162 lines
5.6 KiB
Python
162 lines
5.6 KiB
Python
import argparse
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import docker
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import sys
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import os
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import json
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import time
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import re
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import pprint
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import subprocess
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from jinja2 import Template
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total_start = time.time()
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parser = argparse.ArgumentParser(description='Scrape websites with a containerized web browser')
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parser.add_argument('website', help='Desired website you want to scrape')
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parser.add_argument('-b', '--browser-path', help='Path to browser binary',
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default='/usr/bin/google-chrome')
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parser.add_argument('-a', '--browser-args', nargs='+', help='Additional Args to pass the browser')
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parser.add_argument('-p', '--proxy-url', help='Proxy URL (e.g., http://user:pass@host:port)')
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parser.add_argument('-i', '--image-name', help='Name of the docker image',
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default='search-api')
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args = parser.parse_args()
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docker_client = docker.from_env()
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try:
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docker_client.images.get(args.image_name)
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except docker.errors.ImageNotFound:
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print(f"Image {args.image_name} not found")
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sys.exit(1)
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env_vars = {
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'WEBSITE': args.website,
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'BROWSER_PATH': args.browser_path,
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'OUTPUT_FILE': '/output/output.txt'
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}
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output_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'output')
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# os.makedirs(output_dir, exist_ok=True)
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# os.chmod(output_dir, 0o777)
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if args.browser_args:
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env_vars['BROWSER_ARGS'] = ','.join(args.browser_args)
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if args.proxy_url:
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env_vars['PROXY_URL'] = args.proxy_url
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try:
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container_start_time = time.time()
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print("Container start time:", container_start_time)
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container = docker_client.containers.run(
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args.image_name,
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# remove=True,
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detach=True,
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environment=env_vars,
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# The `,z` part is needed to avoid SELinux issues
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volumes={output_dir: {'bind': '/output', 'mode': 'rw,z'}},
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user='0'
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)
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max_cpu_percent = 0
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max_memory_mb = 0
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total_rx_bytes = 0
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total_tx_bytes = 0
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stats_stream = container.stats(stream=True)
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while container.status in ['running', 'created']:
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container.reload()
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if container.status != 'running':
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break
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try:
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stats = next(stats_stream)
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stats = json.loads(stats.decode('utf-8'))
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if 'online_cpus' not in stats['cpu_stats'] or 'usage' not in stats.get('memory_stats', {}):
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continue
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cpu_delta = stats['cpu_stats']['cpu_usage']['total_usage'] - stats['precpu_stats']['cpu_usage']['total_usage']
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system_delta = stats['cpu_stats'].get('system_cpu_usage', 0) - stats['precpu_stats'].get('system_cpu_usage', 0)
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online_cpus = stats['cpu_stats']['online_cpus']
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if system_delta > 0:
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cpu_percent = (cpu_delta / system_delta) * online_cpus * 100.0
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max_cpu_percent = max(max_cpu_percent, cpu_percent)
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if 'usage' in stats.get('memory_stats', {}):
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memory_mb = stats['memory_stats']['usage'] / 1024 / 1024
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max_memory_mb = max(max_memory_mb, memory_mb)
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networks = stats.get('networks', {})
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if isinstance(networks, dict):
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for interface in networks.values():
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total_rx_bytes = max(total_rx_bytes, interface.get('rx_bytes', 0))
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total_tx_bytes = max(total_tx_bytes, interface.get('tx_bytes', 0))
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except Exception as e:
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print('Error:', e)
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break
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container.reload() # Refresh container status
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container.wait()
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print("Container logs:")
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logs = container.logs().decode('utf-8')
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for line in logs.strip().split('\n'):
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if "Cold start" in line:
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coldstart_stop_time = float(re.search(r'([\d.]+)', line).group(1))
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if "Start response" in line:
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scrape_start_time = float(re.search(r'([\d.]+)', line).group(1))
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if "Stop response" in line:
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scrape_stop_time = float(re.search(r'([\d.]+)', line).group(1))
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print(f"\t{line}")
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container.remove()
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metrics = [
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{"name": "Max CPU", "value": f"{max_cpu_percent:.2f}", "unit": "%"},
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{"name": "Max Memory", "value": f"{max_memory_mb:.2f}", "unit": "MB"},
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{"name": "Total Transfer", "value": f"{(total_rx_bytes + total_tx_bytes) / 1024:.0f}", "unit": "KB"},
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{"name": "Cold Start Time", "value": f"{(coldstart_stop_time - container_start_time):.3f}", "unit": "seconds"},
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{"name": "Time to Response", "value": f"{(scrape_stop_time - scrape_start_time):.3f}", "unit": "seconds"},
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{"name": "Total Runtime", "value": f"{(time.time() - total_start):.3f}", "unit": "seconds"}
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]
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with open('output/output.txt', 'r', encoding='utf-8') as f:
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text_content = f.read()
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with open('report.html', 'r') as f:
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template = Template(f.read())
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rendered_html = template.render(metrics=metrics, text_content=text_content)
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with open('output/report.html', 'w') as f:
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f.write(rendered_html)
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# Try running `open` to launch the html file automatically, fail silently
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try:
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subprocess.run(['open', 'output/report.html'])
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print("Report opened in browser")
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except (subprocess.CalledProcessError, FileNotFoundError):
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print("what happened")
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pass
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print(f"""Performance:
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Max CPU: {max_cpu_percent:.2f}%
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Max Memory: {max_memory_mb:.2f}MB
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Total Transfer: {(total_rx_bytes + total_tx_bytes) / 1024} KBs""")
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print(f"Cold Start Time: {(coldstart_stop_time - container_start_time):.3f} seconds")
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print(f"Time to Response: {(scrape_stop_time - scrape_start_time):.3f} seconds")
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print(f"Completed everything in: {(time.time() - total_start):.3f} seconds")
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except Exception as e:
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print(f"Error running container: {e}")
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sys.exit(1)
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