app.py

import streamlit as st
from apify_client import ApifyClient
import requests
import pandas as pd

def fetch_google_maps_info(website_name):
    apify_client = ApifyClient("apify_api_uz0y556N4IG2aLcESj67kmnGSUpHF12XAkLp")

    # Prepare the Actor input for Google Maps
    run_input = {
        "searchStringsArray": [website_name],
        # ... other parameters
    }

    # Run the Actor and wait for it to finish
    run = apify_client.actor("nwua9Gu5YrADL7ZDj").call(run_input=run_input)

    # Fetch Actor results from the run's dataset
    items = list(apify_client.dataset(run["defaultDatasetId"]).iterate_items())
    return items[0] if items else None

def fetch_weather_info(lat, lon):
    API_KEY = "91b23cab82ee530b2052c8757e343b0d"
    url = f"https://api.openweathermap.org/data/3.0/onecall?lat={lat}&lon={lon}&exclude=hourly,daily&appid={API_KEY}"
    response = requests.get(url)
    return response.json()

# Main Streamlit app
website_name = st.text_input("Enter a website / company name:")

if website_name:
    google_maps_data = fetch_google_maps_info(website_name)

    if google_maps_data:
        # Formatting and displaying all the data in Streamlit table
        table_data = {}
        for key, value in google_maps_data.items():
            # Handle lists of strings
            if isinstance(value, list) and all(isinstance(item, str) for item in value):
                table_data[key] = ", ".join(value)
            # Handle lists of dictionaries
            elif isinstance(value, list) and all(isinstance(item, dict) for item in value):
                table_data[key] = ", ".join([str(item) for item in value])
            # Handle nested dictionaries
            elif isinstance(value, dict):
                table_data[key] = ", ".join([f"{k}: {v}" for k, v in value.items()])
            else:
                table_data[key] = value

        st.table(table_data)

        # Fetch weather info based on Google Maps data's location
        lat = google_maps_data["location"]["lat"]
        lng = google_maps_data["location"]["lng"]

        if lat and lng:
            # Display location on Streamlit map
            df_location = pd.DataFrame({'lat': [lat], 'lon': [lng]})
            st.map(df_location)

            weather_data = fetch_weather_info(lat, lng)
            current_weather = weather_data.get("current", {})
            st.write(f"Temperature: {current_weather.get('temp')}°C")
            st.write(f"Weather: {current_weather.get('weather')[0].get('description')}")
    else:
        st.write("No results found for this website / company name on Google Maps.")