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#!/usr/bin/env python
# Copyright 2020 the V8 project authors. All rights reserved.
# Use of this source code is governed by a BSD-style license that can be
# found in the LICENSE file.
import heapq
import os
import platform
import random
import signal
import subprocess
# Base dir of the build products for Release and Debug.
OUT_DIR = os.path.abspath(
os.path.join(os.path.dirname(__file__), '..', '..', '..', 'out'))
def list_processes_linux():
"""Returns list of tuples (pid, command) of processes running in the same out
directory as this checkout.
"""
if platform.system() != 'Linux':
return []
try:
cmd = 'pgrep -fa %s' % OUT_DIR
output = subprocess.check_output(cmd, shell=True) or ''
processes = [
(int(line.split()[0]), line[line.index(OUT_DIR):])
for line in output.splitlines()
]
# Filter strange process with name as out dir.
return [p for p in processes if p[1] != OUT_DIR]
except:
return []
def kill_processes_linux():
"""Kill stray processes on the system that started in the same out directory.
All swarming tasks share the same out directory location.
"""
if platform.system() != 'Linux':
return
for pid, cmd in list_processes_linux():
try:
print('Attempting to kill %d - %s' % (pid, cmd))
os.kill(pid, signal.SIGKILL)
except:
pass
class FixedSizeTopList():
"""Utility collection for gathering a fixed number of elements with the
biggest value for the given key. It employs a heap from which we pop the
smallest element when the collection is 'full'.
If you need a reversed behaviour (collect min values) just provide an
inverse key."""
def __init__(self, size, key=None):
self.size = size
self.key = key or (lambda x: x)
self.data = []
self.discriminator = 0
def add(self, elem):
elem_k = self.key(elem)
heapq.heappush(self.data, (elem_k, self.extra_key(), elem))
if len(self.data) > self.size:
heapq.heappop(self.data)
def extra_key(self):
# Avoid key clash in tuples sent to the heap.
# We want to avoid comparisons on the last element of the tuple
# since those elements might not be comparable.
self.discriminator += 1
return self.discriminator
def as_list(self):
original_data = [rec for (_, _, rec) in self.data]
return sorted(original_data, key=self.key, reverse=True)
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