利用代理ip池 轻松抓取百万数据。

1.今天我们来讲下一个非常有用的东西，代理ip池，结果就是一个任务每隔一定时间去到目标ip代理提供网站去爬取可用数据存到mysql数据库，并且检测数据库已有数据是否可用，不可用就删除。

2. 编写 提取代理ip到数据库 的爬虫

2.1准备mysql表

CREATE TABLE `t_ips` (

`id` int(10) NOT NULL AUTO_INCREMENT COMMENT '主键',

`ip` varchar(15) COLLATE utf8_unicode_ci DEFAULT NULL COMMENT 'ip',

`port` int(10) NOT NULL COMMENT 'port',

`type` int(10) NOT NULL DEFAULT '0' COMMENT '0:http 1:https',

PRIMARY KEY (`id`)

) ENGINE=InnoDB AUTO_INCREMENT=421 DEFAULT CHARSET=utf8 COLLATE=utf8_unicode_ci COMMENT='ip表';

2.2创建爬虫工程，编写items.py(对应数据库的字段)

import scrapy

class IpsItem(scrapy.Item):

# define the fields for your item here like:

# name = scrapy.Field()

ip = scrapy.Field()

port = scrapy.Field()

httpType = scrapy.Field()

2.3编写settings.py

# -*- coding: utf-8 -*-

####################自已的配置################

MAX_PAGE = 2 ##抓取的代理ip网址 的 页数

#0 : http 1:https

TYPE = 0 ### 代理ip类型

URL = 'http://www.bugng.com/gnpt?page=' ### 代理ip网址

TIMER_STOP_TIME = 20 ### 定时器暂停执行时间

#####################################

BOT_NAME = 'ips'

SPIDER_MODULES = ['ips.spiders']

NEWSPIDER_MODULE = 'ips.spiders'

USER_AGENT = 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/56.0.2924.87 Safari/537.36'

ITEM_PIPELINES = {

'ips.pipelines.IpsPipeline': 300,

}

# 禁止重试

RETRY_ENABLED = False

# Crawl responsibly by identifying yourself (and your website) on the user-agent

#USER_AGENT = 'csdn (+http://www.yourdomain.com)'

# Obey robots.txt rules

ROBOTSTXT_OBEY = False

# 减小下载超时:

DOWNLOAD_TIMEOUT = 2

# 禁止cookies:

COOKIES_ENABLED = False

# 延迟下载 防止被ban

DOWNLOAD_DELAY=2

2.4编写spider

这里用到了bs4,需要自行安装

# -*- coding: utf-8 -*-

import scrapy

import logging

from bs4 import BeautifulSoup

from ips.items import IpsItem

from ips.settings import *

class XicispiderSpider(scrapy.Spider):

name = 'xiciSpider'

allowed_domains = ['xicidaili.com']

start_urls = ['http://xicidaili.com/']

### 开始 放入url

def start_requests(self):

req = []

for i in range(1,MAX_PAGE):

### 代理ip网址的第几页的 url

req.append(scrapy.Request(URL + str(i-1)))

return req

## 每一页url的 解析回调函数，利用bs4解析

def parse(self, response):

print('@@@@@@@@@ 开始解析 '+response.url)

try:

soup = BeautifulSoup(str(response.body, encoding = "utf-8"),'html.parser')

trs = soup.find('table',{'class':'table'}).find_all('tr')

for tr in trs[1:]:

tds = tr.find_all('td')

cur = 0

item = IpsItem()

item['httpType'] = TYPE

for td in tds:

if cur == 0:

item['ip'] = td.text

if cur == 1:

item['port'] = td.text

cur = cur +1

yield item #### 给pipline处理

except Exception as e:

logging.log(logging.WARN, '@@@@@@@@@ start parser ' + str(e)) 

2.5编写pipline

这里需要安装 : pip install mysqlclient

这里插入数据库之前做两个校验：

1.数据是否存在

2.数据是否可用

# -*- coding: utf-8 -*-

import MySQLdb

import MySQLdb.cursors

from twisted.enterprise import adbapi

import logging

import requests

class IpsPipeline(object):

def __init__(self):

dbargs = dict(

host='你的数据库ip',

db='数据库名称',

user='root',

passwd='数据库密码',

charset='utf8',

cursorclass=MySQLdb.cursors.DictCursor,

use_unicode=True,

)

self.dbpool = adbapi.ConnectionPool('MySQLdb', **dbargs)

