services/location_services.py

import os
import pandas as pd
from dotenv import load_dotenv
import requests
from geopy.distance import geodesic

load_dotenv()

def find_place(input_text, api_key):
    # Define the base URL and parameters for the request
    base_url = "https://maps.googleapis.com/maps/api/place/findplacefromtext/json"
    params = {
        "fields": "formatted_address,name,rating,opening_hours,geometry",
        "input": input_text,
        "inputtype": "textquery",
        "key": api_key  # Replace with your actual API key
    }

    # Make the GET request
    response = requests.get(base_url, params=params)

    # Check if the request was successful
    if response.status_code == 200:
        # Return the response content (JSON)
        return response.json()
    else:
        # Return an error message if the request failed
        return f"Request failed with status code: {response.status_code}"
    
    

def get_zip_code(address):
    base_url = "https://maps.googleapis.com/maps/api/geocode/json"
    params = {
        "address": address,
        "key": "AIzaSyDXCm-fwucr6R93CHa9Bb4j5qArup5D4kY"
    }
    response = requests.get(base_url, params=params)
    if response.status_code == 200:
        data = response.json()
        if data['status'] == 'OK':
            # Extract the postal code from the address components
            for component in data['results'][0]['address_components']:
                if 'postal_code' in component['types']:
                    return component['long_name']
            return None
        else:
            return f"API request returned status: {data['status']}"
    else:
        return f"Request failed with status code: {response.status_code}"


def get_distances_for_multiple_destinations(origin, destinations, api_key):
    destinations_param = '|'.join(destinations)

    base_url = "https://maps.googleapis.com/maps/api/distancematrix/json"
    params = {
        "origins": origin,
        "destinations": destinations_param,
        "key": api_key
    }

    response = requests.get(base_url, params=params)
    if response.status_code == 200:
        data = response.json()
        if data['status'] == 'OK':
            results = []
            for element in data['rows'][0]['elements']:
                if element['status'] == 'OK':
                    distance = element['distance']['text']
                    results.append(distance)
                else:
                    results.append("Distance calculation failed")
            return results
        else:
            return ["API request returned error: " + data['status']]
    else:
        return [f"Request failed with status code: {response.status_code}"]

class LocationDataHandler:
    def __init__(self, data_frame):
        # self.data_file = data_file
        self.api_key = os.getenv('GOOGLE_MAPS_API_KEY')
        self.data_frame = data_frame

    def get_latlong_from_address(self, address):
        try:
            result = find_place(address, self.api_key)
            lat = result['candidates'][0]['geometry']['location']['lat']
            lng = result['candidates'][0]['geometry']['location']['lng']
            return lat, lng
        except Exception as e:
            print(f"Error retrieving location for {address}: {e}")
            return None

    def calculate_distance(self, ref_point, latitude, longitude):
        try:
            location = (latitude, longitude)
            return geodesic(ref_point, location).kilometers
        except Exception as e:
            print(f"Error calculating distance: {e}")
            return None

    def filter_by_address(self, address, max_distance_km=30):
        ref_point = self.get_latlong_from_address(address)
        if not ref_point:
            return None
        
        def distance_calculation(row):
            return self.calculate_distance(ref_point, row['Latitude'], row['Longitude'])

        # Calculate distance for each row
        self.data_frame['Distance'] = self.data_frame.apply(distance_calculation, axis=1)

        # Select top 10 within the maximum distance
        df = self.data_frame[self.data_frame['Distance'] <= max_distance_km].sort_values(by='Distance').head(10).reset_index(drop=True)

        # Calculate Actual Distance Using GMaps API
        destinations = df.apply(lambda row: f"{row['Latitude']},{row['Longitude']}", axis=1).tolist()
        distances = get_distances_for_multiple_destinations(f"{ref_point[0]},{ref_point[1]}", destinations, self.api_key)

        # Add the distances back to the DataFrame
        df['Distance'] = distances

        return df