Python之(scrapy)爬虫

  一、Scrapy是Python开发的一个快速、高层次的屏幕抓取和web抓取框架,用于抓取web站点并从页面中提取结构化的数据。Scrapy用途广泛,可以用于数据挖掘、监测和自动化测试

    Scrapy吸引人的地方在于它是一个框架,任何人都可以根据需求方便的修改。它也提供了多种类型爬虫的基类,如BaseSpider、sitemap爬虫等,最新版本又提供了web2.0爬虫的支持。

    Scrapy是一个为爬取网站数据、提取结构性数据而设计的应用程序框架,它可以应用在广泛领域:Scrapy 常应用在包括数据挖掘,信息处理或存储历史数据等一系列的程序中。通常我们可以很简单的通过 Scrapy 框架实现一个爬虫,抓取指定网站的内容或图片。

   二、结构图

    Python之(scrapy)爬虫

    

  Scrapy Engine(引擎):负责Spider、ItemPipeline、Downloader、Scheduler中间的通讯,信号、数据传递等。
  Scheduler(调度器):它负责接受引擎发送过来的Request请求,并按照一定的方式进行整理排列,入队,当引擎需要时,交还给引擎。
  Downloader(下载器):负责下载Scrapy Engine(引擎)发送的所有Requests请求,并将其获取到的Responses交还给Scrapy Engine(引擎),由引擎交给Spider来处理。
  Spider(爬虫):它负责处理所有Responses,从中分析提取数据,获取Item字段需要的数据,并将需要跟进的URL提交给引擎,再次进入Scheduler(调度器)。
  Item Pipeline(管道):它负责处理Spider中获取到的Item,并进行进行后期处理(详细分析、过滤、存储等)的地方。
  Downloader Middlewares(下载中间件):一个可以自定义扩展下载功能的组件。
  Spider Middlewares(Spider中间件):一个可以自定扩展和操作引擎和Spider中间通信的功能组件。

  三、框架介绍(入门):

  常用命令:

  1)新建项目 

scrapy startproject <project_name>

  2)爬虫爬取

scrapy crawl <spider_name>

  3)生成爬虫文件

scrapy genspider [-t template] <name> <domain>

  目录结构:

  Python之(scrapy)爬虫

  这里重点介绍文件的意义:

  1)scrapy.cfg(主要用来指定配置和名称等)

# Automatically created by: scrapy startproject
#
# For more information about the [deploy] section see:
# https://scrapyd.readthedocs.io/en/latest/deploy.html

[settings]
default = scrapy_demo.settings

[deploy]
#url = http://localhost:6800/
project = scrapy_demo

   2)settings.py

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

# Scrapy settings for scrapy_demo 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 = 'scrapy_demo'

SPIDER_MODULES = ['scrapy_demo.spiders']
NEWSPIDER_MODULE = 'scrapy_demo.spiders'


# Crawl responsibly by identifying yourself (and your website) on the user-agent
#USER_AGENT = 'scrapy_demo (+http://www.yourdomain.com)'

# Obey robots.txt rules
ROBOTSTXT_OBEY = True

# 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 = {
#    'scrapy_demo.middlewares.ScrapyDemoSpiderMiddleware': 543,
#}

# Enable or disable downloader middlewares
# See https://doc.scrapy.org/en/latest/topics/downloader-middleware.html
#DOWNLOADER_MIDDLEWARES = {
#    'scrapy_demo.middlewares.ScrapyDemoDownloaderMiddleware': 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 = {
#    'scrapy_demo.pipelines.ScrapyDemoPipeline': 300,
#}

# 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'

   说明:a、BOT_NAME-->项目名称

      b、SPIDER_MODULES,NEWSPIDER_MODULE-->爬虫目录,新爬虫目录

      c、ROBOTSTXT_OBEY-->是否准守网站规则,robots.txt

      d、CONCURRENT_REQUESTS-->并发数

      e、DOWNLOAD_DELAY-->现在延时(秒)

      f、CONCURRENT_REQUESTS_PER_DOMAIN、CONCURRENT_REQUESTS_PER_IP-->并发请求域和ip

      g、COOKIES_ENABLED-->cookie开启

      h、TELNETCONSOLE_ENABLED-->telnet是否开启

      i、DEFAULT_REQUEST_HEADERS-->默认请求头

      j、SPIDER_MIDDLEWARES-->爬虫中间件

      k、DOWNLOADER_MIDDLEWARES-->下载中间件

      l、EXTENSIONS-->扩展

      m、ITEM_PIPELINES-->管道

  3)items.py(主要用于模型的定义) 

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

# Define here the models for your scraped items
#
# See documentation in:
# https://doc.scrapy.org/en/latest/topics/items.html

import scrapy


# class ScrapyDemoItem(scrapy.Item):
#     # define the fields for your item here like:
#     # name = scrapy.Field()
#     pass


class DouYuItem(scrapy.Item):
    # 标题
    title = scrapy.Field()
    # 热度
    hot = scrapy.Field()
    # 图片url
    img_url = scrapy.Field()

