Develop Reference

Two threads reading/writing on the same serial port at the same time

Imagine we have a thread reading a temperature sensor 10 times per second via USB serial port.
And, when a user presses a button, we can change the sensor mode, also via USB serial.
Problem: the change_sensor_mode() serial write operation can happen in the middle of the polling thread "write/read_until" serial operation, and this causes serial data corruption.
How to handle this general multithreading problem with Python serial?
Example:
import threading, serial, time
serial_port = serial.Serial(port="COM2", timeout=1.0)
def poll_temperature():
while True:
serial_port.write(b"GETTEMP\r\n")
recv = serial_port.read_until(b"END")
print(recv)
time.sleep(0.2)
def change_sensor_mode():
serial_port.write(b"CHANGEMODE2\r\n")
t1 = threading.Thread(target=poll_temperature)
t1.start()
time.sleep(4.12342) # simulate waiting for user input
change_sensor_mode()
I was thinking about adding a manual lock = True / lock = False before/after the serial operation in poll_temperature, and then the main thread should wait:
global lock
def change_sensor_mode():
elapsed = 0
t0 = time.time()
while lock and elapsed < 1.0:
time.sleep(0.010)
elapsed += 0.010
serial_port.write(b"CHANGEMODE2\r\n")
but there is surely a more standard way to achieve this. How to handle multiple threads writing to serial?

You should use a threading.Lock that is shared by any thread that wants to write to this serial port.
import threading
write_lock = threading.Lock() # all writers have to lock this
read_lock = threading.Lock() # all readers have to lock this
def poll_temperature():
while True:
with write_lock:
serial_port.write(b"GETTEMP\r\n")
with read_lock:
recv = serial_port.read_until(b"END")
print(recv)
time.sleep(0.2)
def change_sensor_mode():
with write_lock:
serial_port.write(b"CHANGEMODE2\r\n")
The way this works is that no two threads can be executing any code that is guarded by the same lock at the same time, so if one thread tries to execute the second function while another thread is executing the write in the first function, then the second thread must wait until the first thread releases the lock.
Using it in a context manager means that if one of the threads failed inside of that block then the lock is automatically released which avoids a deadlock.

Best way to respond quickly to a variable that is changed by another thread

I have written a program to consume data that I am sending to it via UDP packets every 10 milliseconds. I am using separate threads because it can take a variable amount of time to run the logic to process the data and if more than 10ms have elapsed I just want it to process the most recently received datagram. I am currently running a while loop and checking every millisecond for a new quote via time.sleep(0.001). I just learned that this time.sleep() is actually taking up to 16 milliseconds to process on a windows server 2019 operating system and it is delaying everything. I could just put pass instead of time.sleep but this ends up using too much CPU (I am running multiple instances of the program). Is there a way I can have the program pause and just wait for maindata.newquote == True before proceeding? The trick is I would like it to respond very quickly (in less than a millisecond) rather than waiting for the next windows timer interrupt.
class maindata:
newquote = False
quote = ''
def startquotesUDP(maindata,myaddress,port):
UDPServerSocket = socket(family=AF_INET, type=SOCK_DGRAM)
UDPServerSocket.bind((myaddress, port))
while True:
bytesAddressPair = UDPServerSocket.recvfrom(bufferSize)
#parse raw data
maindata.quote = parsed_data
maindata.newquote = True
threading.Thread(target=startquotesUDP,args=(maindata,address,port,)).start()
while True:
if maindata.newquote == False:
time.sleep(0.001) #This is what I want to improve
else:
#process maindata.quote
maindata.newquote = False

My answer is the same as #balmy above, but I wouldn't even bother with a semaphore.
The producer just writes to a queue
while True:
result = ...
queue.put(result)
sleep as necessary
The receiver can receive every result by doing
while True:
result = queue.get()
handle result
If you prefer only to see the most recent result sent by the producer, in case it has send multiple results since the last time you looked, then:
while True:
result = queue.get()
while not queue.empty():
result = queue.get()
handle result

