Update app.py

app.py

@@ -300,6 +300,8 @@ def show_dimensions_selector(search_type):
 
 
 def show_paginated_dataframe(report, rows_per_page=20, model_type='english'):
+    logger.info("Displaying paginated dataframe")
+    
     # Check if required columns are present
     required_columns = ['page', 'query', 'clicks', 'impressions', 'ctr', 'position']
     missing_columns = [col for col in required_columns if col not in report.columns]
@@ -317,45 +319,18 @@ def show_paginated_dataframe(report, rows_per_page=20, model_type='english'):
         except ValueError:
             return x
     
-    def format_relevancy_score(x):
-        if x is None:
-            return '<button class="calculate-btn">Calculate</button>'
-        try:
-            return f"{float(x):.2f}"
-        except ValueError:
-            return x
-    
     report['ctr'] = report['ctr'].apply(format_ctr)
     if 'relevancy_score' not in report.columns:
         report['relevancy_score'] = None
-    report['relevancy_score'] = report['relevancy_score'].apply(format_relevancy_score)
     
-    def make_clickable(url):
-        return f'<a href="{url}" target="_blank">{url}</a>'
-    
-    report['clickable_url'] = report['page'].apply(make_clickable)
-    
-    columns = ['clickable_url', 'query', 'impressions', 'clicks', 'ctr', 'position', 'relevancy_score']
+    columns = ['page', 'query', 'impressions', 'clicks', 'ctr', 'position', 'relevancy_score']
     report = report[columns]
 
-    sort_column = st.selectbox("Sort by:", columns[1:], index=columns[1:].index('impressions'))
+    sort_column = st.selectbox("Sort by:", columns, index=columns.index('impressions'))
     sort_order = st.radio("Sort order:", ("Descending", "Ascending"))
     
     ascending = sort_order == "Ascending"
-    
-    def safe_float_convert(x):
-        try:
-            return float(x.rstrip('%')) / 100 if isinstance(x, str) and x.endswith('%') else float(x)
-        except ValueError:
-            return 0
-    
-    report['ctr_numeric'] = report['ctr'].apply(safe_float_convert)
-    report['relevancy_score_numeric'] = report['relevancy_score'].apply(lambda x: safe_float_convert(x) if x != '<button class="calculate-btn">Calculate</button>' else -1)
-    
-    sort_column_numeric = sort_column + '_numeric' if sort_column in ['ctr', 'relevancy_score'] else sort_column
-    report = report.sort_values(by=sort_column_numeric, ascending=ascending)
-    
-    report = report.drop(columns=['ctr_numeric', 'relevancy_score_numeric'])
+    report = report.sort_values(by=sort_column, ascending=ascending)
 
     total_rows = len(report)
     total_pages = (total_rows - 1) // rows_per_page + 1
@@ -376,44 +351,40 @@ def show_paginated_dataframe(report, rows_per_page=20, model_type='english'):
     start_idx = (st.session_state.current_page - 1) * rows_per_page
     end_idx = start_idx + rows_per_page
     
-    # Create a placeholder for the dataframe
-    dataframe_placeholder = st.empty()
-    
-    # Function to update the dataframe
-    def update_dataframe():
-        df_html = report.iloc[start_idx:end_idx].to_html(escape=False, index=False)
-        df_html = df_html.replace('</table>', ''.join([
-            '<style>',
-            '.calculate-btn { cursor: pointer; padding: 5px 10px; background-color: #4CAF50; color: white; border: none; border-radius: 4px; }',
-            '.calculate-btn:hover { background-color: #45a049; }',
-            '</style>',
-            *[f'<script>document.getElementsByTagName("table")[0].rows[{i+1}].cells[6].onclick = function(e) {{ if(e.target.classList.contains("calculate-btn")) {{ Streamlit.setComponentValue("calculate_relevancy", {start_idx + i}); }} }}</script>'
-              for i in range(min(rows_per_page, len(report) - start_idx))]
-        ]) + '</table>')
-        dataframe_placeholder.markdown(df_html, unsafe_allow_html=True)
+    page_data = report.iloc[start_idx:end_idx].reset_index(drop=True)
     
-    # Initial dataframe display
-    update_dataframe()
-    
-    # Handle relevancy calculation
-    if st.session_state.get('calculate_relevancy') is not None:
-        row_index = st.session_state.calculate_relevancy
-        logger.info(f"Calculating relevancy for row index: {row_index}")
-        try:
-            page_content = fetch_content(report.iloc[row_index]['page'])
-            query = report.iloc[row_index]['query']
-            relevancy_score = calculate_single_relevancy_score(page_content, query, model_type)
-            logger.info(f"Relevancy score calculated: {relevancy_score}")
-            report.at[row_index, 'relevancy_score'] = f"{relevancy_score:.2f}"
-            st.session_state.calculate_relevancy = None  # Reset the state
-            update_dataframe()  # Update the dataframe display
-            st.success(f"Relevancy score calculated for row {row_index + 1}")
-        except Exception as e:
-            logger.error(f"Error calculating relevancy score: {str(e)}")
-            st.error(f"Error calculating relevancy score: {str(e)}")
+    for idx, row in page_data.iterrows():
+        col1, col2, col3, col4, col5, col6, col7, col8 = st.columns([3, 2, 1, 1, 1, 1, 1, 1])
+        with col1:
+            st.write(f"[{row['page']}]({row['page']})")
+        with col2:
+            st.write(row['query'])
+        with col3:
+            st.write(row['impressions'])
+        with col4:
+            st.write(row['clicks'])
+        with col5:
+            st.write(row['ctr'])
+        with col6:
+            st.write(row['position'])
+        with col7:
+            st.write(row['relevancy_score'] if row['relevancy_score'] is not None else "N/A")
+        with col8:
+            if st.button("Calculate", key=f"calc_{idx}"):
+                logger.info(f"Calculating relevancy for row index: {start_idx + idx}")
+                try:
+                    page_content = fetch_content(row['page'])
+                    query = row['query']
+                    relevancy_score = calculate_single_relevancy_score(page_content, query, model_type)
+                    logger.info(f"Relevancy score calculated: {relevancy_score}")
+                    report.at[start_idx + idx, 'relevancy_score'] = f"{relevancy_score:.2f}"
+                    st.success(f"Relevancy score calculated for row {start_idx + idx + 1}")
+                    st.experimental_rerun()
+                except Exception as e:
+                    logger.error(f"Error calculating relevancy score: {str(e)}")
+                    st.error(f"Error calculating relevancy score: {str(e)}")
 
     return report
-
 # -------------
 # Main Streamlit App Function
 # -------------