Update app.py

app.py

@@ -2,16 +2,15 @@ import marimo
 import pandas as pd
 import io
 import matplotlib.pyplot as plt
-from script import getSearchResult, getClustersWithGraph, compare_clusters
 import os
+from script import getSearchResult, getClustersWithGraph, compare_clusters
 
 app = marimo.App()
 
-# 1) Upload + config
+# Cell 1: Upload + Config
 @app.cell
-def _(mo):
+def cell_config(mo):
     csv_upload = mo.ui.file(label="Upload Keyword CSV (1 column)")
-    # pull secrets from env (set in HF Space Secrets)
     api_key = os.environ.get("GOOGLE_API_KEY", "")
     cse_id  = os.environ.get("GOOGLE_CSE_ID", "")
     country = mo.ui.text(label="Country Code (e.g. UK)", value="UK")
@@ -22,9 +21,9 @@ def _(mo):
     run_button   = mo.ui.button(label="Run Clustering Comparison")
     return csv_upload, api_key, cse_id, country, language, database, serp_table, cluster_table, run_button
 
-# 2) Timestamp selectors selectors
+# Cell 2: Timestamp Selectors
 @app.cell
-def _(mo):
+def cell_timestamps(mo):
     timestamp_options = [
         ("Latest available (max)", "max"),
         ("March 2024 core update (2024-04-26 00:00:00.000000)", "2024-04-26 00:00:00.000000"),
@@ -38,43 +37,41 @@ def _(mo):
     timestamp_2 = mo.ui.dropdown(timestamp_options, label="Choose Timestamp 2")
     return timestamp_1, timestamp_2
 
-# 3) Read CSV
+# Cell 3: Read CSV
 @app.cell
-def _(csv_upload):
-    if csv_upload.value:
+def cell_read_csv(csv_upload):
+    if csv_upload is not None and csv_upload.value:
         df_keywords = pd.read_csv(io.BytesIO(csv_upload.value.read()))
         keywords = df_keywords.iloc[:, 0].tolist()
-    else:
-        df_keywords, keywords = None, []
-    return df_keywords, keywords
+        return df_keywords, keywords
+    return None, []
 
-# 4) Run search + clustering + comparison
+# Cell 4: Run Search, Cluster, Compare
 @app.cell
-def _(keywords, api_key, cse_id, country, language, database, serp_table, timestamp_1, timestamp_2, run_button):
+def cell_run(keywords, api_key, cse_id, country, language, database, serp_table, timestamp_1, timestamp_2, run_button):
     if run_button.clicked and keywords:
-        # 1st timestamp data fetch + cluster
+        # First timestamp cluster
         getSearchResult(keywords, language, country, api_key, cse_id, database, serp_table)
         fig1, clusters1 = getClustersWithGraph(database, serp_table, timestamp_1.value)
-
-        # 2nd timestamp data fetch + cluster
+        # Second timestamp cluster
         getSearchResult(keywords, language, country, api_key, cse_id, database, serp_table)
         fig2, clusters2 = getClustersWithGraph(database, serp_table, timestamp_2.value)
-
+        # Compare
         movement = compare_clusters(clusters1, clusters2)
         return fig1, fig2, movement
     return None, None, None
 
-# 5) Display the two network graphs
+# Cell 5: Display Graphs
 @app.cell
-def _(fig1, fig2):
-    if fig1 and fig2:
+def cell_display_graphs(fig1, fig2):
+    if fig1 is not None and fig2 is not None:
         display(fig1)
         display(fig2)
     return None
 
-# 6) Show the movement table
+# Cell 6: Show Movement Table
 @app.cell
-def _(movement):
+def cell_display_movement(movement):
     if movement is not None:
         movement.sort_values(by="searchTerms", inplace=True)
         movement.reset_index(drop=True, inplace=True)