I have two python programs which one of them connects to a bluetooth device(socket package), it receives and saves data from device, and another one read the stored data and draw a real time plot. I should make one application from these two programs.
I tried to mix these two python programs, but since bluetooth should wait to receive data (through a while loop), the other parts of program does not work. I tried to solve this problem using Clock.schedule_interval, but the program will hang after a period of time. So I decided to run these two programs simultaneously. I read, we can run some python programs at a same time using a python script. Is there any trick to join these two programs and build one application?
Any help would be greatly appreciated.
Install threaded:
pip install threaded
Create a new python file:
from threading import Thread
def runFile1(): import file1
def runFile2(): import file2
Thread(target=runFile1).start()
runFile2()
Run the new python file.
It can be done with threading. To do communication between the threaded function and your main function, use objects such as queue.Queue and threading.Event.
the bluetooth functions can be placed into a function that is the target of the thread
import time
from threading import Thread
from queue import Queue
class BlueToothFunctions(Thread):
def __init__(self, my_queue):
super().__init__()
self.my_queue = my_queue
# optional: causes this thread to end immediately if the main program is terminated
self.daemon = True
def run(self) -> None:
while True:
# do all the bluetooth stuff foreverer
g = self.my_queue.get()
if g == (None, None):
break
print(g)
time.sleep(1.0)
print("bluetooth closed")
if __name__ == '__main__':
_queue = Queue() # just one way to communicate to a thread
# pass an object reference so both main and thread have a way to communicate on this common queue
my_bluetooth = BlueToothFunctions(_queue)
my_bluetooth.start() # creates the thread and executes run() method
for i in range(5):
# communicate to the threaded functions
_queue.put(i)
_queue.put((None, None)) # optional, a way to cause the thread to end
my_bluetooth.join(timeout=5.0) # optional, pause here until thread ends
print('program complete')
Related
I have functioning code that displays data in a GUI which is periodically updated with new information downloaded from the web. (The base code for the threaded approach was sourced from https://www.oreilly.com/library/view/python-cookbook/0596001673/ch09s07.html) I am using a threaded solution so as to improve blocking IO issues (IO code not included in the simplified code example below, as the IO does not appear to be the problem). The code runs fine if I run it as a single instance. However, it would be most convenient if I could use multiprocessing to run several instances of the code in parallel, using a different input list for each instance. When I try to implement the multiprocessing version, each separate process hangs during the attempt to create the root window: "window = tk.Tk()". Here is the working single instance version:
import threading
import random
import tkinter as tk
import random
import queue #Queue
import multiprocessing
import psutil
class GuiPartBase:
def __init__(self, master, queue, myList, endCommand):
self.queue = queue
# Set up the GUI
a = Label(master, text="Test Tkinter Display!")
a.pack()
## etc
def processIncoming(self):
"""Handle all messages currently in the queue, if any."""
while self.queue.qsize():
try:
result = (self.queue.get(0))
## do stuff with incoming data...
print('result =', result)
except queue.Empty:
# just on general principles...
pass
class ThreadedClientBase:
"""
Launch the main part of the GUI and the worker thread. periodicCall and
endApplication could reside in the GUI part, but putting them here
means that you have all the thread controls in a single place.
"""
def __init__(self, master, mylist):
"""
Start the GUI and the asynchronous threads. We are in the main
(original) thread of the application, which will later be used by
the GUI as well. We spawn a new thread for the worker (I/O).
"""
self.master = master
self.mylist = mylist
# Create the queue
self.queue = queue.Queue()
# Set up the GUI part
self.gui = GuiPartBase(self.master, self.queue, mylist, self.endApplication)
# Set up the thread to do asynchronous I/O
# More threads can also be created and used, if necessary
self.running = 1
self.thread1 = threading.Thread(target=self.workerThread1)
self.thread1.start()
# Start the periodic call in the GUI to check if the queue contains
# anything
self.periodicCall()
def periodicCall(self):
"""
Check every 200 ms if there is something new in the queue.
"""
self.gui.processIncoming()
if not self.running:
# This is the brutal stop of the system. You may want to do
# some cleanup before actually shutting it down.
import sys
sys.exit(1)
self.master.after(200, self.periodicCall)
def workerThread1(self):
"""
This is where we handle the asynchronous I/O. For example, it may be
a 'select( )'. One important thing to remember is that the thread has
to yield control pretty regularly, by select or otherwise.
