More parallel code optimizations.

1 files changed, 31 insertions, 36 deletions

diff --git a/sphinx/util/parallel.py b/sphinx/util/parallel.py
index a6985c86b..618fbdc38 100644
--- a/sphinx/util/parallel.py
+++ b/sphinx/util/parallel.py
@@ -10,14 +10,16 @@
 """
 
 import os
+import time
 import traceback
+from math import sqrt
 
 try:
     import multiprocessing
 except ImportError:
     multiprocessing = None
 
-from math import sqrt
+from six import iteritems
 
 from sphinx.errors import SphinxParallelError
 
@@ -48,10 +50,8 @@ class ParallelTasks(object):
 
     def __init__(self, nproc):
         self.nproc = nproc
-        # main task performed by each task, returning result
-        self._task_func = 0
         # (optional) function performed by each task on the result of main task
-        self._result_func = 0
+        self._result_funcs = {}
         # task arguments
         self._args = {}
         # list of subprocesses (both started and waiting)
@@ -75,55 +75,50 @@ class ParallelTasks(object):
         except BaseException as err:
             pipe.send((True, (err, traceback.format_exc())))
 
-    def _result_func_wrapper(self, arg, result):
-        result_func = self._result_func(arg, result)
-        if result_func:
-            result_func(result)
-
     def add_task(self, task_func, arg=None, result_func=None):
-        self._task_func = task_func  # dummy code after first call
-        self._result_func = result_func or (lambda *x: None)  # dummy code after first call
         tid = self._taskid
         self._taskid += 1
+        self._result_funcs[tid] = result_func or (lambda arg: None)
         self._args[tid] = arg
         precv, psend = multiprocessing.Pipe(False)
         proc = multiprocessing.Process(target=self._process,
-                                       args=(psend, self._task_func, arg))
+                                       args=(psend, task_func, arg))
         self._procs[tid] = proc
-        if self._pworking < self.nproc:
-            self._precvs[tid] = precv
-            self._pworking += 1
-            proc.start()
-        else:
-            self._precvsWaiting[tid] = precv
+        self._precvsWaiting[tid] = precv
+        self._join_one()
 
     def join(self):
         while self._pworking:
-            for tid, pipe in self._precvs.items():
-                if pipe.poll():
-                    exc, result = pipe.recv()
-                    if exc:
-                        raise SphinxParallelError(*result)
-                    self._result_func_wrapper(self._args[tid], result)
-                    self._procs[tid].join()
-                    if len(self._precvsWaiting) > 0:
-                        newtid, newprecv = self._precvsWaiting.popitem()
-                        self._precvs[newtid] = newprecv
-                        self._procs[newtid].start()
-                        break
-                    else:
-                        self._pworking -= 1
+            self._join_one()
+
+    def _join_one(self):
+        for tid, pipe in iteritems(self._precvs):
+            if pipe.poll():
+                exc, result = pipe.recv()
+                if exc:
+                    raise SphinxParallelError(*result)
+                self._result_funcs.pop(tid)(self._args.pop(tid), result)
+                self._procs[tid].join()
+                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):
     # determine how many documents to read in one go
     nargs = len(arguments)
-    chunksize = min(nargs // nproc, maxbatch)
-    if chunksize == 0:
-        chunksize = 1
-    if chunksize == maxbatch:
+    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