百度招聘都是通过ajax返回的数据，用scrapy爬就很尴尬了。
建模，items文件：
1 # -*- coding: utf-8 -*- 2 3 # Define here the models for your scraped items 4 # 5 # See documentation in: 6 # http://doc.scrapy.org/en/latest/topics/items.html 7 8 import scrapy 9 10 11 class BaiduItem(scrapy.Item): 12 # 职位名称 13 job_name = scrapy.Field() 14 # 职位类别 15 job_type = scrapy.Field() 16 # 工作地点 17 address = scrapy.Field() 18 # 招聘人数 19 number = scrapy.Field() 20 # 更新时间 21 pub_time = scrapy.Field() 22 # 详情页面 ref="#/jobDetail/2/1345536716" 23 detail_link = scrapy.Field() 24 # 工作职责 25 duty = scrapy.Field() 26 # 职责要求 27 require = scrapy.Field() 28 pass
settings.py文件如下，设定了MONGO_HOST，下载器中间件。
1 # -*- coding: utf-8 -*- 2 3 # Scrapy settings for BaiDu project 4 # 5 # For simplicity, this file contains only settings considered important or 6 # commonly used. You can find more settings consulting the documentation: 7 # 8 # http://doc.scrapy.org/en/latest/topics/settings.html 9 # http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html 10 # http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html 11 12 BOT_NAME = 'BaiDu' 13 14 SPIDER_MODULES = ['BaiDu.spiders'] 15 NEWSPIDER_MODULE = 'BaiDu.spiders' 16 17 MONGO_HOST = "127.0.0.1" 18 MONGO_PORT = 27017 19 MONGO_DBNAME = "baidu" 20 MONGO_COLNAME = "zhaopin" 21 22 # Crawl responsibly by identifying yourself (and your website) on the user-agent 23 #USER_AGENT = 'BaiDu (+http://www.yourdomain.com)' 24 25 # Obey robots.txt rules 26 ROBOTSTXT_OBEY = True 27 28 # Configure maximum concurrent requests performed by Scrapy (default: 16) 29 #CONCURRENT_REQUESTS = 32 30 31 # Configure a delay for requests for the same website (default: 0) 32 # See http://scrapy.readthedocs.org/en/latest/topics/settings.html#download-delay 33 # See also autothrottle settings and docs 34 #DOWNLOAD_DELAY = 3 35 # The download delay setting will honor only one of: 36 #CONCURRENT_REQUESTS_PER_DOMAIN = 16 37 #CONCURRENT_REQUESTS_PER_IP = 16 38 39 # Disable cookies (enabled by default) 40 #COOKIES_ENABLED = False 41 42 # Disable Telnet Console (enabled by default) 43 #TELNETCONSOLE_ENABLED = False 44 45 # Override the default request headers: 46 #DEFAULT_REQUEST_HEADERS = { 47 # 'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8', 48 # 'Accept-Language': 'en', 49 #} 50 51 # Enable or disable spider middlewares 52 # See http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html 53 #SPIDER_MIDDLEWARES = { 54 # 'BaiDu.middlewares.BaiduSpiderMiddleware': 543, 55 #} 56 57 # Enable or disable downloader middlewares 58 # See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html 59 #DOWNLOADER_MIDDLEWARES = { 60 # 'BaiDu.middlewares.MyCustomDownloaderMiddleware': 543, 61 #} 62 63 # Enable or disable extensions 64 # See http://scrapy.readthedocs.org/en/latest/topics/extensions.html 65 #EXTENSIONS = { 66 # 'scrapy.extensions.telnet.TelnetConsole': None, 67 #} 68 69 # Configure item pipelines 70 # See http://scrapy.readthedocs.org/en/latest/topics/item-pipeline.html 71 ITEM_PIPELINES = { 72 'BaiDu.pipelines.BaiduPipeline': 300, 73 'BaiDu.pipelines.MongPipeline': 301, 74 } 75 76 # Enable and configure the AutoThrottle extension (disabled by default) 77 # See http://doc.scrapy.org/en/latest/topics/autothrottle.html 78 #AUTOTHROTTLE_ENABLED = True 79 # The initial download delay 80 #AUTOTHROTTLE_START_DELAY = 5 81 # The maximum download delay to be set in case of high latencies 