1.框架了解：高性能的异步下载、解析、持久化存储
2.下载安装，创建项目-----------
pip install wheel
Twisted 5步安装！
二.安装
Linux：
pip3 install scrapy
Windows：
a. pip3 install wheel
b. 下载twisted http://www.lfd.uci.edu/~gohlke/pythonlibs/#twisted
c. 进入下载目录，执行 pip3 install Twisted‑17.1.0‑cp35‑cp35m‑win_amd64.whl
d. pip3 install pywin32
e. pip3 install scrapy
scrapy startproject 项目名称
3.项目使用--5步听视频总结：
1.新建工程 scrapy startproject fristBlood
2.cd fristBlood 新建爬虫文件scrapy genspider chouti www.chouti.com(在spiders中会新增一个chouti.py,注意名称、start_url，注释#allowed_domains)
3.在chouti.py中进行parse方法的编写
4.配置文件的配置：在settings中进行UA伪装、ROBOTSTXT_OBEY = False
5.配置完后，在cmd中执行：scarpy crawl 爬虫文件名称
1.爬取chouti fristBlood
# -*- coding: utf-8 -*-
import scrapy
class ChoutiSpider(scrapy.Spider):
#爬虫文件的名称：可以指定某一个具体的爬虫文件
name = 'chouti'
#允许的域名：
#allowed_domains = ['www.chouti.com']
#起始url列表：工程被执行后就可以获取该列表中url所对应的页面数据
start_urls = ['https://dig.chouti.com/']
#该方法作用:就是讲起始url列表中指定url对应的页面数据进行解析操作
#response参数：就是对起始url发起请求后对应的响应对象
def parse(self, response):
print(response)
chouti.py
2.爬取糗百 ---注意parse中 qiubaiPro
#extract()可以将selector对象中存储的文本内容获取
封装一个可迭代类型
基于终端指令执行 scarpy crawl -o data.csv qiubai --nolog---不常用
# -*- coding: utf-8 -*-
import scrapy
class QiubaiSpider(scrapy.Spider):
name = 'qiubai'
#allowed_domains = ['www.fdsfds.com']
start_urls = ['https://www.qiushibaike.com/text/']
def parse(self, response):
#xpath返回的列表元素类型为Selecor类型
div_list = response.xpath('//div[@id="content-left"]/div')
#声明一个用于存储解析到数据的列表
all_data = []
for div in div_list:
#extract()可以将selector对象中存储的文本内容获取
#author = div.xpath('./div[1]/a[2]/h2/text()')[0].extract()
author = div.xpath('./div[1]/a[2]/h2/text()').extract_first() #取出第一个元素，不用[0]了--意义同上行
content = div.xpath('.//div[@class="content"]/span//text()').extract() #//text获取的内容不止一个，extract()获取多个列表内容
content = "".join(content) #将列表转化成字符串
dict = {
'author':author,
'content':content
}
all_data.append(dict)
return all_data
#持久化存储方式：
#1.基于终端指令：必须保证parse方法有一个可迭代类型对象的返回
#2.基于管道
qiubai.py
3.爬取糗百--基于管道执行--注意item pipeLinepro
pipelines.py编写
在settings中开启ITEM_PIPELINES 67-69行
ITEM_PIPELINES数值越小，优先级越高（管道中）
一个写到磁盘，一个写到数据库中
屏蔽日志信息 scarpy crawl chouti --nolog
cls清屏
import scrapy
class PipelineproItem(scrapy.Item):
# define the fields for your item here like:
# name = scrapy.Field()
author = scrapy.Field()
content = scrapy.Field()
items.py
# -*- coding: utf-8 -*-
# Scrapy settings for pipeLinePro project
#
# For simplicity, this file contains only settings considered important or
# commonly used. You can find more settings consulting the documentation:
#
# https://doc.scrapy.org/en/latest/topics/settings.html
# https://doc.scrapy.org/en/latest/topics/downloader-middleware.html
# https://doc.scrapy.org/en/latest/topics/spider-middleware.html
BOT_NAME = 'pipeLinePro'
SPIDER_MODULES = ['pipeLinePro.spiders']
NEWSPIDER_MODULE = 'pipeLinePro.spiders'
# Crawl responsibly by identifying yourself (and your website) on the user-agent
#USER_AGENT = 'pipeLinePro (+http://www.yourdomain.com)'
USER_AGENT = 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.77 Safari/537.36'
# Obey robots.txt rules
ROBOTSTXT_OBEY = False
# 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://doc.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://doc.scrapy.org/en/latest/topics/spider-middleware.html
#SPIDER_MIDDLEWARES = {
