streamlit_app.py

# Import python packages
import streamlit as st
import requests, pandas as pd
from snowflake.snowpark.functions import col

# Write directly to the app
st.title(":cup_with_straw: Customize Your Smoothie! :cup_with_straw:")
st.write("Choose the fruits you want in your custom Smoothie!")

name_on_order = st.text_input('Name on Smoothie:')
st.write('The name on your Smoothie will bea:', name_on_order )

cnx = st.connection("snowflake")
session = cnx.session()
my_dataframe = session.table("smoothies.public.fruit_options").select(col('FRUIT_NAME'), col('SEARCH_ON'))
#st.dataframe(data=my_dataframe, use_container_width=True)
#st.stop()

#Convert the Snowpark Dataframe to a Pandas Dataframe so we can use the LOC function
pd_df=my_dataframe.to_pandas()
#st.dataframe(pd_df)
#st.stop()

ingredients_list = st.multiselect(
    'Choose up to 5 ingredients:',
    my_dataframe,
    max_selections=5
)
if ingredients_list:
    
    ingredients_string = ''

    for fruit_chosen in ingredients_list:
        ingredients_string += fruit_chosen + ' '

        search_on=pd_df.loc[pd_df['FRUIT_NAME'] == fruit_chosen, 'SEARCH_ON'].iloc[0]
        # st.write('The search value for ', fruit_chosen,' is ', search_on, '.')

        st.subheader(fruit_chosen + ' Nutrition Information')
        fruityvice_response = requests.get("https://fruityvice.com/api/fruit/" + search_on)
        fv_df = st.dataframe(data=fruityvice_response.json(), use_container_width=True)
    
    #st.write(ingredients_string)

    my_insert_stmt = """ insert into smoothies.public.orders(ingredients, name_on_order)
        values ('""" + ingredients_string +  """','""" + name_on_order+ """')"""
    #st.write(my_insert_stmt)
    #st.stop()
    
    time_to_insert = st.button('Submit Order')
    
    
    if time_to_insert:
        session.sql(my_insert_stmt).collect()
        st.success('Your Smoothie is ordered, ' + name_on_order + '!', icon="✅")