app.py

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

# Function to fetch Google Maps info using the antonces~gmaps actor
def fetch_google_maps_info(website_name):
    apify_client = ApifyClient("apify_api_uz0y556N4IG2aLcESj67kmnGSUpHF12XAkLp")
    run_input = {"searchStringsArray": [website_name]}
    run = apify_client.actor("antonces~gmaps").call(run_input=run_input)
    items = list(apify_client.dataset(run["defaultDatasetId"]).iterate_items())
    return items[0] if items else None

# Function to fetch weather info from OpenWeatherMap API
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()

# Function to fetch website content using the antonces~web-scraper-task actor
def fetch_website_content(website_url):
    apify_client = ApifyClient("apify_api_uz0y556N4IG2aLcESj67kmnGSUpHF12XAkLp")
    run_input = {}
    run = apify_client.actor("antonces~web-scraper-task").call(run_input=run_input)
    items = list(apify_client.dataset(run["defaultDatasetId"]).iterate_items())
    return items if items else None

# Streamlit app for Data Visualization
st.title("Data Visualization")

# Input for website or company name
website_name = st.text_input("Enter a website / company name:")

if website_name:
    # Initialize the progress bar
    progress_bar = st.progress(0)
    
    # Fetch Google Maps data
    google_maps_data = fetch_google_maps_info(website_name)
    progress_bar.progress(50)

    if google_maps_data:
        # Display website link
        website_link = google_maps_data.get('website')
        st.text_area("Website Link:", website_link)

        # Display location and fetch weather info
        lat = google_maps_data["location"]["lat"]
        lng = google_maps_data["location"]["lng"]
        st.map(pd.DataFrame({'lat': [lat], 'lon': [lng]}))
        weather_data = fetch_weather_info(lat, lng)
        current_weather = weather_data.get("current", {})
        temp = current_weather.get('temp')
        temp_in_celsius = temp - 273.15
        st.write(f"**Location:** {lat}, {lng}")
        st.write(f"**Temperature:** {temp_in_celsius:.2f}°C")
        st.write(f"**Weather:** {current_weather.get('weather')[0].get('description')}")
        
        # Display Occupancy Data
        st.subheader("Occupancy Data")
        occupancy_data = google_maps_data.get('popularTimesHistogram', {})
        for day, day_data in occupancy_data.items():
            hours = [entry['hour'] for entry in day_data]
            occupancy = [entry['occupancyPercent'] for entry in day_data]
            st.write(day)
            st.bar_chart(pd.Series(occupancy, index=hours))

        # Display Review Count and Distribution
        st.subheader("Review Count and Distribution")
        st.write(f"Total Reviews Count: {google_maps_data['reviewsCount']}")
        review_distribution = google_maps_data.get('reviewsDistribution', {})
        st.bar_chart(pd.Series(review_distribution))
        
        # Display Reviews Table
        st.subheader("Customer Reviews")
        reviews = google_maps_data.get('reviews', [])
        review_df = pd.DataFrame(reviews)
        st.table(review_df[['name', 'text', 'publishAt', 'likesCount', 'stars']])
        
        # Fetch and Display Website Content
        st.subheader("Website Content")
        website_content_data = fetch_website_content(website_link)
        progress_bar.progress(100)
        
        if website_content_data:
            website_df = pd.DataFrame(website_content_data)
            st.table(website_df)
        else:
            st.write("Unable to retrieve website content.")
    else:
        st.write("No results found for this website / company name on Google Maps.")