"""
while self.running:
# simulate asynchronous I/O,
time.sleep(rand.random() * 1.5)
msg = rand.random()
self.queue.put(msg)
def endApplication(self):
self.running = 0
def runGUIthread(threadedList2Get):
print('entering runGUIthread...')
print('list2Get = ', threadedList2Get)
window = tk.Tk()
print('type of window = ', type(window))
print('window = ', window)
client = ThreadedClientBase(window, threadedList2Get)
print('type of client = ', type(client))
print('client = ', client)
window.mainloop()
if __name__ == '__main__':
rand = random.Random()
testList2a = ['abc','def','geh']
testList2b = ['xyz', 'lmn', 'opq']
allLists = [testList2a,testList2b]
runGUIthread(testList2a)
So, like I said, the above works - a single tkinter GUI is displayed appropriately without errors. However, if I attempt to implement multiprocessing with the following code below, the code spawns two processes as expected, and as documented by the printout of pid. However, each process prints the 'list2Get' (in runGUIthread), and then there is nothing else. There is no error message and the python code seems to have exited as there is no persistent process listed in the system activity monitor. Presumably the code is "hanging"/ exiting at the line "window = tk.TK()", as the line "print('type of window=',type(window))" is never executed:
if __name__ == '__main__':
rand = random.Random()
testList2a = ['abc','def','geh']
testList2b = ['xyz', 'lmn', 'opq']
allLists = [testList2a,testList2b]
#runGUIthread(testList2a)
for list in allLists:
p = multiprocessing.Process(target=runGUIthread, args=(list,))
p.start()
ps = psutil.Process(p.pid)
print('pid = ', ps)
#with multiprocessing.Pool(processes=2) as pool:
# pool.map(runGUIthread, allLists)
I am not experienced with multiprocessing, so perhaps I have implemented it incorrectly. I tried using multiprocessing.Pool(), with the same results.
I have not been able to find info indicating that tkinter can't spawn multiple GUI displays in the same program. In fact I found an instance of somebody accidentally spawning multiple GUI's, although this appears to be with Python 3.8 using concurrent.futures.ProcessPoolExecutor (Concurrent.futures opens new windows in tkinter instead of running the function). I am currently on Python 3.7, and was hoping not to have to reinstall a new enviroment to make this multiprocessing code work, although perhaps that is necessary...?
Other info: using python 3.7.6, tkinter 8.6.8, Eclipse 4.11.0, macOS10.13.6.
Any help appreciated.
You cannot use tkinter code across multiple processes. At least, you can't run the same tkinter code. It simply isn't designed to be used that way. When you create a root window, underneath the covers a tcl interpreter is created, and this interpreter can't be pickled or shared between processes, and doesn't use python's global interpreter lock.
In short, all of your GUI code needs to be in a single thread in a single process.
The following answer is a slightly better explanation, written by one of the developers on the Tcl core team: https://stackoverflow.com/a/38767665/7432. Here is the opening paragraph of that answer:
Each Tcl interpreter object (i.e., the context that knows how to run a Tcl procedure) can only be safely used from the OS thread that creates it. This is because Tcl doesn't use a global interpreter lock like Python, and instead makes extensive use of thread-specific data to reduce the number of locks required internally. (Well-written Tcl code can take advantage of this to scale up very large on suitable hardware.)
I found that this has been reported as part of a bug related to tkinter, python, and macOSX: https://bugs.python.org/issue33111.
(The bug was reported for python 2.7 and 3.6.4 and OSX 10.11.6, but apparently is still a problem with python 3.7.6 and OSX 10.13.6.)
However, there is a partial workaround (also reported at the same site), which for my case seems to work perfectly:
import multiprocessing
multiprocessing.set_start_method("spawn", force=True)
...
... other code same as initial ...
...
if __name__ == '__main__':
testList2a = ['abc','def','geh']
testList2b = ['xyz', 'lmn', 'opq']
allLists = [testList2a,testList2b]
with multiprocessing.Pool(processes=2) as pool:
pool.map(runGUIthread, allLists)
The result is the spawning of multiple GUIs, one for each process.
Per the bug report, in python 3.8, the default start method for multiprocessing when run on MacOS has been changed and is now "spawn" instead of "fork", so the problem will not reveal itself (unless you change the start method to be "fork", in which case the code will fail).
