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# -*- coding: utf-8 -*-
"""
sphinx.util.parallel
~~~~~~~~~~~~~~~~~~~~
Parallel building utilities.
:copyright: Copyright 2007-2018 by the Sphinx team, see AUTHORS.
:license: BSD, see LICENSE for details.
"""
from __future__ import absolute_import
import os
import time
import traceback
from math import sqrt
try:
import multiprocessing
except ImportError:
multiprocessing = None
from sphinx.errors import SphinxParallelError
from sphinx.util import logging
if False:
# For type annotation
from typing import Any, Callable, Dict, List, Sequence # NOQA
logger = logging.getLogger(__name__)
# our parallel functionality only works for the forking Process
parallel_available = multiprocessing and (os.name == 'posix')
class SerialTasks:
"""Has the same interface as ParallelTasks, but executes tasks directly."""
def __init__(self, nproc=1):
# type: (int) -> None
pass
def add_task(self, task_func, arg=None, result_func=None):
# type: (Callable, Any, Callable) -> None
if arg is not None:
res = task_func(arg)
else:
res = task_func()
if result_func:
result_func(res)
def join(self):
# type: () -> None
pass
class ParallelTasks:
"""Executes *nproc* tasks in parallel after forking."""
def __init__(self, nproc):
# type: (int) -> None
self.nproc = nproc
# (optional) function performed by each task on the result of main task
self._result_funcs = {} # type: Dict[int, Callable]
# task arguments
self._args = {} # type: Dict[int, List[Any]]
# list of subprocesses (both started and waiting)
self._procs = {} # type: Dict[int, multiprocessing.Process]
# list of receiving pipe connections of running subprocesses
self._precvs = {} # type: Dict[int, Any]
# list of receiving pipe connections of waiting subprocesses
self._precvsWaiting = {} # type: Dict[int, Any]
# number of working subprocesses
self._pworking = 0
# task number of each subprocess
self._taskid = 0
def _process(self, pipe, func, arg):
# type: (Any, Callable, Any) -> None
try:
collector = logging.LogCollector()
with collector.collect():
if arg is None:
ret = func()
else:
ret = func(arg)
failed = False
except BaseException as err:
failed = True
errmsg = traceback.format_exception_only(err.__class__, err)[0].strip()
ret = (errmsg, traceback.format_exc())
logging.convert_serializable(collector.logs)
pipe.send((failed, collector.logs, ret))
def add_task(self, task_func, arg=None, result_func=None):
# type: (Callable, Any, Callable) -> None
tid = self._taskid
self._taskid += 1
self._result_funcs[tid] = result_func or (lambda arg, result: None)
self._args[tid] = arg
precv, psend = multiprocessing.Pipe(False)
proc = multiprocessing.Process(target=self._process,
args=(psend, task_func, arg))
self._procs[tid] = proc
self._precvsWaiting[tid] = precv
self._join_one()
def join(self):
# type: () -> None
while self._pworking:
self._join_one()
def _join_one(self):
# type: () -> None
for tid, pipe in self._precvs.items():
if pipe.poll():
exc, logs, result = pipe.recv()
if exc:
raise SphinxParallelError(*result)
for log in logs:
logger.handle(log)
self._result_funcs.pop(tid)(self._args.pop(tid), result)
self._procs[tid].join()
self._precvs.pop(tid)
self._pworking -= 1
break
else:
time.sleep(0.02)
while self._precvsWaiting and self._pworking < self.nproc:
newtid, newprecv = self._precvsWaiting.popitem()
self._precvs[newtid] = newprecv
self._procs[newtid].start()
self._pworking += 1
def make_chunks(arguments, nproc, maxbatch=10):
# type: (Sequence[unicode], int, int) -> List[Any]
# determine how many documents to read in one go
nargs = len(arguments)
chunksize = nargs // nproc
if chunksize >= maxbatch:
# try to improve batch size vs. number of batches
chunksize = int(sqrt(nargs / nproc * maxbatch))
if chunksize == 0:
chunksize = 1
nchunks, rest = divmod(nargs, chunksize)
if rest:
nchunks += 1
# partition documents in "chunks" that will be written by one Process
return [arguments[i * chunksize:(i + 1) * chunksize] for i in range(nchunks)]
|
