Remove old top5 designations and make N configurable (with default 50)

app.py

@@ -234,15 +234,15 @@ def render_hub_user_link(hub_id):
     return f'<a target="_blank" href="{link}" style="color: var(--link-text-color); text-decoration: underline;text-decoration-style: dotted;">{hub_id}</a>'
 
 
-def obtain_top_5_users(user_ids_annotations: Dict[str, int]) -> pd.DataFrame:
+def obtain_top_users(user_ids_annotations: Dict[str, int], N: int = 50) -> pd.DataFrame:
     """
-    This function returns the top 5 users with the most annotations.
+    This function returns the top N users with the most annotations.
 
     Args:
         user_ids_annotations: A dictionary with the user ids as the key and the number of annotations as the value.
 
     Returns:
-        A pandas dataframe with the top 5 users with the most annotations.
+        A pandas dataframe with the top N users with the most annotations.
     """
 
     dataframe = pd.DataFrame(
@@ -250,7 +250,7 @@ def obtain_top_5_users(user_ids_annotations: Dict[str, int]) -> pd.DataFrame:
     )
     dataframe[NAME] = dataframe[NAME].apply(render_hub_user_link)
     dataframe = dataframe.sort_values(by=NUMBER_ANNOTATIONS, ascending=False)
-    return dataframe.head(50)
+    return dataframe.head(N)
 
 
 def fetch_data() -> None:
@@ -260,7 +260,7 @@ def fetch_data() -> None:
 
     print(f"Starting to fetch data: {datetime.datetime.now()}")
 
-    global source_dataset, target_dataset, user_ids_annotations, annotated, remaining, percentage_completed, top5_dataframe
+    global source_dataset, target_dataset, user_ids_annotations, annotated, remaining, percentage_completed, top_dataframe
     source_dataset, target_dataset = obtain_source_target_datasets()
     user_ids_annotations = get_user_annotations_dictionary(target_dataset)
 
@@ -274,8 +274,8 @@ def fetch_data() -> None:
     print(f"Data fetched: {datetime.datetime.now()}")
 
 
-def get_top5() -> pd.DataFrame:
-    return obtain_top_5_users(user_ids_annotations)
+def get_top(N = 50) -> pd.DataFrame:
+    return obtain_top_users(user_ids_annotations, N=N)
 
 
 def main() -> None:
@@ -368,7 +368,7 @@ def main() -> None:
                 kpi_chart, inputs=[], outputs=[kpi_hall_plot], every=update_interval_charts
             )
 
-            top5_df_plot = gr.Dataframe(
+            top_df_plot = gr.Dataframe(
                 headers=[NAME, NUMBER_ANNOTATIONS],
                 datatype=[
                     "markdown",
@@ -379,7 +379,7 @@ def main() -> None:
                 interactive=False,
                 every=update_interval,
             )
-            demo.load(get_top5, None, [top5_df_plot], every=update_interval_charts)
+            demo.load(get_top, None, [top_df_plot], every=update_interval_charts)
 
     # Launch the Gradio interface
     demo.launch()