The Need Taxi Backend API

Predict taxi fares through machine learning using random forest and linear_regression.

Installation On OSX

- pip install virtualenv
- virtualenv venv 
- source <desired-path>/bin/activate - OSX
- pip install -r requirements.txt
- export FLASK_APP=app/hello.py - OSX
- flask run

Installation On Windows

- pip install virtualenv
- virtualenv venv
- venv\Scripts\activate.bat - Windows
- pip install -r requirements.txt
- set FLASK_APP=app\app.py - Windows
- flask run

Running on http://127.0.0.1:5000/

Docker

docker build -t need-taxi-backend .
docker-compose up -d
docker build -t  need-taxi-backend_app . && docker run -it  need-taxi-backend_app

Endpoints

HEAD | POST predict-fares
HEAD | POST calculation-duration-distances

You can see endpoint details in the postman collection.

Sample Request:

HEAD | POST http://127.0.0.1:5000/api/v1/predict-fares

Request Payload:
{
   "pickup_latitude" : 41.05,
   "pickup_longitude" : 28.98,
   "drop_off_latitude" : 41.14,
   "drop_off_longitude" : 28.46,
   "taxi_type" : 0
}

Response:
{
  "linear_regression_prediction": 186.66,
  "random_forest_prediction": 184.4
}