Upload app.py

app.py

@@ -0,0 +1,181 @@
+import pandas as pd
+import pickle as pkl
+import smtplib
+from email.mime.multipart import MIMEMultipart
+from email.mime.text import MIMEText
+import streamlit as st
+import base64
+
+
+def set_light_background(image_file):
+    with open(image_file, "rb") as image:
+        encoded = base64.b64encode(image.read()).decode()
+    ext = image_file.split('.')[-1]
+
+    st.markdown(
+        f"""
+        <style>
+        .stApp {{
+            background: linear-gradient(
+                rgba(255, 255, 255, 0.7), 
+                rgba(255, 255, 255, 0.7)
+            ),
+            url("data:image/{ext};base64,{encoded}");
+            background-size: cover;
+            background-repeat: no-repeat;
+            background-attachment: fixed;
+        }}
+        h1, h2, h3, h4, h5, h6 {{
+            color: #1a1a1a;
+        }}
+        .stApp {{
+            color: #202020;
+        }}
+        </style>
+        """,
+        unsafe_allow_html=True
+    )
+
+set_light_background("musicbg.jpg")
+
+
+
+# 🎯 Add Image at the Top
+st.image("inno.jpg", use_container_width=True,width=500) 
+st.markdown(
+    f"<h1 style='text-align: center;'>Subscription & Business Analytics</h1>", 
+    unsafe_allow_html=True)
+# 🎯 Add Image at the Top
+st.image("music.png", use_container_width=True,width=500) 
+
+st.header("Business and Data Understanding")
+st.subheader("Business Statements")
+st.write(""" 
+- The business problem statement is **music streaming service** that offers"
+" different subscription plans (Free, Premium, Family). The main goal is to analyze"
+" user behavior and predict customer churn—whether a user will leave the platform .""")
+
+st.subheader("Business Objective")
+st.write("""
+- Identify key factors contributing to customer churn (e.g., subscription type, engagement metrics, payment method).
+- Improve customer retention strategies by targeting at-risk users with promotions, better recommendations, or engagement campaigns.
+- Enhance user experience by understanding listening habits, subscription patterns, and customer service interactions.
+- Optimize marketing efforts to encourage conversions from free users to premium plans.""")
+
+st.subheader("Business Constraints")
+st.write("""
+- Business constraints are limitations or restrictions that affect decision-making, 
+         operations, or strategic planning within a business. They can include:
+
+- Financial Constraints:  Budget limitations, funding availability, or cost-cutting measures.
+- Time Constraints: Project deadlines, time-to-market pressures, or regulatory timelines.
+- Resource Constraints: Limited workforce, technology, or raw materials.
+- Legal & Compliance Constraints: Industry regulations, data privacy laws (e.g., GDPR), or contractual obligations.
+- Market Constraints: Customer demand, competition, or economic conditions.
+- Technical Constraints: Software/hardware limitations, system integrations, or scalability issues.
+- Operational Constraints:  Supply chain restrictions, production capabilities, or logistics limitations.""")
+
+st.header("Data Understanding")
+st.write("""
+- *Dataset Size:* 125000 rows × 20 columns.
+- *Data Types:*  float64(3), int64(11), object(4)
+- *Data Features:*'age', 'location', 'subscription_type', 'payment_plan',
+       'num_subscription_pauses', 'customer_service_inquiries', 'signup_date',
+       'weekly_hours', 'average_session_length' 'song_skip_rate',
+       'weekly_songs_played', 'weekly_unique_songs', 'num_favorite_artists',
+       'num_platform_friends', 'num_playlists_created', 'num_shared_playlists',
+       'notifications_clicked', 'churned'. """)
+
+
+
+st.write(r"https://www.kaggle.com/competitions/streaming-subscription-churn-model/overview")
+st.write("Demo data")
+data = pd.read_csv("data.csv")
+st.write(data)
+dff = st.file_uploader("Upload File:")
+
+with open("pipe.pkl","rb") as file:
+    pipe = pkl.load(file)
+
+with open("model.pkl","rb") as file:
+    model = pkl.load(file)
+
+if dff:
+    df =pd.read_csv(dff)
+    req = df
+    test = pipe.transform(req)
+
+    predicted = model.predict(test)
+    df["churned"] = predicted
+
+    st.table(df[["customer_id","churned"]])
+
+    ans = {
+        0: {
+            "name": "name",
+            "email": "email",
+            "mail": {
+                "subject": "🎶 Discover New Music You'll Love, name!",
+                "body": "Hey name,\n\nWe noticed you have a fantastic taste for music, "
+                "exploring tons of unique songs every week! To help you find even more tracks you'll love, "
+                "we've put together some recommendations just for you.\n\nBased on your listening habits, "
+                "we think you might enjoy:\n\n* **Daily Mixes:** Personalized playlists refreshed daily with music "
+                "we think you'll be excited about.\n* **New Music Friday:** Stay up-to-date with the freshest releases "
+                "from your favorite genres and artists.\n* **Genre Playlists:** Dive deeper into genres you love or explore "
+                "something completely new.\n\nReady to discover your next favorite song? Click here to explore: [Link to App/Music Platform]\n\nHappy listening,\nYour Music Team"
+            }
+        },
+        1: {
+            "name": "name",
+            "email": "email",
+            "mail": {
+                "subject": "We Miss You, Moon! Come Back for More Music & Family Fun!",
+                "body": "Hi name,\n\nWe've noticed you've been away from our music platform, "
+                "and we wanted to reach out and see if everything is alright."
+                " We truly value you as a Family plan subscriber and want to ensure you and your family are getting the most out of our service.\n\nTo welcome you back, "
+                "we'd like to offer you a special **30-day free trial** to re-engage with all the latest music, podcasts, "
+                "and features you might have missed. Rediscover millions of songs, create new playlists, "
+                "and share the joy of music with your family again.\n\nClick here to reactivate your free trial and start listening: [Link to Reactivation Page]\n\nWe hope to see you back soon!\n\nBest regards,\nYour Music Team"
+            }
+        }
+    }
+
+    st.bar_chart(df["churned"].value_counts())
+
+    mails_data = pd.DataFrame(ans).T
+
+    if st.button('Send Mail'):
+        for i in df.index:
+            cust_id = df.iloc[i]["customer_id"]
+            name = df.iloc[i]["name"]
+            email_id = df.iloc[i]["email"]
+            pred = df.iloc[i]["churned"]
+            
+            sender_email = "moon24012407@gmail.com"
+            receiver_email = email_id
+            password = "rjig xxky lwfc xkcb"
+            
+            # Email content
+            subject = mails_data.iloc[pred]['mail']['subject'].replace('name',name)
+            
+            body = mails_data.iloc[pred]['mail']['body'].replace('name',name)
+            
+            
+            # Create the email
+            message = MIMEMultipart()
+            message["From"] = sender_email
+            message["To"] = receiver_email
+            message["Subject"] = subject
+            message.attach(MIMEText(body, "plain"))
+            
+            # Set up the SMTP server and send the email
+            try:
+                server = smtplib.SMTP("smtp.gmail.com", 587)
+                server.starttls()  # Secure the connection
+                server.login(sender_email, password)
+                server.sendmail(sender_email, receiver_email, message.as_string())
+                server.quit()
+                st.write(f"{cust_id} : Email sent successfully!")
+            except Exception as e:
+                st.write(f"{cust_id} : Failed to send email: {e}")
+st.write("Accurace : 0.82328")