So I have a pyhthon application which im attempting to emulate a queue line up system. It import a library and calls to that library, specificaly psycopg2. An example code is as below
import threading,queue,psycopg2
q = queue.Queue()
def workerChecker():
while True:#Keeps the thread always checking for new things in queue
item = q.get()
addItemToDb(item) <------This part
q.task_done()
threading.Thread(target=workerChecker, daemon=True).start()
def addItemToDb(item):
#Do something and use psycopg2 to insert item to db here
So I can't seem to find a clear answer online on which thread will the codes in addItemToDb run in.
More specifically, will all the codes in the function addItemToDb be restricted to execution within the same thread as workerChecker ? Given that it uses an imported library.
Any assistance or help will be really appreciated...
The code inside addItemToDb will be restricted to the thread that runs workerChecker as long as it is called only by that function, but it can be used anywhere outside that thread in the main thread or any other thread that you create.
If you want to make sure that only workerChecker has access to that function you could define addItemToDb inside workerChecker
def workerChecker():
def addItemToDb(item):
# addItemToDb definition
pass
while True:
item = q.get()
addItemToDb(item)
q.task_done()
I have a project that I'm writing in Python that will be sending hardware (Phidgets) commands. Because I'll be interfacing with more than one hardware component, I need to have more than one loop running concurrently.
I've researched the Python multiprocessing module, but it turns out that the hardware can only be controlled by one process at a time, so all my loops need to run in the same process.
As of right now, I've been able to accomplish my task with a Tk() loop, but without actually using any of the GUI tools. For example:
from Tk import tk
class hardwareCommand:
def __init__(self):
# Define Tk object
self.root = tk()
# open the hardware, set up self. variables, call the other functions
self.hardwareLoop()
self.UDPListenLoop()
self.eventListenLoop()
# start the Tk loop
self.root.mainloop()
def hardwareLoop(self):
# Timed processing with the hardware
setHardwareState(self.state)
self.root.after(100,self.hardwareLoop)
def UDPListenLoop(self):
# Listen for commands from UDP, call appropriate functions
self.state = updateState(self.state)
self.root.after(2000,self.UDPListenLoop)
def eventListenLoop(self,event):
if event == importantEvent:
self.state = updateState(self.event.state)
self.root.after(2000,self.eventListenLoop)
hardwareCommand()
So basically, the only reason for defining the Tk() loop is so that I can call the root.after() command within those functions that need to be concurrently looped.
This works, but is there a better / more pythonic way of doing it? I'm also wondering if this method causes unnecessary computational overhead (I'm not a computer science guy).
Thanks!
The multiprocessing module is geared towards having multiple separate processes. Although you can use Tk's event loop, that is unnecessary if you don't have a Tk based GUI, so if you just want multiple tasks to execute in the same process you can use the Thread module. With it you can create specific classes which encapsulate a separate thread of execution, so you can have many "loops" executing simultaneously in the background. Think of something like this:
from threading import Thread
class hardwareTasks(Thread):
def hardwareSpecificFunction(self):
"""
Example hardware specific task
"""
#do something useful
return
def run(self):
"""
Loop running hardware tasks
"""
while True:
#do something
hardwareSpecificTask()
class eventListen(Thread):
def eventHandlingSpecificFunction(self):
"""
Example event handling specific task
"""
#do something useful
return
def run(self):
"""
Loop treating events
"""
while True:
#do something
eventHandlingSpecificFunction()
if __name__ == '__main__':
# Instantiate specific classes
hw_tasks = hardwareTasks()
event_tasks = eventListen()
# This will start each specific loop in the background (the 'run' method)
hw_tasks.start()
event_tasks.start()
while True:
#do something (main loop)
You should check this article to get more familiar with the threading module. Its documentation is a good read too, so you can explore its full potential.
I want to run a function continuoulsy in parallel to my main process.How do i do it in python?multiprocessing?threading or thread module?
I am new to python.Any help much appreciated.
If the aim is to capture stderr and do some action you can simply replace sys.stderr by a custom object:
>>> import sys
>>> class MyLogger(object):
... def __init__(self, callback):
... self._callback = callback
... def write(self, text):
... if 'log' in text:
... self._callback(text)
... sys.__stderr__.write(text) # continue writing to normal stderr
...
>>> def the_callback(s):
... print('Stderr: %r' % s)
...
>>> sys.stderr = MyLogger(the_callback)
>>> sys.stderr.write('Some log message\n')
Stderr: 'Some log message'
Some log message
>>>
>>> sys.stderr.write('Another message\n')
Another message
If you want to handle tracebacks and exceptions you can use sys.excepthook.