82 #AUTOTHROTTLE_MAX_DELAY = 60 83 # The average number of requests Scrapy should be sending in parallel to 84 # each remote server 85 #AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0 86 # Enable showing throttling stats for every response received: 87 #AUTOTHROTTLE_DEBUG = False 88 89 # Enable and configure HTTP caching (disabled by default) 90 # See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings 91 #HTTPCACHE_ENABLED = True 92 #HTTPCACHE_EXPIRATION_SECS = 0 93 #HTTPCACHE_DIR = 'httpcache' 94 #HTTPCACHE_IGNORE_HTTP_CODES = [] 95 #HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'
主要的代码来了spider（baidu.py）文件如下，找到了百度的ajax请求获取数据。
1 # -*- coding: utf-8 -*- 2 import scrapy 3 import requests 4 import json 5 from BaiDu.items import BaiduItem 6 7 8 class BaiduSpider(scrapy.Spider): 9 name = 'baidu' 10 allowed_domains = ['baidu.com'] 11 # start_urls = ['http://talent.baidu.com/external/baidu/index.html#/social/2'] 12 # 百度是ajax，传入ajax的url 13 start_urls = [ 14 'http://talent.baidu.com/baidu/web/httpservice/getPostList?workPlace=0%2F4%2F7%2F9&recruitType=2&pageSize=10&curPage=1'] 15 16 def start_requests(self): 17 i = 1 18 while True: 19 url = 'http://talent.baidu.com/baidu/web/httpservice/getPostList?workPlace=0%2F4%2F7%2F9&recruitType=2&pageSize=10&curPage={}'.format( 20 i) 21 i = i + 1 22 try: 23 # 到最后一页应该会报错吧 24 yield scrapy.FormRequest(url) 25 except Exception as e: 26 print(e) 27 break 28 29 def parse(self, response): 30 # with open('baidu.html', 'wb') as f: # debug 31 # f.write(response.body) 32 host = 'http://talent.baidu.com/external/baidu/index.html#/jobDetail/2/' 33 item = BaiduItem() 34 json_datas = json.loads(response.body)['postList'] # 每次返回一页的十条数据 35 for json_data in json_datas: 36 item['job_name'] = json_data['name'] 37 item['job_type'] = json_data['postType'] 38 item['address'] = json_data['workPlace'] 39 item['number'] = json_data['recruitNum'] 40 item['pub_time'] = json_data['publishDate'] 41 item['detail_link'] = host + str(json_data['postId']) 42 item['duty'] = json_data['workContent'] 43 item['require'] = json_data['serviceCondition'] 44 # todo 字符串需要处理 45 # print('------------------',item) 46 yield item
pipelines.py文件，把数据保存成json格式，插入到mongo数据库。
1 # -*- coding: utf-8 -*- 2 3 # Define your item pipelines here 4 # 5 # Don't forget to add your pipeline to the ITEM_PIPELINES setting 6 # See: http://doc.scrapy.org/en/latest/topics/item-pipeline.html 7 import json 8 from scrapy.conf import settings 9 from pymongo import MongoClient 10 11 12 class BaiduPipeline(object): 13 """保存json格式""" 14 15 def __init__(self): 16 self.file = open('baidu.json', 'wb') 17 18 def process_item(self, item, spider): 19 str_data = json.dumps(dict(item), ensure_ascii=False) + ', ' 20 self.file.write(str_data.encode()) 21 return item 22 23 def close_spider(self): 24 self.file.close() 25 26 27 class MongPipeline(object): 28 """将数据插入到本地mongo数据库中，框架爬虫很快，插入数据稍慢""" 29 30 def __init__(self): 31 host = settings['MONGO_HOST'] 32 port = settings['MONGO_PORT'] 33 dbname = settings['MONGO_DBNAME'] 34 colname = settings['MONGO_COLNAME'] 35 36 # 链接数据库 37 self.client = MongoClient(host, port) 38 # 选择数据库 39 self.db = self.client[dbname] 40 # 选择集合 41 self.col = self.db[colname] 42 43 def process_item(self, item, spider): 44 dict_data = dict(item) 45 self.col.insert(dict_data) 46 return item 47 48 def close_spider(self, spider): 49 self.client.close()