Update trend_crawl.py

trend_crawl.py

@@ -1,6 +1,7 @@
 from trendspy import Trends
 import streamlit as st
 from datetime import datetime, timezone
+tr = Trends()
 
 TREND_TOPICS = {
     1: "Autos and Vehicles",
@@ -23,9 +24,7 @@ TREND_TOPICS = {
     18: "Technology",
     19: "Travel and Transportation"
 }
-
 trends_json = {}
-
 def process_trends_for_country(country_code, trends_list):
     if country_code not in trends_json:
         trends_json[country_code] = {"All categories" : {}}
@@ -56,24 +55,27 @@ def process_trends_for_country(country_code, trends_list):
         trends_json[country_code]["All categories"][topic_name] = {
             "searchQueries": trend.volume, 
             "articles": articles,
-            "ended_timestamp": convert_to_datetime(trend.started_timestamp[0]),
+            "is_trend_finished": trend.is_trend_finished,
         }
         trends_json[country_code][category][topic_name] = {
             "searchQueries": trend.volume, 
             "articles": articles,
         }
-        return trends_json
 
 def convert_to_datetime( raw_time):
     """Converts time in seconds to a datetime object with UTC timezone, if it exists."""
     return datetime.fromtimestamp(raw_time, tz=timezone.utc) if raw_time else None
 
 def get_trends(countries: list):
-    tr = Trends()
     for country in countries:
         trends = tr.trending_now(geo=country)
         
         process_trends_for_country(country, trends)
         all_categories = trends_json[country]["All categories"]
+        # sorted_all_categories = dict(
+        #     sorted(all_categories.items(), key=lambda x: x[1]["searchQueries"], reverse=True)
+        # )
+        #trends_json[country]["All categories"] = sorted_all_categories
     return trends_json
 
+