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Python爬虫框架Scrapy学习笔记

2016-10-29  本文已影响1385人  codefine
scrapy.png

本文主要内容针对Scrapy有初步了解的同学。结合作者的实际项目中遇到的一些问题,汇成本文。
之后会写一些具体的爬虫demo, 放到 https://github.com/hanguangchao/scrapy_awesome
鉴于作者接触爬虫不久,水平有限,文章难免出现纰漏,还请各位达人留言指导。

内容提要

Scrapy问题记录

Scrapy问题示例代码

Scrapy常用代码片段

Scrapy常用设置

Scrapy参考资料

安装

pip install scrapy

使用

# 终端执行以下命令,创建一个爬虫
scrapy startproject myspider

# 运行第一个爬虫
# myspider/myspider/spiders/myspider.py中定义爬虫 spider1
cd myspider 
scrapy crawl spider1

可以利用scrapy shell 分析网页

通过sel.xpath() 返回一个Selector, 可以判断页面结构是否存在。

scrapy shell http://news.163.com/

sel.xpath('h1').extract()

使用中遇到的一些问题

针对以上问题,下面给出具体的代码示例

# myspider/items.py

import scrapy

class Item1(scrapy.Item):
    url = scrapy.Field()
    name = scrapy.Field()

class Item2(scrapy.Item):
    url = scrapy.Field()
    job_id = scrapy.Field()
    job_title = scrapy.Field()


# myspider/spiders/myspider.py

class Spider1(CrawlSpider):
    # 爬虫的名字
    name = "spider1"
    
    # 要抓取的网页限制
    allowed_domains = ["mysite.com"]
    
    # 指定开始抓取的url
    start_urls = [
        "http://mysite.com/",
        "http://mysite2.com/",
    ]
    
    # parse方法为抓取入口
    # 抓取 start_urls 中的网址
    def parse(self, response):
        sel = Selector(response)
        
        # 在一个页面抓取多个Item
        # 在分析网页过程中,通过 yield item ,可以生成多个item
        item = new Item1()
        item['url'] = response.url
        item['name'] = sel.xpath('').extract()
        yield item
        
        item2 = new Item2()
        item2['url'] = response.url
        item2['job_id'] = sel.xpath('//h2[1]/a/@href').extract()
        item2['job_title'] = sel.xpath('//div[@class="box"]/a/text()').extract()

        # 如何使爬虫进入下一级网页?
        # 使用 yield Request()方法
        yield Request(url, callback=self.parse1)
        
        # 在爬虫中携带自定义数据
        # 添加meta参数
        yield Request(url, 
            meta={'referer' : url, 'job_id': item2['job_id']},
            callback=self.parse2)
        
        # 重复抓取一个页面的方法
        # scrapy默认会过滤重复网页,发起Request添加dont_filter=True,则可以重复请求
        # 使用的时候要注意, 不要进入死循环
        if some_condition:
            yield Request(url, callback=self.parse, dont_filter=True)
        
    def parse1(self, response):
        sel = Selector(response)
      
    def parse2(self, response):
        sel = Selector(response)
        # 使用 response.meta 来访问
        print response.meta['job_id']    
# 在pipelines中的脚本示例
# myspider/pipelines.py
class MyPipeline(object):
    def __init__(self):
        print("MyPipeline init")

    def open_spider(self, spider):
        print("Pipeline opend")

    def close_spider(self, spider):
        print("MyPipeline closed")
        
    def process_item(self, item, spider):
        print 'process_item'
        if isinstance(item, Item1):
            # item1的存储逻辑
            print item
        if isinstance(item, Item2):
            # item2的存储逻辑
            print item  
            
# myspider/settings.py
# 使用MyPipeline分析Item

ITEM_PIPELINES = {
       'myspider.pipelines. MyPipeline': 300,
}
            

使用custom_settings 该设置是一个dict.当启动spider时,该设置将会覆盖项目级的设置. 由于设置必须在初始化(instantiation)前被更新,所以该属性 必须定义为class属性

# myspider/spiders/spider3.py
class Spider3(CrawlerSpider):
    name = "spider3"

    custom_settings = {
        "DOWNLOAD_DELAY": 5.0,
        "RETRY_ENABLED": False,
        "LOG_LEVEL" : 'DEBUG',

