Track ALL parents for leaf detection
all_parent_ids.update(parent_ids)
# Use min() for O(n) instead of sorted()[0] which is O(n log n)
selected_parent = min(parent_ids) if parent_count > 1 else parent_ids[0]
child_to_parent[task_id] = (selected_parent, parent_count)
return task_map, child_to_parent, all_task_ids, all_parent_ids
def _find_leaf_tasks(self, all_task_ids, all_parent_ids):
# Leaves are tasks that are not parents of any other task
return all_task_ids - all_parent_ids
def _build_linear_stacks(self, leaf_task_ids, task_map, child_to_parent):
for leaf_id in leaf_task_ids:
frames = []
visited = set()
current_id = leaf_id
thread_id = None
# Follow the single parent chain from leaf to root
while current_id is not None:
# Cycle detection
if current_id in visited:
break
visited.add(current_id)
# Check if task exists in task_map
if current_id not in task_map:
break
task_info, tid = task_map[current_id]
# Set thread_id from first task
if thread_id is None:
thread_id = tid
# Add all frames from all coroutines in this task
if task_info.coroutine_stack:
for coro_info in task_info.coroutine_stack:
for frame in coro_info.call_stack:
frames.append(frame)
# Get pre-computed parent info (no sorting needed!)
parent_info = child_to_parent.get(current_id)
# Add task boundary marker with parent count annotation if multiple parents
task_name = task_info.task_name or "Task-" + str(task_info.task_id)
if parent_info:
selected_parent, parent_count = parent_info
if parent_count > 1:
task_name = f"{task_name} ({parent_count} parents)"
frames.append(FrameInfo(("<task>", None, task_name, None)))
current_id = selected_parent
else:
# Root task - no parent
frames.append(FrameInfo(("<task>", None, task_name, None)))
current_id = None
# Yield the complete stack if we collected any frames
if frames and thread_id is not None:
yield frames, thread_id, leaf_id
def _is_gc_frame(self, frame):
if isinstance(frame, tuple):
funcname = frame[2] if len(frame) >= 3 else ""
else:
funcname = getattr(frame, "funcname", "")
return "<GC>" in funcname or "gc_collect" in funcname
def _collect_thread_status_stats(self, stack_frames):
"""Collect aggregate and per-thread status statistics from a sample.
Returns:
tuple: (aggregate_status_counts, has_gc_frame, per_thread_stats)
- aggregate_status_counts: dict with has_gil, on_cpu, has_exception, etc.
- has_gc_frame: bool indicating if any thread has GC frames
- per_thread_stats: dict mapping thread_id to per-thread counts
"""
status_counts = {
"has_gil": 0,
"on_cpu": 0,
"gil_requested": 0,
"unknown": 0,
"has_exception": 0,
"total": 0,
}
has_gc_frame = False
per_thread_stats = {}
for interpreter_info in stack_frames:
threads = getattr(interpreter_info, "threads", [])
for thread_info in threads:
status_counts["total"] += 1
# Track thread status using bit flags
status_flags = getattr(thread_info, "status", 0)
if status_flags & THREAD_STATUS_HAS_GIL:
status_counts["has_gil"] += 1
if status_flags & THREAD_STATUS_ON_CPU:
status_counts["on_cpu"] += 1
if status_flags & THREAD_STATUS_GIL_REQUESTED:
status_counts["gil_requested"] += 1
if status_flags & THREAD_STATUS_UNKNOWN:
status_counts["unknown"] += 1
if status_flags & THREAD_STATUS_HAS_EXCEPTION:
status_counts["has_exception"] += 1
# Track per-thread statistics
thread_id = getattr(thread_info, "thread_id", None)
if thread_id is not None:
if thread_id not in per_thread_stats:
per_thread_stats[thread_id] = {
"has_gil": 0,
"on_cpu": 0,
"gil_requested": 0,
"unknown": 0,
"has_exception": 0,
"total": 0,
"gc_samples": 0,
}
thread_stats = per_thread_stats[thread_id]
thread_stats["total"] += 1
if status_flags & THREAD_STATUS_HAS_GIL:
thread_stats["has_gil"] += 1
if status_flags & THREAD_STATUS_ON_CPU:
thread_stats["on_cpu"] += 1
if status_flags & THREAD_STATUS_GIL_REQUESTED:
thread_stats["gil_requested"] += 1
if status_flags & THREAD_STATUS_UNKNOWN:
thread_stats["unknown"] += 1
if status_flags & THREAD_STATUS_HAS_EXCEPTION:
thread_stats["has_exception"] += 1
# Check for GC frames in this thread
frames = getattr(thread_info, "frame_info", None)
if frames:
for frame in frames:
if self._is_gc_frame(frame):
thread_stats["gc_samples"] += 1
has_gc_frame = True
break
return status_counts, has_gc_frame, per_thread_stats