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import fcntl, os, select, time
from subprocess import Popen, PIPE
# Run a series of subprocesses. Try to keep up to a certain number going in
# parallel at any given time. Enforce time limits.
#
# This is implemented using non-blocking I/O, and so is Unix-specific.
#
# We assume that, if a task closes its standard error, then it's safe to
# wait for it to terminate. So an ill-behaved task that closes its standard
# output and then hangs will hang us, as well. However, as it takes special
# effort to close one's standard output, this seems unlikely to be a
# problem in practice.
class TaskPool(object):
# A task we should run in a subprocess. Users should subclass this and
# fill in the methods as given.
class Task(object):
def __init__(self):
self.pipe = None
self.start_time = None
# Record that this task is running, with |pipe| as its Popen object,
# and should time out at |deadline|.
def start(self, pipe, deadline):
self.pipe = pipe
self.deadline = deadline
# Return a shell command (a string or sequence of arguments) to be
# passed to Popen to run the task. The command will be given
# /dev/null as its standard input, and pipes as its standard output
# and error.
def cmd(self):
raise NotImplementedError
# TaskPool calls this method to report that the process wrote
# |string| to its standard output.
def onStdout(self, string):
raise NotImplementedError
# TaskPool calls this method to report that the process wrote
# |string| to its standard error.
def onStderr(self, string):
raise NotImplementedError
# TaskPool calls this method to report that the process terminated,
# yielding |returncode|.
def onFinished(self, returncode):
raise NotImplementedError
# TaskPool calls this method to report that the process timed out and
# was killed.
def onTimeout(self):
raise NotImplementedError
# If a task output handler (onStdout, onStderr) throws this, we terminate
# the task.
class TerminateTask(Exception):
pass
def __init__(self, tasks, cwd='.', job_limit=4, timeout=150):
self.pending = iter(tasks)
self.cwd = cwd
self.job_limit = job_limit
self.timeout = timeout
self.next_pending = self.get_next_pending()
# Set self.next_pending to the next task that has not yet been executed.
def get_next_pending(self):
try:
return self.pending.next()
except StopIteration:
return None
def run_all(self):
# The currently running tasks: a set of Task instances.
running = set()
with open(os.devnull, 'r') as devnull:
while True:
while len(running) < self.job_limit and self.next_pending:
t = self.next_pending
p = Popen(t.cmd(), bufsize=16384,
stdin=devnull, stdout=PIPE, stderr=PIPE,
cwd=self.cwd)
# Put the stdout and stderr pipes in non-blocking mode. See
# the post-'select' code below for details.
flags = fcntl.fcntl(p.stdout, fcntl.F_GETFL)
fcntl.fcntl(p.stdout, fcntl.F_SETFL, flags | os.O_NONBLOCK)
flags = fcntl.fcntl(p.stderr, fcntl.F_GETFL)
fcntl.fcntl(p.stderr, fcntl.F_SETFL, flags | os.O_NONBLOCK)
t.start(p, time.time() + self.timeout)
running.add(t)
self.next_pending = self.get_next_pending()
# If we have no tasks running, and the above wasn't able to
# start any new ones, then we must be done!
if not running:
break
# How many seconds do we have until the earliest deadline?
now = time.time()
secs_to_next_deadline = max(min([t.deadline for t in running]) - now, 0)
# Wait for output or a timeout.
stdouts_and_stderrs = ([t.pipe.stdout for t in running]
+ [t.pipe.stderr for t in running])
(readable,w,x) = select.select(stdouts_and_stderrs, [], [], secs_to_next_deadline)
finished = set()
terminate = set()
for t in running:
# Since we've placed the pipes in non-blocking mode, these
# 'read's will simply return as many bytes as are available,
# rather than blocking until they have accumulated the full
# amount requested (or reached EOF). The 'read's should
# never throw, since 'select' has told us there was
# something available.
if t.pipe.stdout in readable:
output = t.pipe.stdout.read(16384)
if output != "":
try:
t.onStdout(output)
except TerminateTask:
terminate.add(t)
if t.pipe.stderr in readable:
output = t.pipe.stderr.read(16384)
if output != "":
try:
t.onStderr(output)
except TerminateTask:
terminate.add(t)
else:
# We assume that, once a task has closed its stderr,
# it will soon terminate. If a task closes its
# stderr and then hangs, we'll hang too, here.
t.pipe.wait()
t.onFinished(t.pipe.returncode)
finished.add(t)
# Remove the finished tasks from the running set. (Do this here
# to avoid mutating the set while iterating over it.)
running -= finished
# Terminate any tasks whose handlers have asked us to do so.
for t in terminate:
t.pipe.terminate()
t.pipe.wait()
running.remove(t)
# Terminate any tasks which have missed their deadline.
finished = set()
for t in running:
if now >= t.deadline:
t.pipe.terminate()
t.pipe.wait()
t.onTimeout()
finished.add(t)
# Remove the finished tasks from the running set. (Do this here
# to avoid mutating the set while iterating over it.)
running -= finished
return None
def get_cpu_count():
"""
Guess at a reasonable parallelism count to set as the default for the
current machine and run.
"""
# Python 2.6+
try:
import multiprocessing
return multiprocessing.cpu_count()
except (ImportError,NotImplementedError):
pass
# POSIX
try:
res = int(os.sysconf('SC_NPROCESSORS_ONLN'))
if res > 0:
return res
except (AttributeError,ValueError):
pass
# Windows
try:
res = int(os.environ['NUMBER_OF_PROCESSORS'])
if res > 0:
return res
except (KeyError, ValueError):
pass
return 1
if __name__ == '__main__':
# Test TaskPool by using it to implement the unique 'sleep sort' algorithm.
def sleep_sort(ns, timeout):
sorted=[]
class SortableTask(TaskPool.Task):
def __init__(self, n):
super(SortableTask, self).__init__()
self.n = n
def start(self, pipe, deadline):
super(SortableTask, self).start(pipe, deadline)
def cmd(self):
return ['sh', '-c', 'echo out; sleep %d; echo err>&2' % (self.n,)]
def onStdout(self, text):
print '%d stdout: %r' % (self.n, text)
def onStderr(self, text):
print '%d stderr: %r' % (self.n, text)
def onFinished(self, returncode):
print '%d (rc=%d)' % (self.n, returncode)
sorted.append(self.n)
def onTimeout(self):
print '%d timed out' % (self.n,)
p = TaskPool([SortableTask(_) for _ in ns], job_limit=len(ns), timeout=timeout)
p.run_all()
return sorted
print repr(sleep_sort([1,1,2,3,5,8,13,21,34], 15))
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