This repository contains the code for a processing microservice in node.js. The microservice connects with an Urban Model Server via a Websocket connection. In this way, different simulation models can be hosted on different isolated microservices with their own programming language, packages and versions.
All of the necessary configuration is done in the config.py file. There are two mandatory configurations:
URLof the Urban Model Server.⚠️ Make sure that both the Urban Model Server and the Processing Microservice are part of the same Docker bridge network. The URL is supposed to point to this Network Gateway and the Port of the Urban Model Platform container.PROCESS_METADATAthat registers the process with the Urban Model Server in accordance with the OGC API Processes standard. If an extension is used, import the metadata from that extension folder. Otherwise, specify it manually.
Although one can use basically any algorithm to handle the input, do calculations and then return an output, there are multiple simulation packages written in Python that one can leverage. Thus, multiple extensions come along with this processing microservice that one can use out of the box. The following extensions are currently available:
Mesa and Mesa-geo are native Python agent-based modelling libraries. To simulate a Mesa/Mesa-Geo model with the processing microserivce, import Mesa.ProcessManager as Mesa in the server.py file and await Mesa.simulate_results(inputParameters) in the execute event. Create Mesa/Mesa-geo model, save it in the Mesa/modelfolder and adapt the Mesa/ProcessManager.py file to execute the model correctly.
NetLogo is one of the most popular agent-based modelling softwares. Build on Java, models are written in a specific NetLogo language. With the help of the great pynetlogo library, this Python processing microservice can run NetLogo models.
To simulate a NetLogo model with the processing microservice, import NetLogo.ProcessManager as NetLogo in the server.py file and await NetLogo.simulate_results(inputParameters) in the execute event. Create or download the NetLogo model, save it in the NetLogo/modelfolder and specify the correct NetLogo input variables and reporters in the NetLogo/ProcessMetadata.py file.