scrapy笔记集合
细读http://scrapy-chs.readthedocs.io/zh_CN/latest/index.html
目录
TinyScrapy(自定义框架)
补充
- 数据采集器
- log
Scrapy介绍
Scrapy是一个为了爬取网站数据,提取结构性数据而编写的应用框架。 其可以应用在数据挖掘,信息处理或存储历史数据等一系列的程序中。
其最初是为了页面抓取 (更确切来说, 网络抓取 )所设计的, 也可以应用在获取API所返回的数据(例如 Amazon Associates Web Services ) 或者通用的网络爬虫。Scrapy用途广泛,可以用于数据挖掘、监测和自动化测试。
Scrapy 使用了 Twisted异步网络库来处理网络通讯。整体架构大致如下
Scrapy Engine
引擎负责控制数据流在系统中所有组件中流动,并在相应动作发生时触发事件。 详细内容查看下面的数据流(Data Flow)部分。
调度器(Scheduler)
调度器从引擎接受request并将他们入队,以便之后引擎请求他们时提供给引擎。
下载器(Downloader)
下载器负责获取页面数据并提供给引擎,而后提供给spider。
Spiders
Spider是Scrapy用户编写用于分析response并提取item(即获取到的item)或额外跟进的URL的类。 每个spider负责处理一个特定(或一些)网站。 更多内容请看 Spiders 。
Item Pipeline
Item Pipeline负责处理被spider提取出来的item。典型的处理有清理、 验证及持久化(例如存取到数据库中)。 更多内容查看 Item Pipeline 。
下载器中间件(Downloader middlewares)
下载器中间件是在引擎及下载器之间的特定钩子(specific hook),处理Downloader传递给引擎的response。 其提供了一个简便的机制,通过插入自定义代码来扩展Scrapy功能。更多内容请看 下载器中间件(Downloader Middleware) 。
Spider中间件(Spider middlewares)
Spider中间件是在引擎及Spider之间的特定钩子(specific hook),处理spider的输入(response)和输出(items及requests)。 其提供了一个简便的机制,通过插入自定义代码来扩展Scrapy功能。更多内容请看 Spider中间件(Middleware) 。
Scrapy中的数据流由执行引擎控制,其过程如下:
- 引擎打开一个网站(open a domain),找到处理该网站的Spider并向该spider请求第一个要爬取的URL(s)。
- 引擎从Spider中获取到第一个要爬取的URL并在调度器(Scheduler)以Request调度。
- 引擎向调度器请求下一个要爬取的URL。
- 调度器返回下一个要爬取的URL给引擎,引擎将URL通过下载中间件(请求(request)方向)转发给下载器(Downloader)。
- 一旦页面下载完毕,下载器生成一个该页面的Response,并将其通过下载中间件(返回(response)方向)发送给引擎。
- 引擎从下载器中接收到Response并通过Spider中间件(输入方向)发送给Spider处理。
- Spider处理Response并返回爬取到的Item及(跟进的)新的Request给引擎。
- 引擎将(Spider返回的)爬取到的Item给Item Pipeline,将(Spider返回的)Request给调度器。
- (从第二步)重复直到调度器中没有更多地request,引擎关闭该网站。
安装
- Linux
- pip3 install scrapy
- Windows
- a. pip3 install wheel
- b. 下载twisted http://www.lfd.uci.edu/~gohlke/pythonlibs/#twisted
- c. 进入下载目录,执行 pip3 install Twisted‑17.1.0‑cp35‑cp35m‑win_amd64.whl
- d. pip3 install scrapy
- e. 下载并安装pywin32:https://sourceforge.net/projects/pywin32/files/ 或者 pip install pywin32
安装(linux、windows)
基本命令
- 1. scrapy startproject 项目名称
- - 在当前目录中创建中创建一个项目文件(类似于Django)
- 2. scrapy genspider [-t template] <name> <domain>
- - 创建爬虫应用
- 如:
- scrapy gensipider -t basic oldboy oldboy.com
- scrapy gensipider -t xmlfeed autohome autohome.com.cn
- PS:
- 查看所有命令:scrapy gensipider -l
- 查看模板命令:scrapy gensipider -d 模板名称
- 3. scrapy list
- - 展示爬虫应用列表
- 4. scrapy crawl 爬虫应用名称
- - 运行单独爬虫应用
- scrapy crawl xxx --nolog
- 5.scrapy shell 进入shell
基本命令(创建项目、运行爬虫,类似于Django)
- 全局命令
- startproject 创建项目
- genspider: scrapy genspider [-t template] <name> <domain>生成爬虫,-l 查看模板; -t 指定模板,name爬虫名,domain域名
- settings 查看设置
- runspider 运行爬虫(运行一个独立的python文件,不必创建项目)
- shell :scrapy shell [url]进入交互式命令行,可以方便调试
- –spider=SPIDER 忽略爬虫自动检测,强制使用指定的爬虫
- -c 评估代码,打印结果并退出:
- $ scrapy shell --nolog http://www.example.com/ -c '(response.status, response.url)'
- (200, 'http://www.example.com/')
- 1
- 2
- –no-redirect 拒绝重定向
- –nolog 不打印日志
- response.status 查看响应码
- response.url
- response.text; response.body 响应文本;响应二进制
- view(response) 打开下载到本地的页面,方便分析页面(比如非静态元素)
-
- fetch 查看爬虫是如何获取页面的,常见选项如下:
- –spider=SPIDER 忽略爬虫自动检测,强制使用指定的爬虫
- –headers 查看响应头信息
- –no-redirect 拒绝重定向
- view 同交互式命令中的view
- version
- 项目命令
- crawl : scrapy crawl <spider> 指定爬虫开始爬取(确保配置文件中ROBOTSTXT_OBEY = False)
- check: scrapy check [-l] <spider>检查语法错误
- list 爬虫list
- edit 命令行模式编辑爬虫(没啥用)
- parse: scrapy parse <url> [options] 爬取并用指定的回掉函数解析(可以验证我们的回调函数是否正确)
- –callback 或者 -c 指定回调函数
- bench 测试爬虫性能
命令
项目结构以及爬虫应用介绍
- project_name/
- scrapy.cfg
- project_name/
- __init__.py
- items.py # 定义Item,类似于Django的Model
- pipelines.py # 定义持久化类
- settings.py # settings
- spiders/ # 所有自定义的爬虫存放文件夹
- __init__.py
- 爬虫1.py
- 爬虫2.py
- 爬虫3.py
- 文件说明:
- scrapy.cfg 项目的主配置信息。(真正爬虫相关的配置信息在settings.py文件中)
- items.py 设置数据存储模板,用于结构化数据,如:Django的Model
- pipelines 数据处理行为,如:一般结构化的数据持久化
- settings.py 配置文件,如:递归的层数、并发数,延迟下载等
- spiders 爬虫目录,如:创建文件,编写爬虫规则
项目结构 及 说明
样例:
- import scrapy
- class XiaoHuarSpider(scrapy.spiders.Spider):
- name = "xiaohuar" # 爬虫名称 *****
- allowed_domains = ["xiaohuar.com"] # 允许的域名
- start_urls = [
- "http://www.xiaohuar.com/hua/", # 其实URL
- ]
- def parse(self, response):
- # 访问起始URL并获取结果后的回调函数
爬虫1.py
- import sys,os
- import io
- sys.stdout=io.TextIOWrapper(sys.stdout.buffer,encoding='gb18030')
windows编码
简单使用示例
- import scrapy
- from scrapy.selector import HtmlXPathSelector
- from scrapy.http.request import Request
- class DigSpider(scrapy.Spider):
- # 爬虫应用的名称,通过此名称启动爬虫命令
- name = "dig"
- # 允许的域名
- allowed_domains = ["chouti.com"]
- # 起始URL
- start_urls = [
- 'http://dig.chouti.com/',
- ]
- has_request_set = {}
- def parse(self, response):
- print(response.url)
- hxs = HtmlXPathSelector(response)
- page_list = hxs.select('//div[@id="dig_lcpage"]//a[re:test(@href, "/all/hot/recent/\d+")]/@href').extract()
- for page in page_list:
- page_url = 'http://dig.chouti.com%s' % page
- key = self.md5(page_url)
- if key in self.has_request_set:
- pass
- else:
- self.has_request_set[key] = page_url
- obj = Request(url=page_url, method='GET', callback=self.parse)
- yield obj
- @staticmethod
- def md5(val):
- import hashlib
- ha = hashlib.md5()
- ha.update(bytes(val, encoding='utf-8'))
- key = ha.hexdigest()
- return key
爬虫1.py
执行此爬虫文件,则在终端进入项目目录执行如下命令:
1
|
scrapy crawl dig - - nolog |
对于上述代码重要之处在于:
- Request是一个封装用户请求的类,在回调函数中yield该对象表示继续访问
- HtmlXpathSelector用于结构化HTML代码并提供选择器功能
选择器
- nodeName 选取此节点的所有节点
- / 从根节点选取
- // 从匹配选择的当前节点选择文档中的节点,不考虑它们的位置
- . 选择当前节点
- .. 选取当前节点的父节点
- @ 选取属性
- * 匹配任何元素节点
- @* 匹配任何属性节点
- Node() 匹配任何类型的节点
常用的路径表达式
- .class .color 选择class=”color”的所有元素
- #id #info 选择id=”info”的所有元素
- * * 选择所有元素
- element p 选择所有的p元素
- element,element div,p 选择所有div元素和所有p元素
- element element div p 选择div标签内部的所有p元素
- [attribute] [target] 选择带有targe属性的所有元素
- [arrtibute=value] [target=_blank] 选择target=”_blank”的所有元素
CSS选择器
- contains a[contains(@href, "link")] 属性href中包含link的a标签
- starts-with a[starts-with(@href, "link") 属性href中以link开头的a标签
- re:test a[re:test(@id, "i\d+") 属性id中格式是i\d+的a标签
- 。。。
css高级用法
- 不带extr。。。的 # 结果为obj
- extract() # 提取为list
- extract_first() # 提取第一个
提取
- #!/usr/bin/env python
