Place the service file (or a link to it) in /etc/systemd/system/ Place the watchdogged.py file somewhere ( and change the ExecStart portion in the .service to point at the file )
then do systemctl daemon-reload followed by systemctl start watchdogged.service
After this you can watch the progress using journalctl --follow -u watchdogged.service
change the PROBABILITY variable to something else to watch it faster/later or succeed.
For ETS's SKLL project, we found out the hard way that Travis-CI's support for numpy and scipy is pretty abysmal. There are pre-installed versions of numpy for some versions of Python, but those are seriously out of date, and scipy is not there are at all. The two most popular approaches for working around this are to (1) build everything from scratch, or (2) use apt-get to install more recent (but still out of date) versions of numpy and scipy. Both of these approaches lead to longer build times, and with the second approach, you still don't have the most recent versions of anything. To circumvent these issues, we've switched to using Miniconda (Anaconda's lightweight cousin) to install everything.
A template for installing a simple Python package that relies on numpy and scipy using Miniconda is provided below. Since it's a common s
| # -*- coding: utf-8 -*- | |
| """ | |
| This script will delete all of the tweets in the specified account. | |
| You may need to hit the "more" button on the bottom of your twitter profile | |
| page every now and then as the script runs, this is due to a bug in twitter. | |
| You will need to get a consumer key and consumer secret token to use this | |
| script, you can do so by registering a twitter application at https://dev.twitter.com/apps | |
| @requirements: Python 2.5+, Tweepy (http://pypi.python.org/pypi/tweepy/1.7.1) |