Fix CIs checks

Author: Omnia-Agabani

smart_pantry_manager/data/pantry_omnia.xlsx

@@ -1,6 +1,13 @@
-# spell-checker: disable
 """
+all_recipes.py
 All Recipes Page for Smart Pantry Application (SQLite version)
+
+Features:
+- Load recipes from SQLite database
+- Display recipe list with ingredients and instructions
+- Supports search/filtering
+
+Date: 2025-11-20
 """
 
 import ast
@@ -10,43 +17,39 @@
 import pandas as pd
 import streamlit as st
 
+# ---------- Page Setup ----------
 st.set_page_config(page_title="All Recipes", page_icon="📜", layout="wide")
 
 st.title("📜 All Recipes")
 st.caption("Browse all available recipes in the Smart Pantry system.")
 
 
-# ---------- Load recipes from SQLite ----------
+# ---------- Load Recipes ----------
 @st.cache_data
-def load_recipes():
+def load_recipes() -> pd.DataFrame:
     """
-    Load recipes from the SQLite database and normalize column names.
-    Returns a DataFrame with columns: Recipe, Ingredients, Instructions
+    Load recipes from SQLite database and normalize column names.
+
+    Returns:
+        pd.DataFrame: Columns = Recipe, Ingredients, Instructions
     """
     db_path = "smart_pantry_manager/data/Recipe_Dataset.sqlite"
-
-    # Check if database file exists
     if not os.path.exists(db_path):
         st.error(f"❌ Database file not found at: {db_path}")
         return pd.DataFrame(columns=["Recipe", "Ingredients", "Instructions"])
 
-    # Connect to SQLite database
     conn = sqlite3.connect(db_path)
-
     try:
-        # Load the table "recipes"
         df = pd.read_sql_query("SELECT * FROM recipes", conn)
-    except Exception as e:
-        st.error(f"Error reading database: {e}")
+    except Exception as err:
+        st.error(f"Error reading database: {err}")
         conn.close()
         return pd.DataFrame(columns=["Recipe", "Ingredients", "Instructions"])
-
     conn.close()
 
     # Normalize column names
     df.columns = [c.strip().lower() for c in df.columns]
 
-    # Rename columns if they exist
     rename_map = {
         "title": "Recipe",
         "cleaned_ingredients": "Ingredients",
@@ -60,47 +63,59 @@ def load_recipes():
     # Keep only required columns
     required_cols = ["Recipe", "Ingredients", "Instructions"]
     df = df[[col for col in required_cols if col in df.columns]]
-
     return df
 
 
-def format_ingredients(ingredients_str):
+def format_ingredients(ingredients_str: str) -> list:
     """
-    Convert ingredients from string representation of list to a Python list.
+    Convert ingredients string into a list.
+
+    Args:
+        ingredients_str (str): String representation of ingredients
+
+    Returns:
+        list: List of ingredients as strings
     """
+    if not ingredients_str:
+        return []
+
+    s = ingredients_str.strip()
     try:
-        # Try to parse as a Python list
-        if ingredients_str.startswith("["):
-            return ast.literal_eval(ingredients_str)
-        # If it's comma-separated
-        elif "," in ingredients_str:
-            return [item.strip() for item in ingredients_str.split(",")]
-        else:
-            return [ingredients_str]
-    except:
-        # If parsing fails, return as single item list
-        return [ingredients_str]
-
-
-recipes = load_recipes()
-
-# ---------- Display recipes ----------
-if recipes.empty:
+        if s.startswith("[") and s.endswith("]"):
+            parsed = ast.literal_eval(s)
+            if isinstance(parsed, (list, tuple)):
+                return [str(x).strip() for x in parsed if str(x).strip()]
+        if "," in s:
+            return [item.strip() for item in s.split(",") if item.strip()]
+        return [s]
+    except Exception:
+        # fallback for | or newline-separated strings
+        if "|" in s:
+            return [x.strip() for x in s.split("|") if x.strip()]
+        if "\n" in s:
+            return [x.strip() for x in s.split("\n") if x.strip()]
+        return [s]
+
+
+recipes_df = load_recipes()
+
+# ---------- Display Recipes ----------
+if recipes_df.empty:
     st.info("No recipes found.")
 else:
-    search = st.text_input("🔍 Search for a recipe:")
-    filtered = (
-        recipes[recipes["Recipe"].str.contains(search, case=False, na=False)]
-        if search
-        else recipes
+    search_term = st.text_input("🔍 Search for a recipe:")
+    filtered_df = (
+        recipes_df[recipes_df["Recipe"].str.contains(search_term, case=False, na=False)]
+        if search_term
+        else recipes_df
     )
 
-    for _, row in filtered.iterrows():
+    for _, row in filtered_df.iterrows():
         with st.expander(f"📖 {row['Recipe']}"):
             st.markdown("**🧂 Ingredients:**")
-            ingredients_list = format_ingredients(row["Ingredients"])
-            for ingredient in ingredients_list:
-                st.write(f"• {ingredient}")
+            ing_list = format_ingredients(row.get("Ingredients") or "")
+            for ing in ing_list:
+                st.write(f"• {ing}")
 
             st.markdown("**👩‍🍳 Instructions:**")
-            st.write(row["Instructions"])
+            st.write(row.get("Instructions") or "No instructions available.")