爬虫之牛掰的scrapy框架
一. Scrapy简介及安装
http://python.jobbole.com/86405/ Scrapy的详细介绍
1.简介
2.安装
1.window上安装:
先安装依赖包:pip3 install wheel
https://www.lfd.uci.edu/~gohlke/pythonlibs/#twisted 下载以后安装pip3 install 安装包
pip3 install pywin32
pip3 install scrapy
2mac上: pip3 install scrapy
二. Scrapy常见命令
1.创建项目: scrapy startproject project-name
2.创建爬虫文件: scrapy genspider filename 指定网站
3.运行项目: scrapy crawl filename
scrapy crawl filename --nolog 不打印日志
三.Scrapy的基本使用
1.创建项目.
通过命令进行创建: scrapy startproject 项目名
2.自动创建目录的结果.
文件说明:
1.boss.py:爬虫文件.一般创建爬虫文件时,以网站域名命名.
通过命令创建: scrapy genspider boss 指定网站
2. items.py:设置数据储存模块,用于结构化数据
3. middlewares
4.pipelines
5.settings:配置文件.
6.spiders 爬虫目录.如:创建文件编写爬虫规则
3,编写文件
(1)爬虫文件中
# -*- coding: utf-8 -*-
import scrapy
from bossDemo.items import BossdemoItem
# 爬虫文件的作用
# 1.url的指定
# 2.请求的发送
# 3.数据的解析
# 4.将item对象通过yield传给管道文件
class BossSpider(scrapy.Spider):
name = 'boss'
# allowed_domains = ['www.xxx.com']
start_urls = ['https://www.zhipin.com/job_detail/?query=python&scity=101180100&industry=&position=']
def parse(self, response):
li_list = response.xpath('//*[@id="main"]/div/div[3]/ul/li')
# print(li_list)
for li in li_list:
title = li.xpath('./div/div[1]/h3/a/div[1]/text()').extract_first()
salary = li.xpath('./div/div[1]/h3/a/span/text()').extract_first()
company = li.xpath('./div/div[2]/div/h3/a/text()').extract_first()
print(title +salary + company)
# 实例化一个item对象
item = BossdemoItem()
# 将解析后的数据储存到item对象中
item['title'] = title
item['salary'] = salary
item['company'] = company
# 将item对象传给管道文件进行持久化储存
yield item
(2)items.py
import scrapy
class BossdemoItem(scrapy.Item):
# define the fields for your item here like:
title = scrapy.Field()
salary = scrapy.Field()
company = scrapy.Field()
(3)Pipelines.py
import pymysql
from redis import Redis
import json
class BossdemoPipeline(object):
# 这个函数只会在开始爬取的时候执行一次
def open_spider(self, spider):
print('爬虫开始')
self.fp = open('./job.txt', 'w', encoding='utf-8' )
# 每提交一次item,这个文件就执行一次
def process_item(self, item, spider):
self.fp.write(item['title'] + '\t' + item['salary'] + '\t' + item['company'] + '\n')
print('爬取中')
return item
# 存储结束后执行这个函数
def close_spider(self,spider):
print('爬虫结束')
self.fp.close()
class MysqlPipeline(object):
cursor = None
conn = None
def open_spider(self, spider):
print('mysql爬虫开始')
self.conn = pymysql.Connect(host='127.0.0.1', port=3306, user='root', password='', db='db1' )
def process_item(self, item, spider):
self.cursor = self.conn.cursor()
sql = 'insert into boss (title, salary, company) values ("%s","%s","%s")'%(item["title"], item["salary"],item["company"])
try:
print('mysql爬虫中')
self.cursor.execute(sql)
self.conn.commit()
except Exception as e:
print(e)
self.conn.rollback()
return item
def close_spider(self, spider):
print('mysql爬虫结束')
self.cursor.close()
self.conn.close()
class RedisPipeline(object):
def open_spider(self, spider):
print('redis储存')
self.conn = Redis(host='127.0.0.1', port='6379')
def process_item(self, item, spider):
dic = {
'title': item['title'],
'salary': item['salary'],
'company': item['company'],
}
print('redis存储中...')