Stopping a Client Thread

I use the following class the listen to around 20 udp ports. There is a problem though with this class in regard to how I stop it. Since I join the thread in the stop method I will have to wait for up to one second for each class to stop since recv has a timeout of one second. How would you recommend I solve this issue?
class UpdClient(threading.Thread):
def __init__(self,port):
super(UpdClient, self).__init__()
self.port = port
self.finished = False
self.sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
self.sock.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
self.sock.bind(('225.0.0.10', self.port))
self.sock.settimeout(1)
def run(self):
while not self.finished:
try:
message = self.sock.recv(4096)
print("*")
except socket.timeout:
continue
def stop(self):
self.finished = True
if self.is_alive():
self.join()
print("Exiting :" + str(self.port))

There is one easy fix you can do to improve this: Split your stop function up into two separate functions, like this:
def stop(self):
self.finished = True
print("Stopping :" + str(self.port))
def wait(self):
self.stop()
if self.is_alive():
self.join()
print("Exiting :" + str(self.port))
And then do this:
for t in threads:
t.stop()
for t in threads:
t.wait()
With 20 threads, this should reduce your average stop time from ~10 seconds to ~1.1 seconds.
But if you want better than this, like a guarantee of 1 second, or an average time below 1 second, there's no good, easy way around this. Some possibly-bad and/or hard options include:
send a message to your own socket, as suggested by User. If your code knows how to handle "garbage" messages, or if your protocol makes it simple to add a new message type that can be easily distinguished from the "real" messages, this should wake your threads up to shut them down very quickly.
close the sockets out from under the client threads. On some platforms, this will cause the recv to fail immediately (you'll want an except to handle that, of course). On others, it will cause it to EOF immediately (which you already handle). There are some platforms where neither happens, and it just continues to block. So you'll really need to test on every platform you care about.*
self.daemon = True. Then you can hard-kill all the threads just by exiting without joining them. With all the downsides that implies.
Completely rewrite your app to use a single-threaded reactor or a multi-threaded proactor (ideally indirectly, through something like asyncio, twisted, or gevent…), instead of a thread per client.
Change the 1-second waits to a loop over waits of no more than 100ms (or however long is acceptable for quit time).
Just accept the 1-second time to quit.
* Off the top of my head, I believe Windows guarantees an error, Linux guarantees either an error or continuing to block but usually continues to block, BSD doesn't guarantee anything but usually continues to block, SysV doesn't guarantee anything but usually EOFs. But don't trust the top of my head; test the platforms you care about.

Under Windows, add this:
def stop(self):
self.sock.close()
# ...
This creates the error:
OSError: [WinError 10004] A blocking operation was interrupted by a call to WSACancelBlockingCall
in the Thread.

