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-1.5.34.tar.gz (86.2 kB view details)

Uploaded Source

Built Distribution

schedula_core-1.5.34-py2.py3-none-any.whl (72.3 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file schedula_core-1.5.34.tar.gz.

File metadata

  • Download URL: schedula_core-1.5.34.tar.gz
  • Upload date:
  • Size: 86.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.1.1 CPython/3.11.0

File hashes

Hashes for schedula_core-1.5.34.tar.gz
Algorithm Hash digest
SHA256 36bcc24f79c8a715548f27e6c40dcd8e2d7403c93e0c450c6df7d029af625ab6
MD5 fd0f5ecbac9c8c0fd2effb07dc7b37e5
BLAKE2b-256 d63e60f929ae967a3b6461eebe632e1b28db71b06ed691fdaf3b29655bea6666

See more details on using hashes here.

File details

Details for the file schedula_core-1.5.34-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for schedula_core-1.5.34-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 c1fb1bea420eae5b8500e8719997388ac43b5f739a642f713dc2f8b9d7f08bcd
MD5 27f9cbf44e8b7655b6dd4111046022fa
BLAKE2b-256 af1ae220117e34afff96bbb047db5f82fc33186fed55db739d4ff53cf3c2a1a1

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