Update Homepage.py

Homepage.py

@@ -76,7 +76,7 @@ if authentication_status:
         ketoan_end_time = col2.date_input(
             "Select end date", value=DEFAULT_END_DATE)
         submit_button = st.form_submit_button(
-            label='Filter',  use_container_width=True)
+            label='Filter')
 
     # the duration between 2 dates exclude Sunday
     duration = sum(1 for i in range((ketoan_end_time - ketoan_start_time).days)
@@ -89,17 +89,17 @@ if authentication_status:
     days_excluding_sundays = days_in_month - sundays_in_month
     #----------------------#
 
-    @st.cache_data(ttl=timedelta(days=1))
+    @st.cache
     def collect_data(link):
         return(pd.DataFrame((requests.get(link).json())))
 
-    @st.cache_data()
+    @st.cache
     def rename_lop(dataframe, column_name):
         dataframe[column_name] = dataframe[column_name].replace(
             {1: "Hoa Cúc", 2: "Gò Dầu", 3: "Lê Quang Định", 5: "Lê Hồng Phong"})
         return dataframe
 
-    @st.cache_data()
+    @st.cache
     def grand_total(dataframe, column):
         # create a new row with the sum of each numerical column
         totals = dataframe.select_dtypes(include=[float, int]).sum()
@@ -171,7 +171,7 @@ if authentication_status:
     ca6 = pd.to_datetime('2000-01-01 19:30:00').time()
     # Create a function that takes a time and returns "Morning" or "Evening" depending on whether the time falls within the specified range
 
-    @st.cache_data()
+    @st.cache
     def time_of_day(time):
         if (time >= start_time) & (time < end_time):
             return "Sáng"
@@ -179,7 +179,7 @@ if authentication_status:
             return "Tối"
     # Create a function that takes a time and returns "Morning" or "Evening" depending on whether the time falls within the specified range
 
-    @st.cache_data()
+    @st.cache
     def day_of_week(day):
         if (day == 5) | (day == 6):
             return "weekend"
@@ -187,7 +187,7 @@ if authentication_status:
             return "weekdays"
     # Create a function that takes a time and returns "Morning" or "Evening" depending on whether the time falls within the specified range
 
-    @st.cache_data()
+    @st.cache
     def cahoc_converter(ca):
         if (ca >= ca1) & (ca < ca2):
             return 1
@@ -369,14 +369,14 @@ if authentication_status:
     # "------------------"
 
     # Define a function
-    @st.cache_data(ttl=timedelta(days=365))
+    @st.cache
     def csv_reader(file):
         df = pd.read_csv(file)
         df = df.query("phanloai == 1")  # Filter lop chính
         df['date_created'] = pd.to_datetime(df['date_created'])
         return df
 
-    @st.cache_data(ttl=timedelta(days=1))
+    @st.cache
     def collect_filtered_data(table, date_column='', start_time='', end_time=''):
         link = f"https://vietop.tech/api/get_data/{table}?column={date_column}&date_start={start_time}&date_end={end_time}"
         df = pd.DataFrame((requests.get(link).json()))
@@ -425,7 +425,7 @@ if authentication_status:
         ['id', 'fullname', 'lop_cn'], as_index=False)['thucthu'].sum()
     # "_______________"
 
-    @st.cache_data()
+    @st.cache
     def thucthu_time(dataframe, column):
         df = dataframe.groupby(['lop_cn', column], as_index=False)[
             'thucthu'].sum()
@@ -656,7 +656,7 @@ if authentication_status:
         lambda x: '{:.2%}'.format(x/100))
 
     # define a function
-    @ st.cache_data()
+    @ st.cache
     def thousands_divider(df, col):
         df[col] = df[col].apply(
             lambda x: '{:,.0f}'.format(x))