CrawlSpider_获取图片名称地址，及入库

1.继承自scrapy.Spider

2.独门秘笈

　　CrawlSpider可以定义规则，再解析html内容的时候，可以根据链接规则提取出指定的链接，然后再向这些链接发送请求

　　所以，如果有需要跟进链接的需求，意思就是爬取了网页之后，需要提取链接再次爬取，使用CrawlSpider是非常合适的

3.提取链接

　　链接提取器，在这里就可以写规则提取指定链接

scrapy.linkextractors.LinkExtractor(

　　allow = (), 　　　　　　# 正则表达式 提取符合正则的链接

　　deny = (), 　　　　　　# (不用)正则表达式 不提取符合正则的链接

　　allow_domains = (), 　　# （不用）允许的域名

　　deny_domains = (), 　　# （不用）不允许的域名

　　restrict_xpaths = (), 　　# xpath，提取符合xpath规则的链接

　　restrict_css = () 　　　　# 提取符合选择器规则的链接

)

4.模拟使用

　　正则用法：　links1 = LinkExtractor(allow=r'list_23_\d+\.html')

　　xpath用法： links2 = LinkExtractor(restrict_xpaths=r'//div[@class="x"]')

　　css用法：    links3 = LinkExtractor(restrict_css='.x')

5.提取连接

　　link.extract_links(response)

对当前网页链接提取

导入链接提取器

使用正则语法，比较多

\b 　表数字

\b+ 　一到多个数字

\.  　转义点号

查看提取的链接

使用xpath语法

查看提取的链接

6.注意事项

　　【注1】callback只能写函数名字符串, callback='parse_item'

　　【注2】在基本的spider中，如果重新发送请求，那里的callback写的是 callback=self.parse_item 【注‐‐稍后看】follow=true 是否跟进 就是按照提取连接规则进行提取

运行原理：

读书网数据入库 

　　1.创建项目：scrapy startproject dushuproject

　　2.跳转到spiders路径 cd\dushuproject\dushuproject\spiders

　　3.创建爬虫类：scrapy genspider ‐t crawl read www.dushu.com

　　4.items

　　5.spiders

　　6.settings

　　7.pipelines

　　数据保存到本地

　　数据保存到mysql数据库 

---

创建项目

> scrapy startproject scrapy_redbook_101

 

cd到spiders目录下，创建爬虫文件

spiders> scrapy genspider ‐t crawl read https://www.dushu.com/book/1188.html

items定义爬取的数据结构类

name名字、src图片

items数据结构类的导包

运行

开启管道

pipelines管道功能

运行

经过计算观察，缺失第一页的数据

运行

这次，没有问题，13页的所有数据

---

入库操作

链接mysql数据库

创建spider01数据库

使用spider01数据库

创建book表

查询book表内容

查询虚拟机ip

settings配置，链接使用数据库

开启数据库插入管道

pipelines数据库插入功能实现

# Define your item pipelines here
#
# Don't forget to add your pipeline to the ITEM_PIPELINES setting
# See: https://docs.scrapy.org/en/latest/topics/item-pipeline.html
 
# useful for handling different item types with a single interface
from itemadapter import ItemAdapter
 
class ScrapyReadbook101Pipeline:
 
    def open_spider(self,spider):
        self.fp = open('book.json','w',encoding='utf-8')
 
    def process_item(self, item, spider):
        self.fp.write(str(item))
        return item
 
    def close_spider(self,spider):
        self.fp.close()
 
# 加载settings文件，数据库参数
from scrapy.utils.project import get_project_settings
# 导入pyymsql
import pymysql
 
# 创建mysql插入管道
class MysqlPipeline:

　　# 获取数据库链接参数
    def open_spider(self,spider):
        settings = get_project_settings()
        self.host = settings['DB_HOST']
        self.port =settings['DB_PORT']
        self.user =settings['DB_USER']
        self.password =settings['DB_PASSWROD']
        self.name =settings['DB_NAME']
        self.charset =settings['DB_CHARSET']
　　　　　# 链接
        self.connect()

