I've recently started experimenting with using Python for web development. So far I've had some success using Apache with mod_wsgi and the Django web framework for Python 2.7. However I have run into some issues with having processes constantly running, updating information and such.
I have written a script I call "daemonManager.py" that can start and stop all or individual python update loops (Should I call them Daemons?). It does that by forking, then loading the module for the specific functions it should run and starting an infinite loop. It saves a PID file in /var/run to keep track of the process. So far so good. The problems I've encountered are:
Now and then one of the processes will just quit. I check ps in the morning and the process is just gone. No errors were logged (I'm using the logging module), and I'm covering every exception I can think of and logging them. Also I don't think these quitting processes has anything to do with my code, because all my processes run completely different code and exit at pretty similar intervals. I could be wrong of course. Is it normal for Python processes to just die after they've run for days/weeks? How should I tackle this problem? Should I write another daemon that periodically checks if the other daemons are still running? What if that daemon stops? I'm at a loss on how to handle this.
How can I programmatically know if a process is still running or not? I'm saving the PID files in /var/run and checking if the PID file is there to determine whether or not the process is running. But if the process just dies of unexpected causes, the PID file will remain. I therefore have to delete these files every time a process crashes (a couple of times per week), which sort of defeats the purpose. I guess I could check if a process is running at the PID in the file, but what if another process has started and was assigned the PID of the dead process? My daemon would think that the process is running fine even if it's long dead. Again I'm at a loss just how to deal with this.
Any useful answer on how to best run infinite Python processes, hopefully also shedding some light on the above problems, I will accept
I'm using Apache 2.2.14 on an Ubuntu machine.
My Python version is 2.7.2
I'll open by stating that this is one way to manage a long running process (LRP) -- not de facto by any stretch.
In my experience, the best possible product comes from concentrating on the specific problem you're dealing with, while delegating supporting tech to other libraries. In this case, I'm referring to the act of backgrounding processes (the art of the double fork), monitoring, and log redirection.
My favorite solution is http://supervisord.org/
Using a system like supervisord, you basically write a conventional python script that performs a task while stuck in an "infinite" loop.
#!/usr/bin/python
import sys
import time
def main_loop():
while 1:
# do your stuff...
time.sleep(0.1)
if __name__ == '__main__':
try:
main_loop()
except KeyboardInterrupt:
print >> sys.stderr, '\nExiting by user request.\n'
sys.exit(0)
Writing your script this way makes it simple and convenient to develop and debug (you can easily start/stop it in a terminal, watching the log output as events unfold). When it comes time to throw into production, you simply define a supervisor config that calls your script (here's the full example for defining a "program", much of which is optional: http://supervisord.org/configuration.html#program-x-section-example).
Supervisor has a bunch of configuration options so I won't enumerate them, but I will say that it specifically solves the problems you describe:
Backgrounding/Daemonizing
PID tracking (can be configured to restart a process should it terminate unexpectedly)
Log normally in your script (stream handler if using logging module rather than printing) but let supervisor redirect to a file for you.
You should consider Python processes as able to run "forever" assuming you don't have any memory leaks in your program, the Python interpreter, or any of the Python libraries / modules that you are using. (Even in the face of memory leaks, you might be able to run forever if you have sufficient swap space on a 64-bit machine. Decades, if not centuries, should be doable. I've had Python processes survive just fine for nearly two years on limited hardware -- before the hardware needed to be moved.)
Ensuring programs restart when they die used to be very simple back when Linux distributions used SysV-style init -- you just add a new line to the /etc/inittab and init(8) would spawn your program at boot and re-spawn it if it dies. (I know of no mechanism to replicate this functionality with the new upstart init-replacement that many distributions are using these days. I'm not saying it is impossible, I just don't know how to do it.)
But even the init(8) mechanism of years gone by wasn't as flexible as some would have liked. The daemontools package by DJB is one example of process control-and-monitoring tools intended to keep daemons living forever. The Linux-HA suite provides another similar tool, though it might provide too much "extra" functionality to be justified for this task. monit is another option.
I assume you are running Unix/Linux but you don't really say. I have no direct advice on your issue. So I don't expect to be the "right" answer to this question. But there is something to explore here.