- # -*- coding:utf-8 -*-
- from scrapy.selector import Selector, HtmlXPathSelector
- from scrapy.http import HtmlResponse
- html = """<!DOCTYPE html>
- <html>
- <head lang="en">
- <meta charset="UTF-8">
- <title></title>
- </head>
- <body>
- <ul>
- <li class="item-"><a id='i1' href="link.html">first item</a></li>
- <li class="item-0"><a id='i2' href="llink.html">first item</a></li>
- <li class="item-1"><a href="llink2.html">second item<span>vv</span></a></li>
- </ul>
- <div><a href="llink2.html">second item</a></div>
- </body>
- </html>
- """
- response = HtmlResponse(url='http://example.com', body=html,encoding='utf-8')
- # hxs = HtmlXPathSelector(response)
- # print(hxs)
- # hxs = Selector(response=response).xpath('//a') # 查找整个html中所有a标签
- # print(hxs)
- # hxs = Selector(response=response).xpath('//a[2]') # 查找整个html中所有a标签的第二个元素
- # print(hxs)
- # hxs = Selector(response=response).xpath('//a[@id]') # 查找整个html中具有id的所有a标签
- # print(hxs)
- # hxs = Selector(response=response).xpath('//a[@id="i1"]') # 查找整个html中id为i1的a标签
- # print(hxs)
- # hxs = Selector(response=response).xpath('//a[@href="link.html"][@id="i1"]') # 查找整个html中href为link.html以及id为i1的a标签
- # print(hxs)
- # hxs = Selector(response=response).xpath('//a[contains(@href, "link")]') # 查找整个html中href包含link字段的所有a标签
- # print(hxs)
- # hxs = Selector(response=response).xpath('//a[starts-with(@href, "link")]') # 查找整个html中href以link开头的所有a标签
- # print(hxs)
- # hxs = Selector(response=response).xpath('//a[re:test(@id, "i\d+")]') # 查找整个html中id格式为i\d+的所有a标签
- # print(hxs)
- # hxs = Selector(response=response).xpath('//a[re:test(@id, "i\d+")]/text()').extract() # 查找整个html中id格式为i\d+的所有a标签的text值,并提出为string的列表
- # print(hxs)
- # hxs = Selector(response=response).xpath('//a[re:test(@id, "i\d+")]/@href').extract() # 查找整个html中id格式为i\d+的所有a标签的href值,并提出为string的列表
- # print(hxs)
- # hxs = Selector(response=response).xpath('/html/body/ul/li/a/@href').extract() # 查找response里,路径为/html/body/ul/li/a的href值,并提出为string的列表
- # print(hxs)
- # hxs = Selector(response=response).xpath('//body/ul/li/a/@href').extract_first()查找response的后代里,路径为body/ul/li/a的href值,并提出第一个值
- # print(hxs)
- # ul_list = Selector(response=response).xpath('//body/ul/li')
- # for item in ul_list:
- # v = item.xpath('./a/span') # 相对路径
- # # 或
- # # v = item.xpath('a/span')
- # # 或
- # # v = item.xpath('*/a/span')
- # print(v)
示例
- # 找div,class=part2的标签,获取share-linkid属性
- hxs = Selector(response)
- linkid_list = hxs.xpath("//div[@class='part2']/@share-linkid").extract()
- # print(linkid_list)
之前做的真实示例
补充:
- '''
- In [326]: text="""
- ...: <div>
- ...: <a>1a</a>
- ...: <p>2p</p>
- ...: <p>3p</p>
- ...: </div>"""
- '''
- # css写法
- #完整子节点列表,从第一个子节点开始计数,并且满足子节点tag限定
- In [332]: sel.css(‘a:nth-child(1)‘).extract()
- Out[332]: [‘<a>1a</a>‘]
- #完整子节点列表,从最后一个子节点开始计数,并且满足子节点tag限定
- In [333]: sel.css(‘a:nth-last-child(1)‘).extract()
- Out[333]: []
- In [340]: sel.css(‘a:first-child‘).extract()
- Out[340]: [‘<a>1a</a>‘]
- In [341]: sel.css(‘a:last-child‘).extract()
- Out[341]: []
- # 上述 -child 修改为 -of-type ,仅对 过滤后的相应子节点列表 进行计数
- # 这句话待验证
- # xpath写法
- In [345]: sel.xpath(‘//div/*‘).extract()
- Out[345]: [‘<a>1a</a>‘, ‘<p>2p</p>‘, ‘<p>3p</p>‘]
- In [346]: sel.xpath(‘//div/node()‘).extract()
- Out[346]: [‘\n ‘, ‘<a>1a</a>‘, ‘\n ‘, ‘<p>2p</p>‘, ‘\n ‘, ‘<p>3p</p>‘, ‘\n‘]
- In [356]: sel.xpath(‘//div/node()[1]‘).extract() #包括纯文本
- Out[356]: [‘\n ‘]
- In [352]: sel.xpath(‘//div/p[last()]‘).extract()
- Out[352]: [‘<p>3p</p>‘]
- In [353]: sel.xpath(‘//div/p[last()-1]‘).extract()
- Out[353]: [‘<p>2p</p>‘]
第几个子节点 css和xpath写法
- 排除一个属性的节点可以使用//tbody/tr[not(@class)]来写
- 排除一个或者两个属性可以使用//tbody/tr[not(@class or @id)]来选择。
- 排查某属性值可使用//tbody/tr[not(@class='xxx')]
not
- 一、节点的前后节点:
- 当前节点的祖先节点:
- //*[title=""]/ancestor::*
- 当前节点的父节点:
- //*[title=""]/parent::*
- //*[title=""]/..
- 当前节点的开始标签之前的所有节点 /preceding
- 当前节点的结束标签之后的所有节点 /following
- 当前节点之后的兄弟节点 /following-sibling::*
- 当前节点之前的兄弟节点 /preceding-sibling::*
- 当前节点的所有后代(子,孙) /descendant
- 包含指定文本:span[contains(text(), "指定文本内容")]
- 取最后一个子元素 //div[@class='box-nav']/a[last()]
- 二、选取包含指定文本的标签前面的某个兄弟节点
- html代码如下:
- <div class="tittle_x F_Left">
- <a href="http://www.ccidnet.com/">首页</a>
- <em>></em>
- <a href="http://www.ccidnet.com/news/">新闻</a>
- <em>></em>
- <a href="http://www.ccidnet.com/news/focus/">焦点直击</a>
- <em>></em>
- <a href="#">正文 </a>
- </div>
- 如上图与代码,我想选择“正文”前面的“焦点直击”为类型,那么可以这样写:
- 类型: //div[@class='tittle_x F_Left']/a[contains(text(),'正文')]/preceding-sibling::a[1]
- 三、选取指定节点之前的不带标签的文本
- 例如:选class="bb"前面的文本:“这是文本。”
- <span>
- <span class="aa">文本</span>
- 这是文本。
- <a class="bb">文本</a>
- </span>
- 可以这样写: //span[@class='aa'][2]/following::text()[1]
- ---------------------
- 作者:那个南墙
- 来源:CSDN
- 原文:https://blog.csdn.net/baidu_38414830/article/details/70325232
- 版权声明:本文为博主原创文章,转载请附上博文链接!
关系选择 即祖先父母后代兄弟
- 获取某标签的多个子标签的text
- xpath("string(.)")
- response.xpath("//div[@class='tpc_content do_not_catch']")[0].xpath("string(.)").extract_first()
- # 这个是获取子标签text的列表
- response.xpath("//div[@class='tpc_content do_not_catch']")[0].xpath("text()").extract()
- 获取单个标签的text
- css("::text")
- xpath("xxxx/text()")
获取多个子标签的text
- 1.CSS写法
- 1.1 获取属性值:
- 标签名::attr(属性名)
- 例:response.css('base::attr(href)')
- 1.2 获取元素内容
- 标签名::text
- 例:response.css('title::text')
- 1.3遇到有相同的标签时,需要在[ ]中加限定内容:
- 标签名[]::attr(属性名)
- 例:response.css('a[href*=image]::attr(href)')
- 2.XPath方法
- 2.1 获取属性值:
- //标签名/@属性名
- 例:response.xpath('//base/@href')
- 2.2 获取元素内容:
- //标签名/text()
- 例:response.xpath('//title/text()')
- 2.3 遇到有相同的标签时,需要在[ ]中加限定内容:
- //标签名[contains(@属性名,"标签名")]/@属性名
- 例:response.xpath('//div[@id="images"]/a/text()')
- 注意:这里id对应的属性值必须用双引号,在scrapy的shell命令模式中,单引号一直报语法错误
补充
- xpath中没有提供对class的原生查找方法。但是 stackoverflow 看到了一个很有才的回答:
- This selector should work but will be more efficient if you replace it with your suited markup:
- 这个表达式应该是可行的。不过如果你把class换成更好识别的标识执行效率会更高
- //*[contains(@class, 'Test')]
- But since this will also match cases like class="Testvalue" or class="newTest".
