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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
if isinstance(value, list):
table_data[key] = ", ".join(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.") |