应用场景

用于工资和薪酬数据收集的验证码处理

薪资数据库、求职委员会和政府劳工门户网站通过 Cloudflare Turnstile 和 reCAPTCHA 保护薪酬数据。当按角色、位置或行业查询薪资范围时,验证码会触发 - 特别是在跨多个职位的批量数据收集期间。以下是处理它们的方法。

薪资门户上的验证码模式

来源类型 验证码 扳机
薪资比较网站 Cloudflare Turnstile 重复搜索查询
工作委员会薪资过滤器 reCAPTCHA v2 多种薪资查询
政府劳工统计 图片验证码 数据下载请求
企业薪资页面 Cloudflare 验证流程 批量页面浏览量
人力资源调查平台 reCAPTCHA v3 表格提交

薪资数据收集器

import requests
import time
import re
from dataclasses import dataclass

@dataclass
class SalaryRecord:
    title: str
    location: str
    min_salary: float
    max_salary: float
    median_salary: float
    sample_size: int
    source: str

class SalaryCollector:
    def __init__(self, api_key):
        self.api_key = api_key
        self.session = requests.Session()
        self.session.headers.update({
            "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36"
        })

    def collect_salary_data(self, portal_url, job_title, location):
        """Search for salary data, solving CAPTCHAs as needed."""
        response = self.session.get(portal_url, params={
            "title": job_title,
            "location": location
        })

        if self._is_turnstile_challenge(response):
            response = self._solve_turnstile_and_retry(response, portal_url)

        return self._parse_salary_data(response.text, portal_url)

    def collect_bulk(self, portal_url, job_titles, locations):
        """Collect salary data for multiple job title + location combos."""
        results = []

        for title in job_titles:
            for location in locations:
                try:
                    data = self.collect_salary_data(
                        portal_url, title, location
                    )
                    results.extend(data)
                    # Respectful delay between requests
                    time.sleep(2)
                except Exception as e:
                    print(f"Failed for {title} in {location}: {e}")

        return results

    def _is_turnstile_challenge(self, response):
        return (
            response.status_code == 403 or
            "cf-turnstile" in response.text or
            "challenges.cloudflare.com" in response.text
        )

    def _solve_turnstile_and_retry(self, response, url):
        match = re.search(r'data-sitekey="(0x[^"]+)"', response.text)
        if not match:
            raise ValueError("Turnstile sitekey not found")

        resp = requests.post("https://ocr.captchaai.com/in.php", data={
            "key": self.api_key,
            "method": "turnstile",
            "sitekey": match.group(1),
            "pageurl": url,
            "json": 1
        })
        task_id = resp.json()["request"]

        for _ in range(60):
            time.sleep(3)
            result = requests.get("https://ocr.captchaai.com/res.php", params={
                "key": self.api_key,
                "action": "get",
                "id": task_id,
                "json": 1
            })
            data = result.json()
            if data["status"] == 1:
                return self.session.post(url, data={
                    "cf-turnstile-response": data["request"]
                })

        raise TimeoutError("Turnstile solve timed out")

    def _parse_salary_data(self, html, source):
        from bs4 import BeautifulSoup
        soup = BeautifulSoup(html, "html.parser")
        records = []

        def text_or_empty(node):
            return node.text.strip() if node and node.text else ""

        for row in soup.select(".salary-row, .compensation-entry, tr[data-salary]"):
            try:
                records.append(SalaryRecord(
                    title=text_or_empty(row.select_one(".job-title, .title")),
                    location=text_or_empty(row.select_one(".location")),
                    min_salary=self._parse_amount(
                        text_or_empty(row.select_one(".min-salary, .low"))
                    ),
                    max_salary=self._parse_amount(
                        text_or_empty(row.select_one(".max-salary, .high"))
                    ),
                    median_salary=self._parse_amount(
                        text_or_empty(row.select_one(".median, .mid"))
                    ),
                    sample_size=int(
                        text_or_empty(row.select_one(".count, .sample")).replace(",", "") or 0
                    ),
                    source=source
                ))
            except (AttributeError, ValueError):
                continue

        return records

    def _parse_amount(self, text):
        if not text:
            return 0.0
        cleaned = re.sub(r'[^\d.]', '', text)
        return float(cleaned) if cleaned else 0.0


# Usage
collector = SalaryCollector("YOUR_API_KEY")
data = collector.collect_bulk(
    "https://salary.example.com/search",
    job_titles=["Software Engineer", "Data Analyst", "Product Manager"],
    locations=["San Francisco", "New York", "Austin"]
)

for record in data:
    print(f"{record.title} in {record.location}: "
          f"${record.min_salary:,.0f}–${record.max_salary:,.0f} "
          f"(median: ${record.median_salary:,.0f})")