- 但是这个表达式会把类似 class="Testvalue" 或者 class="newTest"也匹配出来。
- //*[contains(concat(' ', @class, ' '), ' Test ')]
- If you wished to be really certain that it will match correctly, you could also use the normalize-space function to clean up stray whitespace characters around the class name (as mentioned by @Terry)
- 如果您希望确定它能够正确匹配,则还可以使用 normalize-space 函数清除类名周围的空白字符(如@Terry所述)
- //*[contains(concat(' ', normalize-space(@class), ' '), ' Test ')]
- Note that in all these versions, the * should best be replaced by whatever element name you actually wish to match, unless you wish to search each and every element in the document for the given condition.
- 请注意在所有这些版本里,除非你想要在所有元素里搜索带有这些条件的元素,否则你最好把*号替换成你想要匹配的具体的元素名(标签名)。
一些函数
数据格式化、持久化
爬取的数据可在parse中直接处理。也可以使用Item进行格式化,交给pipelines进行持久化处理。
- import scrapy
- from scrapy.selector import HtmlXPathSelector
- from scrapy.http.request import Request
- from scrapy.http.cookies import CookieJar
- from scrapy import FormRequest
- class XiaoHuarSpider(scrapy.Spider):
- # 爬虫应用的名称,通过此名称启动爬虫命令
- name = "xiaohuar"
- # 允许的域名
- allowed_domains = ["xiaohuar.com"]
- start_urls = [
- "http://www.xiaohuar.com/list-1-1.html",
- ]
- # custom_settings = {
- # 'ITEM_PIPELINES':{
- # 'spider1.pipelines.JsonPipeline': 100
- # }
- # }
- has_request_set = {}
- def parse(self, response):
- # 分析页面
- # 找到页面中符合规则的内容(校花图片),保存
- # 找到所有的a标签,再访问其他a标签,一层一层的搞下去
- hxs = HtmlXPathSelector(response)
- items = hxs.select('//div[@class="item_list infinite_scroll"]/div')
- for item in items:
- src = item.select('.//div[@class="img"]/a/img/@src').extract_first()
- name = item.select('.//div[@class="img"]/span/text()').extract_first()
- school = item.select('.//div[@class="img"]/div[@class="btns"]/a/text()').extract_first()
- url = "http://www.xiaohuar.com%s" % src
- from ..items import XiaoHuarItem
- obj = XiaoHuarItem(name=name, school=school, url=url)
- yield obj
- urls = hxs.select('//a[re:test(@href, "http://www.xiaohuar.com/list-1-\d+.html")]/@href')
- for url in urls:
- key = self.md5(url)
- if key in self.has_request_set:
- pass
- else:
- self.has_request_set[key] = url
- req = Request(url=url,method='GET',callback=self.parse)
- yield req
- @staticmethod
- def md5(val):
- import hashlib
- ha = hashlib.md5()
- ha.update(bytes(val, encoding='utf-8'))
- key = ha.hexdigest()
- return key
spiders/xiahuar.py
- import scrapy
- class XiaoHuarItem(scrapy.Item):
- name = scrapy.Field()
- school = scrapy.Field()
- url = scrapy.Field()
items.py
- import json
- import os
- import requests
- class JsonPipeline(object):
- def __init__(self):
- self.file = open('xiaohua.txt', 'w')
- def process_item(self, item, spider):
- v = json.dumps(dict(item), ensure_ascii=False)
- self.file.write(v)
- self.file.write('\n')
- self.file.flush()
- return item
- class FilePipeline(object):
- def __init__(self):
- if not os.path.exists('imgs'):
- os.makedirs('imgs')
- def process_item(self, item, spider):
- response = requests.get(item['url'], stream=True)
- file_name = '%s_%s.jpg' % (item['name'], item['school'])
- with open(os.path.join('imgs', file_name), mode='wb') as f:
- f.write(response.content)
- return item
pipelines.py
- ITEM_PIPELINES = {
- 'spider1.pipelines.JsonPipeline': 100,
- 'spider1.pipelines.FilePipeline': 300,
- }
- # 每行后面的整型值,确定了他们运行的顺序,item按数字从低到高的顺序,通过pipeline,通常将这些数字定义在0-1000范围内。
settings.py
对于pipeline可以做更多,如下:
- from scrapy.exceptions import DropItem
- class CustomPipeline(object):
- def __init__(self,v):
- self.value = v
- def process_item(self, item, spider):
- # 操作并进行持久化
- # return表示会被后续的pipeline继续处理
- return item
- # 表示将item丢弃,不会被后续pipeline处理
- # raise DropItem()
- @classmethod
- def from_crawler(cls, crawler):
- """
- 初始化时候,用于创建pipeline对象
- :param crawler:
- :return:
- """
- val = crawler.settings.getint('MMMM')
- return cls(val)
- def open_spider(self,spider):
- """
- 爬虫开始执行时,调用
- :param spider:
- :return:
- """
- print('')
- def close_spider(self,spider):
- """
- 爬虫关闭时,被调用
- :param spider:
- :return:
- """
- print('')
自定义pipeline
中间件
- class SpiderMiddleware(object):
- def process_spider_input(self,response, spider):
- """
- 下载完成,执行,然后交给parse处理
- :param response:
- :param spider:
- :return:
- """
- pass
- def process_spider_output(self,response, result, spider):
- """
- spider处理完成,返回时调用
- :param response:
- :param result:
- :param spider:
- :return: 必须返回包含 Request 或 Item 对象的可迭代对象(iterable)
- """
- return result
- def process_spider_exception(self,response, exception, spider):
- """
- 异常调用
- :param response:
- :param exception:
- :param spider:
- :return: None,继续交给后续中间件处理异常;含 Response 或 Item 的可迭代对象(iterable),交给调度器或pipeline
- """
- return None
- def process_start_requests(self,start_requests, spider):
- """
- 爬虫启动时调用
- :param start_requests:
- :param spider:
- :return: 包含 Request 对象的可迭代对象
- """
- return start_requests
爬虫中间件
- class DownMiddleware1(object):
- def process_request(self, request, spider):
- """
- 请求需要被下载时,经过所有下载器中间件的process_request调用
- :param request:
- :param spider:
- :return:
- None,继续后续中间件去下载;
- Response对象,停止process_request的执行,开始执行process_response
- Request对象,停止中间件的执行,将Request重新调度器
- raise IgnoreRequest异常,停止process_request的执行,开始执行process_exception
- """
- pass
- def process_response(self, request, response, spider):
- """
- spider处理完成,返回时调用
- :param response:
- :param result:
- :param spider:
- :return:
- Response 对象:转交给其他中间件process_response
- Request 对象:停止中间件,request会被重新调度下载
- raise IgnoreRequest 异常:调用Request.errback
- """
- print('response1')
- return response
- def process_exception(self, request, exception, spider):
- """
- 当下载处理器(download handler)或 process_request() (下载中间件)抛出异常
- :param response:
- :param exception:
- :param spider:
- :return:
- None:继续交给后续中间件处理异常;
- Response对象:停止后续process_exception方法
- Request对象:停止中间件,request将会被重新调用下载
- """
- return None
下载器中间件
- 首先需要明确:
- 请求是引擎发出来的,不是爬虫发出来的
- 引擎从爬虫拿url,给调度器去重,同时会从调度器的任务队列里取出一个任务,给下载器
- 下载器下载完以后,下载器把response返回给引擎
- 先说process_request(request, spider)
- 当设置了很多中间件的时候,会按照setting里的设置,按照从小到大执行
- 假如有两个中间件的等级一样,这两个中间都会被执行。(执行顺序没有得出有效结论)
- 即使某个中间件的设置时错的,比如,故意在代理中间件里给一个错误的ip,依然不会中断中间件的执行,也就是,scrapy无法检测代理中的操作是否合法。
- 经过中间件故意的错误的加代理,下载器仍然去执行这个任务了,只不过根据另一个中间件:RetryMiddleware 的设定去处理了这个请求(默认的是,请求连续失败三次退出任务)
- 当这个请求第一次失败时候,依然会再次经过设置的中间件。
- 第一个发出error信号的不是引擎,是scraper,它是连接引擎、爬虫、下载器的一个东西。。。。然后引擎才发出错误信号
- (重点)每一个任务,也就是每一个请求,不管在什么情况下,只要设置了中间件,就会孜孜不倦的去通过这些中间件,然后到达下载器
- 然后说process_response(request, response, spider)
- 因为获取的响应是从下载器到引擎的,所以response经过中间件的顺序刚好与request相反
- 是从大到小执行的
- ---------------------
- 作者:fiery_heart
- 来源:CSDN
- 原文:https://blog.csdn.net/fiery_heart/article/details/82229871
- 版权声明:本文为博主原创文章,转载请附上博文链接!
下载中间件的总结(转)
- class MyMiddleware(object):
- # Not all methods need to be defined. If a method is not defined,
- # scrapy acts as if the spider middleware does not modify the
- # passed objects.
- @classmethod
- def from_crawler(cls, crawler):
- # This method is used by Scrapy to create your spiders.
