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Browse files- app.py +54 -0
- requirements.txt +5 -0
app.py
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from tqdm import tqdm
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from itertools import islice
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from youtube_comment_downloader import *
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from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
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import matplotlib.pyplot as plt
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import csv
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import streamlit as st
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import pandas as pd
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import base64
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st.title("Youtube Comment Downloader")
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# Input URL video
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video_url = st.text_input("Masukkan URL video YouTube:")
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# Input jumlah komentar yang ingin diambil
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num_comments = st.number_input("Jumlah komentar yang ingin diambil:", min_value=1, value=10)
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if st.button("Ambil Data Komentar"):
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# Inisialisasi YoutubeCommentDownloader
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downloader = YoutubeCommentDownloader()
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# Mendapatkan komentar
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comments = downloader.get_comments_from_url(video_url, sort_by=SORT_BY_POPULAR)
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# Membuka file CSV untuk menulis
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with open('comments.csv', mode='w', encoding='utf-8', newline='') as file:
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# Membuat objek writer
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writer = csv.DictWriter(file, fieldnames=['cid', 'text', 'time', 'author', 'channel', 'votes', 'photo', 'heart', 'reply'])
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# Menulis header
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writer.writeheader()
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# Menulis data komentar
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for comment in tqdm(islice(comments, num_comments)):
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# Menghapus kolom 'time_parsed' dari komentar
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comment.pop('time_parsed', None)
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writer.writerow(comment)
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st.success(f"Komentar berhasil diunduh dan disimpan dalam file 'comments.csv'")
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# Membaca data dari file CSV
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comments_df = pd.read_csv('comments.csv')
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# Menampilkan tabel dengan menggunakan st.table()
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st.subheader("Data Komentar")
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st.table(comments_df)
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# Menyiapkan link untuk mendownload file CSV
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csv = comments_df.to_csv(index=False)
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b64 = base64.b64encode(csv.encode()).decode()
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href = f'<a style="background-color: #008CBA; color: white; padding: 10px 20px; text-decoration: none; border-radius: 5px; font-weight: bold;" href="data:file/csv;base64,{b64}" download="comments.csv">Download File CSV</a>'
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st.markdown(href, unsafe_allow_html=True)
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requirements.txt
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youtube-comment-downloader
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tqdm
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torch
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transformers
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matplotlib
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