创建项目 scrapy startproject yingke cd yingke
创建爬虫 scrapy genspider live
分析http://www.inke.cn/hotlive_list.html网页的response，找到响应里面数据的规律，并找到的位置，通过response.xpath()获取到
通过在pipline里面进行数据的清洗，过滤，保存
实现翻页，进行下一页的请求处理
运行爬虫 scrapy crawl live
说明：这个程序直接在parse方法里面进行图片保存，保存在本地，正常使用yield关键字进行在pipline中保存。
# -*- coding: utf-8 -*-
import scrapy
import re
class LiveSpider(scrapy.Spider):
name = 'live'
allowed_domains = ['inke.cn']
start_urls = ['http://www.inke.cn/hotlive_list.html?page=1']
def parse(self, response):
div_list = response.xpath("//div[@class='list_box']")
for div in div_list:
item = {}
img_src = div.xpath("./div[@class='list_pic']/a/img/@src").extract_first()
item["user_name"] = div.xpath(
"./div[@class='list_user_info']/span[@class='list_user_name']/text()").extract_first()
print(item["user_name"])
yield scrapy.Request( # 发送详情页的请求
img_src,
callback=self.parse_img,
meta={"item": item}
)
# 下一页
now_page = re.findall("page=(.*)", response.request.url)[0]
now_page= int(now_page)
next_url = "http://www.inke.cn/hotlive_list.html?page={}".format(str(now_page+ 1))
yield scrapy.Request(
next_url,
callback=self.parse
)
def parse_img(self, response):
user_name = response.meta["item"]["user_name"]
with open("images/{}.png".format(user_name), "wb") as f:
f.write(response.body)
运行效果：
966412-20171108235525653-109786030.png