- s = cls()
- crawler.signals.connect(s.spider_opened, signal=signals.spider_opened)
- crawler.signals.connect(s.item_scraped, signal=signals.item_scraped)
- crawler.signals.connect(s.spider_closed, signal=signals.spider_closed)
- crawler.signals.connect(s.spider_error, signal=signals.spider_error)
- crawler.signals.connect(s.spider_idle, signal=signals.spider_idle)
- return s
- # 当spider开始爬取时发送该信号。该信号一般用来分配spider的资源,不过其也能做任何事。
- def spider_opened(self, spider):
- spider.logger.info('pa chong kai shi le: %s' % spider.name)
- print('start','')
- def item_scraped(self,item, response, spider):
- global hahaha
- hahaha += 1
- # 当某个spider被关闭时,该信号被发送。该信号可以用来释放每个spider在 spider_opened 时占用的资源。
- def spider_closed(self,spider, reason):
- print('-------------------------------all over------------------------------------------')
- global hahaha
- print(spider.name,' closed')
- # 当spider的回调函数产生错误时(例如,抛出异常),该信号被发送。
- def spider_error(self,failure, response, spider):
- code = response.status
- print('spider error')
- # 当spider进入空闲(idle)状态时该信号被发送。空闲意味着:
- # requests正在等待被下载
- # requests被调度
- # items正在item pipeline中被处理
- def spider_idle(self,spider):
- for i in range(10):
- print(spider.name)
- '''
- start 1
- jiandan
- jiandan
- jiandan
- jiandan
- jiandan
- jiandan
- jiandan
- jiandan
- jiandan
- jiandan
- -------------------------------all over------------------------------------------
- jiandan closed
- '''
信号在中间件的使用
自定义命令
- 在spiders同级创建任意目录,如:commands
- 在其中创建 crawlall.py 文件 (此处文件名就是自定义的命令)
- from scrapy.commands import ScrapyCommand
- from scrapy.utils.project import get_project_settings
- class Command(ScrapyCommand):
- requires_project = True
- def syntax(self):
- return '[options]'
- def short_desc(self):
- return 'Runs all of the spiders'
- def run(self, args, opts):
- spider_list = self.crawler_process.spiders.list()
- for name in spider_list:
- self.crawler_process.crawl(name, **opts.__dict__)
- self.crawler_process.start()
crawlall.py
- 在settings.py 中添加配置 COMMANDS_MODULE = '项目名称.目录名称'
- 在项目目录执行命令:scrapy crawlall
自定义扩展(涉及信号)
自定义扩展时,利用信号在指定位置注册制定操作
- 信号:
- engine_started = object()
- engine_stopped = object()
- spider_opened = object()
- spider_idle = object()
- spider_closed = object()
- spider_error = object()
- request_scheduled = object()
- request_dropped = object()
- response_received = object()
- response_downloaded = object()
- item_scraped = object()
- item_dropped = object()
- 用法
- crawler.signals.connect(ext.spider_opened, signal=signals.spider_opened) # 当开始spider时,执行本类中用户自定义的spider_opened方法
信号的类别 和 用法
- from scrapy import signals
- class MyExtension(object):
- def __init__(self, value):
- self.value = value
- @classmethod
- def from_crawler(cls, crawler):
- val = crawler.settings.getint('MMMM')
- ext = cls(val)
- crawler.signals.connect(ext.spider_opened, signal=signals.spider_opened)
- crawler.signals.connect(ext.spider_closed, signal=signals.spider_closed)
- return ext
- def spider_opened(self, spider):
- print('open')
- def spider_closed(self, spider):
- print('close')
自定义扩展
信号在扩展的使用
跟中间件类似,先自己创建一个py文件(名字自定义)放在项目目录里,再在settings文件中添加extension。
- # -*- coding:utf-8 -*-
- from scrapy import signals
- class MyExtension(object):
- def __init__(self,**kwargs):
- self.__dict__.update(kwargs)
- @classmethod
- def from_crawler(cls, crawler):
- ext = cls(a=1,b=2,x=11,y=12)
- crawler.signals.connect(ext.spider_opened, signal=signals.spider_opened)
- crawler.signals.connect(ext.spider_closed, signal=signals.spider_closed)
- return ext
- def spider_opened(self, spider):
- print('open')
- print(self.a)
- print(self.b)
- def spider_closed(self, spider):
- print('close')
- print(self.x)
- print(self.y)
项目名称/extension.py
- EXTENSIONS = {
- # 'scrapy.extensions.telnet.TelnetConsole': None,
- "cl.extensions.MyExtension":200,
- }
settings.py
- open
- 1
- 2
- close
- 11
- 12
注1:信号可在中间件使用,见中间件部分。
注2:信号可配合数据采集器,见后面笔记。
避免重复访问(去重)
- scrapy默认使用 scrapy.dupefilter.RFPDupeFilter 进行去重,相关去重配置有:
- DUPEFILTER_CLASS = 'scrapy.dupefilter.RFPDupeFilter'
- DUPEFILTER_DEBUG = False
- JOBDIR = "保存范文记录的日志路径,如:/root/" # 最终路径为 /root/requests.seen
Scrapy中默认配置
- class RepeatUrl:
- def __init__(self):
- self.visited_url = set()
- @classmethod
- def from_settings(cls, settings):
- """
- 初始化时,调用
- :param settings:
- :return:
- """
- return cls()
- def request_seen(self, request):
- """
- 检测当前请求是否已经被访问过
- :param request:
- :return: True表示已经访问过;False表示未访问过
- """
- if request.url in self.visited_url:
- return True
- self.visited_url.add(request.url)
- return False
- def open(self):
- """
- 开始爬去请求时,调用
- :return:
- """
- print('open replication')
- def close(self, reason):
- """
- 结束爬虫爬取时,调用
- :param reason:
- :return:
- """
- print('close replication')
- def log(self, request, spider):
- """
- 记录日志
- :param request:
- :param spider:
- :return:
- """
- print('repeat', request.url)
自定义URL去重操作
settings说明
http://scrapy-chs.readthedocs.io/zh_CN/latest/topics/settings.html
- # -*- coding: utf-8 -*-
- # Scrapy settings for step8_king project
- #
- # For simplicity, this file contains only settings considered important or
- # commonly used. You can find more settings consulting the documentation:
- #
- # http://doc.scrapy.org/en/latest/topics/settings.html
- # http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html
- # http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html
- # 1. 爬虫名称
- BOT_NAME = 'step8_king'
- # 2. 爬虫应用路径
- SPIDER_MODULES = ['step8_king.spiders']
- NEWSPIDER_MODULE = 'step8_king.spiders'
- # Crawl responsibly by identifying yourself (and your website) on the user-agent
- # 3. 客户端 user-agent请求头
- # USER_AGENT = 'step8_king (+http://www.yourdomain.com)'
- # Obey robots.txt rules
- # 4. 禁止爬虫配置
- # ROBOTSTXT_OBEY = False
- # Configure maximum concurrent requests performed by Scrapy (default: 16)
- # 5. 并发请求数
- # CONCURRENT_REQUESTS = 4
- # Configure a delay for requests for the same website (default: 0)
- # See http://scrapy.readthedocs.org/en/latest/topics/settings.html#download-delay
- # See also autothrottle settings and docs
- # 6. 延迟下载秒数
- # DOWNLOAD_DELAY = 2
- # The download delay setting will honor only one of:
- # 7. 单域名访问并发数,并且延迟下次秒数也应用在每个域名
- # CONCURRENT_REQUESTS_PER_DOMAIN = 2
- # 单IP访问并发数,如果有值则忽略:CONCURRENT_REQUESTS_PER_DOMAIN,并且延迟下次秒数也应用在每个IP
- # CONCURRENT_REQUESTS_PER_IP = 3
- # Disable cookies (enabled by default)
- # 8. 是否支持cookie,cookiejar进行操作cookie
- # COOKIES_ENABLED = True
- # COOKIES_DEBUG = True
- # Disable Telnet Console (enabled by default)
- # 9. Telnet用于查看当前爬虫的信息,操作爬虫等...
