Skip to main content

Produce a plan that dispatches calls based on a graph of functions, satisfying data dependencies.

Project description

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 - a CO:sub:2 vehicle simulator. 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):

$ pip install schedula-core

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

$ python setup.py install

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

schedula-core-1.4.7.tar.gz (70.5 kB view details)

Uploaded Source

Built Distribution

schedula_core-1.4.7-py2.py3-none-any.whl (70.6 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file schedula-core-1.4.7.tar.gz.

File metadata

  • Download URL: schedula-core-1.4.7.tar.gz
  • Upload date:
  • Size: 70.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.0

File hashes

Hashes for schedula-core-1.4.7.tar.gz
Algorithm Hash digest
SHA256 e8b3880361ad3c60d14054397d12d0d960c994f5efc7bc052d5d6c1544e7d82f
MD5 838aa0f247d0af9aea0545f603e1f722
BLAKE2b-256 5302a7852471c511acb0bef951e72dfe54a5136c74ca162899e1abf397dc738e

See more details on using hashes here.

File details

Details for the file schedula_core-1.4.7-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for schedula_core-1.4.7-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 20dd102fa4ed4b28b1be7f59a00c9cf247ca24d0e8f189df6f7485211fb7646b
MD5 e5a74dc6db17d6964a0131838daa31df
BLAKE2b-256 cfa0e79a6be44c206b25854944d2b31a188b1a1931ff0625238f09e131692d12

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page