418 lines
15 KiB
Python
418 lines
15 KiB
Python
'''
|
|
The documentation for the classes and methods are below. Here are some examples
|
|
of threadpool in use:
|
|
|
|
1. Powering a single api scraping generator with many threads:
|
|
|
|
>>> pool = threadpool.ThreadPool(thread_count, paused=True)
|
|
>>> job_gen = ({'function': api.get_item, 'kwargs': {'id': i}} for i in range(lower, upper+1))
|
|
>>> pool.add_generator(job_gen)
|
|
>>> for job in pool.result_generator():
|
|
>>> if job.exception:
|
|
>>> raise job.exception
|
|
>>> if job.value is not None:
|
|
>>> yield job.value
|
|
|
|
2. Git-fetching a bunch of repositories with no error handling:
|
|
|
|
>>> def git_fetch(d):
|
|
>>> command = [GIT, '-C', d, 'fetch', '--all']
|
|
>>> print(command)
|
|
>>> subprocess.check_output(command, stderr=subprocess.STDOUT)
|
|
>>>
|
|
>>> def callback(job):
|
|
>>> if job.exception:
|
|
>>> print(f'{job.name} caused {job.exception}.')
|
|
>>>
|
|
>>> pool = threadpool.ThreadPool(thread_count, paused=False)
|
|
>>> kwargss = [{'function': git_fetch, 'args': [d], 'name': d, 'callback': callback} for d in dirs]
|
|
>>> pool.add_many(kwargss)
|
|
>>> pool.join()
|
|
'''
|
|
import collections
|
|
import logging
|
|
import queue
|
|
import threading
|
|
import traceback
|
|
|
|
from voussoirkit import lazychain
|
|
from voussoirkit import sentinel
|
|
|
|
log = logging.getLogger('threadpool')
|
|
|
|
PENDING = sentinel.Sentinel('PENDING')
|
|
RUNNING = sentinel.Sentinel('RUNNING')
|
|
FINISHED = sentinel.Sentinel('FINISHED')
|
|
RAISED = sentinel.Sentinel('RAISED')
|
|
|
|
NO_MORE_JOBS = sentinel.Sentinel('NO_MORE_JOBS')
|
|
|
|
NO_RETURN = sentinel.Sentinel('NO_RETURN', truthyness=False)
|
|
NO_EXCEPTION = sentinel.Sentinel('NO_EXCEPTION', truthyness=False)
|
|
|
|
class ThreadPoolException(Exception):
|
|
pass
|
|
|
|
class PoolClosed(ThreadPoolException):
|
|
pass
|
|
|
|
class PooledThread:
|
|
def __init__(self, pool):
|
|
self.pool = pool
|
|
self.thread = threading.Thread(target=self.start)
|
|
self.thread.daemon = True
|
|
self.thread.start()
|
|
|
|
def __repr__(self):
|
|
return f'PooledThread {self.thread}'
|
|
|
|
def _run_once(self):
|
|
# Any exceptions caused by the job's primary function are already
|
|
# wrapped safely, but there are two other sources of potential
|
|
# exceptions:
|
|
# 1. A generator given to add_generator that encounters an exception
|
|
# while generating the kwargs causes get_next_job to raise.
|
|
# 2. The callback function given to the Job raises.
|
|
# It's hard to say what the correct course of action is, but I
|
|
# realllly don't want them taking down the whole worker thread.
|
|
try:
|
|
job = self.pool.get_next_job()
|
|
except BaseException:
|
|
traceback.print_traceback()
|
|
return
|
|
|
|
if job is NO_MORE_JOBS:
|
|
return NO_MORE_JOBS
|
|
|
|
log.debug('%s is running job %s.', self, job)
|
|
self.pool._running_count += 1
|
|
try:
|
|
job.run()
|
|
except BaseException:
|
|
traceback.print_traceback()
|
|
self.pool._running_count -= 1
|
|
|
|
def join(self):
|
|
log.debug('%s is joining.', self)
|
|
self.thread.join()
|
|
|
|
def start(self):
|
|
while True:
|
|
# Let's wait for jobs_available first and unpaused second.
|
|
# If the time between the two waits is very long, the worst thing
|
|
# that can happen is there are no more jobs by the time we get
|
|
# there, and the loop comes around again. On the other hand, if
|
|
# unpaused.wait is first and the time until available.wait is very
|
|
# long, we might wind up running a job despite the user pausing
|
|
# the pool in the interim.
|
|
self.pool._jobs_available.wait()
|
|
self.pool._unpaused_event.wait()
|
|
status = self._run_once()
|
|
if status is NO_MORE_JOBS and self.pool.closed:
|
|
break
|
|
|
|
class ThreadPool:
|
|
'''
|
|
The ThreadPool is used to perform large numbers of tasks using a pool of
|
|
worker threads. Jobs are run in the order they are added.
|
|
|
|
The pool supports two main paradigms of usage:
|
|
|
|
1. Callback / async style
|
|
If the job function performs your desired side effects by itself, or is
|
|
given a callback function, you can simply add it to the pool and wait
|
|
for it to run.
|
|
|
|
2. Generator style
|
|
If you want to yield the job results back to the main thread for
|
|
processing (e.g. you are feeding the results into sqlite, which must be
|
|
done on the thread which opened the sqlite connection), you can use
|
|
`result_generator` to get each job in the order they were added to the
|
|
pool. This style also makes it easier to terminate the main thread when
|
|
a single job encounters an issue. Just `raise job.exception`.
|
|
'''
|
|
def __init__(self, size, paused=True):
|
|
'''
|
|
size:
|
|
The number of worker threads.
|
|
|
|
paused:
|
|
If True, the pool will start in a paused state and you will have to
|
|
call `start` to start it. If False, the pool will run as soon as
|
|
jobs are added to it.
|
|
'''
|
|
if not isinstance(size, int):
|
|
raise TypeError(f'size must be an int, not {type(size)}.')
|
|
if size < 1:
|
|
raise ValueError(f'size must be >= 1, not {size}.')
|
|
|
|
self._unpaused_event = threading.Event()
|
|
if not paused:
|
|
self._unpaused_event.set()
|
|
|
|
self._jobs_available = threading.Event()
|
|
|
|
self._closed = False
|
|
self._running_count = 0
|
|
self._result_queue = None
|
|
self._pending_jobs = lazychain.LazyChain()
|
|
self._job_manager_lock = threading.Lock()
|
|
|
|
self._size = size
|
|
self._threads = [PooledThread(pool=self) for x in range(size)]
|
|
|
|
@property
|
|
def closed(self):
|
|
return self._closed
|
|
|
|
@property
|
|
def paused(self):
|
|
return not self._unpaused_event.is_set()
|
|
|
|
@property
|
|
def running_count(self):
|
|
return self._running_count
|
|
|
|
@property
|
|
def size(self):
|
|
return self._size
|
|
|
|
def assert_not_closed(self):
|
|
'''
|
|
If the pool is closed (because you called `join`), raise PoolClosed.
|
|
Otherwise do nothing.
|
|
'''
|
|
if self._closed:
|
|
raise PoolClosed()
|
|
|
|
def add(self, function, *, name=None, callback=None, args=tuple(), kwargs=dict()):
|
|
'''
|
|
Add a new job to the pool.
|
|
|
|
See the Job class for parameter details.
|
|
'''
|
|
self.assert_not_closed()
|
|
|
|
job = Job(
|
|
pool=self,
|
|
function=function,
|
|
name=name,
|
|
args=args,
|
|
kwargs=kwargs,
|
|
)
|
|
self._pending_jobs.append(job)
|
|
self._jobs_available.set()
|
|
|
|
return job
|
|
|
|
def add_generator(self, kwargs_gen):
|
|
'''
|
|
Add jobs from a generator which yields kwarg dictionaries. Unlike
|
|
`add` and `add_many`, the Job objects are not returned by this method
|
|
(since they don't exist yet!). If you want them, use `result_generator`
|
|
to iterate the pool's jobs as they complete. Otherwise, they should
|
|
have their own side effects or use a callback.
