Update app.py

app.py

@@ -1,212 +1,250 @@
-import socket
+import streamlit as st
+from streamlit_lottie import st_lottie
+from streamlit_option_menu import option_menu
 import requests
-from urllib.parse import urlparse
+import pandas as pd
+import plotly.express as px
+import plotly.graph_objects as go
+from datetime import datetime
+import httpx
+import asyncio
+import aiohttp
 from bs4 import BeautifulSoup
-import streamlit as st
-import matplotlib.pyplot as plt
-from reportlab.lib.pagesizes import letter
-from reportlab.pdfgen import canvas
-import geoip2.database
-
-def analyze_ip_free(url):
-    """
-    Analyze IP address and geolocation of a given URL
-    Uses GeoLite2 database to retrieve location information
-    
-    Args:
-        url (str): Website URL to analyze
-    
-    Returns:
-        dict: IP and location details or error information
-    """
-    try:
-        domain = urlparse(url).netloc
-        ip = socket.gethostbyname(domain)
-        with geoip2.database.Reader('GeoLite2-City.mmdb') as reader:
-            response = reader.city(ip)
-            return {
-                "ip": ip,
-                "city": response.city.name or "Unknown",
-                "region": response.subdivisions.most_specific.name or "Unknown",
-                "country": response.country.name or "Unknown",
-                "latitude": response.location.latitude or "Unknown",
-                "longitude": response.location.longitude or "Unknown",
-            }
-    except Exception as e:
-        return {"error": str(e)}
-
-def analyze_uptime_free(url):
-    """
-    Check website availability and response status
-    
-    Args:
-        url (str): Website URL to check
-    
-    Returns:
-        dict: Uptime status and status code
-    """
-    try:
-        response = requests.get(url, timeout=5)
-        return {
-            "status": "Up" if response.status_code == 200 else "Down",
-            "status_code": response.status_code,
-        }
-    except requests.exceptions.RequestException as e:
-        return {"status": "Down", "error": str(e)}
-
-def analyze_seo_free(url):
-    """
-    Extract basic SEO information from the website
-    
-    Args:
-        url (str): Website URL to analyze
-    
-    Returns:
-        dict: SEO-related metadata 
-    """
-    try:
-        response = requests.get(url)
-        soup = BeautifulSoup(response.text, 'html.parser')
-        title = soup.title.string if soup.title else "No Title"
-        meta_description = soup.find("meta", attrs={"name": "description"})
-        keywords = soup.find("meta", attrs={"name": "keywords"})
-        
-        return {
-            "title": title,
-            "meta_description": meta_description["content"] if meta_description else "No Description",
-            "keywords": keywords["content"] if keywords else "No Keywords",
-        }
-    except Exception as e:
-        return {"error": str(e)}
-
-def analyze_carbon_free(url):
-    """
-    Estimate website's carbon footprint based on page size
-    
-    Args:
-        url (str): Website URL to analyze
-    
-    Returns:
-        dict: Page size and estimated CO2 emissions
-    """
-    try:
-        response = requests.get(url)
-        page_size = len(response.content) / 1024  # in kilobytes
-        co2_estimation = page_size * 0.02  # rough CO2 emission estimate
-        return {
-            "page_size_kb": round(page_size, 2),
-            "estimated_co2_g": round(co2_estimation, 2),
-        }
-    except Exception as e:
-        return {"error": str(e)}
-
-def draw_bar_chart(data, title, xlabel, ylabel):
-    """
-    Create a bar chart visualization
-    
-    Args:
-        data (dict): Data to visualize
-        title (str): Chart title
-        xlabel (str): X-axis label
-        ylabel (str): Y-axis label
-    """
-    keys, values = list(data.keys()), list(data.values())
-    plt.figure(figsize=(8, 5))
-    plt.bar(keys, values, color='skyblue')
-    plt.title(title)
-    plt.xlabel(xlabel)
-    plt.ylabel(ylabel)
-    plt.tight_layout()
-    plt.savefig('chart.png')
-    plt.show()
+import whois
+import ssl
+import socket
+import dns.resolver
+from urllib.parse import urlparse
+import json
+import numpy as np
+from selenium import webdriver
+from selenium.webdriver.chrome.options import Options
+from webdriver_manager.chrome import ChromeDriverManager
+from PIL import Image
+import io
+import time
 
-def export_to_pdf_free(results, file_path):
-    """
-    Export analysis results to a PDF report
-    
-    Args:
-        results (dict): Analysis results
-        file_path (str): Path to save PDF
-    """
-    c = canvas.Canvas(file_path, pagesize=letter)
-    c.drawString(30, 750, "Website Analysis Report")
-    c.drawString(30, 730, "=" * 50)
-    y = 700
-    for section, content in results.items():
-        c.drawString(30, y, f"{section}:")
-        y -= 20
-        for key, value in content.items():
-            c.drawString(50, y, f"- {key}: {value}")
-            y -= 20
-        y -= 20
-    c.save()
+# تخصيص المظهر
+st.set_page_config(layout="wide", page_title="محلل المواقع المتقدم")
 