Threadsafe printing across multiple processes python 2.x

I have experienced a very weird issue that I just can't explain when dealing with printing to a file from multiple processes (started with the subprocess module). The behavior I am seeing is that some of my output is slightly truncated and some of it is just completely missing. I am using a slightly modified version of Alex Martelli's solution for thread safe printing found here How do I get a thread safe print in Python 2.6?. The main difference is in the write method. To guarantee that output is not interleaved between the multiple processes writing to the same file I buffer the output and only write when I see a newline.
import sys
import threading
tls = threading.local()
class ThreadSafeFile(object):
"""
#author: Alex Martelli
#see: https://stackoverflow.com/questions/3029816/how-do-i-get-a-thread-safe-print-in-python-2-6
#summary: Allows for safe printing of output of multi-threaded programs to stdout.
"""
def __init__(self, f):
self.f = f
self.lock = threading.RLock()
self.nesting = 0
self.dataBuffer = ""
def _getlock(self):
self.lock.acquire()
self.nesting += 1
def _droplock(self):
nesting = self.nesting
self.nesting = 0
for i in range(nesting):
self.lock.release()
def __getattr__(self, name):
if name == 'softspace':
return tls.softspace
else:
raise AttributeError(name)
def __setattr__(self, name, value):
if name == 'softspace':
tls.softspace = value
else:
return object.__setattr__(self, name, value)
def write(self, data):
self._getlock()
self.dataBuffer += data
if data == '\n':
self.f.write(self.dataBuffer)
self.f.flush()
self.dataBuffer = ""
self._droplock()
def flush(self):
self.f.flush()
It should also be noted that to get this to behave abnormally it is going to require either a lot of time or a machine with multiple processors or cores. I ran the offending program in my test suite ~7000 times on a single processor machine before it reported a failure. This program that I've created to demonstrate the issue I've been experiencing in my test suite also seems to work on a single processor machine, but when you execute it on a multicore or multiprocessor machine it will certainly fail.
The following program shows the issue and it is somewhat more involved than I wanted it to be, but I wanted to preserve enough of the behavior of my programs as possible.
The code for process 1 main.py
import subprocess, sys, socket, time, random
from threadSafeFile import ThreadSafeFile
sys.stdout = ThreadSafeFile(sys.__stdout__)
usage = "python main.py nprocs niters"
workerFilename = "/path/to/worker.py"
def startMaster(n, iters):
host = socket.gethostname()
for i in xrange(n):
#set up ~synchronization between master and worker
sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
sock.bind((host,0))
sock.listen(1)
socketPort = sock.getsockname()[1]
cmd = 'ssh %s python %s %s %d %d %d' % \
(host, workerFilename, host, socketPort, i, iters)
proc = subprocess.Popen(cmd.split(), shell=False, stdout=None, stderr=None)
conn, addr = sock.accept()
#wait for worker process to start
conn.recv(1024)
for j in xrange(iters):
#do very bursty i/o
for k in xrange(iters):
print "master: %d iter: %d message: %d" % (n,i, j)
#sleep for some amount of time between .02s and .5s
time.sleep(1 * (random.randint(1,50) / float(100)))
#wait for worker to finish
conn.recv(1024)
sock.close()
proc.kill()
def main(nprocs, niters):
startMaster(nprocs, niters)
if __name__ == "__main__":
if len(sys.argv) != 3:
print usage
sys.exit(1)
nprocs = int(sys.argv[1])
niters = int(sys.argv[2])
main(nprocs, niters)
code for process 2 worker.py
import sys, socket,time, random, time
from threadSafeFile import ThreadSafeFile
usage = "python host port id iters"
sys.stdout = ThreadSafeFile(sys.__stdout__)
def main(host, port, n, iters):
#tell master to start
sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
sock.connect((host, port))
sock.send("begin")
for i in xrange(iters):
#do bursty i/o
for j in xrange(iters):
print "worker: %d iter: %d message: %d" % (n,i, j)
#sleep for some amount of time between .02s and .5s
time.sleep(1 * (random.randint(1,50) / float(100)))
#tell master we are done
sock.send("done")
sock.close()
if __name__ == "__main__":
if len(sys.argv) != 5:
print usage
sys.exit(1)
host = sys.argv[1]
port = int(sys.argv[2])
n = int(sys.argv[3])
iters = int(sys.argv[4])
main(host,port,n,iters)
When testing I ran main.py as follows:
python main.py 1 75 > main.out
The resulting file should be of length 75*75*2 = 11250 lines of the format:
(master|worker): %d iter: %d message: %d
Most of the time it is short 20-30 lines, but I have seen on occasion the program having the appropriate number of lines. After further investigation of the rare successes some of the lines are being truncated with something like:
ter: %d message: %d
Another interesting aspect to this is that when starting the ssh process using multiprocessing instead of subprocess this program behaves as intended. Some may just say why bother using subprocess when multiprocessing works fine. Unfortunately, it is the academic in me that really wants to know why this is behaving abnormally. Any thoughts and/or insights would be very appreciated. Thanks.
***edit
Ben I understand that threadSafeFile uses different locks per process, but I need it in my larger project for 2 reasons.
1) Each process may have multiple threads that will be writing to stdout even though this example does not. So I need to guarantee both safety at the thread level and at the process level.
2) If I don't make sure that when stdout gets flushed that there is a '\n' at the end of the buffer then there is going to be some potential execution trace where process 1 writes its buffer to a file without a trailing '\n' and then process 2 comes in and writes its buffer. Now we have lines interleaving and that's not what I want.
I also understand that this mechanism makes things a bit restrictive for what can be printed. Right now, in my stage of development of this project, restrictiveness is ok. When I can guarantee correctness I can start to relax the restrictions.
Your comment about locking inside of the conditional check if data == '\n' is incorrect. If the lock goes inside the conditional check then threadSafeFile is no longer thread safe in the general case. If any thread can add to the data buffer then there will be a race condition at dataBuffer += data as this is not an atomic operation. Perhaps your comment is simply related to this example in which we only have 1 thread per process, but if that's the case then we don't even need a lock at all.
In regards to OS level locks, my understanding was that multiple programs were able to safely write to the same file on a unix platform iff the number of bytes being written was smaller than the size of the internal buffer. Shouldn't the OS take care of all of the necessary locking for me in this case?

