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How to Avoid Python Programs from Hanging When Reading Process Output?

Susan Sarandon
Susan SarandonOriginal
2024-11-02 13:54:29413browse

How to Avoid Python Programs from Hanging When Reading Process Output?

Stop reading process output in Python without hang?

Problem:

A Python program needs to interact with an external process (e.g., "top") that continuously produces output. However, simply reading the output directly can cause the program to hang indefinitely.

Solution:

To prevent hanging, it's essential to employ non-blocking or asynchronous mechanisms when reading process output. Here are a few possible approaches:

Spooled Temporary File (Recommended)

This method utilizes a dedicated file object to store the process output.

#!/usr/bin/env python<br>import subprocess<br>import tempfile<br>import time</p>
<p>def main():</p>
<pre class="brush:php;toolbar:false"># Open a temporary file (automatically deleted on closure)
f = tempfile.TemporaryFile()

# Start the process and redirect stdout to the file
p = subprocess.Popen(["top"], stdout=f)

# Wait for a specified duration
time.sleep(2)

# Kill the process
p.terminate()
p.wait()

# Rewind and read the captured output from the file
f.seek(0)
output = f.read()

# Print the output
print(output)
f.close()

if name == "__main__":

main()

Thread-based Output Reading

This approach employs a separate thread to continuously read the process output while the main thread proceeds with other tasks.

import collections<br>import subprocess<br>import threading<br>import time</p>
<p>def read_output(process, append):</p>
<pre class="brush:php;toolbar:false">for line in iter(process.stdout.readline, ""):
    append(line)

def main():

# Start the process and redirect stdout
process = subprocess.Popen(["top"], stdout=subprocess.PIPE, close_fds=True)

# Create a thread for output reading
q = collections.deque(maxlen=200)
t = threading.Thread(target=read_output, args=(process, q.append))
t.daemon = True
t.start()

# Wait for the specified duration
time.sleep(2)

# Print the saved output
print(''.join(q))

if name == "__main__":

main()

signal.alarm() (Unix-only)

This method uses Unix signals to terminate the process after a specified timeout, regardless of whether all output has been read.

import collections<br>import signal<br>import subprocess</p>
<p>class Alarm(Exception):</p>
<pre class="brush:php;toolbar:false">pass

def alarm_handler(signum, frame):

raise Alarm

def main():

# Start the process and redirect stdout
process = subprocess.Popen(["top"], stdout=subprocess.PIPE, close_fds=True)

# Set signal handler
signal.signal(signal.SIGALRM, alarm_handler)
signal.alarm(2)

try:
    # Read and save a specified number of lines
    q = collections.deque(maxlen=200)
    for line in iter(process.stdout.readline, ""):
        q.append(line)
    signal.alarm(0)  # Cancel alarm
except Alarm:
    process.terminate()
finally:
    # Print the saved output
    print(''.join(q))

if name == "__main__":

main()

threading.Timer

This approach employs a timer to terminate the process after a specified timeout. It works on both Unix and Windows systems.

import collections<br>import subprocess<br>import threading</p>
<p>def main():</p>
<pre class="brush:php;toolbar:false"># Start the process and redirect stdout
process = subprocess.Popen(["top"], stdout=subprocess.PIPE, close_fds=True)

# Create a timer for process termination
timer = threading.Timer(2, process.terminate)
timer.start()

# Read and save a specified number of lines
q = collections.deque(maxlen=200)
for line in iter(process.stdout.readline, ""):
    q.append(line)
timer.cancel()

# Print the saved output
print(''.join(q))

if name == "__main__":

main()

No Threads, No Signals

This method uses a simple time-based loop to check for process output and kill it if it exceeds a specified timeout.

import collections<br>import subprocess<br>import sys<br>import time</p>
<p>def main():</p>
<pre class="brush:php;toolbar:false">args = sys.argv[1:]
if not args:
    args = ['top']

# Start the process and redirect stdout
process = subprocess.Popen(args, stdout=subprocess.PIPE, close_fds=True)

# Save a specified number of lines
q = collections.deque(maxlen=200)

# Set a timeout duration
timeout = 2

now = start = time.time()
while (now - start) < timeout:
    line = process.stdout.readline()
    if not line:
        break
    q.append(line)
    now = time.time()
else:  # On timeout
    process.terminate()

# Print the saved output
print(''.join(q))

if name == "__main__":

main()

Note: The number of lines stored can be adjusted as needed by setting the 'maxlen' parameter of the deque data structure.

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