If you want to capture logs created by the logging module you can implement your own Handler class similar to the above Logger but reimplementing the emit method.
A more interesting, but less practical solution would be to use some kind of scheduler and generators to simulate parallel execution without actually creating threads(searching on the internet will yield some nice results about this)
It definitely depends on your aim, but I'd suggest looking at the threading module. There are many good StackOverflow questions on the use of threading and multithreading (e.g., Multiprocessing vs Threading Python).
Here's a brief skeleton from one of my projects:
import threading # Threading module itself
import Queue # A handy way to pass tasks to your thread
job_queue = Queue.Queue()
job_queue.append('one job to do')
# This is the function that we want to keep running while our program does its thing
def function_to_run_in_background():
# Do something...here is one form of flow control
while True:
job_to_do = job_queue.get() # Get the task from the Queue
print job_to_do # Print what it was we fetched
job_queue.task_done() # Signal that we've finished with that queue item
# Launch the thread...
t = threadingThread(target=function_to_run_in_background, args=(args_to_pass,))
t.daemon = True # YOU MAY NOT WANT THIS: Only use this line if you want the program to exit without waiting for the thread to finish
t.start() # Starts the thread
t.setName('threadName') # Makes it easier to interact with the thread later
# Do other stuff
sleep(5)
print "I am still here..."
job_queue.append('Here is another job for the thread...')
# Wait for everything in job_queue to finish. Since the thread is a daemon, the program will now exit, killing the thread.
job_queue.join()
if you just want to run a function in background in the same process, do:
import thread
def function(a):
pass
thread.start_new(function, (1,)) # a is 1 then
I found that client-server architecture was solution for me. Running server, and spawning many clients talking to server and between clients directly, something like messenger.
Talking/comunication can be achieved through network or text file located in memory, (to speed things up and save hard drive).
Bakuriu: give u a good tip about logging module.
I have two functions, draw_ascii_spinner and findCluster(companyid).
I would like to:
Run findCluster(companyid) in the backround and while its processing....
Run draw_ascii_spinner until findCluster(companyid) finishes
How do I begin to try to solve for this (Python 2.7)?
Use threads:
import threading, time
def wrapper(func, args, res):
res.append(func(*args))
res = []
t = threading.Thread(target=wrapper, args=(findcluster, (companyid,), res))
t.start()
while t.is_alive():
# print next iteration of ASCII spinner
t.join(0.2)
print res[0]
You can use multiprocessing. Or, if findCluster(companyid) has sensible stopping points, you can turn it into a generator along with draw_ascii_spinner, to do something like this:
for tick in findCluster(companyid):
ascii_spinner.next()
Generally, you will use Threads. Here is a simplistic approach which assumes, that there are only two threads: 1) the main thread executing a task, 2) the spinner thread:
#!/usr/bin/env python
import time
import thread
def spinner():
while True:
print '.'
time.sleep(1)
def task():
time.sleep(5)
if __name__ == '__main__':
thread.start_new_thread(spinner, ())
# as soon as task finishes (and so the program)
# spinner will be gone as well
task()
This can be done with threads. FindCluster runs in a separate thread and when done, it can simply signal another thread that is polling for a reply.
You'll want to do some research on threading, the general form is going to be this
Create a new thread for findCluster and create some way for the program to know the method is running - simplest in Python is just a global boolean
Run draw_ascii_spinner in a while loop conditioned on whether it is still running, you'll probably want to have this thread sleep for a short period of time between iterations
Here's a short tutorial in Python - http://linuxgazette.net/107/pai.html
Run findCluster() in a thread (the Threading module makes this very easy), and then draw_ascii_spinner until some condition is met.
Instead of using sleep() to set the pace of the spinner, you can wait on the thread's wait() with a timeout.
It is possible to have a working example? I am new in Python. I have 6 tasks to run in one python program. These 6 tasks should work in coordinations, meaning that one should start when another finishes. I saw the answers , but I couldn't adopted the codes you shared to my program.
I used "time.sleep" but I know that it is not good because I cannot know how much time it takes each time.
# Sending commands
for i in range(0,len(cmdList)): # port Sending commands
cmd = cmdList[i]
cmdFull = convert(cmd)
port.write(cmd.encode('ascii'))
# s = port.read(10)
print(cmd)
# Terminate the command + close serial port
port.write(cmdFull.encode('ascii'))
print('Termination')
port.close()
# time.sleep(1*60)