|
|
|
|
See the Job class for kwarg details.
|
|
'''
|
|
self.assert_not_closed()
|
|
|
|
these_jobs = (Job(pool=self, **kwargs) for kwargs in kwargs_gen)
|
|
self._pending_jobs.extend(these_jobs)
|
|
self._jobs_available.set()
|
|
|
|
def add_many(self, kwargss):
|
|
'''
|
|
Add multiple new jobs to the pool at once. This is better than calling
|
|
`add` in a loop because we only have to aquire the lock one time.
|
|
|
|
Provide an iterable of kwarg dictionaries. That is:
|
|
[
|
|
{'function': print, 'args': [4], 'name': '4'},
|
|
{'function': sample, 'kwargs': {'x': 2}},
|
|
]
|
|
|
|
See the Job class for kwarg details.
|
|
'''
|
|
self.assert_not_closed()
|
|
|
|
kwargss = list(kwargss)
|
|
if not kwargss:
|
|
raise ValueError(f'{kwargss} must not be empty.')
|
|
|
|
these_jobs = [Job(pool=self, **kwargs) for kwargs in kwargss]
|
|
self._pending_jobs.extend(these_jobs)
|
|
self._jobs_available.set()
|
|
|
|
return these_jobs
|
|
|
|
def get_next_job(self):
|
|
with self._job_manager_lock:
|
|
try:
|
|
job = next(self._pending_jobs)
|
|
except StopIteration:
|
|
# If we ARE closed, we want to keep the flag set so that all
|
|
# the threads can keep waking up and seeing no more jobs.
|
|
if not self.closed:
|
|
self._jobs_available.clear()
|
|
if self._result_queue is not None:
|
|
# If the user provided a generator to add_generator that
|
|
# actually produces no items, and then immediately starts
|
|
# waiting inside result_generator for the results, they
|
|
# will hang as _result_queue never gets anything.
|
|
# So, here's this.
|
|
self._result_queue.put(NO_MORE_JOBS)
|
|
return NO_MORE_JOBS
|
|
else:
|
|
if self._result_queue is not None:
|
|
# This will block if the queue is full.
|
|
self._result_queue.put(job)
|
|
return job
|
|
|
|
def join(self):
|
|
'''
|
|
Permanently close the pool, preventing any new jobs from being added,
|
|
and block until all jobs are complete.
|
|
'''
|
|
log.debug('%s is joining.', self)
|
|
self._closed = True
|
|
# The threads which are currently paused at _jobs_available.wait() need
|
|
# to be woken up so they can realize the pool is closed and break.
|
|
self._jobs_available.set()
|
|
self.start()
|
|
for thread in self._threads:
|
|
thread.join()
|
|
|
|
def result_generator(self, *, buffer_size=None):
|
|
'''
|
|
This generator will start the job pool, then yield finished/raised Job
|
|
objects in the order they were added. Note that a slow job will
|
|
therefore hold up the generator, though it will not stop the job pool
|
|
from running and spawning new jobs in their other threads.
|
|
|
|
For best results, you should create the pool in the paused state, add
|
|
your jobs, then use this method to start the pool. Any jobs that run
|
|
while the result_generator is not active will not be stored, since we
|
|
don't necessarily know if this method will ever be used. So, any jobs
|
|
that start before the result_generator is active will not be yielded
|
|
and will simply be lost to garbage collection.
|
|
|
|
If more jobs are added while the generator is running, they will be
|
|
yielded as expected.
|
|
|
|
When there are no more outstanding jobs, the generator will stop
|
|
iteration and return. If the pool was paused before generating, it
|
|
will be paused again. This prevents subsequently added jobs from being
|
|
lost as described.
|
|
|
|
buffer_size:
|
|
The size of the buffer which holds jobs before they are yielded.
|
|
If you expect your production to outpace your consumption, you may
|
|
wish to set this value to prevent high memory usage. When the buffer
|
|
is full, new jobs will be blocked from starting.