- # 使用telnet ip port ,然后通过命令操作
- # TELNETCONSOLE_ENABLED = True
- # TELNETCONSOLE_HOST = '127.0.0.1'
- # TELNETCONSOLE_PORT = [6023,]
- # 10. 默认请求头
- # 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',
- # }
- # Configure item pipelines
- # See http://scrapy.readthedocs.org/en/latest/topics/item-pipeline.html
- # 11. 定义pipeline处理请求
- # ITEM_PIPELINES = {
- # 'step8_king.pipelines.JsonPipeline': 700,
- # 'step8_king.pipelines.FilePipeline': 500,
- # }
- # 12. 自定义扩展,基于信号进行调用
- # Enable or disable extensions
- # See http://scrapy.readthedocs.org/en/latest/topics/extensions.html
- # EXTENSIONS = {
- # # 'step8_king.extensions.MyExtension': 500,
- # }
- # 13. 爬虫允许的最大深度,可以通过meta查看当前深度;0表示无深度
- # DEPTH_LIMIT = 3
- # 14. 爬取时,0表示深度优先Lifo(默认);1表示广度优先FiFo
- # 后进先出,深度优先
- # DEPTH_PRIORITY = 0
- # SCHEDULER_DISK_QUEUE = 'scrapy.squeue.PickleLifoDiskQueue'
- # SCHEDULER_MEMORY_QUEUE = 'scrapy.squeue.LifoMemoryQueue'
- # 先进先出,广度优先
- # DEPTH_PRIORITY = 1
- # SCHEDULER_DISK_QUEUE = 'scrapy.squeue.PickleFifoDiskQueue'
- # SCHEDULER_MEMORY_QUEUE = 'scrapy.squeue.FifoMemoryQueue'
- # 15. 调度器队列
- # SCHEDULER = 'scrapy.core.scheduler.Scheduler'
- # from scrapy.core.scheduler import Scheduler
- # 16. 访问URL去重
- # DUPEFILTER_CLASS = 'step8_king.duplication.RepeatUrl'
- # Enable and configure the AutoThrottle extension (disabled by default)
- # See http://doc.scrapy.org/en/latest/topics/autothrottle.html
- """
- 17. 自动限速算法
- from scrapy.contrib.throttle import AutoThrottle
- 自动限速设置
- 1. 获取最小延迟 DOWNLOAD_DELAY
- 2. 获取最大延迟 AUTOTHROTTLE_MAX_DELAY
- 3. 设置初始下载延迟 AUTOTHROTTLE_START_DELAY
- 4. 当请求下载完成后,获取其"连接"时间 latency,即:请求连接到接受到响应头之间的时间
- 5. 用于计算的... AUTOTHROTTLE_TARGET_CONCURRENCY
- target_delay = latency / self.target_concurrency
- new_delay = (slot.delay + target_delay) / 2.0 # 表示上一次的延迟时间
- new_delay = max(target_delay, new_delay)
- new_delay = min(max(self.mindelay, new_delay), self.maxdelay)
- slot.delay = new_delay
- """
- # 开始自动限速
- # AUTOTHROTTLE_ENABLED = True
- # The initial download delay
- # 初始下载延迟
- # AUTOTHROTTLE_START_DELAY = 5
- # The maximum download delay to be set in case of high latencies
- # 最大下载延迟
- # AUTOTHROTTLE_MAX_DELAY = 10
- # The average number of requests Scrapy should be sending in parallel to each remote server
- # 平均每秒并发数
- # AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0
- # Enable showing throttling stats for every response received:
- # 是否显示
- # AUTOTHROTTLE_DEBUG = True
- # Enable and configure HTTP caching (disabled by default)
- # See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings
- """
- 18. 启用缓存
- 目的用于将已经发送的请求或相应缓存下来,以便以后使用
- from scrapy.downloadermiddlewares.httpcache import HttpCacheMiddleware
- from scrapy.extensions.httpcache import DummyPolicy
- from scrapy.extensions.httpcache import FilesystemCacheStorage
- """
- # 是否启用缓存策略
- # HTTPCACHE_ENABLED = True
- # 缓存策略:所有请求均缓存,下次在请求直接访问原来的缓存即可
- # HTTPCACHE_POLICY = "scrapy.extensions.httpcache.DummyPolicy"
- # 缓存策略:根据Http响应头:Cache-Control、Last-Modified 等进行缓存的策略
- # HTTPCACHE_POLICY = "scrapy.extensions.httpcache.RFC2616Policy"
- # 缓存超时时间
- # HTTPCACHE_EXPIRATION_SECS = 0
- # 缓存保存路径
- # HTTPCACHE_DIR = 'httpcache'
- # 缓存忽略的Http状态码
- # HTTPCACHE_IGNORE_HTTP_CODES = []
- # 缓存存储的插件
- # HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'
- """
- 19. 代理,需要在环境变量中设置
- from scrapy.contrib.downloadermiddleware.httpproxy import HttpProxyMiddleware
- 方式一:使用默认
- os.environ
- {
- http_proxy:http://root:woshiniba@192.168.11.11:9999/
- https_proxy:http://192.168.11.11:9999/
- }
- 方式二:使用自定义下载中间件
- def to_bytes(text, encoding=None, errors='strict'):
- if isinstance(text, bytes):
- return text
- if not isinstance(text, six.string_types):
- raise TypeError('to_bytes must receive a unicode, str or bytes '
- 'object, got %s' % type(text).__name__)
- if encoding is None:
- encoding = 'utf-8'
- return text.encode(encoding, errors)
- class ProxyMiddleware(object):
- def process_request(self, request, spider):
- PROXIES = [
- {'ip_port': '111.11.228.75:80', 'user_pass': ''},
- {'ip_port': '120.198.243.22:80', 'user_pass': ''},
- {'ip_port': '111.8.60.9:8123', 'user_pass': ''},
- {'ip_port': '101.71.27.120:80', 'user_pass': ''},
- {'ip_port': '122.96.59.104:80', 'user_pass': ''},
- {'ip_port': '122.224.249.122:8088', 'user_pass': ''},
- ]
- proxy = random.choice(PROXIES)
- if proxy['user_pass'] is not None:
- request.meta['proxy'] = to_bytes("http://%s" % proxy['ip_port'])
- encoded_user_pass = base64.encodestring(to_bytes(proxy['user_pass']))
- request.headers['Proxy-Authorization'] = to_bytes('Basic ' + encoded_user_pass)
- print "**************ProxyMiddleware have pass************" + proxy['ip_port']
- else:
- print "**************ProxyMiddleware no pass************" + proxy['ip_port']
- request.meta['proxy'] = to_bytes("http://%s" % proxy['ip_port'])
- DOWNLOADER_MIDDLEWARES = {
- 'step8_king.middlewares.ProxyMiddleware': 500,
- }
- """
- """
- 20. Https访问
- Https访问时有两种情况:
- 1. 要爬取网站使用的可信任证书(默认支持)
- DOWNLOADER_HTTPCLIENTFACTORY = "scrapy.core.downloader.webclient.ScrapyHTTPClientFactory"
- DOWNLOADER_CLIENTCONTEXTFACTORY = "scrapy.core.downloader.contextfactory.ScrapyClientContextFactory"
- 2. 要爬取网站使用的自定义证书
- DOWNLOADER_HTTPCLIENTFACTORY = "scrapy.core.downloader.webclient.ScrapyHTTPClientFactory"
- DOWNLOADER_CLIENTCONTEXTFACTORY = "step8_king.https.MySSLFactory"
- # https.py
- from scrapy.core.downloader.contextfactory import ScrapyClientContextFactory
- from twisted.internet.ssl import (optionsForClientTLS, CertificateOptions, PrivateCertificate)
- class MySSLFactory(ScrapyClientContextFactory):
- def getCertificateOptions(self):
- from OpenSSL import crypto
- v1 = crypto.load_privatekey(crypto.FILETYPE_PEM, open('/Users/wupeiqi/client.key.unsecure', mode='r').read())
- v2 = crypto.load_certificate(crypto.FILETYPE_PEM, open('/Users/wupeiqi/client.pem', mode='r').read())
- return CertificateOptions(
- privateKey=v1, # pKey对象
- certificate=v2, # X509对象
- verify=False,
- method=getattr(self, 'method', getattr(self, '_ssl_method', None))
- )
- 其他:
- 相关类
- scrapy.core.downloader.handlers.http.HttpDownloadHandler
- scrapy.core.downloader.webclient.ScrapyHTTPClientFactory
- scrapy.core.downloader.contextfactory.ScrapyClientContextFactory
- 相关配置
- DOWNLOADER_HTTPCLIENTFACTORY
- DOWNLOADER_CLIENTCONTEXTFACTORY
- """
- """
- 21. 爬虫中间件
- class SpiderMiddleware(object):
- def process_spider_input(self,response, spider):
- '''
- 下载完成,执行,然后交给parse处理
- :param response:
- :param spider:
- :return:
- '''
- pass
- def process_spider_output(self,response, result, spider):
- '''
- spider处理完成,返回时调用
- :param response:
- :param result:
- :param spider:
- :return: 必须返回包含 Request 或 Item 对象的可迭代对象(iterable)
- '''
- return result
- def process_spider_exception(self,response, exception, spider):
- '''
- 异常调用
- :param response:
- :param exception:
- :param spider:
- :return: None,继续交给后续中间件处理异常;含 Response 或 Item 的可迭代对象(iterable),交给调度器或pipeline
- '''
- return None
- def process_start_requests(self,start_requests, spider):
- '''
- 爬虫启动时调用
- :param start_requests:
- :param spider:
- :return: 包含 Request 对象的可迭代对象
- '''
- return start_requests
- 内置爬虫中间件:
- 'scrapy.contrib.spidermiddleware.httperror.HttpErrorMiddleware': 50,
- 'scrapy.contrib.spidermiddleware.offsite.OffsiteMiddleware': 500,
- 'scrapy.contrib.spidermiddleware.referer.RefererMiddleware': 700,
- 'scrapy.contrib.spidermiddleware.urllength.UrlLengthMiddleware': 800,
- 'scrapy.contrib.spidermiddleware.depth.DepthMiddleware': 900,
- """
- # from scrapy.contrib.spidermiddleware.referer import RefererMiddleware
- # Enable or disable spider middlewares
- # See http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html
- SPIDER_MIDDLEWARES = {
- # 'step8_king.middlewares.SpiderMiddleware': 543,
- }
- """
- 22. 下载中间件
- class DownMiddleware1(object):
- def process_request(self, request, spider):
- '''
- 请求需要被下载时,经过所有下载器中间件的process_request调用
- :param request:
- :param spider:
- :return:
- None,继续后续中间件去下载;
- Response对象,停止process_request的执行,开始执行process_response
- Request对象,停止中间件的执行,将Request重新调度器
- raise IgnoreRequest异常,停止process_request的执行,开始执行process_exception
- '''
- pass
- def process_response(self, request, response, spider):
- '''
- spider处理完成,返回时调用
- :param response:
- :param result:
- :param spider:
- :return:
- Response 对象:转交给其他中间件process_response
- Request 对象:停止中间件,request会被重新调度下载
- raise IgnoreRequest 异常:调用Request.errback
- '''
- print('response1')
- return response
- def process_exception(self, request, exception, spider):
- '''
- 当下载处理器(download handler)或 process_request() (下载中间件)抛出异常
- :param response:
- :param exception:
- :param spider:
- :return:
- None:继续交给后续中间件处理异常;
- Response对象:停止后续process_exception方法
- Request对象:停止中间件,request将会被重新调用下载
- '''
- return None
- 默认下载中间件
- {
- 'scrapy.contrib.downloadermiddleware.robotstxt.RobotsTxtMiddleware': 100,
- 'scrapy.contrib.downloadermiddleware.httpauth.HttpAuthMiddleware': 300,
- 'scrapy.contrib.downloadermiddleware.downloadtimeout.DownloadTimeoutMiddleware': 350,
- 'scrapy.contrib.downloadermiddleware.useragent.UserAgentMiddleware': 400,
- 'scrapy.contrib.downloadermiddleware.retry.RetryMiddleware': 500,
- 'scrapy.contrib.downloadermiddleware.defaultheaders.DefaultHeadersMiddleware': 550,
- 'scrapy.contrib.downloadermiddleware.redirect.MetaRefreshMiddleware': 580,
- 'scrapy.contrib.downloadermiddleware.httpcompression.HttpCompressionMiddleware': 590,
- 'scrapy.contrib.downloadermiddleware.redirect.RedirectMiddleware': 600,
- 'scrapy.contrib.downloadermiddleware.cookies.CookiesMiddleware': 700,
- 'scrapy.contrib.downloadermiddleware.httpproxy.HttpProxyMiddleware': 750,
- 'scrapy.contrib.downloadermiddleware.chunked.ChunkedTransferMiddleware': 830,
- 'scrapy.contrib.downloadermiddleware.stats.DownloaderStats': 850,
- 'scrapy.contrib.downloadermiddleware.httpcache.HttpCacheMiddleware': 900,
- }
- """
- # from scrapy.contrib.downloadermiddleware.httpauth import HttpAuthMiddleware
- # Enable or disable downloader middlewares
- # See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html
- # DOWNLOADER_MIDDLEWARES = {
- # 'step8_king.middlewares.DownMiddleware1': 100,
- # 'step8_king.middlewares.DownMiddleware2': 500,
- # }
- settings
settings.py参数说明
补充:这里有一些没写到的:https://www.cnblogs.com/Chenjiabing/p/6907251.html
- 暂停和恢复爬虫
- 初学者最头疼的事情就是没有处理好异常,当爬虫爬到一半的时候突然因为错误而中断了,但是这时又不能从中断的地方开始继续爬,顿时感觉心里日了狗,但是这里有一个方法可以暂时的存储你爬的状态,当爬虫中断的时候继续打开后依然可以从中断的地方爬,不过虽说持久化可以有效的处理,但是要注意的是当使用cookie临时的模拟登录状态的时候要注意cookie的有效期
- 只需要在setting.py中JOB_DIR=file_name其中填的是你的文件目录,注意这里的目录不允许共享,只能存储单独的一个spdire的运行状态,如果你不想在从中断的地方开始运行,只需要将这个文件夹删除即可
- 当然还有其他的放法:scrapy crawl somespider -s JOBDIR=crawls/somespider-1,这个是在终端启动爬虫的时候调用的,可以通过ctr+c中断,恢复还是输入上面的命令
暂停和恢复爬虫
- class xxxSpider(scrapy.Spider):
- name = 'xxx'
- '''略'''
- def parse(self, response):
- print(response.url)
- print(self.settings["ABCD"])
其他
待补充
TinyScrapy
解读原理之循序渐进twisted
- from twisted.web.client import getPage, defer
- from twisted.internet import reactor
- def all_done(arg):
- reactor.stop()
- def callback(contents):
- print(contents)
- deferred_list = []
- url_list = ['http://www.bing.com', 'http://www.baidu.com', ]
- for url in url_list:
- deferred = getPage(bytes(url, encoding='utf8'))
- deferred.addCallback(callback) # 单个deferred完成任务时执行的callback
- deferred_list.append(deferred)
- dlist = defer.DeferredList(deferred_list)
- dlist.addBoth(all_done) # 所有deferred返回结果完成任务时执行的callback
- reactor.run()
1、执行多个url爬取任务,成功后各自执行callback,以及整个大任务执行callback
- from twisted.web.client import getPage, defer
- from twisted.internet import reactor
- def all_done(arg):
- reactor.stop()
- def onedone(response):
- print(response)
- @defer.inlineCallbacks
- def task(url):
- deferred = getPage(bytes(url, encoding='utf8'))
- deferred.addCallback(onedone)
- yield deferred
- deferred_list = []
- url_list = ['http://www.bing.com', 'http://www.baidu.com', ]
- for url in url_list:
- deferred = task(url) # 把下面的两个操作封装进task,同样是每个任务单独执行callback
- # deferred = getPage(url)
- # deferred.addCallback(onedone)
- deferred_list.append(deferred)
- dlist = defer.DeferredList(deferred_list)
- dlist.addBoth(all_done) # 所有deferred返回结果完成任务时执行的callback
- reactor.run()
2、把每个任务及执行callback封装到一个函数里
- from twisted.web.client import getPage, defer
- from twisted.internet import reactor
- def all_done(arg):
- reactor.stop()
- def onedone(response):
- print(response)
- @defer.inlineCallbacks
- def task():
- deferred2 = getPage(bytes("http://www.baidu.com", encoding='utf8'))
- deferred2.addCallback(onedone)
- yield deferred2
- deferred1 = getPage(bytes("http://www.google.com", encoding='utf8')) # 访问一个无法访问的url,因此无法执行callback
- deferred1.addCallback(onedone)
- yield deferred1
- ret = task()
- ret.addBoth(all_done) # 所有deferred返回结果完成任务时执行的callback
- reactor.run()
3、执行的任务中存在无法访问的url,导致不能执行该单独任务的callback
- from twisted.web.client import getPage, defer
- from twisted.internet import reactor
- def all_done(arg):
- reactor.stop()
- def onedone(response):
- print(response)
- @defer.inlineCallbacks
- def task():
- deferred2 = getPage(bytes("http://www.baidu.com", encoding='utf8'))
- deferred2.addCallback(onedone)
- yield deferred2
- stop_deferred = defer.Deferred() # 此为任务卡死的deferred,如果不手动执行callback,则程序会一直卡在这
- stop_deferred.callback("aasdfsdf") # 手动执行callback
- yield stop_deferred
- ret = task()
- ret.addBoth(all_done) # 所有deferred返回结果完成任务时执行的callback
- reactor.run()
4、对卡死的任务手动执行callback
- from twisted.web.client import getPage, defer
- from twisted.internet import reactor
- running_list = []
- stop_deferred = None
- def all_done(arg):
- reactor.stop()
- def onedone(response,url):
- print(response)
- running_list.remove(url) # 把正在运行的任务列表去除本callback对应的已完成的url
- def check_empty(response):
- if not running_list: # 正在运行的任务列表,如果为空,在把卡死任务手动执行callback
- stop_deferred.callback(None)
- @defer.inlineCallbacks
- def open_spider(url): # 把爬虫任务封装到这
- deferred2 = getPage(bytes(url, encoding='utf8')) # 执行任务
- deferred2.addCallback(onedone, url) # callback
- deferred2.addCallback(check_empty) # 检查正在运行的任务是否为空,是,则手动执行callback
- yield deferred2
- @defer.inlineCallbacks
- def stop(url):
- global stop_deferred # 执行卡死任务
- stop_deferred = defer.Deferred()
- yield stop_deferred
- @defer.inlineCallbacks
- def task(url):
- yield open_spider(url) # 启动爬虫任务
- yield stop(url) # 启动卡死任务
- running_list.append("http://www.baidu.com")
- ret = task("http://www.baidu.com")
- ret.addBoth(all_done)
- reactor.run()
5、监控正在运行的任务列表,适时手动执行callback
- from twisted.web.client import getPage, defer
- from twisted.internet import reactor
- class ExecutionEngine(object):
- def __init__(self):
- self.stop_deferred = None
- self.running_list = []
- def onedone(self,response,url):
- print(response)
- self.running_list.remove(url) # 把正在运行的任务列表去除本callback对应的已完成的url
- def check_empty(self,response):
- if not self.running_list: # 监控正在运行的任务列表,如果为空,在把卡死任务手动执行callback
- self.stop_deferred.callback(None)
- @defer.inlineCallbacks
- def open_spider(self,url): # 爬虫任务
- deferred2 = getPage(bytes(url, encoding='utf8'))
- deferred2.addCallback(self.onedone, url) # 添加callback
- deferred2.addCallback(self.check_empty) # 添加callback2,监控正在运行的任务列表
- yield deferred2
- @defer.inlineCallbacks
- def stop(self,url):
- self.stop_deferred = defer.Deferred() # 卡死任务
- yield self.stop_deferred
- @defer.inlineCallbacks
- def task(url):
- engine = ExecutionEngine()
- engine.running_list.append(url) # 正在执行任务的列表添加新url
- yield engine.open_spider(url)
- yield engine.stop(url)
- def all_done(arg):
- reactor.stop()
- if __name__ == '__main__':
- ret = task("http://www.baidu.com")
- ret.addBoth(all_done)
- reactor.run()
6、把第5步进一步封装为类
开发TinyScrapy
- #!/usr/bin/env python
- # -*- coding:utf-8 -*-
- from twisted.web.client import getPage, defer
- from twisted.internet import reactor
- import queue
- class Request(object):
- def __init__(self, url, callback):
- self.url = url
- self.callback = callback
- class Scheduler(object):
- def __init__(self, engine):
- self.q = queue.Queue()
- self.engine = engine
- def enqueue_request(self, request):
- """
- :param request:
- :return:
- """
- self.q.put(request)
- def next_request(self):
- try:
- req = self.q.get(block=False)
- except Exception as e:
- req = None
- return req
- def size(self):
- return self.q.qsize()
- class ExecutionEngine(object):
- def __init__(self):
- self._closewait = None
- self.running = True
- self.start_requests = None
- self.scheduler = Scheduler(self)
- self.inprogress = set()
- def check_empty(self, response):
- if not self.running:
- self._closewait.callback('......')