多源聚合 (JavaScript)

class SalaryAggregator {
  constructor(apiKey) {
    this.apiKey = apiKey;
    this.sources = [];
  }

  addSource(name, searchUrl) {
    this.sources.push({ name, searchUrl });
  }

  async collectForRole(jobTitle, location) {
    const results = [];

    for (const source of this.sources) {
      try {
        const data = await this.querySource(source, jobTitle, location);
        results.push({ source: source.name, ...data });
      } catch (error) {
        results.push({ source: source.name, error: error.message });
      }
    }

    return this.aggregateResults(results, jobTitle, location);
  }

  async querySource(source, jobTitle, location) {
    const url = `${source.searchUrl}?title=${encodeURIComponent(jobTitle)}&location=${encodeURIComponent(location)}`;
    const response = await fetch(url);
    const html = await response.text();

    if (html.includes('cf-turnstile') || response.status === 403) {
      return this.solveAndRetry(source.searchUrl, html, jobTitle, location);
    }

    return this.parseSalaryData(html);
  }

  async solveAndRetry(baseUrl, html, jobTitle, location) {
    const match = html.match(/data-sitekey="(0x[^"]+)"/);
    if (!match) throw new Error('Turnstile sitekey not found');

    const submitResp = await fetch('https://ocr.captchaai.com/in.php', {
      method: 'POST',
      body: new URLSearchParams({
        key: this.apiKey,
        method: 'turnstile',
        sitekey: match[1],
        pageurl: baseUrl,
        json: '1'
      })
    });
    const { request: taskId } = await submitResp.json();

    for (let i = 0; i < 60; i++) {
      await new Promise(r => setTimeout(r, 3000));
      const result = await fetch(
        `https://ocr.captchaai.com/res.php?key=${this.apiKey}&action=get&id=${taskId}&json=1`
      );
      const data = await result.json();
      if (data.status === 1) {
        const response = await fetch(baseUrl, {
          method: 'POST',
          body: new URLSearchParams({
            'cf-turnstile-response': data.request,
            title: jobTitle,
            location: location
          })
        });
        return this.parseSalaryData(await response.text());
      }
    }
    throw new Error('Turnstile solve timed out');
  }

  aggregateResults(results, jobTitle, location) {
    const valid = results.filter(r => !r.error && r.median);
    if (valid.length === 0) return null;

    const medians = valid.map(r => r.median);
    return {
      jobTitle,
      location,
      avgMedian: medians.reduce((a, b) => a + b, 0) / medians.length,
      sources: valid.length,
      range: { min: Math.min(...medians), max: Math.max(...medians) }
    };
  }
}

// Usage
const aggregator = new SalaryAggregator('YOUR_API_KEY');
aggregator.addSource('SalaryDB', 'https://salarydb.example.com/search');
aggregator.addSource('PayScale', 'https://payscale.example.com/lookup');

const result = await aggregator.collectForRole('Software Engineer', 'San Francisco');
console.log(`Median salary: $${result.avgMedian.toLocaleString()} (${result.sources} sources)`);

数据收集策略

方法 每天的数量 验证码频率 最适合
有延迟的顺序 100-500 个查询 低的 小调查
代理轮换 500-2,000 次查询 缓和 区域分析
多会话并行 2,000-10,000 次查询 高的 综合数据集

故障排除

问题 原因 处理方式
每次搜索时都会旋转门 会话已过期 保留 qa_session_cookie cookie
薪资数据显示“需要登录” 门户需要身份验证 搜索前先进行身份验证
验证码解决后结果为空 缺少 POST 参数 包括所有隐藏的表单字段
运行之间的数据不一致 门户显示不同的范围 使用一致的查询参数

常问问题

每天可以查询多少次薪资?

这取决于门户的速率限制,而不是 CaptchaAI。 CaptchaAI 解决 Turnstile 成功率 100%。空间请求间隔 2 至 5 秒,并QA 测试会话以进行大容量收集。

我应该使用代理来收集工资数据吗?

是的,特别是对于数千个职位的批量收集。与数据中心 IP 相比,自有服务器基础设施显着降低了验证码频率。

我可以收集实时薪资数据吗?

大多数薪资门户每月或每季度更新一次数据,因此不需要实时收集。安排每周或每月收集综合数据集。

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