Delete app.py

app.py

@@ -1,263 +0,0 @@
-import streamlit as st 
-import pandas as pd
-import numpy as np
-import requests
-
-
-df = pd.read_pickle('popular.pkl')
-
-books = pd.read_pickle('books.pkl')
-similarity_scores = pd.read_pickle('similarity.pkl')
-pt = pd.read_pickle('pt.pkl')
-final_books = pd.read_pickle("final.pkl")
-
-
-
-def recommend_book(book_name):
-    # fetch index
-    index = np.where(pt.index==book_name)[0][0]
-   
-    similar_items = sorted(list(enumerate(similarity_scores[index])),key=lambda x:x[1],reverse=True)[1:6]
-    
-    data=[]
-    for i in similar_items:
-        item=[]
-        temp_df = books[books['Book-Title'] == pt.index[i[0]]]
-        item.extend(list(temp_df.drop_duplicates('Book-Title')['Book-Title'].values))
-        item.extend(list(temp_df.drop_duplicates('Book-Title')['Book-Author'].values))
-        item.extend(list(temp_df.drop_duplicates('Book-Title')['Image-URL-M'].values))
-        
-        
-        data.append(item) 
-    return data
-
-def fetch_book_details(book_name):
-    url = 'https://www.googleapis.com/books/v1/volumes?q={}'.format(book_name)
-    response=requests.get(url)
-    obj=response.json()
-    book_details=[]
-    ids = [id['id'] for id in obj['items']]
-    ids = ids[0]
-    title = obj['items'][0]['volumeInfo']['title']
-    author = obj['items'][0]['volumeInfo']['authors'][0]
-    publish_date= obj['items'][0]['volumeInfo']['publishedDate'] 
-    image = obj['items'][0]['volumeInfo']['imageLinks']['thumbnail']
-    preview_link = obj['items'][0]['volumeInfo']['previewLink']
-    info =  obj['items'][0]['volumeInfo']['infoLink']
-    book_details.append(ids)
-    book_details.append(title)
-    
-    book_details.append(author)
-  
-    book_details.append(publish_date)
-    book_details.append(preview_link)
-    book_details.append(info)
-    book_details.append(image)
-    print(book_details)
-    return book_details
-
-
-
-menu = ['top20','recommender','about']
-
-option = st.sidebar.selectbox("Select One: ",menu)
-
-if option == 'top20':
-    st.title("Top 20 Books")
-    st.text("")
-    col1,col2,col3,col4=st.columns(4)
-    with col1:
-        st.image(df['Image-URL-M'][0])
-        st.markdown(f"[{df['Book-Title'][0]}]({fetch_book_details(df['Book-Title'][0])[5]})")
-       
-        st.markdown(f"<b>Author:<b>{df['Book-Author'][0]}",unsafe_allow_html=True)
-        st.markdown(f"Votes - {df['num_ratings'][0]}")
-        st.markdown(f"rating - {round(df['avg_ratings'][0],2)}")
-    with col2:
-        st.image(df['Image-URL-M'][3])
-        st.markdown(f"[{df['Book-Title'][3]}]({fetch_book_details(df['Book-Title'][3])[5]})")
-
-        st.markdown(f"<b>Author:<b>{df['Book-Author'][3]}",unsafe_allow_html=True)
-        st.markdown(f"Votes - {df['num_ratings'][3]}")
-        st.markdown(f"rating - {round(df['avg_ratings'][3],2)}")
-    with col3:
-        st.image(df['Image-URL-M'][5])
-        st.markdown(f"[{df['Book-Title'][5]}]({fetch_book_details(df['Book-Title'][5])[5]})")
-     
-        st.markdown(f"<b>Author:<b>{df['Book-Author'][5]}",unsafe_allow_html=True)
-        st.markdown(f"Votes - {df['num_ratings'][5]}")
-        st.markdown(f"rating - {round(df['avg_ratings'][5],2)}")
-    with col4:
-        st.image(df['Image-URL-M'][9])
-        st.markdown(f"[{df['Book-Title'][9]}]({fetch_book_details(df['Book-Title'][9])[5]})")
-
-        st.markdown(f"<b>Author:<b>{df['Book-Author'][9]}",unsafe_allow_html=True)
-        st.markdown(f"Votes - {df['num_ratings'][9]}")
-        st.markdown(f"rating - {round(df['avg_ratings'][9],2)}")
-
-    st.text("")
-    col1,col2,col3,col4=st.columns(4)
-    with col1:
-        st.image(df['Image-URL-M'][13])
-        st.markdown(f"[{df['Book-Title'][13]}]({fetch_book_details(df['Book-Title'][13])[5]})")
-        st.markdown(df['Book-Title'][13][0:40])