self.conn.lpush('Jobinfo', json.dumps(dic))
def close_spider(self, spider):
print('redis结束')
备注:
1.爬虫文件需要定义一个类,并继承(scrapy.Spider)
2.必须定义name, 即爬虫名,如果没有那么,会报错,因为源码中这样规定的:
3.编写函数parse,这里需要注意的是,该函数不能改变,是因为Scrapy中默认callback函数的函数名就是parse.
4.scrapy发送post请求
# 1.scrapy中post请求的发送:重写源码中的start_requests方法
# 因为源码中这样写的:for url in self.start_urls:
# yield self.make_requests_from_url(url) (make_requests_from_url方法的返回结果是Request对象)
# 2.在scrapy 框架中,会自动对cookie进行处理,可以在settings中设置不处理 COOKIES_ENABLED = False
示例代码:
import scrapy
class LoginSpider(scrapy.Spider):
name = 'login'
# allowed_domains = ['www.xxx.com']
start_urls = ['http://www.renren.com/ajaxLogin/login?1=1&uniqueTimestamp=201903160368']
def start_requests(self):
data = {
"email": "15516092050",
"icode": '',
"origURL": "http://www.renren.com/home",
"domain": "renren.com",
"key_id": '1',
"captcha_type": "web_login",
"password": "5e088a2ee22d34dd081aac25578e67bd3a2d851cdfbcf1f0c9ab7056bd1bad62",
"rkey": "3f4696f6fa1b89e9061868300bf11484",
"f": "http%3A%2F%2Fwww.renren.com%2F969395731",
}
for url in self.start_urls:
yield scrapy.FormRequest(url=url, formdata=data, callback=self.parse)
def parse(self, response):
detail_url = 'http://www.renren.com/969395731'
yield scrapy.Request(url = detail_url, callback=self.GetDetail)
def GetDetail(self, response):
ret = response.text
print(ret)
5.scrapy请求传参的方式
1.用scrapy爬取数据时,如果发现需要爬取的数据不在同一页面内,则必须使用请求传参的方式进行持久化储存
2.示例代码
class MovieSpider(scrapy.Spider):
name = 'movie'
# allowed_domains = ['www.xxx.com']
start_urls = ['http://www.55xia.com/']
def parse(self, response):
div_list = response.xpath('/html/body/div[1]/div[2]/div[1]/div/div | /html/body/div[1]/div[2]/div[3]/div/div')
for div in div_list:
item = MoviedemoItem()
detail_url = div.xpath('./div/div/h1/a/@href')
if not detail_url:
continue
else:
detail_url = 'http:' + detail_url.extract_first()
name = div.xpath('./div/div/h1/a/text()').extract_first()
score = div.xpath('./div/div/h1/em/text()')
if not score:
score = '暂无评价'
else:
score = score.extract_first()
item['name'] = name
item['score'] = score
print(name)
print(score)
yield scrapy.Request(url=detail_url, callback=self.GetDetail, meta={'item':item})
def GetDetail(self,response):
item = response.meta['item']
direct = response.xpath('/html/body/div[1]/div/div/div[1]/div[1]/div[2]/table/tbody/tr[1]/td[2]/a/text()').\
extract_first()
detail = response.xpath('/html/body/div[1]/div/div/div[1]/div[2]/div[2]//text()'). extract_first()
item['direct'] = direct
item['detail'] = detail
print(direct)
print(detail)
yield item
6.提高scrapy框架效率
# 增加并发：
# 默认scrapy开启的并发线程为32个，可以适当进行增加。在settings配置文件中修改CONCURRENT_REQUESTS = 100值为100,并发设置成了为100。
#
# 降低日志级别：
# 在运行scrapy时，会有大量日志信息的输出，为了减少CPU的使用率。可以设置log输出信息为INFO或者ERROR即可。在配置文件中编写：LOG_LEVEL = ‘INFO’
#
# 禁止cookie：
# 如果不是真的需要cookie，则在scrapy爬取数据时可以禁止cookie从而减少CPU的使用率，提升爬取效率。在配置文件中编写：COOKIES_ENABLED = False
#
# 禁止重试：
# 对失败的HTTP进行重新请求（重试）会减慢爬取速度，因此可以禁止重试。在配置文件中编写：RETRY_ENABLED = False
#
# 减少下载超时：
# 如果对一个非常慢的链接进行爬取，减少下载超时可以能让卡住的链接快速被放弃，从而提升效率。在配置文件中进行编写：DOWNLOAD_TIMEOUT = 10 超时时间为10s
CONCURRENT_REQUESTS = 10
