This is a project building an agent-based modeling system in Python. The ultimate goal is to build a GUI front-end that will allow non-coders to build models, while at the same time permitting coders to use Python for more flexibility in model creation.
We are currently building Indra3, a new version of the system. Our API server is moving along, we have a react frontend in progress, and many models have been ported to version 3.
For an introduction to agent-based modeling, please see this notebook.
To configure your system for development, first install Python 3 and git and
then run make linux_dev_env (on Linux) or make mac_dev_env (on MacOS).
For Windows, you will need to run something like Windows Subsystem for
Linux.
This will set up your login and install some dependencies using pip.
Follow the outputted instructions for setting your environment variables.
To run tests, run make tests.
To push to staging, run make staging. This will build the staging server,
currently at PythonAnywhere (https://indraabm.pythonanywhere.com).
The master branch is protected, and can only be accessed via pull requests. Currently production is running on Heroku. When a pull request from staging to master is approved, Travis should automatically deploy to the prod server.
The list of approved reviewers is in db/reviewers.txt.
If ImportError: bad magic number in 'config': b'\x03\xf3\r\n' occurs,
please try to run find . -name \*.pyc -delete .
To enable debugging statements while running the models, set INDRA_DEBUG
environment variable to True. Deeper levels of debugging statements
can be enabled with INDRA_DEBUG2 and INDRA_DEBUG3 environment variables.
- Trying to get all previous models working from the API server.
- Implementing HATEOAS for use by front ends.
Frontend:
- Dark mode currently does not change the colors of components, such as the header or buttons.
- Mobile design has not been implememnted. We had planned on having the carousel image be below the menu items.
- There are some unused component files that should be removed.
- A lot of testing needs to be implemented.