Mubarak

README.md

@@ -1 +1,27 @@
-# Usecase-8-Project-5
+# Jarir Books Scraper and Clustering Project
+
+This project involves scraping book data from **Jarir.com**, analyzing the data, and clustering books based on their features. The project includes deploying the clustering model using **FastAPI** for API access and **Streamlit** for an interactive web application.
+
+---
+
+## Features
+
+1. **Scraping Book Data**  
+   - Collect book information such as title, author, price, category, etc., from Jarir.com.
+
+2. **Data Processing**  
+   - Clean and preprocess the scraped data.
+   - Extract relevant features for clustering.
+
+3. **Clustering Model**  
+   - Use clustering algorithms (e.g., KMeans, DBSCAN) to group books into meaningful clusters.
+
+4. **Deployment**  
+   - **FastAPI**: Expose the clustering model through an API.  
+   - **Streamlit**: Create an interactive app to visualize and explore the book clusters.
+
+---
+
+
+## Streamlit Link: 
+https://book-clusters.streamlit.app/

app.py

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+import streamlit as st
+import requests
+
+# Set up the Streamlit app
+st.title("Books Clusters")
+
+# User inputs
+publication_date = st.number_input("تاريخ النشر", min_value=1800, max_value=2024, value=2000)
+num_pages = st.number_input("عدد الصفحات", min_value=20, max_value=1400, value=100)
+price = st.number_input("السعر", min_value=2, max_value=550, value=50)  # Add other types as necessary
+IsNew = st.checkbox(label=" وصل حديثا", value=False) 
+category = st.selectbox("التصنيف", ["الادارة والاعمال", "الادب والشعر", "التاريخ والجغرافيا", "التراجم والسير", "التقنية والكمبيوتر", "الخيال العلمي", "العلوم الاجتماعية والسياسية", "العلوم والرياضيات", "القانون", "القصة والرواية", "الكتب الطبية", "تطوير الذات", "دراسات اسلامية"])  # Add other makes as needed
+cover = st.selectbox("الغلاف", ["غلاف ورقي", "غلاف مقوى", "غلاف مقوى فني", "كتاب الكتروني"])  # Add other makes as needed
+selected_lang = st.radio(
+    "اختر اللغة:",
+    options=["عربي", "انجليزي"],
+    index=0,  # Default selection (0 = "عربي")
+    horizontal=True  # Displays options in a horizontal layout
+)
+
+# Prediction button
+if st.button("Predict"):
+    # API request URL
+    url = "https://jarir-books.onrender.com/predict"
+
+
+    # Data for the POST request
+    data = {
+        "publication_date" : publication_date,
+        "num_pages" : num_pages,
+        "price" : price,
+        "IsNew" : IsNew,
+        "mng_cate": 0,
+        "poet_cate": 0,
+        "hist_cate": 0,
+        "tr_cate": 0,
+        "tec_cate":0,
+        "fan_cate":0,
+        "pol_cate":0,
+        "math_cate":0,
+        "law_cate":0,
+        "story_cate":0,
+        "midec_cate":0,
+        "dev_cate":0,
+        "islam_cate":0,
+        "hard_cvr":0,
+        "art_cvr":0,
+        "ppr_cvr":0,
+        "e_cvr":0,
+        "ar":0,
+        "e":0
+    }
+    if category == "الادارة والاعمال":
+        data["mng_cate"] = 1
+
+    elif category == "الادب والشعر":
+        data["poet_cate"] = 1
+
+    elif category =="التاريخ والجغرافيا":
+        data["hist_cate"] = 1
+
+    elif category ==  "التراجم والسير":
+        data["tr_cate"] = 1
+
+    elif category == "التقنية والكمبيوتر":
+        data["tec_cate"] = 1
+
+    elif category ==  "الخيال العلمي":
+        data["fan_cate"] = 1
+
+    elif category == "العلوم الاجتماعية والسياسية":
+        data["pol_cate"] = 1
+
+    elif category == "العلوم والرياضيات":
+        data["math_cate"] = 1
+
+    elif category == "القانون":
+        data["law_cate"] = 1
+
+    elif category == "القصة والرواية":
+        data["story_cate"] = 1
+
+    elif category == "الكتب الطبية":
+        data["midec_cate"] = 1
+    elif category == "تطوير الذات":
+        data["dev_cate"] = 1
+    elif category == "دراسات اسلامية":
+        data["islam_cate"] = 1
+
+    if cover == "غلاف ورقي":
+        data["ppr_cvr"] = 1
+
+    elif cover == "غلاف مقوى":
+        data["hard_cvr"] = 1
+
+    elif cover == "غلاف مقوى فني":
+        data["art_cvr"] = 1
+
+    elif cover == "كتاب الكتروني":
+        data["e_cvr"] = 1
+
+    if selected_lang == "عربي":
+        data["ar"] = 1
+
+    elif selected_lang == "انجليزي":
+        data["e"] = 1
+
+    try:
+        response = requests.post(url, json=data)
+        response.raise_for_status()  # Check for request errors
+        prediction = response.json()  # Parse JSON response
+        print(prediction)
+        # {'Cheap_Price': 0, 'Good_Price': 1, 'High_Price': 2} 
+
+        st.header("Recommended Books")
+        imgs= prediction["img_urls"]
+        # Display all recommended books with their images
+        for i in range(len(prediction["titles"])):
+            st.subheader(f"{prediction['titles'][i]}")
+            st.image(imgs[i], use_column_width=True)
+            st.write(f"سنة النشر: {prediction['year'][i]}")
+            st.write(f"المؤلف: {prediction['author'][i]}")
+            st.write(f"التصنيف: {prediction['category'][0]}")
+
+    except requests.exceptions.RequestException as e:
+        st.error(f"Error requesting prediction from API. Please try again.{e}")
+        st.write(e)