In each process you create a ThreadSafeFile for sys.stdout, each of which has a lock, but they're different locks; there's nothing connecting the locks used in all the different processes. So you're getting the same effect as if you used no locks at all; no process is ever going to be blocked by a lock held in another process, since they all have their own.
The only reason this works when run on a single processor machine is the buffering you do to queue up writes until a newline is encountered. This means that each line of output is written all in one go. On a uniprocessor, it's not unlikely that the OS will decide to switch processes in the middle of a bunch of successive calls to write, which would trash your data. But if the output is all written in chunks of a single line and you don't care about the order in which lines end up in the file, then it's very very unlikely for a context switch to happen in the middle of an operation you care about. Not theoretically impossible though, so I wouldn't call this code correct even for a uniprocessor.
ThreadSafeFile is very specifically only thread safe. It relies on the fact that the program only has a single ThreadSafeFile object for each file it's writing to. So any writes to that file are going to be going through that single object, synchronizing upon the lock.
When you have multiple processes, you don't have the shared global memory that threads in a single process do. So each process necessarily has its own separate ThreadSafeFile(sys.stdout) object. This is exactly the same mistake as if you had used threads and spawned N threads, each of which created its own ThreadSafeFile(sys.stdout).
I have no idea how this works when you use multiprocessing, because you haven't posted the code you used to do that. But my understanding is that this would still fail, for all the same reasons, if you used multiprocessing in such a way that each process created its own fresh ThreadSafeFile. Maybe you're not doing that in the version that uses multiprocessing?
What you need to do is arrange for the synchronization object (the lock) to be connected somehow. The multiprocessing module can do this for you. Note in the example here how the lock is created once and then passed in to each new process as it is created. (This still results in 10 different lock objects in 10 different processes of course, but what Python must be doing behind the scenes is creating an OS-level lock and then making each of the copied Python-level lock objects refer to the single OS-level lock).
If you want to do this with subprocessing, where you're just starting totally independent worker commands from separate scripts, then you'll need some way to get them all talking to a single OS-level lock. I don't know of anything in the standard library that helps you do that. I would just use multiprocessing.
As another thought, your buffering and locking code looks a little suspicious too. What happens if something calls sys.stdout.write("foo\n")? I'm not certain, but at a guess this is only working because the implementation of print happens to call sys.stdout.write on whatever you're printing, then call it again with a single newline. There is absolutely no reason it has to do this! It could just as easily assemble a single string of output in memory and then only call sys.stdout.write once. Plus, what happens if you need to print a block of multiple lines that need to go together in the output?
Another problem is that you acquire the lock the first time a process writes to the buffer, continue to hold it as the buffer is filled, then write the line, and finally release the lock. If your lock actually worked and a process took a long time between starting a line and finishing it it would block all other processes from even buffering up their writes! Maybe that's sort of what you want, if the intention that when a process starts writing something it gets a guarantee that its output will hit the file next. But in that case, you don't even need the buffering at all. I think you should be acquiring the lock just after if data == '\n':, and then you wouldn't need all that code tracking the nesting level either.