        "DOWNLOADER_MIDDLEWARES" : {
        
        }
        
        "ITEM_PIPELINES" : {
    
        }
    }

            

防止爬虫被ban

# settings.py
# 绕过robots策略
ROBOTSTXT_OBEY = False
# 禁用Cookie
COOKIES_ENABLED = False
# 限制爬取速度
DOWNLOAD_DELAY = 5
# 禁止重定向
REDIRECT_ENABLED = False
# 全局并发数
CONCURRENT_REQUESTS = 500
# 禁止重试
RETRY_ENABLED = False
# 减小下载超时
DOWNLOAD_TIMEOUT = 15

常用的Middleware


from proxy import PROXIES, FREE_PROXIES

class CustomHttpProxyMiddleware(object):

    def process_request(self, request, spider):
        if self.use_proxy(request):
            p = random.choice(FREE_PROXIES)
            try:
                request.meta['proxy'] = "http://%s" % p['ip_port']
            except Exception, e:
                #log.msg("Exception %s" % e, _level=log.CRITICAL)
                log.critical("Exception %s" % e)
from agents import AGENTS
class CustomUserAgentMiddleware(object):
    def process_request(self, request, spider):
        agent = random.choice(AGENTS)
        request.headers['User-Agent'] = agent
from selenium import webdriver
from scrapy.http import HtmlResponse
import time

class CustomJavaScriptMiddleware(object):
    def process_request(self, request, spider):
        print "PhantomJS is starting..."
        driver = webdriver.PhantomJS() #指定使用的浏览器
        driver.get(request.url)
        time.sleep(1)
        js = "var q=document.documentElement.scrollTop=10000" 
        driver.execute_script(js) #可执行js,模仿用户操作。此处为将页面拉至最底端。       
        time.sleep(1)
        body = driver.page_source
        print ("访问"+request.url)
        return HtmlResponse(driver.current_url, body=body, encoding='utf-8', request=request)

常用的Pipeline

过滤重复的Item

#pipelines.py
from scrapy.exceptions import DropItem

class DuplicatesPipeline(object):

    def __init__(self):
        self.ids_seen = set()

    def process_item(self, item, spider):
        if item['id'] in self.ids_seen:
            raise DropItem("Duplicate item found: %s" % item)
        else:
            self.ids_seen.add(item['id'])
            return item

#settings.py

ITEM_PIPELINES = {
    'mySpider.pipelines. DuplicatesPipeline': 301,
}


把Item存储到MySQL的Pipeline


from twisted.enterprise import adbapi
import datetime
import MySQLdb.cursors

class SQLStorePipeline(object):

    def __init__(self):
        self.dbpool = adbapi.ConnectionPool('MySQLdb',
            host='127.0.0.1',
            db='webspider',
            user='mysql',
            passwd='secret',
            cursorclass=MySQLdb.cursors.DictCursor,
            charset='utf8',
            use_unicode=True
            )
        print("SQLStorePipeline init")
    def close_spider(self, spider):
        print("SQLStorePipeline closed")

    def open_spider(self, spider):
        print("SQLStorePipeline opend")

    def process_item(self, item, spider):
        if isinstance(item, myItem):
            query = self.dbpool.runInteraction(self._conditional_insert, item)
            query.addErrback(self._database_error, item)
            return item

    def _conditional_insert(self, tx, item):
        try:
            tx.execute(sql)
        except Exception, e:
            print e
       
    def _database_error(self, e, item):
        print "Database error: ", e

把Item保存到JSON文件

import json
import codecs
from collections import OrderedDict


class JsonWithEncodingPipeline(object):
    def __init__(self):
        self.file = codecs.open('data_utf8.json', 'w', encoding='utf-8')

    def process_item(self, item, spider):
        line = json.dumps(OrderedDict(item), ensure_ascii=False, sort_keys=True) + "\n"
        self.file.write(line)
        return item

    def close_spider(self, spider):
        print("JsonWithEncodingPipeline closed")
        self.file.close()

    def open_spider(self, spider):
        print("JsonWithEncodingPipeline opend")
        
              
# @todo 把Item保存到Redis 
class RedisStorePipeline(object):
    pass

# @todo 把Item保存到MongoDB
class MongodbStorePipeline(object):
    pass

参考资料

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