Upload 5 files

app.py

@@ -0,0 +1,263 @@
+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=)")
+      
+    

books.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:016d6dfd03e12b3ea03e517b958bd9057027c6b4358f171731ce13471e9299de
+size 71737055

final.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:eafc2fcb1b9ed77c9c705e150802bc3693300e42dffcc4e028028e9191526940
+size 194208

pt.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9dc904c5ae29c70eedbc05cf3a04bf5a0f5d8b61ec9b8896c3b18169a721af6e
+size 4601037

similarity.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:46ab3e5bb4fdf61ad7306384fc20e4eac45dfc823639b0f78859462d43556edb
+size 3987651