continuous-threading 1.3.0

Library to help manage threads that run continuously for a long time.

This library provides several classes to help manage threads that run continuously.

There are some problems with threads runing continuously in a loop. Calculation threads are greedy and keep running which starves other threads. Another problem is if you don’t exit an infinite loop in a thread it may keep running after python has tried to exit. Daemon threads will close, but resources/variables may not be cleaned up properly. Mostly, I needed to finish writing data to a file before the thread closed. This library aims to solve those problems.

This library provides 4 main thread utilities:

• shutdown - Call join(timeout) on every non-daemon thread that is active.

• Thread - threading with context manager support

• ContinuousThread - Run a function continuously in a loop (It is suggested sleep is called periodically if no I/O)

• PausableThread - Continuous thread that can be stopped and started again.

• OperationThread - Thread that will run a calculation in a separate thread with different data.

• PeriodicThread - Thread that runs a function periodically at a given interval.

Shutdown Update

Noticed issue with Python 3.8 on Windows. Python’s threading._shutdown method is never called or hangs before exit. This library is dependent on that function. I added a shutdown method that can be added to the end of your code. This will ensure that join() is called on all of the non-daemon threads.

This issue may have been caused by me adding a _stop method to the Thread class. Python’s threading library may require the use of the _stop function. I removed this method and everything seems to work, so this may not be an issue anymore.

import time
import continuous_threading

def do_something():
    print('hello')
    time.sleep(1)

th = continuous_threading.PausableThread(target=do_something)
th.start()

time.sleep(10)

continuous_threading.shutdown()

Thread context manager

This library turns threads into a context manager which automatically starts and stops threads.

import continuous_threading

thread_success = [False]

def do_something():
    print('here')
    thread_success[0] = True


with continuous_threading.Thread(target=do_something):
    print('in context')

assert thread_success[0] is True

ContinuousThread

The ContinuousThread is a simple thread in an infinite while loop. The while loop keeps looping while the thread alive Event is set. Call thread.stop(), thread.close(), or thread.join() to stop the thread. The thread should also stop automatically when the python program is exiting/closing.

import continuous_threading

class CountingThread(continuous_threading.ContinuousThread):
    def __init__(self):
        super().__init__()
        self.counter = 0

    def _run(self):
        self.counter += 1


with CountingThread() as th:
    print('in context')

assert th.counter > 0
print("Simple context manager print caused %d thread iterations" % th.counter)

Example of start and stop methods. .. code-block:: python

import time import continuous_threading

class CountingThread(continuous_threading.ContinuousThread):

def __init__(self):

super().__init__() self.counter = 0

def _run(self):

self.counter += 1

th = CountingThread() th.start() time.sleep(0.1) th.stop() # or th.close() or th.join()

assert th.counter > 0 print(“Simple context manager print caused %d thread iterations” % th.counter)

New init function .. code-block:: python

import time import continuous_threading

COUNTER = [0]

def init_counter():

return {‘counter’: COUNTER} # dict gets pass as kwargs to the target function.

def inc_coutner(counter):

counter[0] += 1

th = continuous_threading.ContinuousThread(target=inc_counter, init=init_counter) th.start() time.sleep(0.1) th.stop() # or th.close() or th.join()

assert th.counter > 0 print(“Simple context manager print caused %d thread iterations” % th.counter)

PausableThread

A continuous thread that can be stopped and started again.

import time
import continuous_threading


counter = [0]

def inc_counter():
    counter[0] += 1

th = continuous_threading.PausableThread(target=inc_counter)

th.start()
time.sleep(0.1)

th.stop()
time.sleep(0.1)

value = counter[0]
assert value > 0

time.sleep(0.1)
assert value == counter[0]

th.start()
time.sleep(0.1)
assert counter[0] > value

Again this can be used as a context manager. .. code-block:: python

import time import continuous_threading

class CountingThread(continuous_threading.PausableThread):

def __init__(self):

super().__init__() self.counter = 0

def _run(self):

self.counter += 1

with CountingThread() as th:

time.sleep(0.1) th.stop() value = th.counter assert value > 0

time.sleep(0.1) assert value == th.counter

th.start() time.sleep(0.1) assert th.counter > value

PeriodicThread

Run a function periodically.

import time
import continuous_threading


time_list = []

def save_time():
    time_list.append(time.time())

th = continuous_threading.PeriodicThread(0.5, save_time)
th.start()

time.sleep(4)
th.join()

print(time_list)

OperationThread

Add data to a queue which will be operated on in a separate thread.

import time
import continuous_threading


values = []

def run_calculation(data1, data2):
    values.append(data1 + data2)

th = continuous_threading.OperationThread(target=run_calculation)
th.start()
th.add_data(1, 1)
time.sleep(0.1)

assert len(values) > 0
assert values[0] == 2

th.add_data(2, 2)
th.add_data(3, 3)
th.add_data(4, 4)
th.add_data(5, 5)

time.sleep(0.1)
assert values == [2, 4, 6, 8, 10]

Process

All of the above Thread classes can also be used as a separate Process:

• Process

• ContinuousProcess

• PausableProcess

• PeriodicProcess

• OperationProcess

• CommandProcess

CommandProcess

Run functions and commands on an object that lives in a different process.

from continuous_threading import CommandProcess


class MyObj(object):
    def __init__(self, x=0, y=0):
        self._x = x
        self._y = y

    def set_x(self, x):
        self._x = x

    def set_y(self, y):
        self._y = y

    def print_obj(self, msg=''):
        print(self._x, self._y, msg)

    def expect(self, x, y, msg=''):
        assert self._x == x, 'X value {} does not match expected {}'.format(self._x, x)
        assert self._y == y, 'Y value {} does not match expected {}'.format(self._y, y)
        self.print_obj(msg=msg)


obj1 = MyObj()
obj2 = MyObj()

proc = CommandProcess(target=obj1)
proc.start()

# Send a command obj1
print('Main Obj1')  # Note: this prints way earlier
proc.send_cmd('print_obj', msg="Obj1")
proc.send_cmd('set_x', 1)
proc.send_cmd('print_obj')
proc.send_cmd('set_y', 2)
proc.send_cmd('print_obj')
proc.send_cmd('expect', 1, 2, msg='Obj1 expected (1,2)')

# Send a command obj2
print('Main Obj2')  # Note: this prints way earlier
proc.obj = obj2
proc.send_cmd('print_obj', msg="Obj2")
proc.send_cmd('set_x', 2)
proc.send_cmd('print_obj')
proc.send_cmd('set_y', 4)
proc.send_cmd('print_obj')
proc.send_cmd('expect', 2, 4, msg='Obj2 expected (2,4)')

# *** IGNORE COMMENTS: I implemented a caching system to save object state. ***
# Change back to obj1 (Remember this obj has attr 0,0 and when sent to other process will be a new obj 0,0).
# Cannot remember objects unless cached (saved in a dict) on the other process. id in process will be different.
#  ... NVM I'll just cache the obj value.
print('Main Obj1 again (Cached)')  # Note: this prints way earlier
proc.obj = obj1
proc.send_cmd('expect', 1, 2, msg="Obj1 Again (Cached)")
proc.send_cmd('set_x', 3)
proc.send_cmd('print_obj')
proc.send_cmd('set_y', 5)
proc.send_cmd('print_obj')
proc.send_cmd('expect', 3, 5, msg='Obj1 Again expected (3,5)')

proc.join()