-        st.markdown(f"<b>Author:<b>{df['Book-Author'][13]}",unsafe_allow_html=True)
-        st.markdown(f"Votes - {df['num_ratings'][13]}")
-        st.markdown(f"rating - {round(df['avg_ratings'][13],2)}")
-    with col2:
-        st.image(df['Image-URL-M'][16])
-        st.markdown(f"[{df['Book-Title'][16]}]({fetch_book_details(df['Book-Title'][16])[5]})")
-    
-        st.markdown(f"<b>Author:<b>{df['Book-Author'][16]}",unsafe_allow_html=True)
-        st.markdown(f"Votes - {df['num_ratings'][16]}")
-        st.markdown(f"rating - {round(df['avg_ratings'][16],2)}")
-    with col3:
-        st.image(df['Image-URL-M'][17])
-        st.markdown(f"[{df['Book-Title'][17]}]({fetch_book_details(df['Book-Title'][17])[5]})")
-        st.markdown(f"<b>Author:<b>{df['Book-Author'][17]}",unsafe_allow_html=True)
-        st.markdown(f"Votes - {df['num_ratings'][17]}")
-        st.markdown(f"rating - {round(df['avg_ratings'][17],2)}")
-    with col4:
-        st.image(df['Image-URL-M'][26])
-        st.markdown(f"[{df['Book-Title'][26]}]({fetch_book_details(df['Book-Title'][26])[5]})")
-        st.markdown(df['Book-Title'][26][0:40])
-        st.markdown(f"<b>Author:<b>{df['Book-Author'][26]}",unsafe_allow_html=True)
-        st.markdown(f"Votes - {df['num_ratings'][26]}")
-        st.markdown(f"rating - {round(df['avg_ratings'][26],2)}")
-
-    st.text("")
-    col1,col2,col3,col4=st.columns(4)
-    with col1:
-        st.image(df['Image-URL-M'][28])
-        st.markdown(f"[{df['Book-Title'][17]}]({fetch_book_details(df['Book-Title'][17])[5]})")
-    
-        st.markdown(f"<b>Author:<b>{df['Book-Author'][28]}",unsafe_allow_html=True)
-        st.markdown(f"Votes - {df['num_ratings'][28]}")
-        st.markdown(f"rating - {round(df['avg_ratings'][28],2)}")
-    with col2:
-        st.image(df['Image-URL-M'][39])
-        st.markdown(f"[{df['Book-Title'][39]}]({fetch_book_details(df['Book-Title'][39])[5]})")
-     
-        st.markdown(f"<b>Author:<b>{df['Book-Author'][39]}",unsafe_allow_html=True)
-        st.markdown(f"Votes - {df['num_ratings'][39]}")
-        st.markdown(f"rating - {round(df['avg_ratings'][39],2)}")
-    with col3:
-        st.image(df['Image-URL-M'][47])
-        st.markdown(f"[{df['Book-Title'][47]}]({fetch_book_details(df['Book-Title'][47])[5]})")
-      
-        st.markdown(f"<b>Author:<b>{df['Book-Author'][47]}",unsafe_allow_html=True)
-        st.markdown(f"Votes - {df['num_ratings'][47]}")
-        st.markdown(f"rating - {round(df['avg_ratings'][47],2)}")
-    with col4:
-        st.image(df['Image-URL-M'][53])
-        st.markdown(f"[{df['Book-Title'][53]}]({fetch_book_details(df['Book-Title'][53])[5]})")
-
-        st.markdown(f"<b>Author:<b>{df['Book-Author'][53]}",unsafe_allow_html=True)
-        st.markdown(f"Votes - {df['num_ratings'][53]}")
-        st.markdown(f"rating - {round(df['avg_ratings'][53],2)}")
-
-    st.text("")
-    col1,col2,col3,col4=st.columns(4)
-    with col1:
-        st.image(df['Image-URL-M'][55])
-        st.markdown(f"[{df['Book-Title'][55]}]({fetch_book_details(df['Book-Title'][55])[5]})")
-        
-        st.markdown(f"<b>Author:<b>{df['Book-Author'][55]}",unsafe_allow_html=True)
-        st.markdown(f"Votes - {df['num_ratings'][55]}")
-        st.markdown(f"rating - {round(df['avg_ratings'][55],2)}")
-    with col2:
-        st.image(df['Image-URL-M'][62])
-        st.markdown(f"[{df['Book-Title'][62]}]({fetch_book_details(df['Book-Title'][62])[5]})")
-        
-        st.markdown(f"<b>Author:<b>{df['Book-Author'][62]}",unsafe_allow_html=True)
-        st.markdown(f"Votes - {df['num_ratings'][62]}")
-        st.markdown(f"rating - {round(df['avg_ratings'][62],2)}")
-    with col3:
-        st.image(df['Image-URL-M'][63])
-        st.markdown(f"[{df['Book-Title'][63]}]({fetch_book_details(df['Book-Title'][63])[5]})")
-        
