用scrapy-redis爬去新浪-以及把数据存储到mysql\mongo

需求：爬取新浪网导航页（[u]http://news.sina.com.cn/guide/[/u]）所有下所有大类、小类、小类里的子链接，以及子链接页面的新闻内容。
准备工作：
a.安装redis(windows或者linux)
b.安装Redis Desktop Manager
c.scrapy-redis的安装以及scrapy的安装
d.安装mongo
e.安装mysql

[b][b]创建项目和相关配置[/b][/b]

创建项目命令：scrapy startproject mysina
进入mysina目录：cd mysina
创建spider爬到：scrapy genspider sina sina.com
执行运行项目脚本命令：scrapy crawl sina
1.item.py

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()

2.spiders/sina_info.py

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})

3.pipelines.py

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

4.settings.py

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

5.start.py

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

6.运行start.py,的效果图，等待指令。。。。。。



7.Redis Desktop Manager输入以下指令



此时开始爬数据的效果图：



8.数据保存到mongo数据库

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()

9.存到mysql数据库

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