# Store results in a CSV for later analysis df = pd.DataFrame(enriched) out_path = Path("filmyzilla_watch.csv") df.to_csv(out_path, mode='a', header=not out_path.exists(), index=False) logging.info(f"Appended len(enriched) rows to out_path")
new_titles = [t for t in raw_titles if t not in known] if not new_titles: logging.info("No new titles detected.") else: logging.info(f"len(new_titles) new title(s) discovered!") enriched = [] for title in new_titles: try: # Use Posy to pull clean metadata result = posy.search(title) if result: movie = posy.enrich(result[0]) enriched.append(movie.__dict__) else: logging.warning(f"Posy could not resolve: title") except Exception as e: logging.error(f"Error processing 'title': e") pip & posy filmyzilla
# ---------------------------------------------------------------------- # Main workflow # ---------------------------------------------------------------------- def main(poll_interval: int = 300): posy = Posy(omdb_api_key=OMDB_KEY) # Posy can forward the key to OMDb # Store results in a CSV for later analysis df = pd
while True: try: html = fetch_latest_page() raw_titles = parse_titles(html) pip & posy filmyzilla
# Update cache with cache_file.open("a") as f: for t in new_titles: f.write(t + "\n")
logging.info(f"Sleeping for poll_intervals...") time.sleep(poll_interval)
# Search for a recent Bollywood hit movies = p.search("RRR") print(f"Found len(movies) matches.")