- def _next_request(self):
- while self.start_requests:
- try:
- request = next(self.start_requests)
- except StopIteration:
- self.start_requests = None
- else:
- self.scheduler.enqueue_request(request)
- print(len(self.inprogress), self.scheduler.size())
- while len(self.inprogress) < 5 and self.scheduler.size() > 0: # 最大并发数为5
- request = self.scheduler.next_request()
- if not request:
- break
- self.inprogress.add(request)
- d = getPage(bytes(request.url, encoding='utf-8'))
- d.addBoth(self._handle_downloader_output, request)
- d.addBoth(lambda x, req: self.inprogress.remove(req), request)
- d.addBoth(lambda x: self._next_request())
- if len(self.inprogress) == 0 and self.scheduler.size() == 0:
- self._closewait.callback(None)
- def _handle_downloader_output(self, response, request):
- """
- 获取内容,执行回调函数,并且把回调函数中的返回值获取,并添加到队列中
- :param response:
- :param request:
- :return:
- """
- import types
- gen = request.callback(response)
- if isinstance(gen, types.GeneratorType):
- for req in gen:
- self.scheduler.enqueue_request(req)
- @defer.inlineCallbacks
- def start(self):
- self._closewait = defer.Deferred()
- yield self._closewait
- @defer.inlineCallbacks
- def open_spider(self, start_requests):
- self.start_requests = start_requests
- yield None
- reactor.callLater(0, self._next_request)
- @defer.inlineCallbacks
- def crawl(start_requests):
- engine = ExecutionEngine()
- start_requests = iter(start_requests)
- yield engine.open_spider(start_requests)
- yield engine.start()
- def _stop_reactor(_=None):
- reactor.stop()
- def parse(response):
- for i in range(10):
- yield Request("http://dig.chouti.com/all/hot/recent/%s" % i, callback)
- if __name__ == '__main__':
- start_requests = [Request("http://www.baidu.com", parse), Request("http://www.baidu1.com", parse), ]
- ret = crawl(start_requests)
- ret.addBoth(_stop_reactor)
- reactor.run()
精简版,方便理解流程
- #!/usr/bin/env python
- # -*- coding:utf-8 -*-
- from twisted.web.client import getPage, defer
- from twisted.internet import reactor
- import queue
- class Response(object):
- def __init__(self, body, request):
- self.body = body
- self.request = request
- self.url = request.url
- @property
- def text(self):
- return self.body.decode('utf-8')
- class Request(object):
- def __init__(self, url, callback=None):
- self.url = url
- self.callback = callback
- class Scheduler(object):
- def __init__(self, engine):
- self.q = queue.Queue()
- self.engine = engine
- def enqueue_request(self, request):
- self.q.put(request)
- def next_request(self):
- try:
- req = self.q.get(block=False)
- except Exception as e:
- req = None
- return req
- def size(self):
- return self.q.qsize()
- class ExecutionEngine(object):
- def __init__(self):
- self._closewait = None
- self.running = True
- self.start_requests = None
- self.scheduler = Scheduler(self)
- self.inprogress = set()
- def check_empty(self, response):
- if not self.running:
- self._closewait.callback('......')
- def _next_request(self):
- while self.start_requests:
- try:
- request = next(self.start_requests)
- except StopIteration:
- self.start_requests = None
- else:
- self.scheduler.enqueue_request(request)
- while len(self.inprogress) < 5 and self.scheduler.size() > 0: # 最大并发数为5
- request = self.scheduler.next_request()
- if not request:
- break
- self.inprogress.add(request)
- d = getPage(bytes(request.url, encoding='utf-8'))
- d.addBoth(self._handle_downloader_output, request)
- d.addBoth(lambda x, req: self.inprogress.remove(req), request)
- d.addBoth(lambda x: self._next_request())
- if len(self.inprogress) == 0 and self.scheduler.size() == 0:
- self._closewait.callback(None)
- def _handle_downloader_output(self, body, request):
- """
- 获取内容,执行回调函数,并且把回调函数中的返回值获取,并添加到队列中
- :param response:
- :param request:
- :return:
- """
- import types
- response = Response(body, request)
- func = request.callback or self.spider.parse
- gen = func(response)
- if isinstance(gen, types.GeneratorType):
- for req in gen:
- self.scheduler.enqueue_request(req)
- @defer.inlineCallbacks
- def start(self):
- self._closewait = defer.Deferred()
- yield self._closewait
- @defer.inlineCallbacks
- def open_spider(self, spider, start_requests):
- self.start_requests = start_requests
- self.spider = spider
- yield None
- reactor.callLater(0, self._next_request)
- class Crawler(object):
- def __init__(self, spidercls):
- self.spidercls = spidercls
- self.spider = None
- self.engine = None
- @defer.inlineCallbacks
- def crawl(self):
- self.engine = ExecutionEngine()
- self.spider = self.spidercls()
- start_requests = iter(self.spider.start_requests())
- yield self.engine.open_spider(self.spider, start_requests)
- yield self.engine.start()
- class CrawlerProcess(object):
- def __init__(self):
- self._active = set()
- self.crawlers = set()
- def crawl(self, spidercls, *args, **kwargs):
- crawler = Crawler(spidercls)
- self.crawlers.add(crawler)
- d = crawler.crawl(*args, **kwargs)
- self._active.add(d)
- return d
- def start(self):
- dl = defer.DeferredList(self._active)
- dl.addBoth(self._stop_reactor)
- reactor.run()
- def _stop_reactor(self, _=None):
- reactor.stop()
- class Spider(object):
- def start_requests(self):
- for url in self.start_urls:
- yield Request(url)
- class ChoutiSpider(Spider):
- name = "chouti"
- start_urls = [
- 'http://dig.chouti.com/',
- ]
- def parse(self, response):
- print(response.text)
- class CnblogsSpider(Spider):
- name = "cnblogs"
- start_urls = [
- 'http://www.cnblogs.com/',
- ]
- def parse(self, response):
- print(response.text)
- if __name__ == '__main__':
- spider_cls_list = [ChoutiSpider, CnblogsSpider]
- crawler_process = CrawlerProcess()
- for spider_cls in spider_cls_list:
- crawler_process.crawl(spider_cls)
- crawler_process.start()
TinyScrapy
示例
- # -*- coding: utf-8 -*-
- import scrapy
- from scrapy.http import Request
- from scrapy.selector import Selector
- class ChoutiSpider(scrapy.Spider):
- name = 'chouti'
- allowed_domains = ['chouti.com']
- start_urls = ['http://chouti.com/']
- cookie_dict = {}
- def start_requests(self):
- for url in self.start_urls:
- yield Request(url, dont_filter=True,callback=self.parse)
- def parse(self,response):
- from scrapy.http.cookies import CookieJar
- cookie_jar = CookieJar() # 对象,中封装了cookies
- cookie_jar.extract_cookies(response,response.request) # 去响应中获取cookies
- for k, v in cookie_jar._cookies.items():
- for i, j in v.items():
- for m, n in j.items():
- self.cookie_dict[m] = n.value
- from urllib.parse import urlencode
- post_dict = {
- "phone":"8618xxxxxxxxxx",
- "password":"xxxx",
- "oneMonth":1,
- }
- yield Request(
- url = "http://dig.chouti.com/login",
- method="POST",
- cookies=self.cookie_dict,
- body=urlencode(post_dict),
- headers={
- "Content-Type":"application/x-www-form-urlencoded;charset=UTF-8",
- },
- callback=self.parse2,
- )
- def parse2(self,response):
- # print(response.text)
- yield Request(
- url="http://dig.chouti.com",
- cookies=self.cookie_dict,
- callback=self.parse3,
- )
- def parse3(self,response):
- # 找div,class=part2的标签,获取share-linkid属性
- hxs = Selector(response)
- linkid_list = hxs.xpath("//div[@class='part2']/@share-linkid").extract()
- # print(linkid_list)
- for linkid in linkid_list:
- base_url = "https://dig.chouti.com/link/vote?linksId={linkid}".format(linkid=linkid)
- yield Request(
- method="POST",
- url=base_url,
- cookies=self.cookie_dict,
- callback=self.parse4,
- )
- def parse4(self,response):
- print(response.text)
- 抽屉网第一页点赞
抽屉网第一页点赞
- # -*- coding: utf-8 -*-
- import scrapy
- from scrapy.http import Request
- from scrapy.selector import Selector
- class ChoutiSpider(scrapy.Spider):
- name = 'chouti'
- allowed_domains = ['chouti.com']
- start_urls = ['http://chouti.com/']
- cookie_dict = {}
- def start_requests(self):
- for url in self.start_urls:
- yield Request(url, dont_filter=True,callback=self.parse)
- def parse(self,response):
- from scrapy.http.cookies import CookieJar
- cookie_jar = CookieJar() # 对象,中封装了cookies
