Rail Station Finder

Rail Station Finder is a small Python/Flask application that uses the Bulma CSS framework and Leaflet maps in the front end. The front end is built with vanilla JavaScript, so no build step is required :)

This is the demo application to accompany the Head in the Corner video on YouTube.

The application is based on the new GEOSEARCH command introduced for the first time in Redis 6.2. For more information, check out its documentation at redis.io.

This application demonstrates how to use GEOSEARCH as a replacement for the GEORADIUS command, and how to use the new box search functionality.

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[Optional] Docker Compose Setup

You can run both the Flask application and Redis using Docker Compose:

$ docker-compose up

To load the sample data in this Docker environment, run the following in a second terminal instance:

$ docker-compose exec app python load_stations.py

Then view the application by pointing your browser at http://localhost:5000.

Setup

(If you are using the Docker Compose setup, skip this section).

To run this example, you'll need Docker (for Redis 6.2) and Python 3 to run the Flask backend. First, clone the repo:

$ git clone https://github.com/redis-developer/introducing-the-geosearch-command.git
$ cd introducing-the-geosearch-command

Starting Redis 6.2

(If you chose to use docker-compose for both services, you are safe to move on).

To start Redis 6.2 (separately from the flask application), you can run:

$ docker-compose up -d redis

This will use port 6379, so if you have another instance of Redis on that port, you'll need to stop that first.

Creating a Python Virtual Environment and Installing Dependencies

(If you are using Docker Compose, skip this section).

The backend and data loader use Python 3. Create and activate a virtual environment, and install the dependencies:

$ python3 -m venv venv
$ . ./venv/bin/activate
(venv) $ pip install -r requirements.txt

Load the Sample Data

The sample data provided consists of a KML file (stations.kml) containing 52 rail stations located around the San Francisco Bay area. Load the data using the Python script provided:

(venv) $ python load_stations.py
Loaded 52 stations.

Start the Application

(If you are using Docker Compose, skip this section).

The application is a Python / Flask application that listens on port 5000. Start it as follows:

(venv) $ export FLASK_ENV=development
(venv) $ flask run
 * Environment: development
 * Debug mode: on
 * Running on http://127.0.0.1:5000/ (Press CTRL+C to quit)
 * Restarting with stat
 * Debugger is active!
 * Debugger PIN: 202-259-673

Usage

Now use your browser to go to http://127.0.0.1:5000/ and you should see a map of the San Francisco Bay area:

Perform Sample Queries

The interface allows you to perform radius and box queries. To being either type, first click on the map at the location you want the query to center on. A red marker will appear, and the latitude and longitude fields in the form will populate:

For a radius query:

• Select "Radius" from the drop down.
• Enter your desired radius in miles (e.g. 5).
• Click "Search".

Results will appear on the map, and you can hover over each station to see its name:

For a box query:

• Select "Box" from the drop down.
• Enter your desired box height and width in miles.
• Click "Search".

Results appear in the same way as for a radius search: