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casymda-0.2.9
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مشاهده بیشترتوضیحات
Simple DES modeling and simulation based on SimPy, BPMN, and pixi.js
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | casymda-0.2.9 |
| نام | casymda |
| نسخه کتابخانه | 0.2.9 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | FFC |
| ایمیل نویسنده | fladdi.mir@gmx.de |
| آدرس صفحه اصلی | https://github.com/fladdimir/casymda |
| آدرس اینترنتی | https://pypi.org/project/casymda/ |
| مجوز | MIT |
# BPMN-based creation of SimPy discrete event simulation models
Wouldn't it be _cool_ to combine the block-based process modeling experience of commercial discrete event simulation packages with the amenities of proper IDE-based source-code editing?
(Think Arena / Anylogic / ExtendSim / Plant Simulation / ... but with simple integration of third-party libraries, industry-standard interfaces, unit- and integration testing, dockerization, serverless execution in the cloud of your choice... and even actually working auto-completion! _:D_)
And all that not only for free, but using the worlds most popular language for data analytics and machine learning?
_Casymda_ enables you to create [SimPy3](https://simpy.readthedocs.io/en/latest/) simulation models, with help of BPMN and the battle-tested [Camunda-Modeler](<http://www.bpmn.io>).
Created BPMN process diagrams are parsed and converted to Python-code, combining visual oversight of model structure with code-based definition of model behavior.
Immediately executable, including a token-based process animation, allowing for space-discrete entity movements, and ready to be wrapped as a gym-environment to let a machine-learning algorithm find a control strategy.
Further information and sample projects:
- <https://fladdimir.github.io/post/> (English)
- <https://casymda.github.io/page/Webpage/Startpage.html> (German)
## Installation
From [PyPI](https://pypi.org/project/casymda/):
``` l
pip install casymda
```
## Features
- connectable blocks for processing of entities
- graphical model description via camunda modeler
- process visualization browser-based or via tkinter
- space-discrete tilemap-movements of entities
- gradually typed (checkout [pyright](https://github.com/microsoft/pyright) for vscode)
Coming soon:
- automated model generation from process event-logs via [PM4Py](http://pm4py.org/)
## Examples
Basic features are illustrated as part of the example models (which also serve as integration tests):
- basics:
- bpmn-based generation of a simple model file
- run the generated model
- process visualization via tkinter
- browser-based visualization (served with [flask](https://palletsprojects.com/p/flask/), animated with [pixijs](https://www.pixijs.com/))
- resources:
- seize and release a resource via graphical modeling
- tilemap:
- entity movement along a shortest path defined by a csv-tilemap (built on networkx: <https://networkx.github.io/>)
For setup just clone the repository and install casymda ([virtual environment](https://docs.python.org/3/tutorial/venv.html) recommended). See [basics-visual-run-tkinter](exec/basics/visual_run.py) for an example of how to cope with python-path issues.
## Design
- [Model generation and execution](diagrams/model+execution.pdf)
- [Blocks and animation](diagrams/blocks+animation.pdf)
## Development
This project trusts [Black](https://black.readthedocs.io/en/stable/) for formatting, [Sonarqube](https://www.sonarqube.org/) for static code analysis, and [pytest](https://docs.pytest.org/en/latest/) for unit & integration testing. Developed and tested on Linux (Ubuntu 20.04), Python 3.8.5.
Tests can be carried out inside a docker-container, optionally including an installation from pypi to verify a successful upload.
### Sonarqube
sonarqube server (public docker image):
``` l
docker-compose up sonarqube
```
sonar-scanner (public docker image):
``` l
docker-compose up analysis
```
(run a docker-based unit-test first for coverage-reporting)
(remember to share your drive via Docker-Desktop settings if necessary, to be re-applied after each password change)
### Tests
``` l
pytest --cov-report term --cov=src/casymda/ tests/
```
integrations tests:
``` l
python3 -m pytest examples
```
(integration-tests require tkinter, which may be installed via `sudo apt-get install python3-tk`)
For Docker-based tests see [docker-compose.yml](docker-compose.yml)
``` l
docker-compose run unit-test
docker-compose run examples-test
docker-compose run examples-test-pypi
```
### Virtual environment setup
``` l
python3 -m venv venv
```
### Editable installation
``` l
pip install -e .
```
### Publish to pypi
``` l
python setup.py sdist
twine upload dist/*
```
pip install twine if necessary,
remember to set the version in [setup.py](setup.py) and [src/casymda](src/casymda/__init__.py) as required
### PyPy3
Tested PyPy3 (7.3.1-final). Install pypy3 pypy3-dev pypy-tk.
Runtime could be decreased by factor ~2 when using PyPy3 for longer simulations runs (e.g. from ~45s to ~25s for a [simple example model test](examples/basics/model/long_run_bpmn_example_test.py) with MAX_ENTITIES set to 40.000 on an i5 notebook).
## Contact
fladdi.mir@gmx.de
feedback / ideas / discussion / cheering / complaints welcome
MIT License
2020
نحوه نصب
نصب پکیج whl casymda-0.2.9:
pip install casymda-0.2.9.whl
نصب پکیج tar.gz casymda-0.2.9:
pip install casymda-0.2.9.tar.gz