Python 框架 之 Scrapy 爬虫（二）
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Python 框架 之 Scrapy 爬虫（二）
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Scrapy是一個為了爬取網站數據，提取結構性數據而編寫的應用框架。 其可以應用在數據挖掘，信息處理或存儲歷史數據等一系列的程序中。其最初是為了頁面抓取 (更確切來說, 網絡抓取)所設計的， 也可以應用在獲取API所返回的數據(例如 Amazon Associates Web Services ) 或者通用的網絡爬蟲。Scrapy用途廣泛，可以用于數據挖掘、監測和自動化測試。
Scrapy 使用了 Twisted異步網絡庫來處理網絡通訊。整體架構大致如下
Scrapy主要包括了以下組件：
- 引擎(Scrapy)
用來處理整個系統的數據流處理, 觸發事務(框架核心) - 調度器(Scheduler)
用來接受引擎發過來的請求, 壓入隊列中, 并在引擎再次請求的時候返回. 可以想像成一個URL（抓取網頁的網址或者說是鏈接）的優先隊列, 由它來決定下一個要抓取的網址是什么, 同時去除重復的網址 - 下載器(Downloader)
用于下載網頁內容, 并將網頁內容返回給蜘蛛(Scrapy下載器是建立在twisted這個高效的異步模型上的) - 爬蟲(Spiders)
爬蟲是主要干活的, 用于從特定的網頁中提取自己需要的信息, 即所謂的實體(Item)。用戶也可以從中提取出鏈接,讓Scrapy繼續抓取下一個頁面 - 項目管道(Pipeline)
負責處理爬蟲從網頁中抽取的實體，主要的功能是持久化實體、驗證實體的有效性、清除不需要的信息。當頁面被爬蟲解析后，將被發送到項目管道，并經過幾個特定的次序處理數據。 - 下載器中間件(Downloader Middlewares)
位于Scrapy引擎和下載器之間的框架，主要是處理Scrapy引擎與下載器之間的請求及響應。 - 爬蟲中間件(Spider Middlewares)
介于Scrapy引擎和爬蟲之間的框架，主要工作是處理蜘蛛的響應輸入和請求輸出。 - 調度中間件(Scheduler Middewares)
介于Scrapy引擎和調度之間的中間件，從Scrapy引擎發送到調度的請求和響應。
Scrapy運行流程大概如下：
一、安裝
Linux:pip3 install scrapyWindows：a. pip3 install wheelb. 下載twisted http://www.lfd.uci.edu/~gohlke/pythonlibs/#twistedc. 進入下載目錄，執行 pip3 install Twisted?17.1.0?cp35?cp35m?win_amd64.whld. pip3 install scrapye. 下載并安裝pywin32：https://sourceforge.net/projects/pywin32/files/二、基本使用
1. 基本命令
1.?scrapy startproject 項目名稱# 在當前目錄中創建一個項目文件（類似于Django）2.?scrapy genspider [-t template] <name> <domain># 創建爬蟲應用scrapy gensipider?-t basic oldboy oldboy.comscrapy gensipider?-t xmlfeed autohome autohome.com.cnPS:查看所有命令：scrapy gensipider?-l查看模板命令：scrapy gensipider?-d 模板名稱3.?scrapy?list#?展示爬蟲應用列表4.?scrapy crawl 爬蟲應用名稱#?運行單獨爬蟲應用，要在項目內運行2.項目結構以及爬蟲應用簡介
project_name/scrapy.cfg # 項目的主配置信息。（真正爬蟲相關的配置信息在settings.py文件中）project_name/__init__.pyitems.py # 設置數據存儲模板，用于結構化數據，如：Django的Modelpipelines.py # 數據處理行為，如：一般結構化的數據持久化settings.py # 配置文件，如：遞歸的層數、并發數，延遲下載等spiders/ # 爬蟲目錄，如：創建文件，編寫爬蟲規則__init__.py爬蟲1.py爬蟲2.py爬蟲3.py注意：一般創建爬蟲文件時，以網站域名命名
爬蟲1.py
import scrapyclass XiaoHuarSpider(scrapy.spiders.Spider):name = "spidername" # 爬蟲名稱 *****allowed_domains = ["spider.com"] # 允許的域名start_urls = ["http://www.flepeng.com/", # 起始URL]def parse(self, response):# 訪問起始URL并獲取結果后的回調函數關于windows編碼
import sys,os sys.stdout=io.TextIOWrapper(sys.stdout.buffer,encoding='gb18030')3.?小試牛刀
import scrapy from scrapy.selector import HtmlXPathSelector # 新版的好像已經棄用，使用Selector from scrapy.http.request import Requestclass DigSpider(scrapy.Spider):name = "dig" # 爬蟲應用的名稱，通過命令啟動爬蟲時，使用此參數allowed_domains = ["chouti.com"] # 允許的域名start_urls = ['http://dig.chouti.com/',] # 起始URLhas_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' % pagekey = self.md5(page_url)if key not in self.has_request_set:self.has_request_set[key] = page_urlobj = Request(url=page_url, method='GET', callback=self.parse)yield obj@staticmethoddef md5(val):import hashlibha = hashlib.md5()ha.update(bytes(val, encoding='utf-8'))key = ha.hexdigest()return key執行此爬蟲文件，則在終端進入項目目錄執行如下命令：
scrapy crawl dig?--nolog # nolog 表示不打印日志對于上述代碼重要之處在于：
- Request是一個封裝用戶請求的類，在回調函數中yield該對象表示繼續訪問
- HtmlXpathSelector用于結構化HTML代碼并提供選擇器功能
4. 選擇器
xpath的路徑表達式：
| nodename | 選取此節點的所有子節點。 |
| / | 從根節點選取。 |
| // | 從匹配選擇的當前節點選擇文檔中的節點，而不考慮它們的位置。 |
| . | 選取當前節點。 |
| .. | 選取當前節點的父節點。 |
| @ | 選取屬性。 |
在下面的表格中，列出了一些路徑表達式以及表達式的結果：
| bookstore | 選取 bookstore 元素的所有子節點。 |
| /bookstore | 選取根元素 bookstore。 注釋：假如路徑起始于正斜杠( / )，則此路徑始終代表到某元素的絕對路徑！ |
| bookstore/book | 選取屬于 bookstore 的子元素的所有 book 元素。 |
| //book | 選取所有 book 子元素，而不管它們在文檔中的位置。 |