Sending data through a socket from another thread does not work in Python

This is my 'game server'. It's nothing serious, I thought this was a nice way of learning a few things about python and sockets.
First the server class initialized the server.
Then, when someone connects, we create a client thread. In this thread we continually listen on our socket.
Once a certain command comes in (I12345001001, for example) it spawns another thread.
The purpose of this last thread is to send updates to the client.
But even though I see the server is performing this code, the data isn't actually being sent.
Could anyone tell where it's going wrong?
It's like I have to receive something before I'm able to send. So I guess somewhere I'm missing something
#!/usr/bin/env python
"""
An echo server that uses threads to handle multiple clients at a time.
Entering any line of input at the terminal will exit the server.
"""
import select
import socket
import sys
import threading
import time
import Queue
globuser = {}
queue = Queue.Queue()
class Server:
def __init__(self):
self.host = ''
self.port = 2000
self.backlog = 5
self.size = 1024
self.server = None
self.threads = []
def open_socket(self):
try:
self.server = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
self.server.bind((self.host,self.port))
self.server.listen(5)
except socket.error, (value,message):
if self.server:
self.server.close()
print "Could not open socket: " + message
sys.exit(1)
def run(self):
self.open_socket()
input = [self.server,sys.stdin]
running = 1
while running:
inputready,outputready,exceptready = select.select(input,[],[])
for s in inputready:
if s == self.server:
# handle the server socket
c = Client(self.server.accept(), queue)
c.start()
self.threads.append(c)
elif s == sys.stdin:
# handle standard input
junk = sys.stdin.readline()
running = 0
# close all threads
self.server.close()
for c in self.threads:
c.join()
class Client(threading.Thread):
initialized=0
def __init__(self,(client,address), queue):
threading.Thread.__init__(self)
self.client = client
self.address = address
self.size = 1024
self.queue = queue
print 'Client thread created!'
def run(self):
running = 10
isdata2=0
receivedonce=0
while running > 0:
if receivedonce == 0:
print 'Wait for initialisation message'
data = self.client.recv(self.size)
receivedonce = 1
if self.queue.empty():
print 'Queue is empty'
else:
print 'Queue has information'
data2 = self.queue.get(1, 1)
isdata2 = 1
if data2 == 'Exit':
running = 0
print 'Client is being closed'
self.client.close()
if data:
print 'Data received through socket! First char: "' + data[0] + '"'
if data[0] == 'I':
print 'Initializing user'
user = {'uid': data[1:6] ,'x': data[6:9], 'y': data[9:12]}
globuser[user['uid']] = user
print globuser
initialized=1
self.client.send('Beginning - Initialized'+';')
m=updateClient(user['uid'], queue)
m.start()
else:
print 'Reset receivedonce'
receivedonce = 0
print 'Sending client data'
self.client.send('Feedback: ' +data+';')
print 'Client Data sent: ' + data
data=None
if isdata2 == 1:
print 'Data2 received: ' + data2
self.client.sendall(data2)
self.queue.task_done()
isdata2 = 0
time.sleep(1)
running = running - 1
print 'Client has stopped'
class updateClient(threading.Thread):
def __init__(self,uid, queue):
threading.Thread.__init__(self)
self.uid = uid
self.queue = queue
global globuser
print 'updateClient thread started!'
def run(self):
running = 20
test=0
while running > 0:
test = test + 1
self.queue.put('Test Queue Data #' + str(test))
running = running - 1
time.sleep(1)
print 'Updateclient has stopped'
if __name__ == "__main__":
s = Server()
s.run()

I don't understand your logic -- in particular, why you deliberately set up two threads writing at the same time on the same socket (which they both call self.client), without any synchronization or coordination, an arrangement that seems guaranteed to cause problems.
Anyway, a definite bug in your code is you use of the send method -- you appear to believe that it guarantees to send all of its argument string, but that's very definitely not the case, see the docs:
Returns the number of bytes sent.
Applications are responsible for
checking that all data has been sent;
if only some of the data was
transmitted, the application needs to
attempt delivery of the remaining
data.
sendall is the method that you probably want:
Unlike send(), this method continues
to send data from string until either
all data has been sent or an error
occurs.
Other problems include the fact that updateClient is apparently designed to never terminate (differently from the other two thread classes -- when those terminate, updateClient instances won't, and they'll just keep running and keep the process alive), redundant global statements (innocuous, just confusing), some threads trying to read a dict (via the iteritems method) while other threads are changing it, again without any locking or coordination, etc, etc -- I'm sure there may be even more bugs or problems, but, after spotting several, one's eyes tend to start to glaze over;-).