First, if your daemons are crashing, you should fix that. Only programs with bugs should crash. Perhaps you should launch them under a debugger and see what happens when they crash (if that's possible). Do you have any trace logging in these processes? If not, add them. That might help diagnose your crash.
Second, are your daemons providing services (opening pipes and waiting for requests) or are they performing periodic cleanup? If they are periodic cleanup processes you should use cron to launch them periodically rather then have them run in an infinite loop. Cron processes should be preferred over daemon processes. Similarly, if they are services that open ports and service requests, have you considered making them work with INETD? Again, a single daemon (inetd) should be preferred to a bunch of daemon processes.
Third, saving a PID in a file is not very effective, as you've discovered. Perhaps a shared IPC, like a semaphore, would work better. I don't have any details here though.
Fourth, sometimes I need stuff to run in the context of the website. I use a cron process that calls wget with a maintenance URL. You set a special cookie and include the cookie info in with wget command line. If the special cookie doesn't exist, return 403 rather than performing the maintenance process. The other benefit here is login to the database and other environmental concerns of avoided since the code that serves normal web pages are serving the maintenance process.
Hope that gives you ideas. I think avoiding daemons if you can is the best place to start. If you can run your python within mod_wsgi that saves you having to support multiple "environments". Debugging a process that fails after running for days at a time is just brutal.
Related
I was wondering what the best practice solution would be to constantly monitor and resart processes, because there are multiple ways in doing it.
Additional info:
I have a unix program which uses multiple processes to work. There's a main process, it always starts first and is not likely to die or terminate without stopping the program.
Then I spawn multiple "module" processes, which take care of some work and communicate through the main process. Those modules sometimes die because of exceptions, and because it's an external program I can't resolve the issues, so I have to restart them if they die.
I've made a program to check if any of the modules died and restart them, but I need to run it manually. My program checks if the pid files of the modules exist and if they listen on a specific tcp port. If the pid file doesn't exist or the socket can't establish connection, it restarts the module.
My thoughts so far:
Cron job to run the checks every minute and restart any dead modules. (kind of an overkill, because they don't die that frequently)
Daemon running in the background, which starts the modules and receives notifications if they die, so it doesn't have to check them constantly. (SIGCHLD signal, os.wait)
If I use the daemon method, how should I communicate with the daemon through my interface? (socket, or maybe a file which gets read if the daemon receives a specific signal)
Usually I would just go with the daemon because it seems to be the best practice method to restart the modules asap(cron only runs once a minute), but I've wanted to get some opinions from more experienced users. (I've never done something like this before, and asking doesn't hurt anyone :D)
I apologize if these questions are answered somewhere else, but I couldn't find any related question.
P.S. If I forgot something or you need more infos, please feel free to ask. :)
I would investigate running the monitoring process as part of a dedicated monitoring framework. Monit is one example, however there are of course others.
This has the advantage of providing additional features which might be useful, such as email alerts and analytics. In my experience, you should be able to use your existing program without too much modification, and Monit itself uses few system resources if that is a concern.
Before you go any further, I am currently working in a very restricted environment. Installing additional dll's/exe's, and other admin like activities are frustratingly difficult. I am fully aware that some of the methodology described in this post is far from best practice...
I would like to start a long running background process that start/stops with Apache. I have a cgi enabled python script that takes as input all of the parameters necessary to run a complex "job". It is not feasible to run this job in the cgi script itself - because a)cgi is already slow to begin with and b)multiple simultaneous requests would definitely cause trouble. The cgi script will do nothing more than enter the parameters into a "jobs" database.
Normally, I would set something up like MSMQ in conjunction with a Windows Service. I would have a web service add a job to the queue, and the windows service would be polling the queue at some standard interval - processing jobs in sequence...
How could I accomplish the same in Apache? I can easily enough create a python script to serve as the background job processor. My questions are:
how do I start it process up with, leave it running with, and stop with Apache?
how can i monitor the process - make sure stays alive with Apache?
Any tips or insight welcome.
Note. OS is Windows Server 2008
Heres a pretty hacky solution for anyone looking to do something similar.
