Scrapy爬取西刺代理ip流程

西刺代理爬虫

1. 新建项目和爬虫

scrapy startproject daili_ips
......
cd daili_ips/
#爬虫名称和domains
scrapy genspider xici xicidaili.com

2. 测试

In [1]: import requests
In [2]: r = requests.get('http://www.xicidaili.com/nn/1')
In [3]: r.status_code
Out[3]: 500
In [4]:

返回500, 猜想是没有加User-Agent致使

In [4]: headers = {'User-Agent':'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/52.0.2743.116 Safari/537.36'}
In [5]: 
In [5]: r = requests.get('http://www.xicidaili.com/nn/1', headers=headers)
In [6]: r.status_code
Out[6]: 200
In [7]:

返回正常

3. 在项目的settings中去掉USER_AGENT的注释

# Crawl responsibly by identifying yourself (and your website) on the user-agent
USER_AGENT = 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/52.0.2743.116 Safari/537.36'

4. 编写items.py

item定义存储哪些字段

import scrapy


class DailiIpsItem(scrapy.Item):
    ip = scrapy.Field()
    port = scrapy.Field()
    position = scrapy.Field()
    type = scrapy.Field()
    speed = scrapy.Field()
    last_check_time = scrapy.Field()

5. 编写spider

# -*- coding: utf-8 -*-
import scrapy
from daili_ips.items import DailiIpsItem


class XiciSpider(scrapy.Spider):
    name = "xici"
    allowed_domains = ["xicidaili.com"]
    start_urls = (
        'http://www.xicidaili.com/',
    )

    def start_requests(self):
        res = []
        for i in range(1, 2):
            url = 'http://www.xicidaili.com/nn/%d'%i
            req = scrapy.Request(url)
            # 存储全部对应地址的请求
            res.append(req)
        return res

    def parse(self, response):
        table = response.xpath('//table[@id="ip_list"]')[0]
        trs = table.xpath('//tr')[1:]   #去掉标题行
        items = []
        for tr in trs:
            pre_item = DailiIpsItem()
            pre_item['ip'] = tr.xpath('td[2]/text()').extract()[0]
            pre_item['port'] = tr.xpath('td[3]/text()').extract()[0]
            pre_item['position'] = tr.xpath('string(td[4])').extract()[0].strip()
            pre_item['type'] = tr.xpath('td[6]/text()').extract()[0]
            pre_item['speed'] = tr.xpath('td[7]/div/@title').re('\d+\.\d*')[0]
            pre_item['last_check_time'] = tr.xpath('td[10]/text()').extract()[0]
            items.append(pre_item)
        return items

编写spider的时候能够经过命令行工具scrapy shell url来测试要提取数据的xpath语法, 这样更高效

6. 编写Pipelines

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

# Define your item pipelines here
#
# Don't forget to add your pipeline to the ITEM_PIPELINES setting
# See: http://doc.scrapy.org/en/latest/top ics/item-pipeline.html
import MySQLdb

class DailiIpsPipeline(object):
    # 该函数必须返回一个具备数据的dict或者item对象
    def process_item(self, item, spider):
        DBS = spider.settings.get('DBS')
        con = MySQLdb.connect(**DBS)
        # 下面这行代码表示设置MySQL使用的字符集为utf8
        con.set_character_set('utf8')
        cur = con.cursor()
        insert_sql = (
            "insert into proxy (ip, port, position, type, speed, last_check_time) "
            "values (%s,%s,%s,%s,%s,%s);"
        )
        values = (item['ip'], item['port'], item['position'], item['type'], item['speed'], item['last_check_time'])
        # 插入数据库
        try:
            cur.execute(insert_sql, values)
        except Exception, e:
            print "插入失败: ", e
            con.rollback()
        else:
            con.commit()
        cur.close()
        con.close()
        return item




        return item

注意:
这里我刚开始作的时候没有加con.set_character_set('utf8')这一行, 结果报错以下

UnicodeEncodeError: 'latin-1' codec can't encode character

可是我在建立数据表的时候已经设置字符集为utf8, 查资料后是MySQLdb正常状况下会尝试将全部的内容转为latin1字符集处理
因此处理方法就是，设置链接和游标的charset为你所但愿的编码

con = MySQLdb.connect(...)
# 设置连接编码
con.set_character_set('utf8')
cur = con.cursor()
# 设置游标编码
cur.execute('SET NAMES utf8;')
cur.execute('SET CHARACTER SET utf8;')
cur.execute('SET CHARACTER_SET_CONNECTION=utf8;')

我在测试后发现仅仅设置链接(con)的编码也不会报错, 因此上述程序并无设置游标编码

7. 建立MySQL数据表

mysql> create table porxy(
    -> id int primary key auto_increment,
    -> ip varchar(20),
    -> port varchar(20),
    -> position varchar(20),
    -> type varchar(20),
    -> speed varchar(20),
    -> last_check_time varchar(20)
    -> )charset=utf8;
Query OK, 0 rows affected (0.01 sec)

mysql>

8. 启用Pipelines

更改settings.py文件, 取消注释

# Configure item pipelines
# See http://scrapy.readthedocs.org/en/latest/topics/item-pipeline.html
#ITEM_PIPELINES = {
#    'daili_ips.pipelines.SomePipeline': 300,
#}

改成

ITEM_PIPELINES = {
   'daili_ips.pipelines.DailiIpsPipeline': 300,
}

后面的数字通常在0-1000之内, 当有多个Pipelines的时候表示执行顺粗, 数字小的先执行

启动爬虫

scrapy crawl xici