| bookstore//book | 選擇屬于 bookstore 元素的后代的所有 book 元素，而不管它們位于 bookstore 之下的什么位置。 |
| //@lang | 選取名為 lang 的所有屬性。 |
示例：自動登陸抽屜并點贊
# -*- coding: utf-8 -*- import scrapy from scrapy.selector import HtmlXPathSelector from scrapy.http.request import Request from scrapy.http.cookies import CookieJar from scrapy import FormRequestclass ChouTiSpider(scrapy.Spider):# 爬蟲應用的名稱，通過此名稱啟動爬蟲命令name = "chouti"# 允許的域名allowed_domains = ["chouti.com"]cookie_dict = {}has_request_set = {}def start_requests(self):url = 'http://dig.chouti.com/'# return [Request(url=url, callback=self.login)]yield Request(url=url, callback=self.login)def login(self, response):cookie_jar = CookieJar()cookie_jar.extract_cookies(response, response.request)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.valuereq = Request(url='http://dig.chouti.com/login',method='POST',headers={'Content-Type': 'application/x-www-form-urlencoded; charset=UTF-8'},body='phone=8615131255089&password=pppppppp&oneMonth=1',cookies=self.cookie_dict,callback=self.check_login)yield reqdef check_login(self, response):req = Request(url='http://dig.chouti.com/',method='GET',callback=self.show,cookies=self.cookie_dict,dont_filter=True)yield reqdef show(self, response):# print(response)hxs = HtmlXPathSelector(response)news_list = hxs.select('//div[@id="content-list"]/div[@class="item"]')for new in news_list:# temp = new.xpath('div/div[@class="part2"]/@share-linkid').extract()link_id = new.xpath('*/div[@class="part2"]/@share-linkid').extract_first()yield Request(url='http://dig.chouti.com/link/vote?linksId=%s' %(link_id,),method='POST',cookies=self.cookie_dict,callback=self.do_favor)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' % pageimport hashlibhash = hashlib.md5()hash.update(bytes(page_url,encoding='utf-8'))key = hash.hexdigest()if key in self.has_request_set:passelse:self.has_request_set[key] = page_urlyield Request(url=page_url,method='GET',callback=self.show)def do_favor(self, response):print(response.text)?處理Cookie
# -*- coding: utf-8 -*- import scrapy from scrapy.http.response.html import HtmlResponse from scrapy.http import Request from scrapy.http.cookies import CookieJarclass ChoutiSpider(scrapy.Spider):name = "chouti"allowed_domains = ["chouti.com"]start_urls = ('http://www.chouti.com/',)def start_requests(self):url = 'http://dig.chouti.com/'yield Request(url=url, callback=self.login, meta={'cookiejar': True})def login(self, response):print(response.headers.getlist('Set-Cookie'))req = Request(url='http://dig.chouti.com/login',method='POST',headers={'Content-Type': 'application/x-www-form-urlencoded; charset=UTF-8'},body='phone=8613121758648&password=woshiniba&oneMonth=1',callback=self.check_login,meta={'cookiejar': True})yield reqdef check_login(self, response):print(response.text)注意：settings.py中設置DEPTH_LIMIT = 1來指定“遞歸”的層數。
5. 格式化處理 pipelines
上述實例只是簡單的處理，所以在parse方法中直接處理。如果對于想要獲取更多的數據處理，則可以利用Scrapy的items將數據格式化，然后統一交由pipelines來處理。
spiders/xiahuar.py
import scrapy from scrapy.selector import HtmlXPathSelector from scrapy.http.request import Request from scrapy.http.cookies import CookieJar from scrapy import FormRequestclass XiaoHuarSpider(scrapy.Spider):name = "xiaohuar"allowed_domains = ["xiaohuar.com"]start_urls = ["http://www.xiaohuar.com/list-1-1.html",]# setting 中的配置pipelines# custom_settings = {# 'ITEM_PIPELINES':{# 'spider1.pipelines.JsonPipeline': 100# }# }has_request_set = {}def parse(self, response):# 分析頁面# 找到頁面中符合規則的內容（校花圖片），保存# 找到所有的a標簽，再訪問其他a標簽，一層一層的搞下去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" % srcfrom ..items import XiaoHuarItemobj = XiaoHuarItem(name=name, school=school, url=url)yield objurls = 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:passelse:self.has_request_set[key] = urlreq = Request(url=url,method='GET',callback=self.parse)yield req@staticmethoddef md5(val):import hashlibha = hashlib.md5()ha.update(bytes(val, encoding='utf-8'))key = ha.hexdigest()return keyitems
