zoukankan      html  css  js  c++  java

  • 小米商品和腾讯招聘多线程爬取

    应用场景

    1、多进程 ：CPU密集程序
    2、多线程 ：爬虫(网络I/O)、本地磁盘I/O

    知识点回顾

    队列

    # 导入模块 from queue import Queue
    # 使用 q = Queue() q.put(url) q.get()
    # 当队列为空时，阻塞 q.empty()
    # 判断队列是否为空，True/False

    线程模块

    # 导入模块 from threading import Thread ​
    # 使用流程 t = Thread(target=函数名)
    # 创建线程对象 t.start()
    # 创建并启动线程 t.join()
    # 阻塞等待回收线程

    小米应用商店抓取(多线程)

    目标

    1. 网址 ：百度搜 - 小米应用商店，进入官网，应用分类 - 聊天社交
    2. 目标 ：爬取应用名称和应用链接

    实现步骤

    1、确认是否为动态加载

    1、页面局部刷新

    2、右键查看网页源代码，搜索关键字未搜到，因此此网站为动态加载网站，需要抓取网络数据包分析

    2、F12抓取网络数据包

    1、抓取返回json数据的URL地址（Headers中的Request URL）

      http://app.mi.com/categotyAllListApi?page={}&categoryId=2&pageSize=30

    2、查看并分析查询参数（headers中的Query String Parameters）只有page在变，0 1 2 3 ... ... ，这样我们就可以通过控制page的值拼接多个返回json数据的URL地址

      page: 1

      categoryId: 2

      pageSize: 30

    3、将抓取数据保存到csv文件

    注意多线程写入的线程锁问题

    from threading import Lock

    lock = Lock()

    lock.acquire()

    lock.release()

    整体思路

    1. 在 __init__(self) 中创建文件对象，多线程操作此对象进行文件写入
    2. 每个线程抓取数据后将数据进行文件写入，写入文件时需要加锁
    3. 所有数据抓取完成关闭文件
    import requests
from threading import Thread
from queue import Queue
import time
from lxml import etree
import csv
from threading import Lock
from fake_useragent import UserAgent


class XiaomiSpider(object):
    def __init__(self):
        self.url = 'http://app.mi.com/categotyAllListApi?page={}&categoryId={}&pageSize=30'
        self.q = Queue()  # 存放所有URL地址的队列
        self.i = 0
        self.id_list = []  # 存放所有类型id的空列表
        # 打开文件
        self.f = open('xiaomi.csv', 'a', newline="")
        self.writer = csv.writer(self.f)
        self.lock = Lock()  # 创建锁
        self.ua = UserAgent()

    def get_cateid(self):
        # 请求
        url = 'http://app.mi.com/'
        headers = {'User-Agent': self.ua.random}
        html = requests.get(url=url, headers=headers).text
        # 解析
        parse_html = etree.HTML(html)
        li_list = parse_html.xpath('//ul[@class="category-list"]/li')
        for li in li_list:
            typ_name = li.xpath('./a/text()')[0]
            typ_id = li.xpath('./a/@href')[0].split('/')[-1]
            pages = self.get_pages(typ_id)  # 计算每个类型的页数
            self.id_list.append((typ_id, pages))

        self.url_in()  # 入队列

    # 获取counts的值并计算页数
    def get_pages(self, typ_id):
        # 每页返回的json数据中,都有count这个key
        url = self.url.format(0, typ_id)
        html = requests.get(url=url, headers={'User-Agent': self.ua.random}).json()
        count = html['count']       # 类别中的数据总数
        pages = int(count) // 30 + 1        # 每页30个，看有多少页

        return pages

    # url入队列
    def url_in(self):
        for id in self.id_list:
            # id为元组,(typ_id, pages)-->('2',pages)
            for page in range(2):
                url = self.url.format(page, id[0])
                print(url)
                # 把URL地址入队列
                self.q.put(url)

    # 线程事件函数: get() - 请求 - 解析 - 处理数据
    def get_data(self):
        while True:
            # 当队列不为空时,获取url地址
            if not self.q.empty():
                url = self.q.get()
                headers = {'User-Agent': self.ua.random}
                html = requests.get(url=url, headers=headers).json()
                self.parse_html(html)
            else:
                break

    # 解析函数
    def parse_html(self, html):
        # 存放1页的数据 - 写入到csv文件
        app_list = []
        for app in html['data']:
            # 应用名称 + 链接 + 分类
            name = app['displayName']
            link = 'http://app.mi.com/details?id=' + app['packageName']
            typ_name = app['level1CategoryName']
            # 把每一条数据放到app_list中,目的为了 writerows()
            app_list.append([name, typ_name, link])
            print(name, typ_name)
            self.i += 1

        # 开始写入1页数据 - app_list
        self.lock.acquire()
        self.writer.writerows(app_list)
        self.lock.release()

    # 主函数
    def main(self):
        self.get_cateid()       # URL入队列
        t_list = []
        # 创建多个线程
        for i in range(1):
            t = Thread(target=self.get_data)
            t_list.append(t)
            t.start()