LOG_LEVEL = 'ERROR'
COOKIES_ENABLED = False
RETRY_ENABLED = False
DOWNLOAD_TIMEOUT = 5
7.设置代理池和UA池
1.UA池：User-Agent池
- 作用：尽可能多的将scrapy工程中的请求伪装成不同类型的浏览器身份。
- 操作流程：
1.在下载中间件中拦截请求
2.将拦截到的请求的请求头信息中的UA进行篡改伪装
3.在配置文件中开启下载中间件
user_agent_list = [
"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.1 "
"(KHTML, like Gecko) Chrome/22.0.1207.1 Safari/537.1",
"Mozilla/5.0 (X11; CrOS i686 2268.111.0) AppleWebKit/536.11 "
"(KHTML, like Gecko) Chrome/20.0.1132.57 Safari/536.11",
"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.6 "
"(KHTML, like Gecko) Chrome/20.0.1092.0 Safari/536.6",
"Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.6 "
"(KHTML, like Gecko) Chrome/20.0.1090.0 Safari/536.6",
"Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/537.1 "
"(KHTML, like Gecko) Chrome/19.77.34.5 Safari/537.1",
"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/536.5 "
"(KHTML, like Gecko) Chrome/19.0.1084.9 Safari/536.5",
"Mozilla/5.0 (Windows NT 6.0) AppleWebKit/536.5 "
"(KHTML, like Gecko) Chrome/19.0.1084.36 Safari/536.5",
"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 "
"(KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3",
"Mozilla/5.0 (Windows NT 5.1) AppleWebKit/536.3 "
"(KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3",
"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_0) AppleWebKit/536.3 "
"(KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3",
"Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 "
"(KHTML, like Gecko) Chrome/19.0.1062.0 Safari/536.3",
"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 "
"(KHTML, like Gecko) Chrome/19.0.1062.0 Safari/536.3",
"Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 "
"(KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3",
"Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 "
"(KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3",
"Mozilla/5.0 (Windows NT 6.1) AppleWebKit/536.3 "
"(KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3",
"Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 "
"(KHTML, like Gecko) Chrome/19.0.1061.0 Safari/536.3",
"Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/535.24 "
"(KHTML, like Gecko) Chrome/19.0.1055.1 Safari/535.24",
"Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/535.24 "
"(KHTML, like Gecko) Chrome/19.0.1055.1 Safari/535.24"
]
2.代理池
- 作用：尽可能多的将scrapy工程中的请求的IP设置成不同的。
- 操作流程：
1.在下载中间件中拦截请求
2.将拦截到的请求的IP修改成某一代理IP
3.在配置文件中开启下载中间件
示例代码
http_proxy = ['http://91.226.35.93:53281', 'http://110.52.235.73:9999', 'http://151.3.53.246:53281']
https_proxy = ['https://106.104.168.15:8080', 'https://93.190.143.59:1080', 'https://223.27.212.41:8080' ]
if request.url.split(':')[0] == 'http':
request.meta['proxy'] = random.choice(http_proxy)
else:
request.meta['proxy'] = random.choice(https_proxy)
8 五大组件
