Update app.py
Browse files
app.py
CHANGED
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@@ -6,11 +6,19 @@ import streamlit as st
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import matplotlib.pyplot as plt
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from reportlab.lib.pagesizes import letter
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from reportlab.pdfgen import canvas
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# تحليل عنوان IP والموقع الجغرافي باستخدام مكتبة GeoLite2
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import geoip2.database
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def analyze_ip_free(url):
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try:
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domain = urlparse(url).netloc
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ip = socket.gethostbyname(domain)
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@@ -27,8 +35,16 @@ def analyze_ip_free(url):
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except Exception as e:
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return {"error": str(e)}
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# تحليل توفر الموقع باستخدام requests
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def analyze_uptime_free(url):
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try:
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response = requests.get(url, timeout=5)
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return {
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except requests.exceptions.RequestException as e:
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return {"status": "Down", "error": str(e)}
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# تحليل تحسين محركات البحث (SEO)
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def analyze_seo_free(url):
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try:
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response = requests.get(url)
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soup = BeautifulSoup(response.text, 'html.parser')
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except Exception as e:
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return {"error": str(e)}
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# تحليل الأثر البيئي
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def analyze_carbon_free(url):
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try:
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response = requests.get(url)
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page_size = len(response.content) / 1024 #
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co2_estimation = page_size * 0.02 #
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return {
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"page_size_kb": round(page_size, 2),
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"estimated_co2_g": round(co2_estimation, 2),
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except Exception as e:
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return {"error": str(e)}
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# رسم الرسوم البيانية باستخدام matplotlib
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def draw_bar_chart(data, title, xlabel, ylabel):
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keys, values = list(data.keys()), list(data.values())
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plt.figure(figsize=(8, 5))
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plt.bar(keys, values, color='skyblue')
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@@ -80,8 +120,14 @@ def draw_bar_chart(data, title, xlabel, ylabel):
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plt.savefig('chart.png')
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plt.show()
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# تصدير التقرير إلى PDF
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def export_to_pdf_free(results, file_path):
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c = canvas.Canvas(file_path, pagesize=letter)
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c.drawString(30, 750, "Website Analysis Report")
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c.drawString(30, 730, "=" * 50)
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@@ -95,58 +141,72 @@ def export_to_pdf_free(results, file_path):
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y -= 20
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c.save()
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#
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url = st.text_input("أدخل رابط الموقع:", "https://example.com")
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if url:
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import matplotlib.pyplot as plt
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from reportlab.lib.pagesizes import letter
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from reportlab.pdfgen import canvas
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import geoip2.database
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def analyze_ip_free(url):
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"""
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Analyze IP address and geolocation of a given URL
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Uses GeoLite2 database to retrieve location information
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Args:
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url (str): Website URL to analyze
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Returns:
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dict: IP and location details or error information
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"""
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try:
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domain = urlparse(url).netloc
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ip = socket.gethostbyname(domain)
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except Exception as e:
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return {"error": str(e)}
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def analyze_uptime_free(url):
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"""
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Check website availability and response status
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Args:
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url (str): Website URL to check
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Returns:
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dict: Uptime status and status code
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"""
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try:
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response = requests.get(url, timeout=5)
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return {
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except requests.exceptions.RequestException as e:
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return {"status": "Down", "error": str(e)}
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def analyze_seo_free(url):
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"""
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Extract basic SEO information from the website
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Args:
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url (str): Website URL to analyze
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Returns:
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dict: SEO-related metadata
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"""
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try:
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response = requests.get(url)
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soup = BeautifulSoup(response.text, 'html.parser')
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except Exception as e:
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return {"error": str(e)}
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def analyze_carbon_free(url):
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"""
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Estimate website's carbon footprint based on page size
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Args:
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url (str): Website URL to analyze
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Returns:
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dict: Page size and estimated CO2 emissions
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"""
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try:
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response = requests.get(url)
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page_size = len(response.content) / 1024 # in kilobytes
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co2_estimation = page_size * 0.02 # rough CO2 emission estimate
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return {
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"page_size_kb": round(page_size, 2),
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"estimated_co2_g": round(co2_estimation, 2),
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except Exception as e:
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return {"error": str(e)}
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def draw_bar_chart(data, title, xlabel, ylabel):
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"""
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Create a bar chart visualization
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Args:
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data (dict): Data to visualize
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title (str): Chart title
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xlabel (str): X-axis label
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ylabel (str): Y-axis label
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"""
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keys, values = list(data.keys()), list(data.values())
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plt.figure(figsize=(8, 5))
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plt.bar(keys, values, color='skyblue')
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plt.savefig('chart.png')
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plt.show()
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def export_to_pdf_free(results, file_path):
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"""
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Export analysis results to a PDF report
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Args:
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results (dict): Analysis results
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file_path (str): Path to save PDF
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"""
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c = canvas.Canvas(file_path, pagesize=letter)
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c.drawString(30, 750, "Website Analysis Report")
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c.drawString(30, 730, "=" * 50)
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y -= 20
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c.save()
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def main():
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"""
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Main Streamlit application for website analysis
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"""
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st.title("أداة تحليل المواقع")
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st.write("تحليل شامل للمواقع باستخدام أدوات مجانية")
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# URL input
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url = st.text_input("أدخل رابط الموقع:", "https://example.com")
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if url:
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# IP Analysis
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st.subheader("1. تحليل عنوان IP والموقع الجغرافي")
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ip_data = analyze_ip_free(url)
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if "error" in ip_data:
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st.error(ip_data["error"])
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else:
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st.json(ip_data)
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# Uptime Analysis
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st.subheader("2. تحليل توافر الموقع")
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uptime_data = analyze_uptime_free(url)
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if "error" in uptime_data:
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st.error(uptime_data["error"])
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else:
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st.json(uptime_data)
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# SEO Analysis
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st.subheader("3. تحليل تحسين محركات البحث (SEO)")
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seo_data = analyze_seo_free(url)
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if "error" in seo_data:
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st.error(seo_data["error"])
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else:
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st.json(seo_data)
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# Carbon Analysis
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st.subheader("4. تحليل الأثر البيئي")
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carbon_data = analyze_carbon_free(url)
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if "error" in carbon_data:
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st.error(carbon_data["error"])
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else:
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st.json(carbon_data)
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# Carbon Analysis Chart
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st.subheader("رسم بياني لتحليل الأثر البيئي")
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co2_data = {
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"Page Size (KB)": carbon_data["page_size_kb"],
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"CO2 Emission (g)": carbon_data["estimated_co2_g"]
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}
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draw_bar_chart(co2_data, "Carbon Analysis", "Category", "Value")
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st.image("chart.png")
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# PDF Export
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st.subheader("5. تصدير التقرير إلى PDF")
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if st.button("تصدير التقرير"):
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results = {
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"IP Analysis": ip_data,
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"Uptime Analysis": uptime_data,
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"SEO Analysis": seo_data,
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"Carbon Analysis": carbon_data,
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}
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file_path = "website_analysis_report.pdf"
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export_to_pdf_free(results, file_path)
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st.success(f"تم تصدير التقرير إلى {file_path}")
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with open(file_path, "rb") as pdf_file:
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st.download_button("تحميل التقرير", data=pdf_file, file_name="website_analysis_report.pdf")
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if __name__ == "__main__":
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main()
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