Set up a windows scheduled task that does that background processing. set it to run once a day or whatever interval you want (it is irrelevant, as you'll see in next steps)
In the Settings tab of the Scheduled Task - make sure the "Allow task to be run on demand" option is checked. Also, under the "If the task is already running..." text, make sure the Do not start a new instance option in selected.
Then, from the cgi script - it is possible to invoke the scheduled task from the command line(subprocess module) see here. With the options set above - if the task is already running - any subsequent run on demands are ignored.
I would like to have my Python program run in the background as a daemon, on either Windows or Unix. I see that the python-daemon package is for Unix only; is there an alternative for cross platform? If possible, I would like to keep the code as simple as I can.
In Windows it's called a "service" and you could implement it pretty easily e.g. with the win32serviceutil module, part of pywin32. Unfortunately the two "mental models" -- service vs daemon -- are very different in detail, even though they serve similar purposes, and I know of no Python facade that tries to unify them into a single framework.
This question is 6 years old, but I had the same problem, and the existing answers weren't cross-platform enough for my use case. Though Windows services are often used in similar ways as Unix daemons, at the end of the day they differ substantially, and "the devil's in the details". Long story short, I set out to try and find something that allows me to run the exact same application code on both Unix and Windows, while fulfilling the expectations for a well-behaved Unix daemon (which is better explained elsewhere) as best as possible on both platforms:
Close open file descriptors (typically all of them, but some applications may need to protect some descriptors from closure)
Change the working directory for the process to a suitable location to prevent "Directory Busy" errors
Change the file access creation mask (os.umask in the Python world)
Move the application into the background and make it dissociate itself from the initiating process
Completely divorce from the terminal, including redirecting STDIN, STDOUT, and STDERR to different streams (often DEVNULL), and prevent reacquisition of a controlling terminal
Handle signals, in particular, SIGTERM.
The fundamental problem with cross-platform daemonization is that Windows, as an operating system, really doesn't support the notion of a daemon: applications that start from a terminal (or in any other interactive context, including launching from Explorer, etc) will continue to run with a visible window, unless the controlling application (in this example, Python) has included a windowless GUI. Furthermore, Windows signal handling is woefully inadequate, and attempts to send signals to an independent Python process (as opposed to a subprocess, which would not survive terminal closure) will almost always result in the immediate exit of that Python process without any cleanup (no finally:, no atexit, no __del__, etc).
Windows services (though a viable alternative in many cases) were basically out of the question for me: they aren't cross-platform, and they're going to require code modification. pythonw.exe (a windowless version of Python that ships with all recent Windows Python binaries) is closer, but it still doesn't quite make the cut: in particular, it fails to improve the situation for signal handling, and you still cannot easily launch a pythonw.exe application from the terminal and interact with it during startup (for example, to deliver dynamic startup arguments to your script, say, perhaps, a password, file path, etc), before "daemonizing".
In the end, I settled on using subprocess.Popen with the creationflags=subprocess.CREATE_NEW_PROCESS_GROUP keyword to create an independent, windowless process:
import subprocess
independent_process = subprocess.Popen(
'/path/to/pythonw.exe /path/to/file.py',
creationflags=subprocess.CREATE_NEW_PROCESS_GROUP
)
However, that still left me with the added challenge of startup communications and signal handling. Without going into a ton of detail, for the former, my strategy was:
pickle the important parts of the launching process' namespace
Store that in a tempfile
Add the path to that file in the daughter process' environment before launching
Extract and return the namespace from the "daemonization" function
For signal handling I had to get a bit more creative. Within the "daemonized" process:
Ignore signals in the daemon process, since, as mentioned, they all terminate the process immediately and without cleanup
Create a new thread to manage signal handling
That thread launches daughter signal-handling processes and waits for them to complete
External applications send signals to the daughter signal-handling process, causing it to terminate and complete
Those processes then use the signal number as their return code
The signal handling thread reads the return code, and then calls either a user-defined signal handler, or uses a cytpes API to raise an appropriate exception within the Python main thread
Rinse and repeat for new signals
That all being said, for anyone encountering this problem in the future, I've rolled a library called daemoniker that wraps both proper Unix daemonization and the above Windows strategy into a unified facade. The cross-platform API looks like this:
from daemoniker import Daemonizer
with Daemonizer() as (is_setup, daemonizer):
if is_setup:
