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Updated example of EJScreen's tool

License: MIT License

Jupyter Notebook 17.56% Python 68.90% CSS 0.10% HTML 12.95% Dockerfile 0.48%

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Dash app setup

Summary

Setup the basic architecture for the dash app and create a simple /mapper page which loads the dashboard

Expected behavior

There is a homepage / which uses the jumbotron template to link to the following information:
- Mapper tool (dash app)
- Original EJScreen tool
- GitHub Repo
- API Docs (swagger UI)

Local db setup

Summary

Set up database migrations using flask_migrate and add a setup.py that creates and populates a local Postgres db

Expected Behavior

The file setup.py has a function create_local_db() which:
- Initiates a local Postgres connection
- Drops the database at that connection if it exists
- Creates a new Postgres database at that connection
- Adds the PostGIS extension
- Creates all of the tables
- Populates the upgraded db with test data
When run.py is executed it attempts to connect to the local Postgres database and if one isn't found it calls create_loacl_db()

Create an regions endpoint

Summary

Create an endpoint POST api/regions/ which allows users to query a set of indicators for one or more census block regions

Expected Behavior

The endpoint GET api/regions:

The endpoint returns the following responses:

200 Success, with following response body:

{'type': 'Feature',
 'properties': {'fips_code': '0500000US01001',
                        'state': 'MD'},
  'geometry': {
      'type': 'Polygon',
      'coordinates': [[[-86.496774, 32.344437],
        [-86.717897, 32.402814],
        [-86.814912, 32.340803],
        [-86.890581, 32.502974],
        [-86.917595, 32.664169],
        [-86.71339, 32.661732],
        [-86.714219, 32.705694],
        [-86.413116, 32.707386],
        [-86.411172, 32.409937],
        [-86.496774, 32.344437]]]},
 'id': '01001'}

Dockerize the application

Summary

Create a docker image of the application that would make it easier to clone and start up the app locally

Expected Behavior

The dockerized app should be a multi-container app with the following components:
- App container - To run and interact with the app manually
- Database container - To host the database that will serve the app
- Testing container - To run the unit tests for the app
The README.md should explain how to run the containers after cloning the project

Project Setup and Exploration

Summary

Set up project and explore the data structure

To Do

Virtual environment
Pre-commit hook
File structure

Create the Indicators table and endpoint

Summary

Create a table to store the indicator values

Expected Behavior

There is a table indicators with the following columns:
- id Unique identifier for an indicator
- category Text representing the category the indicator belongs to (e.g. demographic, environmental, etc.)
- source Text representing the data source for this indicator
- source_name Text representing the name of this indicator in the original datasource
- display_name Text representing the human readable name for this indicator to display in reports
- description Text of the description of the indicator

There is an endpoint api/indicators/ which returns the following response

{
     "status": "success", 
     "data": [
         "id": 1,
         "category": "Demographic",
         "source": "EJScreen",
         "source_name": "ACSTOTPOP",
         "display_name": "Total Population",
         "description": "The total population of the census block"
    ]
}

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