-def main():
-    """
-    Main Streamlit application for website analysis
-    """
-    st.title("أداة تحليل المواقع")
-    st.write("تحليل شامل للمواقع باستخدام أدوات مجانية")
+# تحميل الأنيميشن
+def load_lottieurl(url):
+    r = requests.get(url)
+    if r.status_code != 200:
+        return None
+    return r.json()
 
-    # URL input
-    url = st.text_input("أدخل رابط الموقع:", "https://example.com")
+lottie_analyzing = load_lottieurl("https://assets5.lottiefiles.com/packages/lf20_qpwbqki6.json")
 
-    if url:
-        # IP Analysis
-        st.subheader("1. تحليل عنوان IP والموقع الجغرافي")
-        ip_data = analyze_ip_free(url)
-        if "error" in ip_data:
-            st.error(ip_data["error"])
-        else:
-            st.json(ip_data)
+# تصميم CSS مخصص
+st.markdown("""
+<style>
+    .main {
+        background-color: #f0f2f6;
+    }
+    .stButton>button {
+        color: white;
+        background-color: #ff4b4b;
+        border-radius: 10px;
+        padding: 15px 25px;
+        border: none;
+    }
+    .stButton>button:hover {
+        background-color: #ff6b6b;
+        border: none;
+    }
+    .metric-card {
+        background-color: white;
+        border-radius: 10px;
+        padding: 20px;
+        box-shadow: 0 4px 6px rgba(0,0,0,0.1);
+    }
+</style>
+""", unsafe_allow_html=True)
 
-        # Uptime Analysis
-        st.subheader("2. تحليل توافر الموقع")
-        uptime_data = analyze_uptime_free(url)
-        if "error" in uptime_data:
-            st.error(uptime_data["error"])
-        else:
-            st.json(uptime_data)
+class WebsiteAnalyzer:
+    def __init__(self):
+        self.headers = {
+            'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36'
+        }
 
-        # SEO Analysis
-        st.subheader("3. تحليل تحسين محركات البحث (SEO)")
-        seo_data = analyze_seo_free(url)
-        if "error" in seo_data:
-            st.error(seo_data["error"])
-        else:
-            st.json(seo_data)
+    async def analyze_performance(self, url):
+        try:
+            start_time = time.time()
+            async with httpx.AsyncClient() as client:
+                response = await client.get(url)
+                load_time = time.time() - start_time
+                page_size = len(response.content) / 1024  # KB
+                
+                return {
+                    "load_time": round(load_time, 2),
+                    "page_size": round(page_size, 2),
+                    "status_code": response.status_code
+                }
+        except Exception as e:
+            return {"error": str(e)}
 
-        # Carbon Analysis
-        st.subheader("4. تحليل الأثر البيئي")
-        carbon_data = analyze_carbon_free(url)
-        if "error" in carbon_data:
-            st.error(carbon_data["error"])
-        else:
-            st.json(carbon_data)
+    async def analyze_seo(self, url):
+        try:
+            async with httpx.AsyncClient() as client:
+                response = await client.get(url)
+                soup = BeautifulSoup(response.text, 'html.parser')
+                
+                # تحليل العناوين
+                headings = {
+                    'h1': len(soup.find_all('h1')),
+                    'h2': len(soup.find_all('h2')),
+                    'h3': len(soup.find_all('h3'))
+                }
+                
+                # تحليل الروابط
+                links = soup.find_all('a')
+                internal_links = len([link for link in links if urlparse(link.get('href', '')).netloc == urlparse(url).netloc])
+                external_links = len(links) - internal_links
+                
+                # تحليل الصور
+                images = soup.find_all('img')
+                images_without_alt = len([img for img in images if not img.get('alt')])
+                
+                return {
+                    "title": soup.title.string if soup.title else "لا يوجد عنوان",
+                    "meta_description": soup.find("meta", {"name": "description"}).get("content") if soup.find("meta", {"name": "description"}) else "لا يوجد وصف",
+                    "headings": headings,
+                    "internal_links": internal_links,
+                    "external_links": external_links,
+                    "images_without_alt": images_without_alt
+                }
+        except Exception as e:
+            return {"error": str(e)}
 