- cookie_jar.extract_cookies(response,response.request) # 去响应中获取cookies
- for k, v in cookie_jar._cookies.items():
- for i, j in v.items():
- for m, n in j.items():
- self.cookie_dict[m] = n.value
- from urllib.parse import urlencode
- post_dict = {
- "phone":"8618xxxxxxxxxx",
- "password":"xxxx",
- "oneMonth":1,
- }
- yield Request(
- url = "http://dig.chouti.com/login",
- method="POST",
- cookies=self.cookie_dict,
- body=urlencode(post_dict),
- headers={
- "Content-Type":"application/x-www-form-urlencoded;charset=UTF-8",
- },
- callback=self.parse2,
- )
- def parse2(self,response):
- # print(response.text)
- yield Request(
- url="http://dig.chouti.com",
- cookies=self.cookie_dict,
- callback=self.parse3,
- )
- def parse3(self,response):
- # 找div,class=part2的标签,获取share-linkid属性
- hxs = Selector(response)
- linkid_list = hxs.xpath("//div[@class='part2']/@share-linkid").extract()
- # print(linkid_list)
- for linkid in linkid_list:
- # 获取每一个ID去点赞
- base_url = "https://dig.chouti.com/link/vote?linksId={linkid}".format(linkid=linkid)
- yield Request(
- method="POST",
- url=base_url,
- cookies=self.cookie_dict,
- callback=self.parse4,
- )
- page_list = hxs.xpath("//div[@id='dig_lcpage']//a/@href").extract()
- for page in page_list:
- # /all/hot/recent/2
- page_url = "http://dig.chouti.com{}".format(page)
- yield Request(url=page_url,method="GET",callback=self.parse3)
- def parse4(self,response):
- print(response.text)
抽屉网所有文章点赞(遍历所有页,无节制的)
补充
发送post请求
- from scrapy.http import Request,FormRequest
- class mySpider(scrapy.Spider):
- # start_urls = ["http://www.example.com/"]
- def start_requests(self):
- url = 'http://www.renren.com/PLogin.do'
- # FormRequest 是Scrapy发送POST请求的方法
- yield scrapy.FormRequest(
- url = url,
- formdata = {"email" : "xxx", "password" : "xxxxx"},
- callback = self.parse_page
- )
- def parse_page(self, response):
- # do something
发送post请求
数据采集器
https://www.cnblogs.com/sufei-duoduo/p/5881385.html
- Scrapy 提供了方便的收集数据的机制。数据以 key/value 方式存储,值大多是计数值。该机制叫做数据收集器(Stats Collector),可以通过 Crawler API 的属性 stats来使用。
- 无论数据收集(stats collection)开启或者关闭,数据收集器永远都是可用的。因此可以 import 进自己的模块并使用其 API(增加值或者设置新的状态键(stats keys))。该做法是为了简化数据收集的方法:不应该使用超过一行代码来收集你的 spider,Scrapy 扩展或者任何你使用数据收集器代码里头的状态。
- 数据收集器的另一个特性是(在启用状态下)很高效,(在关闭情况下)非常高效(几乎察觉不到)。
- 数据收集器对每个 spider 保持一个状态。当 spider 启动时,该表自动打开,当 spider 关闭时,自动关闭。
可用的数据采集器种类
- 可用的数据收集器
- 除了基本的 StatsCollector ,Scrapy 也提供了基于 StatsCollector 的数据收集器。 您可以通过 STATS_CLASS 设置来选择。默认使用的是 MemoryStatsCollector 。
- MemoryStatsCollector
- class scrapy.statscol.MemoryStatsCollector
- 一个简单的数据收集器。其在 spider 运行完毕后将其数据保存在内存中。数据可以通过 spider_stats 属性访问。该属性是一个以 spider 名字为键(key)的字典。
- 这是 Scrapy 的默认选择。
- spider_stats
- 保存了每个 spider 最近一次爬取的状态的字典(dict)。该字典以 spider 名字为键,值也是字典。
- DummyStatsCollector
- class scrapy.statscol.DummyStatsCollector
- 该数据收集器并不做任何事情但非常高效。您可以通过设置 STATS_CLASS 启用这个收集器,来关闭数据收集,提高效率。 不过,数据收集的性能负担相较于 Scrapy 其他的处理(例如分析页面)来说是非常小的。
数据采集器种类
使用方法
- #设置数据:
- stats.set_value('hostname', socket.gethostname())
- #增加数据值:
- stats.inc_value('pages_crawled')
- #当新的值比原来的值大时设置数据:
- stats.max_value('max_items_scraped', value)
- #当新的值比原来的值小时设置数据:
- stats.min_value('min_free_memory_percent', value)
- #获取数据:
- >>> stats.get_value('pages_crawled')
- #获取所有数据:
- >>> stats.get_stats()
- {'pages_crawled': 1238, 'start_time': datetime.datetime(2009, 7, 14, 21, 47, 28, 977139)}
常用方法
- class ExtensionThatAccessStats(object):
- def __init__(self, stats):
- self.stats = stats
- @classmethod
- def from_crawler(cls, crawler):
- return cls(crawler.stats)
在extension中的使用
- """
- Extension for collecting core stats like items scraped and start/finish times
- """
- import datetime
- from scrapy import signals
- class CoreStats(object):
- def __init__(self, stats):
- self.stats = stats
- @classmethod
- def from_crawler(cls, crawler):
- o = cls(crawler.stats)
- crawler.signals.connect(o.spider_opened, signal=signals.spider_opened)
- crawler.signals.connect(o.spider_closed, signal=signals.spider_closed)
- crawler.signals.connect(o.item_scraped, signal=signals.item_scraped)
- crawler.signals.connect(o.item_dropped, signal=signals.item_dropped)
- crawler.signals.connect(o.response_received, signal=signals.response_received)
- return o
- def spider_opened(self, spider):
- print("haha")
- self.stats.set_value('start_time', datetime.datetime.utcnow(), spider=spider)
- def spider_closed(self, spider, reason):
- self.stats.set_value('finish_time', datetime.datetime.utcnow(), spider=spider)
- self.stats.set_value('finish_reason', reason, spider=spider)
- print("spider_closed","spider start time",self.stats.get_value("start_time"))
- print("spider_closed","item_scraped",self.stats.get_value("item_scraped_count"))
- print("spider_closed","response_received",self.stats.get_value("response_received_count"))
- print("spider_closed","spider finish time",self.stats.get_value("finish_time"))
- print("spider_closed","spider finish reason",self.stats.get_value("finish_reason"))
- def item_scraped(self, item, spider):
- self.stats.inc_value('item_scraped_count', spider=spider)
- def response_received(self, spider):
- self.stats.inc_value('response_received_count', spider=spider)
- def item_dropped(self, item, spider, exception):
- reason = exception.__class__.__name__
- self.stats.inc_value('item_dropped_count', spider=spider)
- self.stats.inc_value('item_dropped_reasons_count/%s' % reason, spider=spider)
- """
- haha
- spider_closed spider start time 2018-11-03 16:44:18.618151
- spider_closed item_scraped None
- spider_closed response_received 4
- spider_closed spider finish time 2018-11-03 16:44:21.951843
- spider_closed spider finish reason finished
- """
实例
log
https://scrapy-chs.readthedocs.io/zh_CN/latest/topics/logging.html#log-levels
- Logging
- Scrapy提供了log功能。您可以通过 scrapy.log 模块使用。当前底层实现使用了 Twisted logging ,不过可能在之后会有所变化。
- log服务必须通过显示调用 scrapy.log.start() 来开启,以捕捉顶层的Scrapy日志消息。 在此之上,每个crawler都拥有独立的log观察者(observer)(创建时自动连接(attach)),接收其spider的日志消息。
- Log levels
- Scrapy提供5层logging级别:
- CRITICAL - 严重错误(critical)
- ERROR - 一般错误(regular errors)
- WARNING - 警告信息(warning messages)
- INFO - 一般信息(informational messages)
- DEBUG - 调试信息(debugging messages)
- 如何设置log级别
- 您可以通过终端选项(command line option) –loglevel/-L 或 LOG_LEVEL 来设置log级别。
- 如何记录信息(log messages)
- 下面给出如何使用 WARNING 级别来记录信息的例子:
- from scrapy import log
- log.msg("This is a warning", level=log.WARNING)
- 在Spider中添加log(Logging from Spiders)
- 在spider中添加log的推荐方式是使用Spider的 log() 方法。该方法会自动在调用 scrapy.log.msg() 时赋值 spider 参数。其他的参数则直接传递给 msg() 方法。
- scrapy.log模块
- scrapy.log.start(logfile=None, loglevel=None, logstdout=None)
- 启动Scrapy顶层logger。该方法必须在记录任何顶层消息前被调用 (使用模块的 msg() 而不是 Spider.log 的消息)。否则,之前的消息将会丢失。
- 参数:
- logfile (str) – 用于保存log输出的文件路径。如果被忽略, LOG_FILE 设置会被使用。 如果两个参数都是 None ,log将会被输出到标准错误流(standard error)。
- loglevel – 记录的最低的log级别. 可用的值有: CRITICAL, ERROR, WARNING, INFO and DEBUG.
- logstdout (boolean) – 如果为 True , 所有您的应用的标准输出(包括错误)将会被记录(logged instead)。 例如,如果您调用 “print ‘hello’” ,则’hello’ 会在Scrapy的log中被显示。 如果被忽略,则 LOG_STDOUT 设置会被使用。
- scrapy.log.msg(message, level=INFO, spider=None)
- 记录信息(Log a message)
- 参数:
- message (str) – log的信息
- level – 该信息的log级别. 参考 Log levels.
- spider (Spider 对象) – 记录该信息的spider. 当记录的信息和特定的spider有关联时,该参数必须被使用。
- scrapy.log.CRITICAL
- 严重错误的Log级别
- scrapy.log.ERROR
- 错误的Log级别 Log level for errors
- scrapy.log.WARNING
- 警告的Log级别 Log level for warnings
- scrapy.log.INFO
- 记录信息的Log级别(生产部署时推荐的Log级别)
- scrapy.log.DEBUG
- 调试信息的Log级别(开发时推荐的Log级别)
- Logging设置
- 以下设置可以被用来配置logging:
- LOG_ENABLED
- LOG_ENCODING
- LOG_FILE
- LOG_LEVEL
- LOG_STDOUT
logging
实例
- LOG_FILE = "my_log.log"
- LOG_LEVEL = 'DEBUG'
settings.py
- class JiandanSpider(scrapy.Spider):
- """略"""
- def parse(self, response):
- import logging
- self.log("test scrapy log",level=logging.ERROR)
- self.log("test scrapy log")
spiders/xx.py
参考or转发
http://www.cnblogs.com/wupeiqi/articles/6229292.html
http://scrapy-chs.readthedocs.io/zh_CN/latest/index.html
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