Python下selenium的实战和普通爬虫的对比

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1.普通爬取数据

"""普通爬取数据爬虫，只要有反爬，cookie就不是很稳定。并不利于数据爬取"""
import requests
import re
from lxml import etree


headers = {
        "User-Agent": "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/71.0.3554.0 Safari/537.36",
        "Referer": "https://www.lagou.com/jobs/list_python?labelWords=&fromSearch=true&suginput=",
        # Cookie需要时常换取
        "Cookie": "_ga=GA1.2.1553999204.1538311958; user_trace_token=20180930205504-0cebb367-c4b0-11e8-bb68-5254005c3644; "
                  "LGUID=20180930205504-0cebbcd1-c4b0-11e8-bb68-5254005c3644; showExpriedIndex=1; showExpriedCompanyHome=1; "
                  "showExpriedMyPublish=1; index_location_city=%E6%B7%B1%E5%9C%B3; sensorsdata2015jssdkcross=%7B%22distinct_"
                  "id%22%3A%22166811f974d15e-026ab47692a8d1-181c7151-2073600-166811f974e549%22%2C%22%24device_id%22%3A%2216681"
                  "1f974d15e-026ab47692a8d1-181c7151-2073600-166811f974e549%22%7D; LG_LOGIN_USER_ID=1d0d39f3227c1f914a3f9c4d95f"
                  "4816a5c6667141cc1313edac4603b4bd6d789; hasDeliver=6; _gid=GA1.2.2026255269.1540465512; WEBTJ-ID=2018102519420"
                  "2-166ab0808f9cb-06806b898438ec-181c7151-2073600-166ab0808fb7ef; Hm_lvt_4233e74dff0ae5bd0a3d81c6ccf756e6=15401"
                  "21809,1540210602,1540465512,1540467723; LGSID=20181025194505-6ab63d2a-d84b-11e8-8168-5254005c3644; PRE_UTM=m_cf_"
                  "cpt_baidu_pc; PRE_HOST=www.baidu.com; PRE_SITE=https%3A%2F%2Fwww.baidu.com%2Fs%3Fie%3Dutf-8%26f%3D8%26rsv_bp%3D0%2"
                  "6rsv_idx%3D1%26tn%3Dbaidu%26wd%3D%25E6%258B%2589%25E5%258B%25BE%25E7%25BD%2591%26rsv_pq%3D8d0dc05a0000aada%26rsv_t%"
                  "3D4664T41fswButqvfw6ZM6FGWfkWjtwR%252Fmpsskb6hctTVnUHewMo9o1%252BqRGk%26rqlang%3Dcn%26rsv_enter%3D1%26rsv_sug3%3D7%26r"
                  "sv_sug1%3D8%26rsv_sug7%3D100; PRE_LAND=https%3A%2F%2Fwww.lagou.com%2Flp%2Fhtml%2Fcommon.html%3Futm_source%3Dm_cf_cpt_baidu_pc;"
                  " _putrc=1D33894D7A6BEB76123F89F2B170EADC; JSESSIONID=ABAAABAAAGFABEF9CEC8B1F38F5075A286961D31667AC5C; login=true; unick=%E6%9D%A"
                  "8%E7%A6%B9; gate_login_token=b0629019d50bbe97eb829d61be9770ad4b570c1e68e239c68ae16cc71c68c808; _gat=1; Hm_lpvt_4233e74dff0ae5bd0a"
                  "3d81c6ccf756e6=1540469398; LGRID=20181025201301-5183464a-d84f-11e8-a347-525400f775ce; TG-TRACK-CODE=index_search; SEARCH_ID=06714"
                  "3e245964eb7af08d8c8d316cd44"
    }


def request_list_page():
    # 获取详情页面url
    url = "https://www.lagou.com/jobs/positionAjax.json?city=%E6%B7%B1%E5%9C%B3&needAddtionalResult=false"
    data = {
        "first": "false",
        "pn": 1,
        "kd": "Python"
    }
    for x in range(1, 31):
        data["pn"] = x
        rep = requests.post(url=url, headers=headers, data=data)
        # json方法，如果返回来的是json数据，自动转换为字典
        result = rep.json()
        # json在线解析分析数据格式
        positions = result["content"]["positionResult"]["result"]
        for position in positions:
            positionId = position["positionId"]
            # 找到详情页url，并传递给解析函数
            position_url = "https://www.lagou.com/jobs/{}.html".format(positionId)
            parse_position_detail(position_url)
            break
        break