# 'pipeLinePro.middlewares.PipelineproSpiderMiddleware': 543,
#}
# Enable or disable downloader middlewares
# See https://doc.scrapy.org/en/latest/topics/downloader-middleware.html
#DOWNLOADER_MIDDLEWARES = {
# 'pipeLinePro.middlewares.PipelineproDownloaderMiddleware': 543,
#}
# Enable or disable extensions
# See https://doc.scrapy.org/en/latest/topics/extensions.html
#EXTENSIONS = {
# 'scrapy.extensions.telnet.TelnetConsole': None,
#}
# Configure item pipelines
# See https://doc.scrapy.org/en/latest/topics/item-pipeline.html
ITEM_PIPELINES = {
'pipeLinePro.pipelines.PipelineproPipeline': 300,
'pipeLinePro.pipelines.MyPipeline': 301,
}
# Enable and configure the AutoThrottle extension (disabled by default)
# See https://doc.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://doc.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'
settings.py
# -*- coding: utf-8 -*-
import scrapy
from pipeLinePro.items import PipelineproItem
class QiubaiSpider(scrapy.Spider):
name = 'qiubai'
#allowed_domains = ['www.ds.com']
start_urls = ['https://www.qiushibaike.com/text/']
def parse(self, response):
# xpath返回的列表元素类型为Selecor类型
div_list = response.xpath('//div[@id="content-left"]/div')
# 声明一个用于存储解析到数据的列表
all_data = []
for div in div_list:
# extract()可以将selector对象中存储的文本内容获取
# author = div.xpath('./div[1]/a[2]/h2/text()')[0].extract()
author = div.xpath('./div[1]/a[2]/h2/text()').extract_first()
content = div.xpath('.//div[@class="content"]/span//text()').extract()
content = "".join(content)
#实例化item对象
item = PipelineproItem()
#将解析到的数据值存储到item对象中
item['author'] = author
item['content'] = content
#将item对象提交给管道
yield item
# 持久化存储方式：
# 1.基于终端指令：必须保证parse方法有一个可迭代类型对象的返回
# 2.基于管道:
#1.items.py:对该文件中的类进行实例化操作（item对象：存储解析到的数据值）。
#2.pipeline.py:管道，作用就是接受爬虫文件提交的item对象，然后将该对象中的数据值进行持久化存储操作
qiubai.py-管道
# -*- coding: utf-8 -*-
import pymysql
class PipelineproPipeline(object):
#作用：每当爬虫文件向管道提交一次item，该方法就会被调用一次。item参数就是接受到爬虫文件给提交过来的item对象
#该方法只有在开始爬虫的时候被调用一次
fp = None
def open_spider(self,spider): #父类的方法
print('开始爬虫')
self.fp = open('./qiubai_data.txt', 'w', encoding='utf-8')
def process_item(self, item, spider): #父类的方法
author = item['author']
content = item['content']
self.fp.write(author+":"+content)
return item
#该方法只有在爬虫结束后被调用一次
def close_spider(self,spider): #父类的方法
print('爬虫结束')
self.fp.close()
class MyPipeline(object):
conn = None
cursor = None
# 作用：每当爬虫文件向管道提交一次item，该方法就会被调用一次。item参数就是接受到爬虫文件给提交过来的item对象
def open_spider(self,spider):
self.conn = pymysql.Connect(host="192.168.12.65", port=3306, db="scrapyDB", charset="utf8", user="root")
self.cursor = self.conn.cursor()
print('mysql')
def process_item(self, item, spider):
author = item['author']
content = item['content']
sql = "insert into qiubai values('%s','%s')" % (author,content) #qiubai是表名
try:
self.cursor.execute(sql) #执行sql
self.conn.commit() #事务的处理，没有问题提交，有问题回滚
except Exception as e:
print(e)
self.conn.rollback()
return item
pipelines.py
管道操作4步---听视频自己总结：
前提要在parse方法中获取解析到的数据，
1.将解析到的数据值存储到item对象中（前提item中要进行属性的声明）,
2.使用yield关键字将item对象提交给管道
3.在pipelines.py中进行PipelineproPipeline方法的编写，编写process_item
4.在配置文件中开启管道
1.#实例化item对象
item = PipelineproItem()
2.在items.py中声明属性
3.#将解析到的数据值存储到item对象中
item['author'] = author
item['content'] = content
4.#将item对象提交给管道
yield item
将数据写入到数据库：新建数据库、表
select * from qiubai 查看写入的内容