# This code is run before daemonization.
do_things_here()
# We need to explicitly pass resources to the daemon; other variables
# may not be correct
is_parent, my_arg1, my_arg2 = daemonizer(
path_to_pid_file,
my_arg1,
my_arg2
)
if is_parent:
# Run code in the parent after daemonization
parent_only_code()
# We are now daemonized, and the parent just exited.
code_continues_here()
Two options come to mind:
Port your program into a windows service. You can probably share much of your code between the two implementations.
Does your program really use any daemon functionality? If not, you rewrite it as a simple server that runs in the background, manages communications through sockets, and perform its tasks. It will probably consume more system resources than a daemon would, but it would be quote platform independent.
In general the concept of a daemon is Unix specific, in particular expected behaviour with respect to file creation masks, process hierarchy, and signal handling.
You may find PEP 3143 useful wherein a proposed continuation of python-daemon is considered for Python 3.2, and many related daemonizing modules and implementations are discussed.
The reason it's unix only is that daemons are a Unix specific concept i.e a background process initiated by the os and usually running as a child of the root PID .
Windows has no direct equivalent of a unix daemon, the closest I can think of is a Windows Service.
There's a program called pythonservice.exe for windows . Not sure if it's supported on all versions of python though
I have several scripts that I use to do some web crawling. They are always running, and should never stop. However, after about a week, they systematically "freeze": there is no output anymore, no response to Ctrl+C or anything. The only way is to kill the process and restart it.
I suspect that these issues come from the library I use for retrieving the data (urllib2), but the issue is very hard to reproduce.
I am thus wondering how I could check the state of the process and kill/restart it automatically if it is frozen. I was thinking of creating a PID file, and update it regularly. Another script could then periodically check the last modification date of this PID file, and restart the process if it's too old. I could use something like Monit to do the monitoring.
Is this how I should do it? Is there another best practice/common way for checking the responsiveness of a process?
If you have a process that is always running, has no connected terminal, and is the process group leader - that is a daemon. You undoubtedly know all that.
There are some defacto practices in coding programs like that. One is to have a signal handler which takes SIGHUP and forces the program to reinitialize itself. This means closing all of the open log files, rereading config scripts, etc. I do not know how applicable that is to your problem but it sometimes solves issues like frozen daemons at my work.
You can customize the idea by employing SIGUSR1 and SIGUSR2 signals to do special things, like write status to a file, or anything else. Since signals come in on an interrupt, the trap statement in scripts and signal handlers in python itself will push program state onto the interrupt stack and do "stuff".
In your case you may want the program fork/exec itself and then kill the parent.
I want to provide a service on the web that people can test out the performance of an algo, which is written in python and running on the linux machine
basically what I want to do is that, there is a very trivial PHP handler, let's say start_algo.php, which accepts the request coming from browser, and in the php code through system() or popen() (something like exec( "python algo.py" ) ) to issue a new process running the python script, I think it is doable in this part
problem is that since it is a web service, surely it has to serve multiple users at the same time, but I am quite confused by the Global Interpreter Lock GIL http://wiki.python.org/moin/GlobalInterpreterLock
that the 'standard' CPython has implemented,
does it mean, if I have 3 users running the algo now (which means 3 separated processes, correct me if I am wrong plz), at a particular moment, there is only one user is being served by the Python interpreter and the other 2 are waiting for their turns?
Many thanks in advance
Ted
If you are opening each script by invoking a new process; you will not run afoul of the GIL. Each process gets its own interpreter and therefore its own interpreter lock.
The GIL is per-process. If you start multiple python processes, each will have its own GIL that prevents the interpreter(s) in this specific process from running more than one thread at a time. But independent processes can run at the same time.
Also, multiple threads inside one Python process do take turns on running (rather frequently, IIRC once per hundred opcode instructions or a few dozen milliseconds depending on the version), so it's not like the GIL prevents concurrency at all - it just prevents multi-threading.