I've been using Google Colab for a few weeks now and I've been wondering what the difference is between the two following commands (for example):
!ffmpeg ...
subprocess.Popen(['ffmpeg', ...
I was wondering because I ran into some issues when I started either of the commands above and then tried to stop execution midway. Both of them cancel on KeyboardInterrupt but I noticed that after that the runtime needs a factory reset because it somehow got stuck. Checking ps aux in the Linux console listed a process [ffmpeg] <defunct> which somehow still was running or at least blocking some ressources as it seemed.
I then did some research and came across some similar posts asking questions on how to terminate a subprocess correctly (1, 2, 3). Based on those posts I generally came to the conclusion that using the subprocess.Popen(..) variant obviously provides more flexibility when it comes to handling the subprocess: Defining different stdout procedures or reacting to different returncode etc. But I'm still unsure on what the first command above using the ! as prefix exactly does under the hood.
Using the first command is much easier and requires way less code to start this process. And assuming I don't need a lot of logic handling the process flow it would be a nice way to execute something like ffmpeg - if I were able to terminate it as expected. Even following the answers from the other posts using the 2nd command never got me to a point where I could terminate the process fully once started (even when using shell=False, process.kill() or process.wait() etc.). This got me frustrated, because restarting and re-initializing the Colab instance itself can take several minutes every time.
So, finally, I'd like to understand in more general terms what the difference is and was hoping that someone could enlighten me. Thanks!
! commands are executed by the notebook (or more specifically by the ipython interpreter), and are not valid Python commands. If the code you are writing needs to work outside of the notebook environment, you cannot use ! commands.
As you correctly note, you are unable to interact with the subprocess you launch via !; so it's also less flexible than an explicit subprocess call, though similar in this regard to subprocess.call
Like the documentation mentions, you should generally avoid the bare subprocess.Popen unless you specifically need the detailed flexibility it offers, at the price of having to duplicate the higher-level functionality which subprocess.run et al. already implement. The code to run a command and wait for it to finish is simply
subprocess.check_call(['ffmpeg', ... ])
with variations for capturing its output (check_output) and the more modern run which can easily replace all three of the legacy high-level calls, albeit with some added verbosity.
Related
I wrote a nextflow workflow that performs five steps. I have done this to be used by me and my colleagues, but not everyone is skilled with nextflow. Therefore, I decided to write a small wrapper in python3 that could run it for them.
The wrapper is very simple, reads the options with argparse and creates a command to be run with subprocess.run(). The issue with the wrapper is that, once the first step of the pipeline is completed, subprocess.run() thinks that the process is over.
I tried using shell=True, I tried using subprocess.Popen() with a while waiting for an output file, but it won't solve it.
How can I tell either subprocess.run() to wait until the end-end, or to nextflow run not to emit any exit code until the last step? Is there a way, or am I better off giving my colleagues a NF tutorial instead?
EDIT:
The reason why I prefer the wrapper, is that nextflow creates lots of temporary files which one has to know how to clean up. The wrapper does it for them, saving disk space and my time.
The first part of your question is a bit tricky to answer without the details, but we know subprocess.run() should wait for the command specified to complete. If your nextflow command is actually exiting before all of your tasks/steps have completed, then there could be a problem with the workflow or with the version of Nextflow itself. Since this occurs after the first process completes, I would suspect the former. My guess is that there might be some plumbing issue somewhere. For example, if your second task/step definition is conditional in any way then this could allow an early exit from your workflow.
I would avoid the wrapper here. Running Nextflow pipelines should be easy, and the documentation that accompanies your workflow should be sufficient to get it up and running quickly. If you need to set multiple params on the command line, you could include one or more configuration profiles to make it easy for your colleagues to get started running it. The section on pipeline sharing is also worth reading if you haven't seen it already. If the workflow does create lots of temporary files, just ensure these are all written to the working directory. So upon successful completion, all you need to clean up should be a simple rm -rf ./work. I tend to avoid automating destructive commands like this to avoid accidental deletes. A line in your workflow's documentation to say that the working directory can be removed (following successful completion of the pipeline) should be sufficient in my opinion and just leave it up to the users to clean up after themselves.
