| import os
|
| import requests
|
| import pandas as pd
|
| from dotenv import load_dotenv
|
| from urllib.parse import quote_plus
|
|
|
| load_dotenv()
|
| API_KEY = os.getenv("RAPIDAPI_KEY")
|
| API_HOST = os.getenv("RAPIDAPI_HOST")
|
|
|
| HEADERS = {
|
| "x-rapidapi-host": API_HOST,
|
| "x-rapidapi-key": API_KEY
|
| }
|
|
|
| BASE_URL = f"https://{API_HOST}/v1/app-store-api/reviews"
|
|
|
| def fetch_appstore_reviews(app_id, page=1, country="us", lang="en"):
|
| params = {
|
| "id": app_id,
|
| "sort": "mostRecent",
|
| "page": page,
|
| "country": country,
|
| "lang": lang
|
| }
|
| try:
|
| resp = requests.get(BASE_URL, headers=HEADERS, params=params, timeout=10)
|
| resp.raise_for_status()
|
| return resp.json()
|
| except Exception as e:
|
| print(f"Exception fetching {app_id}:", e)
|
| return None
|
|
|
| def search_appstore_app(query, country="us"):
|
| """Search Apple App Store for an app, returning trackId."""
|
| try:
|
|
|
| safe_query = quote_plus(str(query))
|
|
|
| url = f"https://{API_HOST}/v1/app-store-api/search"
|
| params = {"q": safe_query, "country": country, "limit": 1}
|
|
|
|
|
| resp = requests.get(url, headers=HEADERS, params=params, timeout=10)
|
| resp.raise_for_status()
|
| results = resp.json()
|
|
|
|
|
| if isinstance(results, dict) and "results" in results:
|
| results = results["results"]
|
|
|
| return results[0]["trackId"] if results else None
|
|
|
| except requests.exceptions.RequestException as e:
|
| print(f"Search failed for {query}:", e)
|
| return None
|
| except Exception as e:
|
| print(f"Unexpected error searching {query}:", e)
|
| return None
|
|
|
| def merge_google_apple(google_df):
|
| apple_data = []
|
| for app in google_df['App']:
|
| app_id = search_appstore_app(app)
|
| if app_id:
|
| reviews = fetch_appstore_reviews(app_id)
|
| if reviews:
|
| ratings = [r.get("score", 0) for r in reviews]
|
| avg_rating = sum(ratings)/len(ratings) if ratings else None
|
| apple_data.append({
|
| "App": app,
|
| "AppleRating": avg_rating,
|
| "AppleReviews": len(reviews)
|
| })
|
| continue
|
|
|
| apple_data.append({"App": app, "AppleRating": None, "AppleReviews": 0})
|
|
|
| apple_df = pd.DataFrame(apple_data)
|
| combined = pd.merge(google_df, apple_df, on="App", how="outer")
|
| os.makedirs("data/cleaned_data", exist_ok=True)
|
| combined.to_csv("data/cleaned_data/combined_apps.csv", index=False)
|
| return combined
|
|
|