def parse_position_detail(url):
    # 页面解析
    res = requests.get(url, headers=headers)
    text = res.text
    html = etree.HTML(text)
    position_depart = html.xpath("//div[@class='company']/text()")
    position_names = html.xpath("//span[@class='name']/text()")
    job_requests = html.xpath("//dd[@class='job_request']//span/text()")
    salary_span = re.sub(r"[\s/]", "", job_requests[0].strip())
    addr_span = re.sub(r"[\s/]", "", job_requests[1].strip())
    exper_span = re.sub(r"[\s/]", "", job_requests[2].strip())
    education_span = re.sub(r"[\s/]", "", job_requests[3].strip())
    full_span = re.sub(r"[\s/]", "", job_requests[4].strip())
    desc = "".join(html.xpath("//dd[@class='job_bt']//text()")).strip()
    print(position_depart, position_names, salary_span, addr_span, exper_span, education_span, full_span, desc)


if __name__ == '__main__':
    request_list_page()

View Code

2.操作selenium获取数据

"""selenium自动化爬取，模拟人的动作，操作浏览器访问"""
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from lxml import etree
import random
import csv
import time
import re


class LagouSpider(object):
    # 获取chromedriver.exe路径
    driver_path = r"E:\Program Files\chromedriver.exe"

    def __init__(self):
        # 实例化这个路径
        self.driver = webdriver.Chrome(executable_path=LagouSpider.driver_path)
        self.url = "https://www.lagou.com/jobs/list_python?city=全国&cl=false&fromSearch=true&labelWords=&suginput="

    def run(self):
        # 页面列表仅限一次，取出while循环
        self.driver.get(self.url)
        while True:
            # 获取页面源码
            source = self.driver.page_source
            # 有异步加载，数据出来的慢，需要等待
            WebDriverWait(driver=self.driver, timeout=10).until(
                EC.presence_of_element_located((By.XPATH, "//div[@class='pager_container']/span[last()]"))
            )
            # 将完整的源码传递给函数解析
            self.parse_list_page(source)
            try:
                # 获取下一页点击标签
                next_btn = self.driver.find_element_by_xpath("//div[@class='pager_container']/span[last()]")
                # 是最后一页，停止循环
                if "pager_next_disabled" in next_btn.get_attribute("class"):
                    break
                else:
                    # 继续循环
                    next_btn.click()
            except:
                print(source)
            time.sleep(1)

    def parse_list_page(self, source):
        # 获取详情url
        html = etree.HTML(source)
        links = html.xpath("//a[@class='position_link']/@href")
        for link in links:
            # 将获取的url传递给函数
            self.request_detail_page(link)
            time.sleep(random.randint(0, 2))

    def request_detail_page(self, url):
        # 打开新的页面窗口
        self.driver.execute_script("window.open('%s')" % url)
        # 移动到新的页面窗口
        self.driver.switch_to.window(self.driver.window_handles[1])
        # 有异步加载，数据出来的慢，需要等待
        WebDriverWait(self.driver, timeout=10).until(
            EC.presence_of_element_located((By.XPATH, "//div[@class='job-name']/span[@class='name']"))
        )
        source = self.driver.page_source
        # 将源码传递给函数解析
        self.parse_detail_page(source)
        # 关闭当前这个详情页
        self.driver.close()
        # 继续切换回职位列表页
        self.driver.switch_to.window(self.driver.window_handles[0])

    def parse_detail_page(self, source):
        # 开始解析数据(不做介绍,前面有详解)
        html = etree.HTML(source)
        position_name = html.xpath("//span[@class='name']/text()")[0]
        job_request_spans = html.xpath("//dd[@class='job_request']//span")
        salary = job_request_spans[0].xpath(".//text()")[0].strip()
        city = job_request_spans[1].xpath(".//text()")[0].strip()
        city = re.sub(r'[\s/]]', "", city)
        work_years = job_request_spans[2].xpath(".//text()")[0].strip()
        work_years = re.sub(r'[\s/]]', "", work_years)
        education = job_request_spans[3].xpath(".//text()")[0].strip()
        education = re.sub(r'[\s/]]', "", education)
        desc = "".join(html.xpath("//dd[@class='job_bt']//text()")).strip()
        company_name = html.xpath("//h2[@class='fl']/text()")[0].strip()
        position = {(position_name, company_name, salary, city, work_years, education, desc)}
        with open("lagou.csv", "a+", encoding="utf-8", newline="") as fp:
            writer = csv.writer(fp)
            writer.writerows(position)


if __name__ == '__main__':
    spider = LagouSpider()
    spider.run()

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