    # 链接数据库函数实现，获取cursor对象
    def connect(self):
        self.conn = pymysql.connect(
                            host=self.host,
                            port=self.port,
                            user=self.user,
                            password=self.password,
                            db=self.name,
                            charset=self.charset
        )
　　　　　# 创建执行mysql语句对象
        self.cursor = self.conn.cursor()
 
　　# 操作数据库函数
    def process_item(self, item, spider):
　　　　　# 插入操作
        sql = 'insert into book(name,src) values("{}","{}")'.format(item['name'],item['src'])
        # 执行sql语句
        self.cursor.execute(sql)
        # 提交
        self.conn.commit()
 
        return item
 
　　#关闭插入，关闭链接
    def close_spider(self,spider):
        self.cursor.close()
        self.conn.close()

运行

虚拟机中，查询表中数据

以上是13页数据的爬取

---

follow=true 跟进 按照提取连接规则进行提取

运行

虚拟机中，查询表中数据

---

项目文件夹

read.py爬虫核心文件

import scrapy
from scrapy.linkextractors import LinkExtractor
from scrapy.spiders import CrawlSpider, Rule
 
from scrapy_readbook_101.items import ScrapyReadbook101Item
 
class ReadSpider(CrawlSpider):
    name = 'read'
    allowed_domains = ['www.dushu.com']
    start_urls = ['https://www.dushu.com/book/1188_1.html']
 
    rules = (
        Rule(LinkExtractor(allow=r'/book/1188_\d+.html'),
                           callback='parse_item',
                           follow=True),
    )
 
    def parse_item(self, response):
 
        img_list = response.xpath('//div[@class="bookslist"]//img')
 
        for img in img_list:
            name = img.xpath('./@data-original').extract_first()
            src = img.xpath('./@alt').extract_first()
 
            book = ScrapyReadbook101Item(name=name,src=src)
            yield book

items.py自定义数据结构类

# Define here the models for your scraped items
#
# See documentation in:
# https://docs.scrapy.org/en/latest/topics/items.html
 
import scrapy
 
class ScrapyReadbook101Item(scrapy.Item):
    # define the fields for your item here like:
    # name = scrapy.Field()
    name = scrapy.Field()
    src = scrapy.Field()

settings.py参数配置文件

# Scrapy settings for scrapy_readbook_101 project
#
# For simplicity, this file contains only settings considered important or
# commonly used. You can find more settings consulting the documentation:
#
#     https://docs.scrapy.org/en/latest/topics/settings.html
#     https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
#     https://docs.scrapy.org/en/latest/topics/spider-middleware.html
 
BOT_NAME = 'scrapy_readbook_101'
 
SPIDER_MODULES = ['scrapy_readbook_101.spiders']
NEWSPIDER_MODULE = 'scrapy_readbook_101.spiders'
 
# Crawl responsibly by identifying yourself (and your website) on the user-agent
#USER_AGENT = 'scrapy_readbook_101 (+http://www.yourdomain.com)'
 
# Obey robots.txt rules
ROBOTSTXT_OBEY = True
 
# Configure maximum concurrent requests performed by Scrapy (default: 16)
#CONCURRENT_REQUESTS = 32
 
# Configure a delay for requests for the same website (default: 0)
# See https://docs.scrapy.org/en/latest/topics/settings.html#download-delay
# See also autothrottle settings and docs
#DOWNLOAD_DELAY = 3
# The download delay setting will honor only one of:
#CONCURRENT_REQUESTS_PER_DOMAIN = 16
#CONCURRENT_REQUESTS_PER_IP = 16
 
# Disable cookies (enabled by default)
#COOKIES_ENABLED = False
 
# Disable Telnet Console (enabled by default)
#TELNETCONSOLE_ENABLED = False
 
# Override the default request headers:
#DEFAULT_REQUEST_HEADERS = {
#   'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
#   'Accept-Language': 'en',
#}
 
