code optimization :)

time_series_gradio.py

@@ -161,7 +161,7 @@ def create_time_series_summary_gradio(historical_df: pd.DataFrame) -> dict:
 
 def create_model_time_series_gradio(historical_df: pd.DataFrame, model_name: str) -> dict:
     def empty_figs():
-        ef = lambda p: go.Figure().update_layout(title=f"{model_name.upper()} - {p} Results Over Time",
+        ef = lambda plat: go.Figure().update_layout(title=f"{model_name.upper()} - {plat} Results Over Time",
             height=500, font=dict(size=16, color='#CCCCCC'), paper_bgcolor='#000000',
             plot_bgcolor='#1a1a1a', margin=dict(b=130)) or go.Figure()
         return {'amd_plot': ef('AMD'), 'nvidia_plot': ef('NVIDIA')}
@@ -182,23 +182,23 @@ def create_model_time_series_gradio(historical_df: pd.DataFrame, model_name: str
             if dd.empty:
                 continue
             r = dd.iloc[0]
-            p = r.get(f'success_{platform}', 0)
-            f = r.get(f'failed_multi_no_{platform}', 0) + r.get(f'failed_single_no_{platform}', 0)
-            s = r.get(f'skipped_{platform}', 0)
+            passed = r.get(f'success_{platform}', 0)
+            failed = r.get(f'failed_multi_no_{platform}', 0) + r.get(f'failed_single_no_{platform}', 0)
+            skipped = r.get(f'skipped_{platform}', 0)
             
             pc = fc = sc = 0
             if i > 0:
-                pd = md[md['date'] == dates[i-1]]
-                if not pd.empty:
-                    pr = pd.iloc[0]
+                prev_dd = md[md['date'] == dates[i-1]]
+                if not prev_dd.empty:
+                    pr = prev_dd.iloc[0]
                     pc = pr.get(f'success_{platform}', 0)
                     fc = pr.get(f'failed_multi_no_{platform}', 0) + pr.get(f'failed_single_no_{platform}', 0)
                     sc = pr.get(f'skipped_{platform}', 0)
             
             data.extend([
-                {'date': date, 'count': p, 'test_type': 'Passed', 'change': p - pc},
-                {'date': date, 'count': f, 'test_type': 'Failed', 'change': f - fc},
-                {'date': date, 'count': s, 'test_type': 'Skipped', 'change': s - sc}
+                {'date': date, 'count': passed, 'test_type': 'Passed', 'change': passed - pc},
+                {'date': date, 'count': failed, 'test_type': 'Failed', 'change': failed - fc},
+                {'date': date, 'count': skipped, 'test_type': 'Skipped', 'change': skipped - sc}
             ])
         return pd.DataFrame(data)