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A restaurant recommendation platform for Flatiron students

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Flateats

Tired of relying on word of mouth to discover the lunchtime hot spots around The Flatiron School, we built a platform to list recommendations and share reviews.

Technologies Used

  • React
  • JavaScript
  • Vanilla CSS
  • Google Maps API
  • Python
  • Flask
  • SQLAlchemy ORM
  • SQLite DB

Installation

This is a project under development, but feel free to clone a copy and have a look around!

Note that you will need a Google Maps API key to run a local copy. This requires a Google Cloud account with payment information, but at the time of writing the included monthly account credit should cover development without accruing charges.

After securing the API key, create a file named .env withing the client/ directory, and add your key as follows.

//  /client/.env

VITE_API_KEY='your key here'

To set up the back end, first install the dependencies and activate the virtual environment in the server/ directory:

pipenv install
pipenv shell

Next, initialize the SQLite database using flask-sqlalchemy:

flask db init
flask db migrate
flask db upgrade

Finally, seed the newly created database with our test data:

python seed.py

Then start the API:

python app.py

The front-end setup is a bit more straightforward. In the client/ directory execute the following:

npm install
npm run dev

Open the site by following the URL in your terminal.

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