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Simple, Pythonic remote execution and deployment
0.9-doc-updates 0.9 3-ssh-config 7-prompt-detection 13-cli-env 18-pylint-config 98-local-skip-ssh 211-rsync-project-default-override 261-contrib-files-comment-strip-dollar-sign 282-task-aliases 312-heavy-cpu-usage 314-update-test-mocks 333-use-logger-in-place-of-print 340-files-append-return-value 457-failure-checking-for-parallel flexible-task-declarations hooks master multiprocessing
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Fabric is a Python (2.5 or higher) library and command-line tool for streamlining the use of SSH for application deployment or systems administration tasks. This branch adds in a few more features to basic Fabric. It will create one process per host given for parallel execution on commands, unless one sets the pool size with the connad flag. I have leveraged the multiprocessing module to do this. There are new command flags for fab: -P, --parallel use the multiprocessing module to fork by hosts -z FORKS, --pool-size=FORKS Set the number of forks to use in the pool. I have also added two decorators: @runs_parallel @runs_sequential These will allow a fab file command to be set to be run either in parallel or sequentially regardless of the fab command flag. Without these commands switch when the flag is set. If you are interested in the guts, the implementation is in the main.py file, and uses the Job_Queue class in the job_queue.py file. Note that this is only implemented in the fab command, as there is no way to determine how one will execute functions if they are using Fabric as a helper library. One other thing to note being that if you set a pool size larger than the number of hosts, it'll set the pool size to the number of hosts. Otherwise an error about poping from an empty list will crop up.