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How To Guide

How To Use The Tool​

Step 1: Adding a Store

  1. Navigate to the Features Tab.
  2. Select Add Store.
  3. Enter the store details:
    • Name (e.g., "Charlie’s Market")
    • Type (e.g., supermarket or convenience store)
    • Location (choose a point on the map using latitude and longitude).
  4. Confirm the addition. The new store will now appear on the map.

Step 2: Simulating Changes

  • Use the Step Function to simulate changes over time:

    1. Click Step to advance the simulation by one period (currently represents one month).
    2. Monitor changes in household food access metrics.
    3. Repeat as needed to observe cumulative impacts over time.

Step 3: Removing a Store

  1. Go to the Remove Store feature.
  2. Select the store you want to remove (e.g., "Charlie’s Market").
  3. Confirm the removal. The store will disappear from the map.
  4. Use the Step Function to evaluate the effects of this change on household food access.

Tips for Effective Use​

  • Analyze Community Needs: Before making changes, review community-level data to target areas with low food access.
  • Simulate Iteratively: Run multiple steps to identify trends and long-term effects.

Troubleshooting Common Issues​

"Simulation taking forever"

  • Normal: Large simulations (50k+ households) can take 10-30 minutes per step
  • Solution: Use reduced sample size

By using the FEAST simulation tool, you can make informed decisions to address food access challenges and create impactful solutions. Explore different scenarios, monitor the outcomes, and leverage the tool’s insights to drive meaningful community improvements. Should you need further support or wish to provide feedback, our team is here to assist.

Getting Started​

To get a local copy up and running follow these simple steps.

Prerequisites​

You will need python to run this application.

Installation​

  1. Clone the repo

    git clone https://github.com/ICICLE-ai/Food-Access-Model.git

  2. Switch to the appropriate branch If you are running the application locally, then switch to the "reduced_household_request" branch. If you are running the application in a production environment, then switch to the "staging" branch.

  git checkout reduced_household_request

  1. Install python dependencies from pyproject.toml

    pip install uv
    uv install

  2. Get a free API Key at https://api.census.gov/data/key_signup.html. This is only necessary if you want to create new data. The current database will hold brown county data.

  3. create a file .env at the root and enter your API in config.py

    API_KEY=[CENSUS API KEY (optional)]
    DB_NAME=[NAME OF DATABASE]
    DB_USER=[DATABASE USER NAME]
    DB_PASS=[DATABASE PASSWORD]
    DB_HOST=[DATABASE HOST]
    DB_PORT=[DATABASE PORT FOR DATABASE]

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Usage​

You can run this project on localhost with:

   uv run run.py

Beyond testing api calls, running this project and the front end service contained in the FASS-Frontend concurrently results in a user-experience using data within the database.

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Contributing​

CONTRIBUTORS:

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

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Contributors​

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