import scrapyclass XiaoHuarItem(scrapy.Item):name = scrapy.Field()school = scrapy.Field()url = scrapy.Field()pipelines
import json import os import requestsclass 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 itemclass 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 itemsettings
ITEM_PIPELINES = {'spider1.pipelines.JsonPipeline': 100,'spider1.pipelines.FilePipeline': 300, } # 后面的整數值，確定了他們運行的順序，item按數字從低到高的順序，通過pipeline，通常將這些數字定義在0-1000范圍內。對于pipeline可以做更多，如下：
自定義pipeline格式
from scrapy.exceptions import DropItemclass CustomPipeline(object):def __init__(self,v):self.value = vdef process_item(self, item, spider):# 運行pipeline時會調用此函數，操作并進行持久化# return表示會被后續的pipeline繼續處理return item# 表示將item丟棄，不會被后續pipeline處理# raise DropItem()@classmethoddef from_crawler(cls, crawler):# 初始化時候，用于創建pipeline對象val = crawler.settings.getint('MMMM')return cls(val)def open_spider(self,spider):# 爬蟲開始執行時，調用print('000000')def close_spider(self,spider):# 爬蟲關閉時，被調用print('111111')6.中間件
爬蟲中間件
class SpiderMiddleware(object):def process_spider_input(self,response, spider):"""下載完成，執行，然后交給parse處理:param response: :param spider: :return: """passdef process_spider_output(self,response, result, spider):"""spider處理完成，返回時調用:param response::param result::param spider::return: 必須返回包含 Request 或 Item 對象的可迭代對象(iterable)"""return resultdef process_spider_exception(self,response, exception, spider):"""異常調用:param response::param exception::param spider::return: None,繼續交給后續中間件處理異常；含 Response 或 Item 的可迭代對象(iterable)，交給調度器或pipeline"""return Nonedef process_start_requests(self,start_requests, spider):"""爬蟲啟動時調用:param start_requests::param spider::return: 包含 Request 對象的可迭代對象"""return start_requests下載器中間件
class DownMiddleware1(object):def process_request(self, request, spider):"""請求需要被下載時，經過所有下載器中間件的process_request調用:param request: :param spider: :return: None,繼續后續中間件去下載；Response對象，停止process_request的執行，開始執行process_responseRequest對象，停止中間件的執行，將Request重新調度器raise IgnoreRequest異常，停止process_request的執行，開始執行process_exception"""passdef process_response(self, request, response, spider):"""spider處理完成，返回時調用:param response::param result::param spider::return: Response 對象：轉交給其他中間件process_responseRequest 對象：停止中間件，request會被重新調度下載raise IgnoreRequest 異常：調用Request.errback"""print('response1')return responsedef process_exception(self, request, exception, spider):"""當下載處理器(download handler)或 process_request() (下載中間件)拋出異常:param response::param exception::param spider::return: None：繼續交給后續中間件處理異常；Response對象：停止后續process_exception方法Request對象：停止中間件，request將會被重新調用下載"""return None7. 自定制命令
- 在spiders同級創建任意目錄，如：commands
- 在其中創建 crawlall.py 文件 （此處文件名就是自定義的命令）
crawlall.py
from scrapy.commands import ScrapyCommand from scrapy.utils.project import get_project_settingsclass Command(ScrapyCommand):requires_project = Truedef syntax(self): # 命令的參數return '[options]'def short_desc(self): # 命令的描述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()- 在settings.py 中添加配置 COMMANDS_MODULE = '項目名稱.目錄名稱'
- 在項目目錄執行命令：scrapy crawlall?
