Parallelized updating alexa ranking

site_list.py

@@ -7,6 +7,7 @@ import requests
 import threading
 from bs4 import BeautifulSoup as bs
 from datetime import datetime
+from argparse import ArgumentParser, RawDescriptionHelpFormatter
 
 pool = list()
 
@@ -22,7 +23,15 @@ def get_rank(domain_to_query, dest):
 					if strong.has_attr("class"):
 						if "metrics-data" in strong["class"]:
 							result = int(strong.text.strip().replace(',', ''))
-	dest = result
+							dest['rank'] = result
+
+parser = ArgumentParser(formatter_class=RawDescriptionHelpFormatter
+                        )
+parser.add_argument("--rank","-r",
+                    action="store_true",  dest="rank", default=False,
+                    help="Update all website ranks (not recommended)."
+                    )
+args = parser.parse_args()
 
 with open("data.json", "r", encoding="utf-8") as data_file:
 	data = json.load(data_file)
@@ -33,18 +42,25 @@ with open("sites.md", "w") as site_file:
 
 	for social_network in data:
 		url_main = data.get(social_network).get("urlMain")
-		th = threading.Thread(target=get_rank, args=(url_main, data.get(social_network)["rank"]))
-		pool.append((url_main, th))
+		data.get(social_network)["rank"] = 0
+		if args.rank:
+			th = threading.Thread(target=get_rank, args=(url_main, data.get(social_network)))
+		else:
+			th = None
+		pool.append((url_main, url_main, th))
+		if args.rank:
 			th.start()
 
 	index = 1
-	for social_network, th in pool:
+	for social_network, url_main, th in pool:
+		if args.rank:
 			th.join()
 		site_file.write(f'{index}. [{social_network}]({url_main})\n')
 		sys.stdout.write("\r{0}".format(f"Updated {index} out of {data_length} entries"))
 		sys.stdout.flush()
 		index = index + 1
 
+	if args.rank:
 		site_file.write(f'\nAlexa.com rank data fetched at ({datetime.utcnow()} UTC)\n')
 
 sorted_json_data = json.dumps(data, indent=2, sort_keys=True)