app.py

import streamlit as st
import os
from Senti import extract_video_id,analyze_sentiment,bar_chart,plot_sentiment
from YoutubeCommentScrapper import save_video_comments_to_csv,get_channel_info,youtube,get_channel_id,get_video_stats



def delete_non_matching_csv_files(directory_path, video_id):
    for file_name in os.listdir(directory_path):
        if not file_name.endswith('.csv'):
            continue
        if file_name == f'{video_id}.csv':
            continue
        os.remove(os.path.join(directory_path, file_name))


st.set_page_config(page_title='Jatin_Agrawal_20BCS6606', page_icon = 'LOGO.png', initial_sidebar_state = 'auto')
#st.set_page_config(page_title=None, page_icon=None, layout="centered", initial_sidebar_state="auto", menu_items=None)
st.sidebar.title("Sentimental Analsis")
st.sidebar.header("Enter YouTube Link")
youtube_link = st.sidebar.text_input("Link")
directory_path = os.getcwd()
hide_st_style = """
            <style>
            #MainMenu {visibility: hidden;}
            footer {visibility: hidden;}
            </style>
            """
st.markdown(hide_st_style, unsafe_allow_html=True)


if youtube_link:
    video_id = extract_video_id(youtube_link)
    channel_id = get_channel_id(video_id)
    if video_id:
        st.sidebar.write("The video ID is:", video_id)     
        csv_file = save_video_comments_to_csv(video_id)
        delete_non_matching_csv_files(directory_path,video_id)
        st.sidebar.write("Comments saved to CSV!")
        st.sidebar.download_button(label="Download Comments", data=open(csv_file, 'rb').read(), file_name=os.path.basename(csv_file), mime="text/csv")
        
        #using fn
        channel_info = get_channel_info(youtube,channel_id)
               
        col1, col2 = st.columns(2)

        with col1:
           channel_logo_url = channel_info['channel_logo_url']
           st.image(channel_logo_url, width=250)

        with col2:
           channel_title = channel_info['channel_title']
           st.title(' ')
           st.text("  YouTube Channel Name  ")
           #st.markdown('** YouTube Channel Name **')
           st.title(channel_title)
           st.title("  ")
           st.title(" ")
           st.title(" ")
           
        
        #Using fn
        
        
        
        st.title(" ")
        col3, col4 ,col5 = st.columns(3)
        
        
        with col3:
           video_count=channel_info['video_count']
           st.header("  Total Videos  ")
           #st.subheader("Total Videos")
           st.subheader(video_count)

        with col4:
           channel_created_date= channel_info['channel_created_date']
           created_date = channel_created_date[:10]
           st.header("Channel Created ")
           st.subheader(created_date)

        with col5:
            
            st.header(" Subscriber_Count ")
            st.subheader(channel_info["subscriber_count"])
            
        st.title(" ")

        stats = get_video_stats(video_id)   
        
        st.title("Video Information :")
        col6, col7 ,col8 = st.columns(3)
        
        
        with col6:
            st.header("  Total Views  ")
           #st.subheader("Total Videos")
            st.subheader(stats["viewCount"])

        with col7:
           st.header(" Like Count ")
           st.subheader(stats["likeCount"])
           

        with col8:
            
            st.header(" Comment Count ")
            st.subheader(stats["commentCount"])
            
        st.header(" ")   
        
        
        _, container, _ = st.columns([10, 80, 10])
        container.video(data=youtube_link)
      
            
        
            
            
        results = analyze_sentiment(csv_file)
        
        
        col9, col10 ,col11 = st.columns(3)
        
        
        with col9:
            st.header("  Positive Comments  ")
           #st.subheader("Total Videos")
            st.subheader(results['num_positive'])

        with col10:
           st.header(" Negative Comments ")
           st.subheader( results['num_negative'])
           

        with col11:
            
            st.header(" Neutral Comments ")
            st.subheader(results['num_neutral'])
        
        
        bar_chart(csv_file)
        
        plot_sentiment(csv_file)
        
            
        st.subheader("Channel Description ")   
        channel_description = channel_info['channel_description']
        st.write(channel_description)
        
    else:
        st.error("Invalid YouTube link")