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| import re
import asyncio
import random
import pandas as pd
from playwright.async_api import async_playwright
CONCURRENCY = 5
EMAIL_REGEX = r"[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}"
MIN_DELAY = 2
MAX_DELAY = 8
USER_AGENTS = [
"Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36",
"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36",
"Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:89.0) Gecko/20100101 Firefox/89.0",
"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/605.1.15 (KHTML, like Gecko) Version/14.1.1 Safari/605.1.15"
]
async def crawl_email(index, homepage):
"""异步爬取单个主页的邮箱"""
result_msg = "未抓取到邮箱"
try:
await asyncio.sleep(random.uniform(MIN_DELAY, MAX_DELAY))
async with async_playwright() as p:
browser = await p.chromium.launch(headless=True)
context = await browser.new_context(
user_agent=random.choice(USER_AGENTS),
viewport={"width": 1920, "height": 1080}
)
page = await context.new_page()
try:
await page.goto(homepage, timeout=30000, wait_until="domcontentloaded")
if random.random() > 0.3:
await page.mouse.move(
random.randint(0, 500),
random.randint(0, 500)
)
await page.evaluate("window.scrollBy(0, window.innerHeight/2)")
await asyncio.sleep(random.uniform(0.5, 1.5))
try:
await page.wait_for_selector('[data-e2e="user-bio"]', timeout=8000)
bio_text = await page.locator('[data-e2e="user-bio"]').inner_text()
emails = re.findall(EMAIL_REGEX, bio_text)
if emails:
return index, emails[0]
except Exception as e:
result_msg = "页面元素加载失败"
except Exception as e:
result_msg = f"页面加载失败: {str(e)[:50]}"
finally:
await browser.close()
except Exception as e:
result_msg = f"浏览器错误: {str(e)[:50]}"
return index, result_msg
async def main():
print(f"启动爬虫，并发数: {CONCURRENCY}")
file_name = "3dsticker_result"
column_name = "主页地址"
file_path = "./result/" + file_name + ".xlsx"
df = pd.read_excel(file_path)
df["邮箱"] = df["邮箱"].astype(str)
output_path = "./retry/" + file_name + ".xlsx"
retry_condition = (
df["邮箱"].str.contains("加载失败", na=False) |
df["邮箱"].str.lower().isin(["nan", "none", "null", ""])
)
retry_df = df[retry_condition]
if len(retry_df) == 0:
print("没有需要重试的记录")
return
print(f"发现 {len(retry_df)} 条需要重试的记录")
tasks = []
for index, row in retry_df.iterrows():
homepage = row[column_name]
if pd.isna(homepage) or not isinstance(homepage, str) or not homepage.startswith(('http', 'www')):
df.at[index, "邮箱"] = "无效链接格式"
continue
tasks.append((index, homepage.strip()))
total = len(tasks)
success_count = 0
for i in range(0, total, CONCURRENCY):
batch = tasks[i:i + CONCURRENCY]
batch_tasks = [crawl_email(idx, url) for idx, url in batch]
batch_num = i // CONCURRENCY + 1
total_batches = (total + CONCURRENCY - 1) // CONCURRENCY
print(f"\n处理批次 {batch_num}/{total_batches} (任务 {i+1}-{min(i+CONCURRENCY, total)})")
results = await asyncio.gather(*batch_tasks)
for index, result in results:
original_status = df.at[index, "邮箱"]
df.at[index, "邮箱"] = result
if "@" in str(result):
status = "✅ 成功"
success_count += 1
else:
status = "❌ 失败"
print(f"行{index+2}: {status} | 原状态: {original_status} | 新结果: {result}")
df.to_excel(output_path, index=False)
print("\n" + "="*50)
print(f"任务完成，文件已保存: {output_path}")
print(f"总记录数: {len(df)}")
print(f"本次处理: {len(retry_df)} 条")
print(f"成功抓取: {success_count} 条")
print(f"仍失败: {len(retry_df) - success_count} 条")
print("="*50)
if __name__ == "__main__":
asyncio.run(main())
|
