用scrapy-redis爬去新浪-以及把数据存储到mysql\mongo

import scrapy

class SinaItem(scrapy.Item):
    #大标题
    parent_title = scrapy.Field()
    #大标题对应的链接
    parent_url = scrapy.Field()
    #小标题
    sub_title = scrapy.Field()
    #小标题的链接
    sub_url = scrapy.Field()
    #大标题和小标题对应的目录
    sub_file_name = scrapy.Field()
    #新闻相关内容
    son_url = scrapy.Field()
    #帖子标题
    head = scrapy.Field()
    #帖子的内容
    content = scrapy.Field()
    #帖子最后存储的位置
    son_path = scrapy.Field()

    spider = scrapy.Field()
    url = scrapy.Field()
    crawled = scrapy.Field()

import scrapy,os
from scrapy_redis.spiders import RedisSpider
from Sina.items import SinaItem

class SinaInfoSpider(RedisSpider):
    name = 'sinainfospider_redis'
    allowed_domains = ['sina.com.cn']
    # 添加起始路径的时候：lpush  myspider:start_urls 起始路径
    redis_key = 'sinainfospider:start_urls'
    # start_urls = ['http://news.sina.com.cn/guide/']
    def parse_detail(self,response):
        """解析帖子的数据"""
        item = response.meta["item"]
        #帖子链接
        item["son_url"] = response.url
        print("response.url===",response.url)
        heads = response.xpath('//h1[@class="main-title"]/text()|//div[@class="blkContainerSblk"]/h1[@id="artibodyTitle"]/text()').extract()

        head = "".join(heads)
        #把节点转换成unicode编码
        contents = response.xpath('//div[@class="article"]/p/text()|//div[@id="artibody"]/p/text()').extract()
        content = "".join(contents)
        item["content"] = content
        item["head"] = head
        # print("item=====",item)
        yield item

    #解析第二层的方法
    def parse_second(self,response):
        #得到帖子的链接
        # print("parse_second--response.url====", response.url)
        son_urls = response.xpath('//a/@href').extract()
        item = response.meta["item"]
        parent_url = item["parent_url"]
        # print("item====",item)
        for url in son_urls:
            #判断当前的页面的链接是否属于对应的类别
           if url.startswith(parent_url) and url.endswith(".shtml"):
               #请求
               yield scrapy.Request(url, callback=self.parse_detail, meta={"item": item})

    def parse(self, response):
        # print("response.url====",response.url)
        #所以的大标题
        parent_titles = response.xpath('//h3[@class="tit02"]/a/text()').extract()
        # 大标题对应的所以的链接
        parent_urls = response.xpath('//h3[@class="tit02"]/a/@href').extract()
        #所有小标题
        sub_titles = response.xpath('//ul[@class="list01"]/li/a/text()').extract()
        #所以小标题对应的链接
        sub_urls = response.xpath('//ul[@class="list01"]/li/a/@href').extract()

        items = []
        for i in range(len(parent_titles)):
            #http://news.sina.com.cn/ 新闻
            parent_url = parent_urls[i]
            parent_title = parent_titles[i]
            for j in range(len(sub_urls)):
                #http://news.sina.com.cn/world/  国际
                sub_url = sub_urls[j]
                sub_title = sub_titles[j]
                #判断url前缀是否相同，相同就是属于，否则不属于
                if sub_url.startswith(parent_url):
                    #装数据
                    #创建目录
                    sub_file_name = "./Data/"+parent_title+"/"+sub_title
                    if  not os.path.exists(sub_file_name):
                        #不存在就创建
                        os.makedirs(sub_file_name)
                    item["parent_url"] = parent_url
                    item["parent_title"] = parent_title
                    item["sub_url"] = sub_url
                    item["sub_title"] = sub_title
                    item["sub_file_name"] = sub_file_name
                    items.append(item)
        #把列表的数据取出
        for  item in items:
            sub_url = item["sub_url"]
            #meta={"item":item} 传递item引用SinaItem对象
            yield scrapy.Request(sub_url,callback=self.parse_second,meta={"item":item})

from datetime import datetime
import json


class ExamplePipeline(object):
    def process_item(self, item, spider):
        # 当前爬取的时间
        item["crawled"] = datetime.utcnow()
        # 爬虫的名称
        item["spider"] = spider.name + "_唠叨"
        return item


class SinaPipeline(object):
    def open_spider(self, spider):
        self.file = open(spider.name + ".json", "w", encoding="utf-8")