  4)pipelines.py(定义管道,同于后续的数据处理)

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

# Define your item pipelines here
#
# Don't forget to add your pipeline to the ITEM_PIPELINES setting
# See: https://doc.scrapy.org/en/latest/topics/item-pipeline.html


# class ScrapyDemoPipeline(object):
#     def process_item(self, item, spider):
#         return item
import urllib2


class DouYuPipline(object):

    def __init__(self):
        self.csv_file = open("douyu.csv", "w")

    def process_item(self, item, spider):
        text = item["title"] + "," + str(item["hot"]) + "," + item["img_url"] + "\n"
        # with open("img/" + item["title"] + "_" + str(item["hot"]) + ".jpg", "wb") as f:
        #     f.write(urllib2.urlopen(item["img_url"]).read())
        self.csv_file.write(text.encode("utf-8"))
        return item

    def close_spider(self, spider):
        self.csv_file.close()

  5)spiders(爬虫目录文件夹,核心内容都在这里)

  a、基于scrapy.Spider(基础类)做的开发

# !/usr/bin/python
# -*- coding: UTF-8 -*-
import json

import scrapy
import time

from scrapy_demo.items import DouYuItem

class DouYuSpider(scrapy.Spider):
    name = "douyu"
    allowed_domains = ["www.douyu.com", "rpic.douyucdn.cn"]
    url = "https://www.douyu.com/gapi/rkc/directory/0_0/"
    page = 1
    start_urls = [url + str(page)]

    def parse(self, response):
        data = json.loads(response.text)["data"]["rl"]
        for detail in data:
            douyu_item = DouYuItem()
            douyu_item["title"] = detail["rn"]
            douyu_item["hot"] = detail["ol"]
            douyu_item["img_url"] = detail["rs1"]
            yield scrapy.Request(detail["rs1"], callback=self.img_data_handle)
            yield douyu_item
        self.page += 1
        yield scrapy.Request(self.url + str(self.page), callback=self.parse)

    def img_data_handle(self, response):
        with open("img/" + str(time.time()) + ".jpg", "wb") as f:
            f.write(response.body)

   说明:Spider必须实现parse函数

      name:爬虫名称(必填)

      allowed_domains :允许的域(选填)

      start_urls:需要爬虫的网址(必填)

  b、基于CrawlSpider(父类为Spider)做的开发

# !/usr/bin/python
# -*- coding: UTF-8 -*-

# !/usr/bin/python
# -*- coding: UTF-8 -*-

from scrapy.linkextractors import LinkExtractor
from scrapy.spiders import CrawlSpider, Rule


class DouYuSpider(CrawlSpider):
    name = "douyuCrawl"
    # allowed_domains = ["www.douyu.com"]
    url = "https://www.douyu.com/directory/all"
    start_urls = [url]

    links = LinkExtractor(allow="https")

    rules = [
        Rule(links, callback="link_handle")
    ]

    def link_handle(self, response):
        print response.body

 

   说明:rules:匹配链接规则,用来匹配html中的链接。

   四、上面介绍了主要的几种文件开发方式、说明一下流程

  1)首先会通过Spider目录下的爬虫文件,获取数据,如果存在item的数据返回,可以使用yield或者return

  2)然后item数据会进入pipline,进行后续的处理。

  3)如果使用yield的方式,回事生成器的方式来做,会一直循环的读取数据,主要退出

  五、记住pipline、middleware、都需要在settings.py文件中配置,如果没有配置则说明该管道或者中间件不存在,当然可以设置优先级,数字越小优先级越高

ITEM_PIPELINES = {
   # 'scrapy_demo.pipelines.ScrapyDemoPipeline': 300,
   'scrapy_demo.pipelines.DouYuPipline': 300,
}

  六、启动

  使用命令的方式启动

scrapy crawl <spider-name>

  但是这样存在一个问题,不好进行调试,我们一般采用pyCharm方式进行开发,所以通过脚本的方式进行启动

  start.py

# !/usr/bin/python
# -*- coding: UTF-8 -*-

from scrapy import cmdline

cmdline.execute(["scrapy", "crawl", "douyuCrawl"])

  七、总结:这个和前面使用的Selenium+浏览器插件的使用方式还是存在差异的,这里针对于ajax的处理还是需要人工手动去需要数据的加载,然后在通过接口去获取数据在解析。Selenium+浏览器的方式是通过模拟浏览器的方式来实现js和其他ajax的加载,从效率上面来说,scrapy会更加高效和强大。但是只是从页面来说的话,Selenium+浏览器是一个不错的选择。

  八、例子源码:https://github.com/lilin409546297/scrapy_demo