Update app.py

app.py

@@ -190,8 +190,7 @@ def rgb_to_hex(rgb):
 
 
 def mol_to_pharm3d(mol, mode='html'):
-    if mol is None:
-        return
+    print('pharmco')
     AllChem.Compute2DCoords(mol)
 
     feats = FEAT_FACTORY.GetFeaturesForMol(mol)
@@ -1066,7 +1065,7 @@ def update_df(file, progress=gr.Progress(track_tqdm=True)):
                 df['Compound'] = df['X1'].parallel_apply(
                     lambda smiles: PandasTools._MolPlusFingerprint(Chem.MolFromSmiles(smiles)))
             df['Scaffold'] = df['Compound'].parallel_apply(MurckoScaffold.GetScaffoldForMol)
-            df['Scaffold SMILES'] = df['Scaffold'].parallel_apply(Chem.MolToSmiles)
+            df['Scaffold SMILES'] = df['Scaffold'].parallel_apply(lambda x: Chem.MolToSmiles(x))
 
         if task == 'Compound-Protein Binding Affinity':
             # Convert Y^ from pIC50 to IC50
@@ -1114,12 +1113,14 @@ def create_html_report(df, file=None, task=None, opts=(), progress=gr.Progress(t
     columns_unique = None
 
     if 'Compound' in df_html.columns and 'Exclude Molecular Graph' not in opts:
-        df_html['Compound'] = df_html['Compound'].parallel_apply(PandasTools.PrintAsImageString)
+        df_html['Compound'] = df_html['Compound'].parallel_apply(
+            lambda x: PandasTools.PrintAsImageString(x) if not pd.isna(x) else x)
     else:
         df_html.drop(['Compound'], axis=1, inplace=True)
 
     if 'Scaffold' in df_html.columns and 'Exclude Scaffold Graph' not in opts:
-        df_html['Scaffold'] = df_html['Scaffold'].parallel_apply(PandasTools.PrintAsImageString)
+        df_html['Scaffold'] = df_html['Scaffold'].parallel_apply(
+            lambda x: PandasTools.PrintAsImageString(x) if not pd.isna(x) else x)
     else:
         df_html.drop(['Scaffold'], axis=1, inplace=True)
 
@@ -1148,7 +1149,8 @@ def create_html_report(df, file=None, task=None, opts=(), progress=gr.Progress(t
     df_html.rename(columns=column_aliases, inplace=True)
     df_html.index.name = 'Index'
     if 'Target FASTA' in df_html.columns:
-        df_html['Target FASTA'] = df_html['Target FASTA'].parallel_apply(wrap_text)
+        df_html['Target FASTA'] = df_html['Target FASTA'].parallel_apply(
+            lambda x: wrap_text(x) if not pd.isna(x) else x)
 
     num_cols = df_html.select_dtypes('number').columns
     num_col_colors = sns.color_palette('husl', len(num_cols))
@@ -1165,7 +1167,8 @@ def create_html_report(df, file=None, task=None, opts=(), progress=gr.Progress(t
         if 'Target ID' in df_html.columns:
             df_html.drop(['Target FASTA'], axis=1, inplace=True)
         if 'Target FASTA' in df_html.columns:
-            df_html['Target FASTA'] = df_html['Target FASTA'].parallel_apply(wrap_text)
+            df_html['Target FASTA'] = df_html['Target FASTA'].parallel_apply(
+                lambda x: wrap_text(x) if not pd.isna(x) else x)
         if 'Scaffold SMILES' in df_html.columns:
             df_html.drop(['Scaffold SMILES'], axis=1, inplace=True)
         styled_df = df_html.fillna('').style.format(precision=3)
@@ -1203,7 +1206,8 @@ def create_html_report(df, file=None, task=None, opts=(), progress=gr.Progress(t
 
     else:
         if 'Exclude Pharmacophore 3D' not in opts:
-            df_html['Pharmacophore'] = df_html['Compound'].parallel_apply(mol_to_pharm3d)
+            df_html['Pharmacophore'] = df_html['Compound'].parallel_apply(
+                lambda x: mol_to_pharm3d(x) if not pd.isna(x) else x)
 
         image_zoom_formatter = HTMLTemplateFormatter(template='<div class="image-zoom-viewer"><%= value %></div>')
         uniprot_id_formatter = HTMLTemplateFormatter(
@@ -1442,10 +1446,12 @@ def submit_report(df, score_list, filter_list, task, progress=gr.Progress(track_
     df_report = df.copy()
     try:
         for filter_name in filter_list:
-            df_report[filter_name] = df_report['Compound'].parallel_apply(FILTER_MAP[filter_name])
+            df_report[filter_name] = df_report['Compound'].parallel_apply(
+                lambda x: FILTER_MAP[filter_name](x) if not pd.isna(x) else x)
 
         for score_name in score_list:
-            df_report[score_name] = df_report['Compound'].parallel_apply(SCORE_MAP[score_name])
+            df_report[score_name] = df_report['Compound'].parallel_apply(
+                lambda x: SCORE_MAP[score_name](x) if not pd.isna(x) else x)
 
         return (create_html_report(df_report, file=None, task=task), df_report,
                 gr.File(visible=False), gr.File(visible=False))