continuous-threading

==================== continuous_threading

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 a couple of main thread utilities:

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

Shutdown Update!

Noticed issue with Python 3.8 on Windows. Python's threading._shutdown method can hang forever preventing the process from exiting. This library is dependent on that function. I override threading._shutdown to automatically "join" all non-daemon threads.

Note: Python's threading.Thread has a _stop method. Try not to override this method.

Problem

.. code-block:: python

import time
import threading

c = 0

def count_loop():
    global c

    while True:
        c += 1
        time.sleep(1)

th = threading.Thread(target=count_loop)
th.start()

time.sleep(5)
print('Count:', c)

# Process will not exit, because thread is running and cannot end

Solution

Added an allow_shutdown() method and a shutdown() function. The "ContinuousThread", "PausableThread", "OperationThread", and "PeriodicThread" do not have this problem. The continuous_threading library overrides threading._shutdown and has fixes to allow ContinuousThread's to close automatically.

.. code-block:: python

import time
import continuous_threading

c = 0

def count():
    global c
    c += 1
    time.sleep(1)

th = continuous_threading.ContinuousThread(target=count)
th.start()

time.sleep(5)
print('Count:', c)

# Process will automatically exit with threading._shutdown() override

.. code-block:: python

import time
import continuous_threading

c = 0

def count_loop():
    global c

    while True:
        c += 1
        time.sleep(1)

th = continuous_threading.Thread(target=count_loop)
th.start()

time.sleep(5)
print('Count:', c)

continuous_threading.shutdown(0)  # Call join on every non-daemon Thread.

# Alternative. This does not call join normally. continuous_threading threading._shutdown override does call "join".
# th.allow_shutdown()  # Release "_tstate_lock" allowing threading._shutdown to continue

# Process will exit, because allow_shutdown or shutdown

Close Infinite Loop Threads Automatically

Control how the override threading._shutdown works.

.. code-block:: python

import time
import continuous_threading

# Change threading._shutdown() to automatically call Thread.allow_shutdown()
continuous_threading.set_allow_shutdown(True)
continuous_threading.set_shutdown_timeout(0)  # Default 1

c = 0

def count_loop():
    global c

    while True:
        c += 1
        time.sleep(1)

th = continuous_threading.Thread(target=count_loop)
th.start()

time.sleep(5)
print('Count:', c)

# Process will exit due to "set_allow_shutdown"

Can also just call continuous_threading.shutdown()

Remove threading._shutdown() override

You can change the threading._shutdown function with

.. code-block:: python

import continuous_threading

# Change back to original threading._shutdown function
continuous_threading.reset_shutdown()

# Set custom function or leave empty to use continuous_threading custom_shutdown()
continuous_threading.set_shutdown()

Thread context manager

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

.. code-block:: python

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.

.. code-block:: python

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.

.. code-block:: python

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.

.. code-block:: python

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.

.. code-block:: python

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.

.. code-block:: python

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()