一.Scrapy的日志等级
- 在使用scrapy crawl spiderFileName运行程序时，在终端里打印输出的就是scrapy的日志信息。
- 日志信息的种类：
ERROR ： 一般错误
WARNING : 警告
INFO : 一般的信息
DEBUG ： 调试信息
- 设置日志信息指定输出：
在settings.py配置文件中，加入
LOG_LEVEL = ‘指定日志信息种类’即可。
LOG_FILE = 'log.txt'则表示将日志信息写入到指定文件中进行存储。
二.请求传参
- 在某些情况下，我们爬取的数据不在同一个页面中，例如，我们爬取一个电影网站，电影的名称，评分在一级页面，而要爬取的其他电影详情在其二级子页面中。这时我们就需要用到请求传参。
- 案例展示：爬取www.id97.com电影网，将一级页面中的电影名称，类型，评分一级二级页面中的上映时间，导演，片长进行爬取。
爬虫文件:
import scrapy
from moviePro.items import MovieproItem class MovieSpider(scrapy.Spider):
name = 'movie'
allowed_domains = ['www.id97.com']
start_urls = ['http://www.id97.com/'] def parse(self, response):
div_list = response.xpath('//div[@class="col-xs-1-5 movie-item"]') for div in div_list:
item = MovieproItem()
item['name'] = div.xpath('.//h1/a/text()').extract_first()
item['score'] = div.xpath('.//h1/em/text()').extract_first()
#xpath(string(.))表示提取当前节点下所有子节点中的数据值（.）表示当前节点
item['kind'] = div.xpath('.//div[@class="otherinfo"]').xpath('string(.)').extract_first()
item['detail_url'] = div.xpath('./div/a/@href').extract_first()
#请求二级详情页面，解析二级页面中的相应内容,通过meta参数进行Request的数据传递
yield scrapy.Request(url=item['detail_url'],callback=self.parse_detail,meta={'item':item}) def parse_detail(self,response):
#通过response获取item
item = response.meta['item']
item['actor'] = response.xpath('//div[@class="row"]//table/tr[1]/a/text()').extract_first()
item['time'] = response.xpath('//div[@class="row"]//table/tr[7]/td[2]/text()').extract_first()
item['long'] = response.xpath('//div[@class="row"]//table/tr[8]/td[2]/text()').extract_first()
#提交item到管道
yield item
items文件:
# -*- coding: utf-8 -*- # Define here the models for your scraped items
#
# See documentation in:
# https://doc.scrapy.org/en/latest/topics/items.html import scrapy class MovieproItem(scrapy.Item):
# define the fields for your item here like:
name = scrapy.Field()
score = scrapy.Field()
time = scrapy.Field()
long = scrapy.Field()
actor = scrapy.Field()
kind = scrapy.Field()
detail_url = scrapy.Field()
管道文件:
# -*- coding: utf-8 -*- # Define your item pipelines here
#
# Don't forget to add your pipeline to the ITEM_PIPELINES setting
# See: https://doc.scrapy.org/en/latest/topics/item-pipeline.html import json
class MovieproPipeline(object):
def __init__(self):
self.fp = open('data.txt','w')
def process_item(self, item, spider):
dic = dict(item)
print(dic)
json.dump(dic,self.fp,ensure_ascii=False)
return item
def close_spider(self,spider):
self.fp.close()
三. 如何提高scrapy的爬虫效率
增加并发：
默认scrapy开启的并发线程为32个，可以适当进行增加。在settings配置文件中修改CONCURRENT_REQUESTS = 100值为100,并发设置成了为100。 降低日志级别：
在运行scrapy时，会有大量日志信息的输出，为了减少CPU的使用率。可以设置log输出信息为INFO或者ERROR即可。在配置文件中编写：LOG_LEVEL = ‘INFO’ 禁止cookie：
如果不是真的需要cookie，则在scrapy爬取数据时可以进制cookie从而减少CPU的使用率，提升爬取效率。在配置文件中编写：COOKIES_ENABLED = False 禁止重试：
对失败的HTTP进行重新请求（重试）会减慢爬取速度，因此可以禁止重试。在配置文件中编写：RETRY_ENABLED = False 减少下载超时：
如果对一个非常慢的链接进行爬取，减少下载超时可以能让卡住的链接快速被放弃，从而提升效率。在配置文件中进行编写：DOWNLOAD_TIMEOUT = 10 超时时间为10s
测试案例：爬取校花网校花图片 www.521609.com
爬虫文件:
import scrapy
from xiaohua.items import XiaohuaItem class XiahuaSpider(scrapy.Spider): name = 'xiaohua'
allowed_domains = ['www.521609.com']
start_urls = ['http://www.521609.com/daxuemeinv/'] pageNum = 1
url = 'http://www.521609.com/daxuemeinv/list8%d.html' def parse(self, response):
li_list = response.xpath('//div[@class="index_img list_center"]/ul/li')
for li in li_list:
school = li.xpath('./a/img/@alt').extract_first()
img_url = li.xpath('./a/img/@src').extract_first() item = XiaohuaItem()
item['school'] = school
item['img_url'] = 'http://www.521609.com' + img_url yield item if self.pageNum < 10:
self.pageNum += 1
url = format(self.url % self.pageNum)
#print(url)
yield scrapy.Request(url=url,callback=self.parse)
items文件:
# -*- coding: utf-8 -*- # Define here the models for your scraped items
#
# See documentation in:
# https://doc.scrapy.org/en/latest/topics/items.html import scrapy class XiaohuaItem(scrapy.Item):
# define the fields for your item here like:
# name = scrapy.Field()
school=scrapy.Field()
img_url=scrapy.Field()
管道文件:
# -*- coding: utf-8 -*- # Define your item pipelines here
#
# Don't forget to add your pipeline to the ITEM_PIPELINES setting
# See: https://doc.scrapy.org/en/latest/topics/item-pipeline.html import json
import os
import urllib.request
class XiaohuaPipeline(object):
def __init__(self):
self.fp = None def open_spider(self,spider):
print('开始爬虫')
self.fp = open('./xiaohua.txt','w') def download_img(self,item):
url = item['img_url']
fileName = item['school']+'.jpg'
if not os.path.exists('./xiaohualib'):
os.mkdir('./xiaohualib')
filepath = os.path.join('./xiaohualib',fileName)
urllib.request.urlretrieve(url,filepath)
print(fileName+"下载成功") def process_item(self, item, spider):
obj = dict(item)
json_str = json.dumps(obj,ensure_ascii=False)
self.fp.write(json_str+'\n') #下载图片
self.download_img(item)
return item def close_spider(self,spider):
print('结束爬虫')
self.fp.close()
settings文件
USER_AGENT = 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_0) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/68.0.3440.106 Safari/537.36' # Obey robots.txt rules
ROBOTSTXT_OBEY = False # Configure maximum concurrent requests performed by Scrapy (default: 16)
CONCURRENT_REQUESTS = 100
COOKIES_ENABLED = False
LOG_LEVEL = 'ERROR'
RETRY_ENABLED = False
DOWNLOAD_TIMEOUT = 3
# Configure a delay for requests for the same website (default: 0)
# See https://doc.scrapy.org/en/latest/topics/settings.html#download-delay
# See also autothrottle settings and docs
# The download delay setting will honor only one of:
#CONCURRENT_REQUESTS_PER_DOMAIN = 16
#CONCURRENT_REQUESTS_PER_IP = 16
DOWNLOAD_DELAY = 3