# Enable or disable spider middlewares
# See https://docs.scrapy.org/en/latest/topics/spider-middleware.html
#SPIDER_MIDDLEWARES = {
#    'scrapy_readbook_101.middlewares.ScrapyReadbook101SpiderMiddleware': 543,
#}
 
# Enable or disable downloader middlewares
# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
#DOWNLOADER_MIDDLEWARES = {
#    'scrapy_readbook_101.middlewares.ScrapyReadbook101DownloaderMiddleware': 543,
#}
 
# Enable or disable extensions
# See https://docs.scrapy.org/en/latest/topics/extensions.html
#EXTENSIONS = {
#    'scrapy.extensions.telnet.TelnetConsole': None,
#}
 
# 参数中一个端口号 一个是字符集 都要注意
DB_HOST = '192.168.231.130'
# 端口号是一个整数
DB_PORT = 3306
DB_USER = 'root'
DB_PASSWROD = '1234'
DB_NAME = 'spider01'
# utf-8的杠不允许写
DB_CHARSET = 'utf8'
 
# Configure item pipelines
# See https://docs.scrapy.org/en/latest/topics/item-pipeline.html
ITEM_PIPELINES = {
   'scrapy_readbook_101.pipelines.ScrapyReadbook101Pipeline': 300,
   # MysqlPipeline
   'scrapy_readbook_101.pipelines.MysqlPipeline':301
}
 
# Enable and configure the AutoThrottle extension (disabled by default)
# See https://docs.scrapy.org/en/latest/topics/autothrottle.html
#AUTOTHROTTLE_ENABLED = True
# The initial download delay
#AUTOTHROTTLE_START_DELAY = 5
# The maximum download delay to be set in case of high latencies
#AUTOTHROTTLE_MAX_DELAY = 60
# The average number of requests Scrapy should be sending in parallel to
# each remote server
#AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0
# Enable showing throttling stats for every response received:
#AUTOTHROTTLE_DEBUG = False
 
# Enable and configure HTTP caching (disabled by default)
# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings
#HTTPCACHE_ENABLED = True
#HTTPCACHE_EXPIRATION_SECS = 0
#HTTPCACHE_DIR = 'httpcache'
#HTTPCACHE_IGNORE_HTTP_CODES = []
#HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'

pipelines.py功能核心功能

# Define your item pipelines here
#
# Don't forget to add your pipeline to the ITEM_PIPELINES setting
# See: https://docs.scrapy.org/en/latest/topics/item-pipeline.html
 
# useful for handling different item types with a single interface
from itemadapter import ItemAdapter
 
class ScrapyReadbook101Pipeline:
 
    def open_spider(self,spider):
        self.fp = open('book.json','w',encoding='utf-8')
 
    def process_item(self, item, spider):
        self.fp.write(str(item))
        return item
 
    def close_spider(self,spider):
        self.fp.close()
 
# 加载settings文件
from scrapy.utils.project import get_project_settings
import pymysql
 
class MysqlPipeline:
 
    def open_spider(self,spider):
        settings = get_project_settings()
        self.host = settings['DB_HOST']
        self.port =settings['DB_PORT']
        self.user =settings['DB_USER']
        self.password =settings['DB_PASSWROD']
        self.name =settings['DB_NAME']
        self.charset =settings['DB_CHARSET']
 
        self.connect()
 
    def connect(self):
        self.conn = pymysql.connect(
                            host=self.host,
                            port=self.port,
                            user=self.user,
                            password=self.password,
                            db=self.name,
                            charset=self.charset
        )
 
        self.cursor = self.conn.cursor()
 
    def process_item(self, item, spider):
 
        sql = 'insert into book(name,src) values("{}","{}")'.format(item['name'],item['src'])
        # 执行sql语句
        self.cursor.execute(sql)
        # 提交
        self.conn.commit()
 
        return item
 
    def close_spider(self,spider):
        self.cursor.close()
        self.conn.close()