EDIT: You may also be interested in this project: https://github.com/goodwright/nextflow.py
I have recently came across a few posts on stack overflow saying that subprocess is much better than os.system, however I am having difficulty finding the exact advantages.
Some examples of things I have run into:
https://docs.python.org/3/library/os.html#os.system
"The subprocess module provides more powerful facilities for spawning new processes and retrieving their results; using that module is preferable to using this function."
No idea in what ways it is more powerful though, I know it is easier in many ways to use subprocess but is it actually more powerful in some way?
Another example is:
https://stackoverflow.com/a/89243/3339122
The advantage of subprocess vs system is that it is more flexible (you can get the stdout, stderr, the "real" status code, better error handling, etc...).
This post which has 2600+ votes. Again could not find any elaboration on what was meant by better error handling or real status code.
Top comment on that post is:
Can't see why you'd use os.system even for quick/dirty/one-time. subprocess seems so much better.
Again, I understand it makes some things slightly easier, but I hardly can understand why for example:
subprocess.call("netsh interface set interface \"Wi-Fi\" enable", shell=True)
is any better than
os.system("netsh interface set interface \"Wi-Fi\" enabled")
Can anyone explain some reasons it is so much better?
First of all, you are cutting out the middleman; subprocess.call by default avoids spawning a shell that examines your command, and directly spawns the requested process. This is important because, besides the efficiency side of the matter, you don't have much control over the default shell behavior, and it actually typically works against you regarding escaping.
In particular, do not do this:
subprocess.call('netsh interface set interface "Wi-Fi" enable')
since
If passing a single string, either shell must be True (see below) or else the string must simply name the program to be executed without specifying any arguments.
Instead, you'll do:
subprocess.call(["netsh", "interface", "set", "interface", "Wi-Fi", "enable"])
Notice that here all the escaping nightmares are gone. subprocess handles escaping (if the OS wants arguments as a single string - such as Windows) or passes the separated arguments straight to the relevant syscall (execvp on UNIX).
Compare this with having to handle the escaping yourself, especially in a cross-platform way (cmd doesn't escape in the same way as POSIX sh), especially with the shell in the middle messing with your stuff (trust me, you don't want to know what unholy mess is to provide a 100% safe escaping for your command when calling cmd /k).
Also, when using subprocess without the shell in the middle you are sure you are getting correct return codes. If there's a failure launching the process you get a Python exception, if you get a return code it's actually the return code of the launched program. With os.system you have no way to know if the return code you get comes from the launched command (which is generally the default behavior if the shell manages to launch it) or it is some error from the shell (if it didn't manage to launch it).
Besides arguments splitting/escaping and return code, you have way better control over the launched process. Even with subprocess.call (which is the most basic utility function over subprocess functionalities) you can redirect stdin, stdout and stderr, possibly communicating with the launched process. check_call is similar and it avoids the risk of ignoring a failure exit code. check_output covers the common use case of check_call + capturing all the program output into a string variable.
Once you get past call & friends (which is blocking just as os.system), there are way more powerful functionalities - in particular, the Popen object allows you to work with the launched process asynchronously. You can start it, possibly talk with it through the redirected streams, check if it is running from time to time while doing other stuff, waiting for it to complete, sending signals to it and killing it - all stuff that is way besides the mere synchronous "start process with default stdin/stdout/stderr through the shell and wait it to finish" that os.system provides.
So, to sum it up, with subprocess:
even at the most basic level (call & friends), you:
avoid escaping problems by passing a Python list of arguments;
avoid the shell messing with your command line;
either you have an exception or the true exit code of the process you launched; no confusion about program/shell exit code;
have the possibility to capture stdout and in general redirect the standard streams;
when you use Popen:
you aren't restricted to a synchronous interface, but you can actually do other stuff while the subprocess run;
you can control the subprocess (check if it is running, communicate with it, kill it).
