Make this example deployable on the web with Heroku

Procfile

@@ -0,0 +1 @@
+web: python run.py -p=$PORT

README.md

@@ -35,6 +35,35 @@ To view and run some example model analyses, launch the IPython Notebook and ope
 * ``server.py``: Defines classes for visualizing the model in the browser via Mesa's modular server, and instantiates a visualization server.
 * ``analysis.ipybn``: Notebook demonstrating how to run experiments and parameter sweeps on the model.
 
+## How to run on the web using Heroku
+
+If you already have a free Heroku account you can deploy this example as a web app by using the following button
+
+[![Deploy](https://www.herokucdn.com/deploy/button.svg)](https://heroku.com/deploy).
+
+Otherwise refer to the [Getting Started on Heroku with Python](https://devcenter.heroku.com/articles/getting-started-with-python) to learn about the basics of hosting a web app on Heroku.
+
+If you already set up your model as a git repository you basically only need to create a `Procfile` with the following content
+
+```bash
+web: python run.py -p=$PORT
+```
+
+This tells heroku to launch your model as a web application by running the file `run.py` and specify Herokus default port from the environmental variable `$PORT`
+
+Make sure your models ModularServer is also launched with the same port by using the following snippet inside your `run.py` (if you don't specify the port, future versions of mesa will use this by default)
+
+```python
+from server import server
+import os
+
+port = int(os.getenv("PORT", 4200))
+
+server.launch(port=port, open_browser=False)
+```
+
+That's it! You can view the Schelling model from this repo at https://mesa-schelling-example.herokuapp.com/
+
 ## Further Reading
 
 Schelling's original paper describing the model:

app.json

@@ -0,0 +1,5 @@
+{
+  "name": "Mesa Schelling Segregation Model",
+  "description": "An example model ready to be deployed on the web",
+  "repository": "https://github.com/Corvince/mesa-schelling-example"
+}

requirements.txt

@@ -1,2 +1 @@
-jupyter==1.0.0
-Mesa==0.7.6
+Mesa

run.py

@@ -1,3 +1,6 @@
 from server import server
+import os
 
-server.launch()
+port = int(os.getenv("PORT", 4200))
+
+server.launch(port=port, open_browser=False)

server.py

@@ -1,22 +1,23 @@
 from mesa.visualization.ModularVisualization import ModularServer
 from mesa.visualization.modules import CanvasGrid, ChartModule, TextElement
+from mesa.visualization.UserParam import UserSettableParameter
 
 from model import SchellingModel
 
 
 class HappyElement(TextElement):
-    '''
+    """
     Display a text count of how many happy agents there are.
-    '''
+    """
 
     def render(self, model):
         return "Happy agents: " + str(model.happy)
 
 
 def schelling_draw(agent):
-    '''
+    """
     Portrayal Method for canvas
-    '''
+    """
     if agent is None:
         return
     portrayal = {"Shape": "circle", "r": 0.5, "Filled": "true", "Layer": 0}
@@ -27,11 +28,24 @@ def schelling_draw(agent):
         portrayal["Color"] = "Blue"
     return portrayal
 
+
 happy_element = HappyElement()
 canvas_element = CanvasGrid(schelling_draw, 20, 20, 500, 500)
 happy_chart = ChartModule([{"Label": "happy", "Color": "Black"}])
 
-server = ModularServer(SchellingModel,
-                       [canvas_element, happy_element, happy_chart],
-                       "Schelling’s Segregation Model",
-                       20, 20, 0.8, 0.2, 4)
+model_params = {
+    "height": 20,
+    "width": 20,
+    "density": UserSettableParameter("slider", "Agent density", 0.8, 0.1, 1.0, 0.1),
+    "minority_pc": UserSettableParameter(
+        "slider", "Fraction minority", 0.2, 0.00, 1.0, 0.05
+    ),
+    "homophily": UserSettableParameter("slider", "Homophily", 3, 0, 8, 1),
+}
+
+server = ModularServer(
+    SchellingModel,
+    [canvas_element, happy_element, happy_chart],
+    "Schelling",
+    model_params,
+)