        # 统一回收线程
        for t in t_list:
            t.join()

        # 关闭文件
        self.f.close()
        print('数量:', self.i)


if __name__ == '__main__':
    start = time.time()
    spider = XiaomiSpider()
    spider.main()
    end = time.time()
    print('执行时间:%.2f' % (end - start))

    腾讯招聘数据抓取(Ajax)

    确定URL地址及目标

    要求与分析

    1. 通过查看网页源码，得知所需数据均为 Ajax 动态加载
    2. 通过F12抓取网络数据包，进行分析
    3. 一级页面抓取数据: 职位名称
    4. 二级页面抓取数据: 工作职责、岗位要求

    一级页面json地址(pageIndex在变,timestamp未检查)

    https://careers.tencent.com/tencentcareer/api/post/Query?timestamp=1563912271089&countryId=&cityId=&bgIds=&productId=&categoryId=&parentCategoryId=&attrId=&keyword=&pageIndex={}&pageSize=10&language=zh-cn&area=cn

    二级页面地址(postId在变,在一级页面中可拿到)

    https://careers.tencent.com/tencentcareer/api/post/ByPostId?timestamp=1563912374645&postId={}&language=zh-cn

    useragents.py文件

    ua_list = [
  'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/535.1 (KHTML, like Gecko) Chrome/14.0.835.163 Safari/535.1',
  'Mozilla/5.0 (Windows NT 6.1; WOW64; rv:6.0) Gecko/20100101 Firefox/6.0',
  'Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 6.1; WOW64; Trident/4.0; SLCC2; .NET CLR 2.0.50727; .NET CLR 3.5.30729; .NET CLR 3.0.30729; Media Center PC 6.0; .NET4.0C; InfoPath.3)',
]

    我们先来回忆一下原来的腾讯招聘爬虫代码

    import time
import json
import random
import requests
from useragents import ua_list


class TencentSpider(object):
    def __init__(self):
        self.one_url = 'https://careers.tencent.com/tencentcareer/api/post/Query?timestamp=1563912271089&countryId=&cityId=&bgIds=&productId=&categoryId=&parentCategoryId=&attrId=&keyword=&pageIndex={}&pageSize=10&language=zh-cn&area=cn'
        self.two_url = 'https://careers.tencent.com/tencentcareer/api/post/ByPostId?timestamp=1563912374645&postId={}&language=zh-cn'
        self.f = open('tencent.json', 'a')  # 打开文件
        self.item_list = []  # 存放抓取的item字典数据

    # 获取响应内容函数
    def get_page(self, url):
        headers = {'User-Agent': random.choice(ua_list)}
        html = requests.get(url=url, headers=headers).text
        html = json.loads(html)  # json格式字符串转为Python数据类型

        return html

    # 主线函数: 获取所有数据
    def parse_page(self, one_url):
        html = self.get_page(one_url)
        item = {}
        for job in html['Data']['Posts']:
            item['name'] = job['RecruitPostName']  # 名称
            post_id = job['PostId']  # postId，拿postid为了拼接二级页面地址
            # 拼接二级地址,获取职责和要求
            two_url = self.two_url.format(post_id)
            item['duty'], item['require'] = self.parse_two_page(two_url)
            print(item)
            self.item_list.append(item)  # 添加到大列表中

    # 解析二级页面函数
    def parse_two_page(self, two_url):
        html = self.get_page(two_url)
        duty = html['Data']['Responsibility']  # 工作责任
        duty = duty.replace('
', '').replace('
', '')  # 去掉换行
        require = html['Data']['Requirement']  # 工作要求
        require = require.replace('
', '').replace('
', '')  # 去掉换行

        return duty, require

    # 获取总页数
    def get_numbers(self):
        url = self.one_url.format(1)
        html = self.get_page(url)
        numbers = int(html['Data']['Count']) // 10 + 1  # 每页有10个推荐

        return numbers

    def main(self):
        number = self.get_numbers()
        for page in range(1, 3):
            one_url = self.one_url.format(page)
            self.parse_page(one_url)

        # 保存到本地json文件:json.dump
        json.dump(self.item_list, self.f, ensure_ascii=False)
        self.f.close()


if __name__ == '__main__':
    start = time.time()
    spider = TencentSpider()
    spider.main()
    end = time.time()
    print('执行时间:%.2f' % (end - start))

    多线程实现

    多线程即把所有一级页面链接提交到队列,进行多线程数据抓取

    代码实现

    import requests
import json
import time
import random
from useragents import ua_list
from threading import Thread
from queue import Queue


class TencentSpider(object):
    def __init__(self):
        self.one_url = 'https://careers.tencent.com/tencentcareer/api/post/Query?timestamp=1563912271089&countryId=&cityId=&bgIds=&productId=&categoryId=&parentCategoryId=&attrId=&keyword=&pageIndex={}&pageSize=10&language=zh-cn&area=cn'
        self.two_url = 'https://careers.tencent.com/tencentcareer/api/post/ByPostId?timestamp=1563912374645&postId={}&language=zh-cn'
        self.q = Queue()
        self.i = 0  # 计数