    def close_spider(self, spider):
        self.file.close()

    def process_item(self, item, spider):
        print("item====", item)
        sub_file_name = item["sub_file_name"]
        print("sub_file_name==", sub_file_name)
        content = item["content"]
        if len(content) > 0:
            file_name = item["son_url"]
            # 切片，从右边查找，替换
            file_name = file_name[7:file_name.rfind(".")].replace("/", "_")
            # './Data/新闻/国内',
            # './Data/新闻/国内/lslsllll.txt',
            file_path = sub_file_name + "/" + file_name + ".txt"
            with open(file_path, "w", encoding="utf-8") as f:
                f.write(content)
            item["son_path"] = file_path
        return item

BOT_NAME = 'Sina'
SPIDER_MODULES = ['Sina.spiders']
NEWSPIDER_MODULE = 'Sina.spiders'
#模拟浏览器身份
USER_AGENT = 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/67.0.3396.99 Safari/537.36'
#使用scrapy_redis自己的去重处理器
DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter"
#使用scrapy_redis自己调度器
SCHEDULER = "scrapy_redis.scheduler.Scheduler"
#爬虫可以暂停/开始， 从爬过的位置接着爬取
SCHEDULER_PERSIST = True
#不设置的话，默认使用的是SpiderPriorityQueue
#优先级队列
SCHEDULER_QUEUE_CLASS = "scrapy_redis.queue.SpiderPriorityQueue"
#普通队列
#SCHEDULER_QUEUE_CLASS = "scrapy_redis.queue.SpiderQueue"
#栈
#SCHEDULER_QUEUE_CLASS = "scrapy_redis.queue.SpiderStack"
# Obey robots.txt rules
ROBOTSTXT_OBEY = False
DOWNLOAD_DELAY = 1
ITEM_PIPELINES = {
   # scrapy默认配置
   'Sina.pipelines.ExamplePipeline': 300,
   'Sina.pipelines.SinaPipeline': 301,
   # 把数据默认添加到redis数据库中
   'scrapy_redis.pipelines.RedisPipeline': 400,
}
# 日志基本
LOG_LEVEL = 'DEBUG'
#配置redis数据库信息
#redis数据库主机---
REDIS_HOST = "127.0.0.1"
#redis端口
REDIS_PORT = 6379
#下载延迟1秒
# DOWNLOAD_DELAY = 1

from scrapy import cmdline
cmdline.execute("scrapy runspider sina_info.py".split())

import json, redis, pymongo

def main():
    # 指定Redis数据库信息
    rediscli = redis.StrictRedis(host='127.0.0.1', port=6379, db=0)
    # 指定MongoDB数据库信息
    mongocli = pymongo.MongoClient(host='localhost', port=27017)
    # 创建数据库名
    db = mongocli['sina']
    # 创建表名
    sheet = db['sina_items']
    offset = 0
    while True:
        # FIFO模式为 blpop，LIFO模式为 brpop，获取键值
        source, data = rediscli.blpop(["sinainfospider_redis:items"])
        item = json.loads(data.decode("utf-8"))
        sheet.insert(item)
        offset += 1
        print(offset)
        try:
            print("Processing: %s " % item)
        except KeyError:
            print("Error procesing: %s" % item)

if __name__ == '__main__':
    main()

import redis, json, time
from pymysql import connect

# redis数据库链接
redis_client = redis.StrictRedis(host="127.0.0.1", port=6379, db=0)
# mysql数据库链接
# mysql_client = connect(host="127.0.0.1", user="root", password="mysql", database="sina", port=3306, charset="uft8")
mysql_client = connect(host="127.0.0.1", user="root", password="mysql",
                 database="sina", port=3306, charset='utf8')
cursor = mysql_client.cursor()

i = 1
while True:
    print(i)
    time.sleep(1)
    source, data = redis_client.blpop(["sinainfospider_redis:items"])
    item = json.loads(data.decode())
    print("source===========", source)
    print("item===========", item)
    sql = "insert into sina_items(parent_url,parent_title,sub_title,sub_url,sub_file_name,son_url,head,content,crawled,spider) values(%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)"
    params = [item["parent_url"], item["parent_title"], item["sub_title"], item["sub_url"], item["sub_file_name"],
              item["son_url"], item["head"], item["content"], item["crawled"], item["spider"], ]
    cursor.execute(sql, params)
    mysql_client.commit()
    i += 1