##处理每个yeild的item

def process_item(self, item, spider):

res = self.dbpool.runInteraction(self.insert_into_table, item)

return item

def insert_into_table(self, conn, item):

ip = item['ip']

port = item['port']

# 先查询存不存在

if self.exsist(item,conn):

return

# 查询 此代理ip是否可用，可用就加入数据库

if self.proxyIpCheck(item['ip'],item['port']) is False:

print("此代理ip不可用，proxy:",item['ip'],':',str(item['port']))

return

sql = 'insert into t_ips (ip,port,type) VALUES ('

sql = sql + '"' + item['ip'] + '",'

sql = sql + str(item['port']) + ','

sql = sql + str(item['httpType']) + ','

sql = sql[0:-1]

sql = sql + ')'

try:

conn.execute(sql)

print(sql)

except Exception as e:

logging.log(logging.WARNING, "sqlsqlsqlsqlsqlsqlsql error>> " + sql)

def exsist(self,item,conn):

sql = 'select * from t_ips where ip="' + item['ip'] + '" and port=' + str(item['port']) + ''

try:

# 执行SQL语句

conn.execute(sql)

# 获取所有记录列表

results = conn.fetchall()

if len(results) > 0: ## 存在

#print("此ip已经存在@@@@@@@@@@@@")

return True

except:

return False

return False

##判断代理ip是否可用

def proxyIpCheck(self,ip, port):

server = ip + ":" + str(port)

proxies = {'http': 'http://' + server, 'https': 'https://' + server}

try:

r = requests.get('https://www.baidu.com/', proxies=proxies, timeout=1)

if (r.status_code == 200):

return True

else:

return False

except:

return False

2.6 测试爬虫 scrapy crwal 爬虫名

3. 到此我们的 提取代理ip到数据库的 爬虫就写好了,接下来就是我们的任务定时器的编写

#####在我们的爬虫项目的settings.py文件的同级目录新建一个start.py文件

import os

import pymysql

import threading

from settings import *

##定时器调用的run方法

def run():

clearIpPool()

### 循环定时器，不然执行一次就over了

timer = threading.Timer(TIMER_STOP_TIME, run)

timer.start()

########从这里开始执行

print("ip池定时器开始，间隔时间：",str(TIMER_STOP_TIME),'s')

########开启定时器 TIMER_STOP_TIME为settings.py中的配置

timer = threading.Timer(TIMER_STOP_TIME,run)

timer.start()

def clearIpPool():

print("定时器执行，清扫ip数据库池")

## 利用 系统scrapy命令重新爬取代理ip

os.system('scrapy crawl xiciSpider --nolog')

# 遍历数据库 去除无用的代理ip

removeUnSafeProxyFromDB()

print("定时器执行完毕")

###### 查询数据库，找出无用的代理ip并且删除

def removeUnSafeProxyFromDB():

# 打开数据库连接

db = pymysql.connect("39.108.112.254", "root", "abc123|||456", "xici")

# 使用cursor()方法获取操作游标

cursor = db.cursor()

# SQL 查询语句

sql = "SELECT * FROM t_ips"

try:

# 执行SQL语句

cursor.execute(sql)

# 获取所有记录列表

results = cursor.fetchall()

for row in results:

id = row[0]

ip = row[1]

port = row[2]

if proxyIpCheck(ip, str(port)) is False:

print("此代理ip不可用，proxy:",ip, ':', str(port))

## 执行删除

sql = "DELETE FROM t_ips WHERE id = "+str(id)

# 执行SQL语句

cursor.execute(sql)

print(sql)

# 提交修改

db.commit()

return

except:

print("Error: unable to fetch data")

# 关闭数据库连接

db.close()

#####检测代理ip是否可用

def proxyIpCheck(ip, port):

server = ip + ":" + str(port)

proxies = {'http': 'http://' + server, 'https': 'https://' + server}

try:

r = requests.get('https://www.baidu.com/', proxies=proxies, timeout=1)

if (r.status_code == 200):

return True

else:

return False

except:

return False 

本文地址：https://blog.csdn.net/yingpu618/article/details/108264545