Update app.py

app.py

@@ -8,8 +8,6 @@ st.set_page_config(layout="wide")
 # load data
 f = open('data.json')
 recipes_json = json.load(f)
-
-# prepare data
 recipes = pd.DataFrame(recipes_json)
 ingredients = pd.DataFrame(recipes_json).explode('ingredients')
 bar_dict = [
@@ -20,7 +18,25 @@ bar_dict = [
     {"ingredients":"cointreau", "have": False}
 ]
 bar_df = pd.DataFrame(bar_dict)
-    
+def similarity(ratings, kind='user', epsilon=1e-9):
+        if kind == 'user':
+            sim = ratings.dot(ratings.T) + epsilon
+        elif kind == 'item':
+            sim = ratings.T.dot(ratings) + epsilon
+        norms = np.array([np.sqrt(np.diagonal(sim))])
+        return (sim / norms / norms.T)
+pivot = ingredients[['name', 'ingredients']].copy()
+pivot['count'] = 1
+pivot = pivot.set_index(['name', 'ingredients'])['count'].unstack().reset_index()
+pivot.rename_axis(None, axis=1, inplace=True)
+pivot.fillna(0, inplace=True)
+pivot_names = pivot.columns
+pivot_np = np.array(pivot.set_index('name'))
+recipe_similarity = pd.DataFrame(similarity(pivot_np, kind='user'))
+recipe_similarity.columns = pivot['name'].values
+recipe_similarity.index = pivot['name'].values
+
+# manage session state
 if 'filter_bar' not in st.session_state:
     st.session_state.filter_bar = recipes['name'].to_list()
 
@@ -28,8 +44,8 @@ if 'bar_df' not in st.session_state:
     st.session_state.bar_df = bar_df
     st.session_state.bar_df_edited = st.session_state.bar_df.copy() 
 
+# recipe finder section
 st.header("Recipe Finder")
-
 with st.expander("Find recipes by name, ingredients, and type"):
     # name search
     name_search = st.text_input('Search recipes by name')
@@ -80,14 +96,6 @@ with st.expander("Find recipes by name, ingredients, and type"):
         filter_1 = recipes['recipe_type'].isin(type_options)
         filter_type = recipes.loc[filter_1, 'name'].to_list()
 
-# def submit_bar():
-    
-
-# def reset_bar():
-#     # st.session_state.bar_df = bar_df
-#     st.session_state.bar_df_edited = bar_df
-#     st.session_state.filter_bar = recipes['name'].to_list()
-    
 
 with st.expander("Find recipes by what you can make with your bar at home"):
     # input home bar
@@ -110,26 +118,25 @@ with st.expander("Find recipes that are similar to one another"):
     #simlar_select = st.selectbox("Select a recipe:", pd.concat([pd.Series(Null),recipes['name']]))
     simlar_select = st.multiselect("Select a recipe:", recipes['name'], max_selections=1)
 
-    def similarity(ratings, kind='user', epsilon=1e-9):
-        if kind == 'user':
-            sim = ratings.dot(ratings.T) + epsilon
-        elif kind == 'item':
-            sim = ratings.T.dot(ratings) + epsilon
-        norms = np.array([np.sqrt(np.diagonal(sim))])
-        return (sim / norms / norms.T)
-
-    pivot = ingredients[['name', 'ingredients']].copy()
-    pivot['count'] = 1
-    pivot = pivot.set_index(['name', 'ingredients'])['count'].unstack().reset_index()
-    pivot.rename_axis(None, axis=1, inplace=True)
-    pivot.fillna(0, inplace=True)
-    pivot_names = pivot.columns
-    pivot_np = np.array(pivot.set_index('name'))
-    recipe_similarity = pd.DataFrame(similarity(pivot_np, kind='user'))
-    recipe_similarity.columns = pivot['name'].values
-    recipe_similarity.index = pivot['name'].values
+    
+        
 
+    
 
+# Recipes section
 st.header("Recipes")
 filter_all = list(set(filter_name) & set(filter_ingredient) & set(filter_source) & set(filter_type) & set(st.session_state.filter_bar))
-st.dataframe(recipes[recipes['name'].isin(filter_all)], hide_index=True)
+
+if len(similar_select) > 0:
+    st.dataframe(
+        recipes.set_index('name') \
+        .join(recipe_similarity[simlar_select], on='name') \
+        .reset_index() \
+        .sort_values(by=simlar_select, ascending=False) \
+        .query('name in @filter_all'),
+        #column_config={"Name": st.column_config.Column(width="medium")
+        hide_index=True) \
+        
+    #recipes[recipes['name'].isin(filter_all)]
+else:
+    st.dataframe(recipes[recipes['name'].isin(filter_all)], hide_index=True)