|
|
'''
|
|
if self._result_queue is not None:
|
|
raise TypeError('The result generator is already open.')
|
|
|
|
self._result_queue = queue.Queue(maxsize=buffer_size or 0)
|
|
|
|
was_paused = self.paused
|
|
|
|
self.start()
|
|
# Considerations for the while loop condition:
|
|
# Why `jobs_available.is_set`: Consider a group of slow-running threads
|
|
# are launched and the jobs are added to the result_queue. The caller
|
|
# of this generator consumes all of them before the threads finish and
|
|
# start a new job. So, we need to watch jobs_available.is_set to know
|
|
# that even though the result_queue is currently empty, we can expect
|
|
# more to be ready soon and shouldn't break yet.
|
|
# Why `not results_queue.empty`: Consider a group of fast-running
|
|
# threads are launched, and exhaust all available jobs. So, we need to
|
|
# watch that result_queue is not empty and has more results.
|
|
# Why not `not closed`: After the pool is closed, the outstanding jobs
|
|
# still need to finish. Closing does not imply pausing or cancelling
|
|
# jobs.
|
|
while self._jobs_available.is_set() or not self._result_queue.empty():
|
|
job = self._result_queue.get()
|
|
if job is NO_MORE_JOBS:
|
|
self._result_queue.task_done()
|
|
break
|
|
job.join()
|
|
yield job
|
|
self._result_queue.task_done()
|
|
self._result_queue = None
|
|
|
|
if was_paused:
|
|
self.pause()
|
|
|
|
def pause(self):
|
|
self._unpaused_event.clear()
|
|
|
|
def start(self):
|
|
self._unpaused_event.set()
|
|
|
|
class Job:
|
|
'''
|
|
Each job contains one function that it will call when it is started.
|
|
|
|
If the function completes successfully (status is threadpool.FINISHED) you
|
|
will find the return value in `job.value`. If it raises an exception
|
|
(status is threadpool.RAISED), you'll find it in `job.exception`, although
|
|
the thread itself will not raise.
|
|
|
|
All job threads are daemons and will not prevent the main thread from
|
|
terminating. Call `job.join()` or `pool.join()` in the main thread to
|
|
ensure jobs complete.
|
|
'''
|
|
def __init__(self, pool, function, *, name=None, callback=None, args=tuple(), kwargs=dict()):
|
|
'''
|
|
When this job is started, `function(*args, **kwargs)` will be called.
|
|
|
|
name:
|
|
An optional value that will appear in the repr of the job and
|
|
has no other purpose. Use this if you intend to print(job) and want
|
|
a human friendly name string.
|
|
|
|
callback:
|
|
An optional function which will be called as `callback(job)` after
|
|
the job is finished running. Use this for async-style processing of
|
|
the job. Note that the callback is called via the job's thread, so
|
|
make sure it is memory safe.
|
|
'''
|
|
self.pool = pool
|
|
self.name = name
|
|
self.status = PENDING
|
|
self.function = function
|
|
self.callback = callback
|
|
self.args = args
|
|
self.kwargs = kwargs
|
|
self.value = NO_RETURN
|
|
self.exception = NO_EXCEPTION
|
|
|
|
self._done_event = threading.Event()
|
|
|
|
def __repr__(self):
|
|
if self.name:
|
|
return f'<{self.status.name} Job {repr(self.name)}>'
|
|
else:
|
|
return f'<{self.status.name} Job on {self.function}>'
|
|
|
|
def run(self):
|
|
self.status = RUNNING
|
|
try:
|
|
self.value = self.function(*self.args, **self.kwargs)
|
|
self.status = FINISHED
|
|
except BaseException as exc:
|
|
self.exception = exc
|
|
self.status = RAISED
|
|
|
|
if self.callback is not None:
|
|
self.callback(self)
|
|
|
|
self._done_event.set()
|
|
|
|
def join(self):
|
|
'''
|
|
Block until this job runs and completes.
|
|
'''
|
|
self._done_event.wait()
|