-            # Carbon Analysis Chart
-            st.subheader("رسم بياني لتحليل الأثر البيئي")
-            co2_data = {
-                "Page Size (KB)": carbon_data["page_size_kb"], 
-                "CO2 Emission (g)": carbon_data["estimated_co2_g"]
+    def analyze_security(self, url):
+        try:
+            domain = urlparse(url).netloc
+            
+            # فحص SSL
+            ctx = ssl.create_default_context()
+            with ctx.wrap_socket(socket.socket(), server_hostname=domain) as s:
+                s.connect((domain, 443))
+                cert = s.getpeercert()
+            
+            # فحص DNS
+            dns_records = {
+                'A': [str(r) for r in dns.resolver.resolve(domain, 'A')],
+                'MX': [str(r) for r in dns.resolver.resolve(domain, 'MX')],
+                'TXT': [str(r) for r in dns.resolver.resolve(domain, 'TXT')]
             }
-            draw_bar_chart(co2_data, "Carbon Analysis", "Category", "Value")
-            st.image("chart.png")
-
-        # PDF Export
-        st.subheader("5. تصدير التقرير إلى PDF")
-        if st.button("تصدير التقرير"):
-            results = {
-                "IP Analysis": ip_data,
-                "Uptime Analysis": uptime_data,
-                "SEO Analysis": seo_data,
-                "Carbon Analysis": carbon_data,
+            
+            # معلومات WHOIS
+            domain_info = whois.whois(domain)
+            
+            return {
+                "ssl_valid": True,
+                "ssl_expiry": cert['notAfter'],
+                "dns_records": dns_records,
+                "domain_info": {
+                    "registrar": domain_info.registrar,
+                    "creation_date": domain_info.creation_date,
+                    "expiration_date": domain_info.expiration_date
+                }
             }
-            file_path = "website_analysis_report.pdf"
-            export_to_pdf_free(results, file_path)
-            st.success(f"تم تصدير التقرير إلى {file_path}")
-            with open(file_path, "rb") as pdf_file:
-                st.download_button("تحميل التقرير", data=pdf_file, file_name="website_analysis_report.pdf")
+        except Exception as e:
+            return {"error": str(e)}
+
+    async def take_screenshot(self, url):
+        try:
+            chrome_options = Options()
+            chrome_options.add_argument('--headless')
+            chrome_options.add_argument('--no-sandbox')
+            chrome_options.add_argument('--disable-dev-shm-usage')
+            
+            driver = webdriver.Chrome(ChromeDriverManager().install(), options=chrome_options)
+            driver.get(url)
+            driver.set_window_size(1920, 1080)
+            
+            screenshot = driver.get_screenshot_as_png()
+            driver.quit()
+            
+            return Image.open(io.BytesIO(screenshot))
+        except Exception as e:
+            return None
+
+def main():
+    st.title("🔍 محلل المواقع المتقدم")
+    
+    # إضافة قائمة جانبية
+    with st.sidebar:
+        selected = option_menu(
+            menu_title="القائمة الرئيسية",
+            options=["تحليل جديد", "التقارير السابقة", "الإعدادات"],
+            icons=["search", "file-text", "gear"],
+            menu_icon="cast",
+            default_index=0,
+        )
+    
+    if selected == "تحليل جديد":
+        col1, col2 = st.columns([2, 1])
+        
+        with col1:
+            url = st.text_input("أدخل رابط الموقع", "https://example.com")
+            if st.button("بدء التحليل"):
+                with st.spinner("جاري التحليل..."):
+                    st_lottie(lottie_analyzing, height=200)
+                    
+                    analyzer = WebsiteAnalyzer()
+                    
+                    # تحليل متزامن
+                    loop = asyncio.new_event_loop()
+                    asyncio.set_event_loop(loop)
+                    performance_data = loop.run_until_complete(analyzer.analyze_performance(url))
+                    seo_data = loop.run_until_complete(analyzer.analyze_seo(url))
+                    security_data = analyzer.analyze_security(url)
+                    screenshot = loop.run_until_complete(analyzer.take_screenshot(url))
+                    
+                    # عرض النتائج
+                    st.success("تم اكتمال التحليل!")
+                    
+                    # عرض البطاقات الإحصائية
+                    cols = st.columns(3)
+                    with cols[0]:
+                        st.metric("زمن التحميل", f"{performance_data['load_time']}s")
+                    with cols[1]:
+                        st.metric("حجم الصفحة", f"{performance_data['page_size']} KB")
+                    with cols[2]:
+                        st.metric("الروابط الداخلية", seo_data['internal_links'])
+                    
+                    # عرض تحليل SEO
+                    with st.expander("تحليل SEO", expanded=True):
+                        st.json(seo_data)
+                        
+                        # رسم بياني للعناوين
+                        fig = px.bar(
+                            x=list(seo_data['headings'].keys()),
+                            y=list(seo_data['headings'].values()),
+                            title="توزيع العناوين",
+                            labels={'x': 'نوع العنوان', 'y': 'العدد'}
+                        )
+                        st.plotly_chart(fig)
+                    
+                    # عرض تحليل الأمان
+                    with st.expander("تحليل الأمان", expanded=True):
+                        st.json(security_data)
+                    
+                    # عرض لقطة الشاشة
+                    if screenshot:
+                        st.image(screenshot, caption="لقطة شاشة للموقع", use_column_width=True)
+        
+        with col2:
+            st.subheader("آخر التحليلات")
+            # هنا يمكن إضافة قائمة بآخر المواقع التي تم تحليلها
+    
+    elif selected == "التقارير السابقة":
+        st.subheader("التقارير السابقة")
+        # هنا يمكن إضافة عرض للتقارير السابقة
+    
+    elif selected == "الإعدادات":
+        st.subheader("إعدادات التحليل")
+        # هنا يمكن إضافة إعدادات التحليل
 
 if __name__ == "__main__":
-    main()
+    main()
+