Given that subprocess does way more than os.system can do - and in a safer, more flexible (if you need it) way - there's just no reason to use system instead.
There are many reasons, but the main reason is mentioned directly in the docstring:
>>> os.system.__doc__
'Execute the command in a subshell.'
For almost all cases where you need a subprocess, it is undesirable to spawn a subshell. This is unnecessary and wasteful, it adds an extra layer of complexity, and introduces several new vulnerabilities and failure modes. Using subprocess module cuts out the middleman.
Tried searching for the solution to this problem but due to there being a command Shell=True (don't think that is related to what I'm doing but I could well be wrong) it get's lots of hits that aren't seemingly useful.
Ok so the problem I is basically:
I'm running a Python script on a cluster. On the cluster the normal thing to do is to launch all codes/etc. via a shell script which is used to request the appropriate resources (maximum run time, nodes, processors per node, etc.) needed to run the job. This shell then calls the script and away it goes.
This isn't an issue, but the problem I have is my 'parent' code needs to wait for it's 'children' to run fully (and generate their data to be used by the parent) before continuing. This isn't a problem when I don't have the shell between it and the script but as it stands .communicate() and .wait() are 'satisfied' when the shell script is done. I need to to wait until the script(s) called by the shell are done.
I could botch it by putting a while loop in that needs certain files to exist before breaking, but this seems messy to me.
So my question is, is there a way I can get .communicate (idealy) or .wait or via some other (clean/nice) method to pause the parent code until the shell, and everything called by the shell, finishes running? Ideally (nearly essential tbh) is that this be done in the parent code alone.
I might not be explaining this very well so happy to provide more details if needed, and if somewhere else answers this I'm sorry, just point me thata way!
Per Python documentation, subprocess.call should be blocking and wait for the subprocess to complete. In this code I am trying to convert few xls files to a new format by calling Libreoffice on command line. I assumed that the call to subprocess call is blocking but seems like I need to add an artificial delay after each call otherwise I miss few files in the out directory.
what am I doing wrong? and why do I need the delay?
from subprocess import call
for i in range(0,len(sorted_files)):
args = ['libreoffice', '-headless', '-convert-to',
'xls', "%s/%s.xls" %(sorted_files[i]['filename'],sorted_files[i]['filename']), '-outdir', 'out']
call(args)
var = raw_input("Enter something: ") # if comment this line I dont get all the files in out directory
EDIT It might be hard to find the answer through the comments below. I used unoconv for document conversion which is blocking and easy to work with from an script.
It's possible likely that libreoffice is implemented as some sort of daemon/intermediary process. The "daemon" will (effectively1) parse the commandline and then farm the work off to some other process, possibly detaching them so that it can exit immediately. (based on the -invisible option in the documentation I suspect strongly that this is indeed the case you have).
If this is the case, then your subprocess.call does do what it is advertised to do -- It waits for the daemon to complete before moving on. However, it doesn't do what you want which is to wait for all of the work to be completed. The only option you have in that scenario is to look to see if the daemon has a -wait option or similar.
1It is likely that we don't have an actual daemon here, only something which behaves similarly. See comments by abernert
The problem is that the soffice command-line tool (which libreoffice is either just a link to, or a further wrapper around) is just a "controller" for the real program soffice.bin. It finds a running copy of soffice.bin and/or creates on, tells it to do some work, and then quits.
So, call is doing exactly the right thing: it waits for libreoffice to quit.
But you don't want to wait for libreoffice to quit, you want to wait for soffice.bin to finish doing the work that libreoffice asked it to do.
It looks like what you're trying to do isn't possible to do directly. But it's possible to do indirectly.
The docs say that headless mode:
… allows using the application without user interface.
This special mode can be used when the application is controlled by external clients via the API.
In other words, the app doesn't quit after running some UNO strings/doing some conversions/whatever else you specify on the command line, it sits around waiting for more UNO commands from outside, while the launcher just runs as soon as it sends the appropriate commands to the app.
