Skip to main content

Event-based draining of process output

Project description

drainers is an abstraction around subprocess.Popen to read and control process output event-wise. It also allows you to abort running processes either gracefully or forcefully without having to directly interact with the processes or threads themself.

Overview

Defining a process

A Drainer is a factory and controller wrapper around subprocess.Popen and therefore takes all of the (optional) parameters that subprocess.Popen’s initializer takes. For example, the minimal Drainer takes a command array:

from drainers import Drainer

def ignore_event(line, is_err):
        pass

my_drainer = Drainer(['ls', '-la'], read_event_cb=ignore_event)
my_drainer.start()

But, extra arguments are allowed, too:

my_drainer = Drainer(['echo', '$JAVA_HOME'], shell=True, bufsize=64,
                                         read_event_cb=ignore_event)
my_drainer.start()

The only two arguments to Drainer that are reserved are stdout and stderr. Drainer requires them to be subprocess.PIPE explicitly, and sets them for you accordingly.

Defining a callback

Drainer’s strength lies in the fact that each line that is read from the process’ standard output or standard error streams leads to a callback function being invoked. This allows you to process virtually any process’ output, as long as it’s line-based.

The callback function can be specified using the read_event_cb parameter to the constructor, as seen in the example above. It is mandatory. The callback function specified needs to have a specific signature:

def my_callback(line, is_err):
        ...

It should take two parameters: line (a string) and is_err (a boolean). The latter indicates that the line is read from the standard error stream. There is nothing more to it. It does not need to return anything: it’s return value will be ignored. Your callback may be a class method, too, like in the following example. Notice that in those cases, you pass foo.my_method as the value for the read_event_cb parameter:

class MyClass(object):

        def my_method(self, line, is_err):
                ...

foo = MyClass()
my_drainer = Drainer(['ls'], read_event_cb=foo.my_method)
my_drainer.start()

The granularity currently is a single line. If you want to read predefined chunks (lines) of data, use BufferedDrainer instead. See examples/buffer_results.py for an example.

Aborting processes

Drainer allows you to abort a running process in the middle of execution, forcefully sending the process a terminate() message (Python equivalent of a Unix SIGTERM message) when a certain condition arises. By default, the process will never be terminated abnormally. To specify termination criteria, implement a callback function that takes no parameters and returns True if abortion is desired and False otherwise. For example, for a long running process you might want to terminate it if the disk is getting (almost) full. But checking how much space is free can be a lengthy operation, so you might want to do it only sparingly:

def out_of_diskspace():
        left = handytools.check_disk_free()
        total = handytools.check_disk_total()
        return (left / total) < 0.03

# The following drainer executes the cruncher and checks whether the disk
# is (almost) full every 5 seconds.  It aborts if free disk space runs
# under 3%.
my_drainer = Drainer(['/bin/crunch', 'inputfile', 'outputfile'],
                     read_event_cb=ignore_event,
                                         should_abort=out_of_diskspace,
                                         check_interval=5.0)
exitcode = my_drainer.start()

The example is pretty self-explaining. You can check the exitcode to see the result of the process.

More examples

See the examples directory for more detailed examples.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Filename, size & hash SHA256 hash help File type Python version Upload date
drainers-0.0.3.tar.gz (9.0 kB) Copy SHA256 hash SHA256 Source None

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page