schedula-core


Nameschedula-core JSON
Version 1.5.49 PyPI version JSON
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home_pagehttps://github.com/vinci1it2000/schedula
SummaryProduce a plan that dispatches calls based on a graph of functions, satisfying data dependencies.
upload_time2024-12-08 16:06:30
maintainerNone
docs_urlNone
authorVincenzo Arcidiacono
requires_pythonNone
licenseEUPL 1.1+
keywords flow-based programming dataflow parallel asynchronous async scheduling dispatch functional programming dataflow programming
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            
About schedula
**************

**schedula** is a dynamic flow-based programming environment for
python, that handles automatically the control flow of the program.
The control flow generally is represented by a Directed Acyclic Graph
(DAG), where nodes are the operations/functions to be executed and
edges are the dependencies between them.

The algorithm of **schedula** dates back to 2014, when a colleague
asked for a method to automatically populate the missing data of a
database. The imputation method chosen to complete the database was a
system of interdependent physical formulas - i.e., the inputs of a
formula are the outputs of other formulas. The current library has
been developed in 2015 to support the design of the CO:sub:`2`MPAS
`tool <https://github.com/JRCSTU/CO2MPAS-TA>`_ - a CO:sub:`2` vehicle
`simulator
<https://jrcstu.github.io/co2mpas/model/?url=https://jrcstu.github.io/co2mpas/model/core/CO2MPAS_model/calibrate_with_wltp_h.html>`_.
During the developing phase, the physical formulas (more than 700)
were known on the contrary of the software inputs and outputs.


Why schedula?
=============

The design of flow-based programs begins with the definition of the
control flow graph, and implicitly of its inputs and outputs. If the
program accepts multiple combinations of inputs and outputs, you have
to design and code all control flow graphs. With normal schedulers, it
can be very demanding.

While with **schedula**, giving whatever set of inputs, it
automatically calculates any of the desired computable outputs,
choosing the most appropriate DAG from the dataflow execution model.

Note: The DAG is determined at runtime and it is extracted using the
   shortest path from the provided inputs. The path is calculated
   based on a weighted directed graph (dataflow execution model) with
   a modified Dijkstra algorithm.

**schedula** makes the code easy to debug, to optimize, and to present
it to a non-IT audience through its interactive graphs and charts. It
provides the option to run a model asynchronously or in parallel
managing automatically the Global Interpreter Lock (GIL), and to
convert a model into a web API service.


Installation
************

To install it use (with root privileges):

.. code:: console

   $ pip install schedula-core

or download the last git version and use (with root privileges):

.. code:: console

   $ python setup.py install

            

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