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streamclone: move applystreamclone() from localrepo.py...
streamclone: move applystreamclone() from localrepo.py Upcoming patches will modernize the streaming clone code. Streaming clone data and code kind of lives in its own world. exchange.py is arguably the most appropriate existing location for it. However, over a dozen patches from now it became apparent that there was a lot of code related to streaming clones and that having it contained within its own module would make it easier to comprehend. So, we establish streamclone.py. It's worth noting that streamclone.py existed a long time ago, last seen in the 1.6 release. It was removed in 04f76a954842. The function was renamed as part of the move because its old name was redundant with the new module name. The only other content change was "self" was renamed to "repo" and minor grammar in the docstring was updated.

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worker.py
152 lines | 4.2 KiB | text/x-python | PythonLexer
# worker.py - master-slave parallelism support
#
# Copyright 2013 Facebook, Inc.
#
# This software may be used and distributed according to the terms of the
# GNU General Public License version 2 or any later version.
from __future__ import absolute_import
import errno
import multiprocessing
import os
import signal
import sys
import threading
from .i18n import _
from . import util
def countcpus():
'''try to count the number of CPUs on the system'''
try:
return multiprocessing.cpu_count()
except NotImplementedError:
return 1
def _numworkers(ui):
s = ui.config('worker', 'numcpus')
if s:
try:
n = int(s)
if n >= 1:
return n
except ValueError:
raise util.Abort(_('number of cpus must be an integer'))
return min(max(countcpus(), 4), 32)
if os.name == 'posix':
_startupcost = 0.01
else:
_startupcost = 1e30
def worthwhile(ui, costperop, nops):
'''try to determine whether the benefit of multiple processes can
outweigh the cost of starting them'''
linear = costperop * nops
workers = _numworkers(ui)
benefit = linear - (_startupcost * workers + linear / workers)
return benefit >= 0.15
def worker(ui, costperarg, func, staticargs, args):
'''run a function, possibly in parallel in multiple worker
processes.
returns a progress iterator
costperarg - cost of a single task
func - function to run
staticargs - arguments to pass to every invocation of the function
args - arguments to split into chunks, to pass to individual
workers
'''
if worthwhile(ui, costperarg, len(args)):
return _platformworker(ui, func, staticargs, args)
return func(*staticargs + (args,))
def _posixworker(ui, func, staticargs, args):
rfd, wfd = os.pipe()
workers = _numworkers(ui)
oldhandler = signal.getsignal(signal.SIGINT)
signal.signal(signal.SIGINT, signal.SIG_IGN)
pids, problem = [], [0]
for pargs in partition(args, workers):
pid = os.fork()
if pid == 0:
signal.signal(signal.SIGINT, oldhandler)
try:
os.close(rfd)
for i, item in func(*(staticargs + (pargs,))):
os.write(wfd, '%d %s\n' % (i, item))
os._exit(0)
except KeyboardInterrupt:
os._exit(255)
# other exceptions are allowed to propagate, we rely
# on lock.py's pid checks to avoid release callbacks
pids.append(pid)
pids.reverse()
os.close(wfd)
fp = os.fdopen(rfd, 'rb', 0)
def killworkers():
# if one worker bails, there's no good reason to wait for the rest
for p in pids:
try:
os.kill(p, signal.SIGTERM)
except OSError as err:
if err.errno != errno.ESRCH:
raise
def waitforworkers():
for _pid in pids:
st = _exitstatus(os.wait()[1])
if st and not problem[0]:
problem[0] = st
killworkers()
t = threading.Thread(target=waitforworkers)
t.start()
def cleanup():
signal.signal(signal.SIGINT, oldhandler)
t.join()
status = problem[0]
if status:
if status < 0:
os.kill(os.getpid(), -status)
sys.exit(status)
try:
for line in fp:
l = line.split(' ', 1)
yield int(l[0]), l[1][:-1]
except: # re-raises
killworkers()
cleanup()
raise
cleanup()
def _posixexitstatus(code):
'''convert a posix exit status into the same form returned by
os.spawnv
returns None if the process was stopped instead of exiting'''
if os.WIFEXITED(code):
return os.WEXITSTATUS(code)
elif os.WIFSIGNALED(code):
return -os.WTERMSIG(code)
if os.name != 'nt':
_platformworker = _posixworker
_exitstatus = _posixexitstatus
def partition(lst, nslices):
'''partition a list into N slices of equal size'''
n = len(lst)
chunk, slop = n / nslices, n % nslices
end = 0
for i in xrange(nslices):
start = end
end = start + chunk
if slop:
end += 1
slop -= 1
yield lst[start:end]