-        st.markdown(f"<b>Author:<b>{df['Book-Author'][63]}",unsafe_allow_html=True)
-        st.markdown(f"Votes - {df['num_ratings'][63]}")
-        st.markdown(f"rating - {round(df['avg_ratings'][63],2)}")
-    with col4:
-        st.image(df['Image-URL-M'][72])
-        st.markdown(f"[{df['Book-Title'][72]}]({fetch_book_details(df['Book-Title'][72])[5]})")
-        
-        st.markdown(f"<b>Author:<b>{df['Book-Author'][72]}",unsafe_allow_html=True)
-        st.markdown(f"Votes - {df['num_ratings'][72]}")
-        st.markdown(f"rating - {round(df['avg_ratings'][72],2)}")
-    
-
-    st.text("")
-    col1,col2,col3,col4=st.columns(4)
-    with col1:
-        st.image(df['Image-URL-M'][73])
-        st.markdown(f"[{df['Book-Title'][73]}]({fetch_book_details(df['Book-Title'][73])[5]})")
-        
-        st.markdown(f"<b>Author:<b>{df['Book-Author'][73]}",unsafe_allow_html=True)
-        st.markdown(f"Votes - {df['num_ratings'][73]}")
-        st.markdown(f"rating - {round(df['avg_ratings'][73],2)}")
-    with col2:
-        st.image(df['Image-URL-M'][78])
-        st.markdown(f"[{df['Book-Title'][78]}]({fetch_book_details(df['Book-Title'][78])[5]})")
-        
-        st.markdown(f"<b>Author:<b>{df['Book-Author'][78]}",unsafe_allow_html=True)
-        st.markdown(f"Votes - {df['num_ratings'][78]}")
-        st.markdown(f"rating - {round(df['avg_ratings'][78],2)}")
-    with col3:
-        st.image(df['Image-URL-M'][84])
-        st.markdown(f"[{df['Book-Title'][84]}]({fetch_book_details(df['Book-Title'][84])[5]})")
-        
-        st.markdown(f"<b>Author:<b>{df['Book-Author'][84]}",unsafe_allow_html=True)
-        st.markdown(f"Votes - {df['num_ratings'][84]}")
-        st.markdown(f"rating - {round(df['avg_ratings'][84],2)}")
-    with col4:
-        st.image(df['Image-URL-M'][85])
-        st.markdown(f"[{df['Book-Title'][85]}]({fetch_book_details(df['Book-Title'][85])[5]})")
-        
-        st.markdown(f"<b>Author:<b>{df['Book-Author'][85]}",unsafe_allow_html=True)
-        st.markdown(f"Votes - {df['num_ratings'][85]}")
-        st.markdown(f"rating - {round(df['avg_ratings'][85],2)}")
-
-elif option=='recommender':
-    st.title("Books Recommender System")
-    book_list = final_books['Book-Title'].values
-    selected_book = st.selectbox("Select your book ",book_list)
-    if st.button("show recommendation"):
-        st.header("Recommend For You....")
-        st.text("")
-        data=recommend_book(selected_book)
-        col1,col2,col3,col4=st.columns(4)
-        
-        with col1:
-            st.image(fetch_book_details(data[0][0])[6])
-            st.markdown(f"[{data[0][0]}]({fetch_book_details(data[0][0])[5]})")
-           
-
-        with col2:
-            st.image(fetch_book_details(data[1][0])[6])
-            st.markdown(f"[{data[1][0]}]({fetch_book_details(data[1][0])[5]})")
-          
-        with col3:
-            st.image(fetch_book_details(data[2][0])[6])
-            st.markdown(f"[{data[2][0]}]({fetch_book_details(data[2][0])[5]})")
-        
-      
-        with col4:
-            st.image(fetch_book_details(data[3][0])[6])
-            st.markdown(f"[{data[3][0]}]({fetch_book_details(data[3][0])[5]})")
-          
-
-elif option=="about":
-	st.title("Book Recommendation Engine V-2.0")
-	st.markdown("This Engine Developed by <a href='https://github.com/datamind321'>DataMind Platform</a>",unsafe_allow_html=True)
-	st.subheader("if you have any query Contact us on : [email protected]") 
-	st.markdown("More on : ")
-	
-	
-	st.markdown("[![Linkedin](https://content.linkedin.com/content/dam/me/business/en-us/amp/brand-site/v2/bg/LI-Bug.svg.original.svg)](https://www.linkedin.com/in/rahul-rathour-402408231/)",unsafe_allow_html=True)
-	
-
-	st.markdown("[![Instagram](https://img.icons8.com/color/1x/instagram-new.png)](https://instagram.com/_technical__mind?igshid=YmMyMTA2M2Y=)")
-      
-