    # 获取响应内容函数
    def get_page(self, url):
        headers = {'User-Agent': random.choice(ua_list)}
        html = requests.get(url=url, headers=headers).text
        # json.loads()把json格式的字符串转为python数据类型
        html = json.loads(html)

        return html

    # 主线函数: 获取所有数据
    def parse_page(self):
        while True:
            if not self.q.empty():
                one_url = self.q.get()
                html = self.get_page(one_url)
                item = {}
                for job in html['Data']['Posts']:
                    item['name'] = job['RecruitPostName']  # 名称
                    post_id = job['PostId']  # 拿postid为了拼接二级页面地址
                    # 拼接二级地址,获取职责和要求
                    two_url = self.two_url.format(post_id)
                    item['duty'], item['require'] = self.parse_two_page(two_url)
                    print(item)
                # 每爬取按完成1页随机休眠
                time.sleep(random.uniform(0, 1))
            else:
                break

    # 解析二级页面函数
    def parse_two_page(self, two_url):
        html = self.get_page(two_url)
        # 用replace处理一下特殊字符
        duty = html['Data']['Responsibility']
        duty = duty.replace('
', '').replace('
', '')
        # 处理要求
        require = html['Data']['Requirement']
        require = require.replace('
', '').replace('
', '')

        return duty, require

    # 获取总页数
    def get_numbers(self):
        url = self.one_url.format(1)
        html = self.get_page(url)
        numbers = int(html['Data']['Count']) // 10 + 1

        return numbers

    def main(self):
        # one_url入队列
        number = self.get_numbers()
        for page in range(1, number + 1):
            one_url = self.one_url.format(page)
            self.q.put(one_url)

        t_list = []
        for i in range(5):
            t = Thread(target=self.parse_page)
            t_list.append(t)
            t.start()

        for t in t_list:
            t.join()

        print('数量:', self.i)


if __name__ == '__main__':
    start = time.time()
    spider = TencentSpider()
    spider.main()
    end = time.time()
    print('执行时间:%.2f' % (end - start))

    多进程实现

    import requests
import json
import time
import random
from useragents import ua_list
from multiprocessing import Process
from queue import Queue


class TencentSpider(object):
    def __init__(self):
        self.one_url = 'https://careers.tencent.com/tencentcareer/api/post/Query?timestamp=1563912271089&countryId=&cityId=&bgIds=&productId=&categoryId=&parentCategoryId=&attrId=&keyword=&pageIndex={}&pageSize=10&language=zh-cn&area=cn'
        self.two_url = 'https://careers.tencent.com/tencentcareer/api/post/ByPostId?timestamp=1563912374645&postId={}&language=zh-cn'
        self.q = Queue()

    # 获取响应内容函数
    def get_page(self, url):
        headers = {'User-Agent': random.choice(ua_list)}
        html = requests.get(url=url, headers=headers).text
        # json格式字符串 -> Python
        html = json.loads(html)

        return html

    # 主线函数: 获取所有数据
    def parse_page(self):
        while True:
            if not self.q.empty():
                one_url = self.q.get()
                html = self.get_page(one_url)
                item = {}
                for job in html['Data']['Posts']:
                    # 名称
                    item['name'] = job['RecruitPostName']
                    # postId
                    post_id = job['PostId']
                    # 拼接二级地址,获取职责和要求
                    two_url = self.two_url.format(post_id)
                    item['duty'], item['require'] = self.parse_two_page(two_url)

                    print(item)
            else:
                break

    # 解析二级页面函数
    def parse_two_page(self, two_url):
        html = self.get_page(two_url)
        # 用replace处理一下特殊字符
        duty = html['Data']['Responsibility']
        duty = duty.replace('
', '').replace('
', '')
        # 处理要求
        require = html['Data']['Requirement']
        require = require.replace('
', '').replace('
', '')

        return duty, require

    # 获取总页数
    def get_numbers(self):
        url = self.one_url.format(1)
        html = self.get_page(url)
        numbers = int(html['Data']['Count']) // 10 + 1

        return numbers

    def main(self):
        # url入队列
        number = self.get_numbers()
        for page in range(1, number + 1):
            one_url = self.one_url.format(page)
            self.q.put(one_url)

        t_list = []
        for i in range(4):
            t = Process(target=self.parse_page)
            t_list.append(t)
            t.start()

        for t in t_list:
            t.join()


if __name__ == '__main__':
    start = time.time()
    spider = TencentSpider()
    spider.main()
    end = time.time()
    print('执行时间:%.2f' % (end - start))
     
  • 相关阅读:
    [NLP] 语义网络与知识图谱入门（二）
    [NLP] 语义网络与知识图谱入门（一）
    [论文理解] LFFD: A Light and Fast Face Detector for Edge Devices
    [学习笔记] 匈牙利匹配
    [NLP] nlp-lstm-cos -> sin
    [ros] ros入门记录
    [推荐系统] 两种协同过滤
    [NN] Guided Backpropgation 可视化
    [torch] pytorch hook学习
    python高级编程和算法
  • 原文地址：https://www.cnblogs.com/gaodenghan/p/14186105.html
Copyright © 2011-2022 走看看