dispy
######
.. note:: Full documentation for dispy is now available at `dispy.org
<https://dispy.org>`_.
`dispy <https://dispy.org>`_ is a comprehensive, yet easy
to use framework for creating and using compute clusters to execute computations
in parallel across multiple processors in a single machine (SMP), among many
machines in a cluster, grid or cloud. dispy is well suited for data parallel
(SIMD) paradigm where a computation is evaluated with different (large) datasets
independently with no communication among computation tasks (except for
computation tasks sending intermediate results to the client).
dispy works with Python versions 2.7+ and 3.1+ on Linux, Mac OS X and Windows; it may
work on other platforms (e.g., FreeBSD and other BSD variants) too.
Features
--------
* dispy is implemented with `pycos <https://pycos.org>`_,
an independent framework for asynchronous, concurrent, distributed, network
programming with tasks (without threads). pycos uses non-blocking sockets with
I/O notification mechanisms epoll, kqueue and poll, and Windows I/O Completion
Ports (IOCP) for high performance and scalability, so dispy works efficiently
with a single node or large cluster(s) of nodes. pycos itself has support for
distributed/parallel computing, including transferring computations, files
etc., and message passing (for communicating with client and other computation
tasks). While dispy can be used to schedule jobs of a computation to get the
results, pycos can be used to create `distributed communicating processes
<https://pycos.org/dispycos.html>`_, for broad range of use cases.
* Computations (Python functions or standalone programs) and their
dependencies (files, Python functions, classes, modules) are
distributed automatically.
* Computation nodes can be anywhere on the network (local or
remote). For security, either simple hash based authentication or
SSL encryption can be used.
* After each execution is finished, the results of execution, output,
errors and exception trace are made available for further
processing.
* Nodes may become available dynamically: dispy will schedule jobs
whenever a node is available and computations can use that node.
* If callback function is provided, dispy executes that function
when a job is finished; this can be used for processing job
results as they become available.
* Client-side and server-side fault recovery are supported:
If user program (client) terminates unexpectedly (e.g., due to
uncaught exception), the nodes continue to execute scheduled
jobs. If client-side fault recover option is used when creating a
cluster, the results of the scheduled (but unfinished at the time of
crash) jobs for that cluster can be retrieved later.
If a computation is marked reentrant when a cluster is created and a
node (server) executing jobs for that computation fails, dispy
automatically resubmits those jobs to other available nodes.
* dispy can be used in a single process to use all the nodes
exclusively (with ``JobCluster`` - simpler to use) or in multiple
processes simultaneously sharing the nodes (with
``SharedJobCluster`` and *dispyscheduler* program).
* Cluster can be `monitored and managed
<https:/dispy.org/httpd.html>`_ with web browser.
Dependencies
------------
dispy requires pycos_ for concurrent, asynchronous network programming with tasks. pycos is
automatically installed if dispy is installed with pip. Under Windows efficient polling notifier
I/O Completion Ports (IOCP) is supported only if `pywin32 <https://github.com/mhammond/pywin32>`_
is installed; otherwise, inefficient *select* notifier is used.
Installation
------------
To install dispy, run::
python -m pip install dispy
Release Notes
-------------
Short summary of changes for each release can be found at `News
<https://pycos.com/forum/viewforum.php?f=11>`_. Detailed logs / changes are at
github `commits <https://github.com/pgiri/dispy/commits/master>`_.
Authors
-------
* Giridhar Pemmasani
Links
-----
* Documentation is at `dispy.org`_.
* `Examples <https://dispy.org/examples.html>`_.
* `Github (Code Respository) <https://github.com/pgiri/dispy>`_.
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