1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
|
"""Module with utilities related to async operations"""
from threading import (
Lock,
_Condition,
_sleep,
_time,
)
from Queue import (
Queue,
Empty,
)
from collections import deque
import sys
import os
#{ Routines
def cpu_count():
""":return:number of CPUs in the system
:note: inspired by multiprocessing"""
num = 0
try:
if sys.platform == 'win32':
num = int(os.environ['NUMBER_OF_PROCESSORS'])
elif 'bsd' in sys.platform or sys.platform == 'darwin':
num = int(os.popen('sysctl -n hw.ncpu').read())
else:
num = os.sysconf('SC_NPROCESSORS_ONLN')
except (ValueError, KeyError, OSError, AttributeError):
pass
# END exception handling
if num == 0:
raise NotImplementedError('cannot determine number of cpus')
return num
#} END routines
class DummyLock(object):
"""An object providing a do-nothing lock interface for use in sync mode"""
__slots__ = tuple()
def acquire(self):
pass
def release(self):
pass
class SyncQueue(deque):
"""Adapter to allow using a deque like a queue, without locking"""
def get(self, block=True, timeout=None):
try:
return self.pop()
except IndexError:
raise Empty
# END raise empty
def empty(self):
return len(self) == 0
put = deque.append
class HSCondition(_Condition):
"""An attempt to make conditions less blocking, which gains performance
in return by sleeping less"""
delay = 0.00002 # reduces wait times, but increases overhead
def wait(self, timeout=None):
waiter = Lock()
waiter.acquire()
self.__dict__['_Condition__waiters'].append(waiter)
saved_state = self._release_save()
try: # restore state no matter what (e.g., KeyboardInterrupt)
if timeout is None:
waiter.acquire()
else:
# Balancing act: We can't afford a pure busy loop, so we
# have to sleep; but if we sleep the whole timeout time,
# we'll be unresponsive. The scheme here sleeps very
# little at first, longer as time goes on, but never longer
# than 20 times per second (or the timeout time remaining).
endtime = _time() + timeout
delay = self.delay
acquire = waiter.acquire
while True:
gotit = acquire(0)
if gotit:
break
remaining = endtime - _time()
if remaining <= 0:
break
# this makes 4 threads working as good as two, but of course
# it causes more frequent micro-sleeping
#delay = min(delay * 2, remaining, .05)
_sleep(delay)
# END endless loop
if not gotit:
try:
self.__dict__['_Condition__waiters'].remove(waiter)
except ValueError:
pass
# END didn't ever get it
finally:
self._acquire_restore(saved_state)
def notify(self, n=1):
__waiters = self.__dict__['_Condition__waiters']
if not __waiters:
return
if n == 1:
__waiters[0].release()
try:
__waiters.pop(0)
except IndexError:
pass
else:
waiters = __waiters[:n]
for waiter in waiters:
waiter.release()
try:
__waiters.remove(waiter)
except ValueError:
pass
# END handle n = 1 case faster
class AsyncQueue(Queue):
"""A queue using different condition objects to gain multithreading performance"""
def __init__(self, maxsize=0):
Queue.__init__(self, maxsize)
self.not_empty = HSCondition(self.mutex)
self.not_full = HSCondition(self.mutex)
self.all_tasks_done = HSCondition(self.mutex)
#} END utilities
|
