Brackr

Brackr allows users to find a bike rack near them using Denver city data, navigate to those bike rack by using their current location, while also allowing citizens of Denver to crowd source the locations of new bike racks and comment or report bike rack issues to make commuting and locking up bikes safer and easier.

Production

Brackr is currently hosted on Heroku: https://brackr.herokuapp.com/

Notes:

• You must allow Brackr to use your browser's current location.
• Bike rack locations are currently strictly limited to the city of Denver
• Locations are seeded courtesy of the City of Denver's Open Data Catalog

Tutorial

You can watch a demo of the application here, which was given on Thursday, August 3rd at Turing School of Software & Design in Denver, Colorado.

On the first page, Brackr will find the 20 nearest bike racks to your current location.

If you're not currently in Denver, or there are any issues with obtaining your current location, a pin will be dropped in the default location.

You can select the pins on the map, or use the "nearest racks" to find a bike rack.

If you want to find the nearest bike racks to a certain location within Denver, use the search bar to find that location and Brackr will re-access the nearest bike racks to your desired location.

You can now also select the little arrow in the bottom right portion of the bike rack info window and you'll be launched into google maps:

If you want to add a bike rack, first you must be logged in. Then navigate to the "Add New Rack" menu option and type in a location or address closet to the new bike rack.

Then drag the green icon to where the bike rack is located.

Finally, confirm that the cross streets and owner information is correct, and your bike will be added!

Setup Instructions

1. Clone down the branch (or fork and then clone down)

git clone https://github.com/lao9/brackr.git

2. Navigate into project root

cd brackr

3. Bundle project gems

bundle install

4. Setup environment keys

Obtain a google maps Geocode API key here and Map API Key here. There should be a button in the top right corner that says "Get a Key".

Next, you'll need to reach out to me (contact info below) to receive the POST_TO_BRACKS_KEY.

Then, using the figaro gem, run the following command in console:

bundle exec figaro install

Then, open the config/application.yml file created and add the following, pasting in the keys acquired from google:

GOOGLE_GEOCODE_KEY: [YOUR_KEY_HERE]
GOOGLE_MAP_KEY: [YOUR_KEY_HERE]
POST_TO_BRACKS_KEY: [YOUR_KEY_HERE]

5. Setup database

rake db:setup

6. Run tests

Check that tests are running by typing rspec in the console.

7. Run server

Run rails s in the console and then navigate to http://localhost:3000 in your browser.

Neat Gems

• Used gem 'geokit' to calculate the distances between the search location and each bike rack.
• Used gem 'figaro' to keep environment and key variables private

API Services Used

Google Maps APIs:

• Geocoding API: Finds cross streets for given latitude and longitude.
• Maps Javascript API: visualized bike rack marker data
• Places API: Use google maps search box in Brackr map

API Endpoints

Default Brack Index

GET /api/v1/bracks

Returns collection of 20 brack objects sorted by distance closest to the default location (Turing School in Denver):

[
    {
        "id": 105,
        "lat": 39.7495666290001,
        "long": -105.000145148,
        "cross_streets": "LoDo",
        "owner": "City of Denver",
        "distance": 0.015287669880779668
    },
    {
        "id": 104,
        "lat": 39.7498516350001,
        "long": -105.000461602,
        "cross_streets": "15th St & Blake St",
        "owner": "City of Denver",
        "distance": 0.017625856700506287
    },
    {
        "id": 106,
        "lat": 39.7497392130001,
        "long": -105.000707391,
        "cross_streets": "1500",
        "owner": "City of Denver",
        "distance": 0.017706108128404854
    }
]

Brack Index with LatLng Params

GET /api/v1/bracks?latlng=39.750596200000004,-104.9964367

Returns collection of 20 brack objects sorted by distance closest to the given location in params:

[
    {
        "id": 383,
        "lat": 39.7505684980001,
        "long": -104.996696391,
        "cross_streets": "17th St & Market St",
        "owner": "City of Denver",
        "distance": 0.013942751541404737
    },
    {
        "id": 59,
        "lat": 39.7503440410001,
        "long": -104.996195264,
        "cross_streets": "LoDo",
        "owner": "City of Denver",
        "distance": 0.02165838893241953
    },
    {
        "id": 365,
        "lat": 39.75017166,
        "long": -104.996291989,
        "cross_streets": "17th St & Lawrence St",
        "owner": "City of Denver",
        "distance": 0.03035737996761881
    }
]

Create New Brack with User, Lat, Long, and Token Params

POST /api/v1/bracks?brack[user_id]=1&brack[lat]="39.7505962"&brack[long]="-104.9964367"&brack[token]=[YOUR_TOKEN_HERE]

Returns the newly added Brack:

{
    "id": 576,
    "lat": 39.7505962,
    "long": -104.9964367,
    "cross_streets": "Curtis Park",
    "owner": "Turing School",
    "distance": 1.013942751541404737
}

Upcoming Features

• Seed with Denver B-Cycle Data
• Allow users to add comments
• Allow users to save their favorite bike rack location

Contact Information

Creator: Lauren Oliveri

Email: [email protected]