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from helper import extract_youtube_id, get_all_comments
import streamlit as st
import random
import pandas as pd
import numpy as np
st.header("💬 Youtube Comments Sentiment Analysis")
st.markdown("""
<style>
.stTextInput > label > div > p {
font-size: 23px;
padding: 0;
margin: 0;
font-weight: 600;
}
</style>
""", unsafe_allow_html=True)
user_input = st.text_input("Enter a youtube link for sentiment analysis")
sentiment_colors = {
"Positive": "#28a745",
"Neutral": "#ffc107",
"Negative": "#dc3545"
}
if st.button('Submit', type="secondary"):
sentiments = ["Positive", "Neutral", "Negative"]
try:
the_youtube_id = extract_youtube_id(user_input)
if the_youtube_id:
with st.spinner("Please wait while we're loading the data..."):
the_data = get_all_comments(the_youtube_id)
data = np.random.choice(["Positive", "Neutral", "Negative"], size=len(the_data))
# Create a DataFrame
sentiment_data = pd.DataFrame(data, columns=["Sentiment"])
sentiment_counts = sentiment_data["Sentiment"].value_counts()
positives = sentiment_counts.get("Positive", 0)
neutrals = sentiment_counts.get("Neutral", 0)
negatives = sentiment_counts.get("Negative", 0)
st.balloons()
st.markdown(f"""<p style="color: gray;">Total comments: {len(the_data)}</p>""", unsafe_allow_html=True)
st.markdown(f"""<p style="color: green;">Positives: {positives}</p>""", unsafe_allow_html=True)
st.markdown(f"""<p style="color: gray;">Neutrals: {neutrals}</p>""", unsafe_allow_html=True)
st.markdown(f"""<p style="color: red;">Negatives: {negatives}</p>""", unsafe_allow_html=True)
for index, data in enumerate(the_data):
sentiment_color = sentiment_colors.get(sentiment_data.iloc[index, 0], "#6c757d")
comment_html = f"""
<div style="background-color: #f9f9f9; border: 1px solid #ddd; border-radius: 10px; padding: 20px; margin: 20px auto; box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);">
<p style="font-size: 18px; line-height: 1.6; color: #333; font-family: 'Arial', sans-serif;">
{data["comment"]}
</p>
<p style="font-size: 16px; color: gray; margin-top: 15px; font-family: 'Arial', sans-serif; font-weight: bold;">
Sentiment Analysis: <span style="color: {sentiment_color}; font-size: 18px; font-weight: bold; padding: 5px 10px; background-color: {sentiment_color + "33"}; border-radius: 5px;">
{sentiment_data.iloc[index, 0]}
</span>
</p>
</div>
"""
st.markdown(comment_html, unsafe_allow_html=True)
else:
st.write("Invalid youtube link.")
except Exception as e:
print(e)
st.write("Invalid youtube link.")
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