=====
zeppy
=====
.. image:: https://img.shields.io/pypi/v/zeppy.svg
:target: https://pypi.python.org/pypi/zeppy
.. image:: https://img.shields.io/travis/santoshphilip/zeppy.svg
:target: https://travis-ci.com/santoshphilip/zeppy
.. image:: https://readthedocs.org/projects/zeppy/badge/?version=latest
:target: https://zeppy.readthedocs.io/en/latest/?badge=latest
:alt: Documentation Status
distributed processing for eppyy
* Free software: Mozilla Public License 2.0 (MPL-2.0)
* Documentation: https://zeppy.readthedocs.io.
Vision
------
To run eppy on multiple nodes in parallel and collect the results.
So what is a node and why would you want to do this ?
A node can be any or all of the following:
- a process (such E+ running on a single core on a multi-core computer)
- so we can do multi-processing and run it on many cores on a single computer
- a computer
- so we can run it on multiple computers that are on the same network
- a group of computer in a local network
- So we can run multiple groups of machines that may be at different locations on different local networks
- This can also be computers at different cloud locations
- a single computer in the local network may act as an access node
Features
--------
Do the distributed processing with a single function call and get all the results back.
Sample code ::
import zeppy import ppipes
result = ppipes.ipc_parallelpipe(runfunction,
args_list,
nworkers=None)
# runfunction is a function you will write,
# that may run idf.run(),
# gather the total energy use and return it
# args_list = {args: [idf1, idf2, idf3, ...]}
# list of files to run
# if nworkers=None:
# it will start up as many nodes as there are items in args_list
# if you don't have enough nodes avaliable, you can set nworkers=n.
# it will start up n nodes and queue up the runs evenly on the nodes
For example the above code can do the following:
- ``runfunction`` will run the *idf* file, and return the *total energy usage*
- ``result`` will be a list *total energy usage* in the same order as the items in ``args_list``
- see the comments in the code for greater clarity
Credits
-------
This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.
.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage
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