Possible Duplicate:
Python: single instance of program
I need to prevent a cron job from running concurrent instances when a job takes longer to complete than the launcher interval. I'm trying to use the flock concept to achieve this, but fcntl module is not behaving the way I expect.
Can anyone tell me why this works to prevent two concurrent instances:
import sys
import time
import fcntl
file_path = '/var/lock/test.py'
file_handle = open(file_path, 'w')
try:
fcntl.lockf(file_handle, fcntl.LOCK_EX | fcntl.LOCK_NB)
print 'no other instance is running'
for i in range(5):
time.sleep(1)
print i + 1
except IOError:
print 'another instance is running exiting now'
sys.exit(0)
And why this does not work:
import sys
import time
import fcntl
def file_is_locked(file_path):
file_handle = open(file_path, 'w')
try:
fcntl.lockf(file_handle, fcntl.LOCK_EX | fcntl.LOCK_NB)
return False
except IOError:
return True
file_path = '/var/lock/test.py'
if file_is_locked(file_path):
print 'another instance is running exiting now'
sys.exit(0)
else:
print 'no other instance is running'
for i in range(5):
time.sleep(1)
print i + 1
My humble opinion (although I may be totally wrong) is that file_handle
is local to the function (in the second case) and therefore, it gets destroyed once the function is done.
The following code seems to work as expected:
#!/usr/bin/env python
#http://stackoverflow.com/questions/14406562/prevent-running-concurrent-instances-of-a-python-script
import sys
import time
import fcntl
file_handle = None
def file_is_locked(file_path):
global file_handle
file_handle= open(file_path, 'w')
try:
fcntl.lockf(file_handle, fcntl.LOCK_EX | fcntl.LOCK_NB)
return False
except IOError:
return True
file_path = '/var/lock/test.py'
if file_is_locked(file_path):
print 'another instance is running exiting now'
sys.exit(0)
else:
print 'no other instance is running'
for i in range(5):
time.sleep(1)
print i + 1
Notice that the only thing I did is setting file_handle
as global variable (although I copied the whole code to have a working example)