Upload Advisernote.py

Advisernote.py

@@ -419,9 +419,30 @@ def extract_notion_plain_text(prop):
         return ", ".join(item.get("name", "") for item in prop.get("people", []) if item.get("name")).strip()
     if prop_type == "number":
         value = prop.get("number")
-        return "" if value is None else str(value).strip()
+        if value is None:
+            return ""
+        if isinstance(value, float) and value.is_integer():
+            return str(int(value)).strip()
+        return str(value).strip()
     return ""
 
+def normalize_phone_text(value):
+    text = "" if value is None else str(value).strip()
+    if text.endswith(".0") and text[:-2].isdigit():
+        text = text[:-2]
+    return text
+
+def is_phone_like_field(field_name):
+    normalized = str(field_name or "").strip().lower()
+    return any(key in normalized for key in ["phone", "mobile", "telephone", "contact number", "cell", "전화", "연락", "휴대"])
+
+def make_excel_safe_phone(value):
+    text = normalize_phone_text(value)
+    if not text:
+        return ""
+    escaped = text.replace('"', '""')
+    return f'="{escaped}"'
+
 def find_notion_property_value(props, preferred_keys, fallback_types=None):
     normalized_lookup = {str(key).strip().lower(): value for key, value in props.items()}
     for key in preferred_keys:
@@ -593,6 +614,8 @@ def fetch_client_contacts_from_notion(search_text="", selected_fields=None, cust
                         )
                     else:
                         row[field_name] = find_notion_property_by_exact_or_contains(props, field_name)
+                    if is_phone_like_field(field_name):
+                        row[field_name] = normalize_phone_text(row[field_name])
 
                 if not any(str(value).strip() for value in row.values()):
                     continue
@@ -1625,8 +1648,15 @@ if check_password():
 
             contacts_df = st.session_state.get("notion_contacts")
             if isinstance(contacts_df, pd.DataFrame):
+                contacts_df = contacts_df.fillna("").astype(str)
+                phone_columns = [col for col in contacts_df.columns if is_phone_like_field(col)]
+                for col in phone_columns:
+                    contacts_df[col] = contacts_df[col].map(normalize_phone_text)
                 st.dataframe(contacts_df, use_container_width=True, hide_index=True)
-                csv_data = contacts_df.to_csv(index=False).encode("utf-8-sig")
+                csv_df = contacts_df.copy()
+                for col in phone_columns:
+                    csv_df[col] = csv_df[col].map(make_excel_safe_phone)
+                csv_data = csv_df.to_csv(index=False).encode("utf-8-sig")
                 st.download_button(
                     "Download CSV",
                     data=csv_data,