REST API Service to get Price Predictions for Airbnb listings

flask_restapi_predict.py

# REST API Service to get Price Predictions for Airbnb listings
@app.route("/predict", methods=["POST"])
def predict():
    
    # initialize the data dictionary that will be returned from the view
    data = {"success": False}

    # ensure an image was properly uploaded to our endpoint
    if flask.request.method == "POST":
        data["predictions"] = []

        parser = reqparse.RequestParser()
        parser.add_argument('country', type=str, help='Country')
        parser.add_argument('city', type=str, help='City')
        parser.add_argument('neighbourhood', type=str, help='Neighbourhood')
        parser.add_argument('roomtype', type=str, help='Room type')
        args = parser.parse_args()

        # Create input to Model from form data
        df_input = pd.DataFrame([[country, city, neighbourhood, propertytype, roomtype, bedtype,
                            cancellationpolicy, hostresponsetime, accommodates, num_bedrooms, num_beds,
                            min_nights, availability_30, availability_60, availability_90, availability_365,
                            num_reviews, reviews_per_month, review_scores_rating, review_scores_accuracy, 
                            review_scores_cleanliness, review_scores_checkin, review_scores_communication,
                            review_scores_location, review_scores_value, host_response_rate,
                            ]], dtype=float)

        # Inference: Get prediction from Model
        prediction_price = model.predict(df_input)[0]
        prediction_price = round(prediction_price)

        # Add prediction results to JSON data
        r = {"prediction_price": prediction_price, "features": features}
        data["predictions"].append(r)
        # indicate that the request was a success
        data["success"] = True

    # return the data dictionary as a JSON response
    return flask.jsonify(data)