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-1.5.30.tar.gz (86.2 kB view details)

Uploaded Source

Built Distribution

schedula_core-1.5.30-py2.py3-none-any.whl (72.3 kB view details)

Uploaded Python 2 Python 3

File details

Details for the file schedula_core-1.5.30.tar.gz.

File metadata

  • Download URL: schedula_core-1.5.30.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-1.5.30.tar.gz
Algorithm Hash digest
SHA256 1ae123d72ef92c01c3e7ead8f1d0d358d599ebf72ad52a26eb9499887d9f83c4
MD5 24efbd270e5b85abf77d14cb0084c994
BLAKE2b-256 a2b9d4358c345258e5d819d678cea72df43ad19cce9ba320a9843f4f4544c71a

See more details on using hashes here.

File details

Details for the file schedula_core-1.5.30-py2.py3-none-any.whl.

File metadata

File hashes

Hashes for schedula_core-1.5.30-py2.py3-none-any.whl
Algorithm Hash digest
SHA256 8dd4fedf85e3a16b86fb4c78c68e23c120990e8ef29c388cc87548856ae4c0d5
MD5 76bb71a5b818d77962a23338023fed9e
BLAKE2b-256 86a5b2b692615e1bdebc0b4da27d85242ec541726f70f7ac19c7ff55430e3f78

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