You have three major problems. The first problem is likely the answer to your question.
Blocking (Question Problem)
The socket.recv is blocking. This means that execution is halted and the thread goes to sleep until it can read data from the socket. So your third update thread just fills the queue up but it only gets emptied when you get a message. The queue is also emptied by one message at a time.
This is likely why it will not send data unless you send it data.
Message Protocol On Stream Protocol
You are trying to use the socket stream like a message stream. What I mean is you have:
self.server = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
The SOCK_STREAM part says it is a stream not a message such as SOCK_DGRAM. However, TCP does not support message. So what you have to do is build messages such as:
data =struct.pack('I', len(msg)) + msg
socket.sendall(data)
Then the receiving end will looking for the length field and read the data into a buffer. Once enough data is in the buffer it can grab out the entire message.
Your current setup is working because your messages are small enough to all be placed into the same packet and also placed into the socket buffer together. However, once you start sending large data over multiple calls with socket.send or socket.sendall you are going to start having multiple messages and partial messages being read unless you implement a message protocol on top of the socket byte stream.
Threads
Even though threads can be easier to use when starting out they come with a lot of problems and can degrade performance if used incorrectly especially in Python. I love threads so do not get me wrong. Python also has a problem with the GIL (global interpreter lock) so you get bad performance when using threads that are CPU bound. Your code is mostly I/O bound at the moment, but in the future it may become CPU bound. Also you have to worry about locking with threading. A thread can be a quick fix but may not be the best fix. There are circumstances where threading is quite simply the easiest way to break some time consuming process. So do not discard threads as evil or terrible. In Python they are considered bad mainly because of the GIL, and in other languages (including Python) because of concurrency issues so most people recommend you to use multiple processes with Python or use asynchronous code. The subject of to use a thread or not is very complex as it depends on the language (way your code is run), the system (single or multiple processors), and contention (trying to share a resource with locking), and other factors, but generally asynchronous code is faster because it utilizes more CPU with less overhead especially if you are not CPU bound.
The solution is the usage of the select module in Python, or something similar. It will tell you when a socket has data to be read, and you can set a timeout parameter.
You can gain more performance by doing asynchronous work (asynchronous sockets). To turn a socket into asynchronous mode you simply call socket.settimeout(0) which will make it not block. However, you will constantly eat CPU spinning waiting for data. The select module and friends will prevent you from spinning.
Generally for performance you want to do as much asynchronous (same thread) as possible, and then expand with more threads that are also doing as much asynchronously as possible. However as previously noted Python is an exception to this rule because of the GIL (global interpreter lock) which can actually degrade performance from what I have read. If you are interesting you should try writing a test case and find out!
You should also check out the thread locking primitives in the threading module. They are Lock, RLock, and Condition. They can help multiple threads share data with out problems.
lock = threading.Lock()
def myfunction(arg):
with lock:
arg.do_something()
Some Python objects are thread safe and others are not.
Sending Updates Asynchronously (Improvement)
Instead of using a third thread only to send updates you could instead use the client thread to send updates by checking the current time with the last time an update was sent. This would remove the usage of a Queue and a Thread. Also to do this you must convert your client code into asynchronous code and have a timeout on your select so that you can at interval check the current time to see if an update is needed.
Summary
I would recommend you rewrite your code using asynchronous socket code. I would also recommend that you use a single thread for all clients and the server. This will improve performance and decrease latency. It would make debugging easier because you would have no possible concurrency issues like you have with threads. Also, fix your message protocol before it fails.