Python爬虫框架Scrapy实例一

目标任务:爬取腾讯社招信息,需要爬取的内容为:职位名称,职位的详情链接,职位类别,招聘人数,工作地点,发布时间。

一、创建Scrapy项目

scrapy startproject Tencent

命令执行后,会创建一个Tencent文件夹,结构如下

二、编写item文件,根据需要爬取的内容定义爬取字段

# -*- coding: utf-8 -*-

import scrapy

class TencentItem(scrapy.Item):

    # 职位名
    positionname = scrapy.Field()
    # 详情连接
    positionlink = scrapy.Field()
    # 职位类别
    positionType = scrapy.Field()
    # 招聘人数
    peopleNum = scrapy.Field()
    # 工作地点
    workLocation = scrapy.Field()
    # 发布时间
    publishTime = scrapy.Field()

三、编写spider文件

进入Tencent目录,使用命令创建一个基础爬虫类:

#  tencentPostion为爬虫名,tencent.com为爬虫作用范围
scrapy genspider tencentPostion "tencent.com"

执行命令后会在spiders文件夹中创建一个tencentPostion.py的文件,现在开始对其编写:

# -*- coding: utf-8 -*-
import scrapy
from tencent.items import TencentItem

class TencentpositionSpider(scrapy.Spider):
    """
    功能:爬取腾讯社招信息
    """
    # 爬虫名
name
= "tencentPosition"
# 爬虫作用范围
allowed_domains = ["tencent.com"] url = "http://hr.tencent.com/position.php?&start=" offset = 0 # 起始url start_urls = [url + str(offset)] def parse(self, response): for each in response.xpath("//tr[@class='even'] | //tr[@class='odd']"): # 初始化模型对象 item = TencentItem() # 职位名称 item['positionname'] = each.xpath("./td[1]/a/text()").extract()[0] # 详情连接 item['positionlink'] = each.xpath("./td[1]/a/@href").extract()[0] # 职位类别 item['positionType'] = each.xpath("./td[2]/text()").extract()[0] # 招聘人数 item['peopleNum'] = each.xpath("./td[3]/text()").extract()[0] # 工作地点 item['workLocation'] = each.xpath("./td[4]/text()").extract()[0] # 发布时间 item['publishTime'] = each.xpath("./td[5]/text()").extract()[0] yield item if self.offset < 1680: self.offset += 10 # 每次处理完一页的数据之后,重新发送下一页页面请求 # self.offset自增10,同时拼接为新的url,并调用回调函数self.parse处理Response yield scrapy.Request(self.url + str(self.offset), callback = self.parse)

四、编写pipelines文件

# -*- coding: utf-8 -*-
import json

class TencentPipeline(object):
  """
功能:保存item数据
"""
def __init__(self): self.filename = open("tencent.json", "w") def process_item(self, item, spider): text = json.dumps(dict(item), ensure_ascii = False) + ",\n" self.filename.write(text.encode("utf-8")) return item def close_spider(self, spider): self.filename.close()

五、settings文件设置(主要设置内容)

# 设置请求头部,添加url
DEFAULT_REQUEST_HEADERS = {
    "User-Agent" : "Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; Trident/5.0;",
    'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8'
}

# 设置item——pipelines
ITEM_PIPELINES = {
    'tencent.pipelines.TencentPipeline': 300,
}

执行命令,运行程序

# tencentPosition为爬虫名
scrapy crwal tencentPosition

 

 

使用CrawlSpider类改写

# 创建项目
scrapy startproject TencentSpider

# 进入项目目录下,创建爬虫文件
scrapy genspider -t crawl tencent tencent.com

item等文件写法不变,主要是爬虫文件的编写

# -*- coding:utf-8 -*-

import scrapy
# 导入CrawlSpider类和Rule
from scrapy.spiders import CrawlSpider, Rule
# 导入链接规则匹配类,用来提取符合规则的连接
from scrapy.linkextractors import LinkExtractor
from TencentSpider.items import TencentItem

class TencentSpider(CrawlSpider):
    name = "tencent"
    allow_domains = ["hr.tencent.com"]
    start_urls = ["http://hr.tencent.com/position.php?&start=0#a"]

    # Response里链接的提取规则,返回的符合匹配规则的链接匹配对象的列表
    pagelink = LinkExtractor(allow=("start=\d+"))

    rules = [
        # 获取这个列表里的链接,依次发送请求,并且继续跟进,调用指定回调函数处理
        Rule(pagelink, callback = "parseTencent", follow = True)
    ]

    # 指定的回调函数
    def parseTencent(self, response):
        for each in response.xpath("//tr[@class='even'] | //tr[@class='odd']"):
            item = TencentItem()
            # 职位名称
            item['positionname'] = each.xpath("./td[1]/a/text()").extract()[0]
            # 详情连接
            item['positionlink'] = each.xpath("./td[1]/a/@href").extract()[0]
            # 职位类别
            item['positionType'] = each.xpath("./td[2]/text()").extract()[0]
            # 招聘人数
            item['peopleNum'] =  each.xpath("./td[3]/text()").extract()[0]
            # 工作地点
            item['workLocation'] = each.xpath("./td[4]/text()").extract()[0]
            # 发布时间
            item['publishTime'] = each.xpath("./td[5]/text()").extract()[0]

            yield item