diff --git a/pipeline/src/pipeline/get_data.py b/pipeline/src/pipeline/get_data.py
index 720fae0..bbd6cfa 100644
--- a/pipeline/src/pipeline/get_data.py
+++ b/pipeline/src/pipeline/get_data.py
@@ -376,17 +376,20 @@ async def scrape_messages(telegram_client, telegram_channels, start_date, end_da
                 wait_time = 5
             ):
                 reply = None
-                if message is not None:
+                print('message.text: ', message.text)
+                if message.text:
                     df_messages = arrange_telegram_messages(df_messages, message, reply, channel)
                 if channel_entity.broadcast and message.post and message.replies:
                     df_replies = pd.DataFrame()
                     try:
                         async for reply in telegram_client.iter_messages(
                             channel_entity,
+                            offset_date=start_date,
+                            reverse=True,
                             reply_to=message.id,
                             wait_time = 5
                         ):
-                            if reply is not None:
+                            if reply.text:
                                 df_replies = arrange_telegram_messages(df_replies, message, reply, channel)
                             time.sleep(5)
                         if len(df_replies) > 0:
diff --git a/pipeline/src/pipeline/utils.py b/pipeline/src/pipeline/utils.py
index 298593d..c8f16de 100644
--- a/pipeline/src/pipeline/utils.py
+++ b/pipeline/src/pipeline/utils.py
@@ -896,37 +896,37 @@ def save_data(name, directory, data, id, sm_code, config):
         with open(tweets_path, "rb") as upload_file:
             blob_client.upload_blob(upload_file, overwrite=True)
 
-    # append to existing twitter dataframe
-    if "rcrc" in data.columns:
-        final_table_columns = ["index", "source", "member_count", "message_count", \
-            "text", "datetime", "id", "date", "rcrc", "cva", "full_text_en"]
-        data.drop(columns=[col for col in data if col not in final_table_columns], inplace=True)
-        if containsNumber(name):
-            name = "_".join(name.split('_')[0:3])
-
-    data_all_path = f"./{directory}/{name}_all.csv"
-    try:
-        if not config["skip-datalake"]:
-            blob_client = get_blob_service_client(f'{directory}/{name}_all.csv', config)
-            with open(data_all_path, "wb") as download_file:
-                download_file.write(blob_client.download_blob().readall())
-        data_old = pd.read_csv(data_all_path)  # , lines=True)
-        data_all = data_old.append(data, ignore_index=True)
-    except:
-        data_all = data.copy()
-
-    # drop duplicates and save
-    try:
-        data_all = data_all.drop_duplicates(subset=[id])
-    except:
-        pass
-    data_all.to_csv(data_all_path, index=False, encoding="utf-8")
-
-    # upload to datalake
-    if not config["skip-datalake"]:
-        blob_client = get_blob_service_client(f'{directory}/{name}_all.csv', config)
-        with open(data_all_path, "rb") as upload_file:
-            blob_client.upload_blob(upload_file, overwrite=True)
+    # # append to existing twitter dataframe
+    # if "rcrc" in data.columns:
+    #     final_table_columns = ["index", "source", "member_count", "message_count", \
+    #         "text", "datetime", "id", "date", "rcrc", "cva", "full_text_en"]
+    #     data.drop(columns=[col for col in data if col not in final_table_columns], inplace=True)
+    #     if containsNumber(name):
+    #         name = "_".join(name.split('_')[0:3])
+
+    # data_all_path = f"./{directory}/{name}_all.csv"
+    # try:
+    #     if not config["skip-datalake"]:
+    #         blob_client = get_blob_service_client(f'{directory}/{name}_all.csv', config)
+    #         with open(data_all_path, "wb") as download_file:
+    #             download_file.write(blob_client.download_blob().readall())
+    #     data_old = pd.read_csv(data_all_path)  # , lines=True)
+    #     data_all = data_old.append(data, ignore_index=True)
+    # except:
+    #     data_all = data.copy()
+
+    # # drop duplicates and save
+    # try:
+    #     data_all = data_all.drop_duplicates(subset=[id])
+    # except:
+    #     pass
+    # data_all.to_csv(data_all_path, index=False, encoding="utf-8")
+
+    # # upload to datalake
+    # if not config["skip-datalake"]:
+    #     blob_client = get_blob_service_client(f'{directory}/{name}_all.csv', config)
+    #     with open(data_all_path, "rb") as upload_file:
+    #         blob_client.upload_blob(upload_file, overwrite=True)
 
 
 def read_db(sm_code, start_date, end_date, config):