You probably have to use that above-mentioned external control API (UNO) directly.
See Scripting LibreOffice for the basics (although there's more info there about internal scripting than external), and the API documentation for details and examples.
But there may be an even simpler answer: unoconv is a simple command-line tool written using the UNO API that does exactly what you want. It starts up LibreOffice if necessary, sends it some commands, waits for the results, and then quits. So if you just use unoconv instead of libreoffice, call is all you need.
Also notice that unoconv is written in Python, and is designed to be used as a module. If you just import it, you can write your own (simpler, and use-case-specific) code to replace the "Main entrance" code, and not use subprocess at all. (Or, of course, you can tear apart the module and use the relevant code yourself, or just use it as a very nice piece of sample code for using UNO from Python.)
Also, the unoconv page linked above lists a variety of other similar tools, some that work via UNO and some that don't, so if it doesn't work for you, try the others.
If nothing else works, you could consider, e.g., creating a sentinel file and using a filesystem watch, so at least you'll be able to detect exactly when it's finished its work, instead of having to guess at a timeout. But that's a real last-ditch workaround that you shouldn't even consider until eliminating all of the other options.
If libreoffice is being using an intermediary (daemon) as mentioned by #mgilson, then one solution is to find out what program it's invoking, and then directly invoke it yourself.
I want to search for a process and show it,emacs for example,I use
`p = subprocess.Popen('ps -A | grep emacs',shell=True,stdout=subprocess.PIPE)`
to get the process, then how can I wake it up and show it?
in other words,the question shoud be : how python change the state of process?
In short, python has a pty module and look for the solution there.
This question is not that simple as it may look like.
It is simple to change the running state of a process by delivering corresponding signals but it is not simple to manipulate foreground/background properties.
When we talk about manipulating the foreground/background processes, we really talk about 'job control.' In UNIX environment, job control is achieved by coordination of several parts, including kernel, controlling terminal, current shell and almost every process invoked in that shell session. Telling a process to get back to foreground, you have to tell others to shut up and go to background simultaneously. See?
Let's come back to your question. There could be 2 answers to this, one is no way and the other is it could be done but how.
Why 2 answers?
Generally you cannot have job control unless you program for it. You also cannot use a simple pipe to achieve the coordination model which leads to job control mechanism; the reason is essential since you cannot deliver signals through a pipe. That's why the answer is no way, at least no way in a simple pipe implementation.
However, if you have enough patience to program terminal I/O, it still can be done with a lot of labor work. Concept is simple: you cheat your slave program, which is emacs in this example, that it has been attached to a real terminal having a true keyboard and a solid monitor standby, and you prepare your master program, which is the python script, to handle and relay necessary events from its controlling terminal to the slave's pseudo-terminal.
This schema is actually adopted by many terminal emulators. You just need to write another terminal emulator in your case... Wait! Does it have to be done with so much effort, always?
Luckily no.
Your shell manages all the stuff for you in an interactive scenario. You just tell shell to 'fg/bg' the task, quite easy in real life. The designated command combination can be found in shell's manpage. It could look like 'jobs -l | grep emacs' along with 'fg %1'. Nonetheless those combined commands cannot be invoked by a program. It's a different story since a program will start a new shell to interpret its commands and such a new shell cannot control the old running emacs because it doesn't have the privilege. Type it in with your keyboard and read it out on your monitor; that's an interactive scenario.
In an automation scenario, think twice before you employ a job control design because most automation scenarios do not require a job control schema. You need an editor here and a player there, that's all right, but just don't make them to stay "background" and pop to "foreground." They'd better exit when they complete their task.
But if you are unlucky to have to program job control in automation procedures, try to program pseudo-terminal master and slave I/O as well. They look like a sophisticated IPC mechanism and their details are OS-dependent. However this is the standard answer to your question; though annoying, I know.
you can get the output generated by this process, reading the stdout descriptor:
out = p.stdout.read()