appalter.py

import pickle 
import streamlit as st 
 
def recommend(book):  
    index = books[books['title'] == book].index[0] 
    distances = sorted(list(enumerate(similarity[index])), reverse=True, key=lambda x: x[1]) 
    recommended_book_name = [] 
    recommended_book_cover = [] 
    recommended_isbn = [] 
    recommended_link = [] 
    # author  desc  genre  img  isbn  link  pages  rating  reviews  title  totalratings 
 
     
    for i in distances[1:7]: 
        isbn = books.iloc[i[0]].isbn 
        recommended_book_cover.append(books.iloc[i[0]].img) 
        recommended_book_name.append(books.iloc[i[0]].title) 
        recommended_isbn.append(books.iloc[i[0]].isbn) 
        recommended_link.append(books.iloc[i[0]].link) 
 
    return recommended_book_cover,recommended_book_name,recommended_isbn,recommended_link 
    # return recommended_book_name,recommended_book_cover 
 
st.set_page_config(layout="wide") 
st.title('Book Recommender System') 
st.caption('For all you bookworms') 
books = pickle.load(open('book_list.pkl','rb')) #read binary me matlab read kar sakte ho  
similarity = pickle.load(open('similarity_matrix.pkl','rb')) 
book_list = books['title'].values 
selected_book = st.selectbox("Type or select a book from the list",book_list) 
 
if st.button('Show Recommendation', use_container_width=True): 
    recommended_book_cover,recommended_book_name,recommended_isbn,recommended_link=recommend(selected_book) 
 
    col1, col2, col3, col4, col5, col6 = st.columns(6) 
    with col1: 
        with st.container(height=200,border=None): 
            st.subheader(recommended_book_name[0]) 
        with st.container(height=320,border=None): 
            st.image(recommended_book_cover[0]) 
        st.link_button('More Info', recommended_link[0], use_container_width=True) 
        st.code('ISBN : '+recommended_isbn[0]) 
    with col2: 
        with st.container(height=200,border=None): 
            st.subheader(recommended_book_name[1]) 
        with st.container(height=320,border=None): 
            st.image(recommended_book_cover[1]) 
        st.link_button('More Info', recommended_link[1], use_container_width=True) 
        st.code('ISBN : '+recommended_isbn[1]) 
    with col3: 
        with st.container(height=200,border=None): 
            st.subheader(recommended_book_name[2]) 
        with st.container(height=320,border=None): 
            st.image(recommended_book_cover[2]) 
        st.link_button('More Info', recommended_link[2], use_container_width=True) 
        st.code('ISBN : '+recommended_isbn[2]) 
    with col4: 
        with st.container(height=200,border=None): 
            st.subheader(recommended_book_name[3]) 
        with st.container(height=320,border=None): 
            st.image(recommended_book_cover[3]) 
        st.link_button('More Info', recommended_link[3], use_container_width=True) 
        st.code('ISBN : '+recommended_isbn[3]) 
    with col5: 
        with st.container(height=200,border=None): 
            st.subheader(recommended_book_name[4]) 
        with st.container(height=320,border=None): 
            st.image(recommended_book_cover[4]) 
        st.link_button('More Info', recommended_link[4], use_container_width=True) 
        st.code('ISBN : '+recommended_isbn[4]) 
    with col6: 
        with st.container(height=200,border=None): 
            st.subheader(recommended_book_name[5]) 
        with st.container(height=320,border=None): 
            st.image(recommended_book_cover[5]) 
        st.link_button('More Info', recommended_link[5], use_container_width=True) 
        st.code('ISBN : '+recommended_isbn[5]) 
 
# to run this app 
# streamlit run appalter.py 
 
 
 
# alternative design