{ "info": { "author": "Sergio Maffioletti, Antonio Messina, Riccardo Murri", "author_email": "gc3pie-dev@googlegroups.com", "bugtrack_url": null, "classifiers": [ "Development Status :: 5 - Production/Stable", "Environment :: Console", "Intended Audience :: Developers", "Intended Audience :: Science/Research", "License :: DFSG approved", "License :: OSI Approved :: GNU Library or Lesser General Public License (LGPL)", "Operating System :: POSIX :: Linux", "Programming Language :: Python", "Programming Language :: Python :: 2", "Programming Language :: Python :: 2.6", "Programming Language :: Python :: 2.7", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Topic :: Scientific/Engineering", "Topic :: Scientific/Engineering :: Bio-Informatics", "Topic :: Scientific/Engineering :: Chemistry", "Topic :: System :: Distributed Computing" ], "description": "========================================================================\n GC3Pie |gitter|\n========================================================================\n\n.. |gitter| image:: https://badges.gitter.im/gc3pie/chat.svg\n :alt: Join the chat at https://gitter.im/gc3pie/chat\n :target: https://gitter.im/gc3pie/chat?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge\n\n.. This file follows reStructuredText markup syntax; see\n http://docutils.sf.net/rst.html for more information\n\nGC3Pie is a python package for executing computational workflows\nconsisting of tasks with complex inter-dependencies. GC3Pie accomplishes\nthis by defining a run-time task list in which a task can only be\nexecuted once all upstream task dependencies have been successfullly\ncompleted. In contrast to other workflow managers, GC3Pie accplications\nare written in python and not a markup language. The advantage is that\nthis makes it trivial to write highly complex workflows. GC3Pies roots\nare in shared-nothing achitectures (server-less for example) and can be\nconfigured to use backends such as batch clusters or clouds.\n\nGC3Pie is a suite of Python classes (and command-line tools built\nupon them) to aid in submitting and controlling batch jobs to clusters\nand grid resources seamlessly. GC3Pie aims at providing the\nbuilding blocks by which Python scripts that combine several\napplications in a dynamic workflow can be quickly developed.\n\nThe GC3Pie suite is comprised of three main components:\n\n * GC3Libs: A python package for controlling the life-cycle of a Grid or batch computational job\n * GC3Utils: Command-line tools exposing the main functionality provided by GC3Libs\n * GC3Apps: Driver scripts to run large job campaigns\n\n\nGC3Libs\n=======\n\nGC3Libs provides services for submitting computational jobs to Grids\nand batch systems and controlling their execution, persisting job\ninformation, and retrieving the final output.\n\nGC3Libs takes an application-oriented approach to batch computing. A\ngeneric ``Application`` class provides the basic operations for\ncontrolling remote computations, but different ``Application``\nsubclasses can expose adapted interfaces, focusing on the most\nrelevant aspects of the application being represented. Specific\ninterfaces are already provided for the GAMESS_ and Rosetta_ suites;\nnew ones can be easily created by subclassing the generic\n``Application`` class.\n\n\nGC3Utils\n========\n\nMost of the time users have lots of different accounts on several\ndiverse resources. The idea underlying GC3Utils is that a user can\nsubmit and control a computational job from one single place with a few\nsimple commands.\n\nCommands are provided to submit a job (``gsub``), check its running\nstatus (``gstat``), get a snapshot of the output files (``gget``,\n``gtail``), or cancel it (``gkill``).\n\n\nGC3Apps\n=======\n\nThere is a need in some scientific communities, to run large job\ncampaigns to analyze a vast number of data files with the same\napplication. The single-job level of control implemented by GC3Utils\nin this case is not enough: you would have to implement \"glue scripts\"\nto control hundreds or thousand scripts at once. GC3Pie has provisons\nfor this, in the form of re-usable Python classes that implement a\nsingle point of control for job families.\n\nThe GC3Apps scripts are driver scripts that run job campaigns using\nthe supported applications on a large set of input data. They can be\nused in production as-is, or adapted to suit your data processing needs.\n\nA Simple Example\n================\n\nThere are several examples and a tutorial in the examples directory.\n\n.. code-block:: python\n\n import sys\n import time\n import gc3libs\n\n class GdemoSimpleApp(gc3libs.Application):\n \"\"\"\n This simple application will run `/bin/hostname`:file: on the remote host,\n and retrieve the output in a file named `stdout.txt`:file: into a\n directory `GdemoSimpleApp_output`:file: inside the current directory.\n \"\"\"\n def __init__(self):\n gc3libs.Application.__init__(\n self,\n # the following arguments are mandatory:\n arguments = [\"/bin/hostname\"],\n inputs = [],\n outputs = [],\n output_dir = \"./GdemoSimpleApp_output\",\n # the rest is optional and has reasonable defaults:\n stdout = \"stdout.txt\",)\n\n # Create an instance of GdemoSimpleApp\n app = GdemoSimpleApp()\n\n # Create an instance of `Engine` using the configuration file present\n # in your home directory.\n engine = gc3libs.create_engine()\n\n # Add your application to the engine. This will NOT submit your\n # application yet, but will make the engine awere *aware* of the\n # application.\n engine.add(app)\n\n # in case you want to select a specific resource, call\n # `Engine.select_resource()`\n if len(sys.argv)>1:\n engine.select_resource(sys.argv[1])\n\n # Periodically check the status of your application.\n while app.execution.state != gc3libs.Run.State.TERMINATED:\n print \"Job in status %s \" % app.execution.state\n # `Engine.progress()` will do the GC3Pie magic:\n # submit new jobs, update status of submitted jobs, get\n # results of terminating jobs etc...\n engine.progress()\n\n # Wait a few seconds...\n time.sleep(1)\n\n print \"Job is now terminated.\"\n print \"The output of the application is in `%s`.\" % app.output_dir\n\nThis is what it looks like when the code is run:\n\n.. code-block:: text\n\n $ python gdemo_simple.py localhost\n gdemo_simple.py: [2019-01-21 14:37:53] INFO : Computational resource 'localhost' initialized successfully.\n Job in status NEW\n gdemo_simple.py: [2019-01-21 14:37:55] INFO : Successfully submitted GdemoSimpleApp@7f07aa094a90 to: localhost\n Job in status SUBMITTED\n Job is now terminated.\n The output of the application is in `./GdemoSimpleApp_output`.\n\nThe output file looks as follows:\n\n.. code-block:: text\n\n $ cat GdemoSimpleApp_output/stdout.txt\n 93607d089233\n\n\nInstallation instructions and further reading\n=============================================\n\nFor up-to-date information, please read the GC3Pie documentation at:\nhttp://gc3pie.readthedocs.io/\n\nInstallation instructions are in the `INSTALL.rst`_ file (in this\nsame directory), or can be read online at:\nhttp://gc3pie.readthedocs.io/en/latest/users/install.html\n\n.. _`INSTALL.rst`: https://github.com/uzh/gc3pie/blob/master/docs/users/install.rst\n\n\n.. References\n\n.. _GC3Pie: http://gc3pie.googlecode.com/\n.. _GAMESS: http://www.msg.chem.iastate.edu/gamess/\n.. _Rosetta: http://www.rosettacommons.org/\n\n\n.. 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