This package has been made to help in the deployment of a co-simulation using OBNL (url) as orchestrator. It allows you to create simulation nodes, links, steps and running sequences. The description for creating wrappers with your tools can be found here (url) as well as examples. A full working demonstration of this package can be found here (url).
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
Python >= 3.5 (https://www.python.org/downloads/)
Docker Community-edition (https://www.docker.com/community-edition)
Install git (if not already done) (More info on git)
If you’re on a Debian-based distribution like Ubuntu, try apt-get:
$ sudo apt-get install git-all
Install virtualenv (if not already done) (More info on virtualenv)
$ pip install virtualenv
Create a Python 3.5 virtual env
$ virtualenv -p python3 ict
Activate the created virtual env (ict)
$ source link/to/ict/bin/activate
Install dependencies
$ pip install -r requirements.txt
Install ictdeploy (in the ictdeploy folder)
$ python setup.py install
A full scale demo with real data and complex models will soon be available.
Use Git for Windows to clone the ictdeploy repository. For instance, when using Git Bash type the following on the command line:
$ git clone https://github.com/IntegrCiTy/ictdeploy.git
Use pip in the Windows command line to install virtualenv and virtualenvwrapper-win:
> pip install virtualenv
> pip install virtualenvwrapper-win
Use mkvirtualenv in the Windows command line to create and start a Python 3.5 virtual environment called ict:
> mkvirtualenv -p C:\path\to\python35.exe ict
Optional: In the virtual environment, set the working directory to the ictdeploy root directory:
(ict) setprojectdir C:\path\to\ictdeploy
In the virtual environment, install dependencies:
(ict) pip install -r requirements.txt
Install ictdeploy (in the ictdeploy folder)
(ict) python setup.py install
A full scale demo with real data and complex models will soon be available.
Pytest (https://docs.pytest.org/en/latest/) is used in this project.
To run tests just run pytest with command line in the dedicated environment in the root forlder of this package.
test_creation.py gathers the tests for the creation of the simulation graph (meta-models, models, nodes, links, ...).
pytest tests/test_creation.py
test_command.py gathers the tests for the execution of commands by wrappers inside Docker containers.
pytest tests/test_command.py
test_deployment.py gathers the tests for the deployment of all different nodes.
pytest tests/test_deployment.py
- Docker-SDK - python interface for the Docker Engine API
- Networkx - manipulation of graph and network
- Pandas - data structures and data analysis tools
- OBNL - co-simulation orchestrator
- Pablo Puerto - Initial work
You should have received a copy of the Apache License Version 2.0 along with this program. If not, see http://www.apache.org/licenses/LICENSE-2.0.
- TO DO ...