單個爬蟲
import sys from scrapy.cmdline import executeif __name__ == '__main__':execute(["scrapy","github","--nolog"])8. 自定義擴展
自定義擴展時，利用信號在指定位置注冊制定操作
from scrapy import signalsclass MyExtension(object):def __init__(self, value):self.value = value@classmethoddef from_crawler(cls, crawler):val = crawler.settings.getint('MMMM')ext = cls(val)# 注冊信號crawler.signals.connect(ext.spider_opened, signal=signals.spider_opened)crawler.signals.connect(ext.spider_closed, signal=signals.spider_closed)return extdef spider_opened(self, spider):print('open')def spider_closed(self, spider):print('close')9. 避免重復訪問
scrapy默認使用 scrapy.dupefilter.RFPDupeFilter 進行去重，相關配置有：
DUPEFILTER_CLASS = 'scrapy.dupefilter.RFPDupeFilter' DUPEFILTER_DEBUG = False JOBDIR = "保存范文記錄的日志路徑，如：/root/" # 最終路徑為 /root/requests.seen自定義URL去重操作
class RepeatUrl:def __init__(self):self.visited_url = set()@classmethoddef from_settings(cls, settings):"""初始化時，調用:param settings: :return: """return cls()def request_seen(self, request):"""檢測當前請求是否已經被訪問過:param request: :return: True表示已經訪問過；False表示未訪問過"""if request.url in self.visited_url:return Trueself.visited_url.add(request.url)return Falsedef open(self):"""開始爬取請求時，調用:return: """print('open replication')def close(self, reason):"""結束爬蟲爬取時，調用:param reason: :return: """print('close replication')def log(self, request, spider):"""記錄日志:param request: :param spider: :return: """print('repeat', request.url)10.其他
settings
# -*- 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. 爬蟲名稱 BOT_NAME = 'step8_king'# 2. 爬蟲應用路徑 SPIDER_MODULES = ['step8_king.spiders'] NEWSPIDER_MODULE = 'step8_king.spiders'# Crawl responsibly by identifying yourself (and your website) on the user-agent # 3. 客戶端 user-agent請求頭 # USER_AGENT = 'step8_king (+http://www.yourdomain.com)'# Obey robots.txt rules # 4. 禁止爬蟲配置，應該開啟，看看是否允許 # ROBOTSTXT_OBEY = False# Configure maximum concurrent requests performed by Scrapy (default: 16) # 5. 并發請求數 # 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. 延遲下載秒數 # DOWNLOAD_DELAY = 2# The download delay setting will honor only one of: # 7. 單域名訪問并發數，并且延遲下次秒數也應用在每個域名 # CONCURRENT_REQUESTS_PER_DOMAIN = 2 # 單IP訪問并發數，如果有值則忽略：CONCURRENT_REQUESTS_PER_DOMAIN，并且延遲下次秒數也應用在每個IP # CONCURRENT_REQUESTS_PER_IP = 3# Disable cookies (enabled by default) # 8. 是否支持cookie，cookiejar進行操作cookie # COOKIES_ENABLED = True # COOKIES_DEBUG = True# Disable Telnet Console (enabled by default) # 9. Telnet用于查看當前爬蟲的信息，操作爬蟲等... # 使用telnet ip port ，然后通過命令操作 # TELNETCONSOLE_ENABLED = True # TELNETCONSOLE_HOST = '127.0.0.1' # TELNETCONSOLE_PORT = [6023,]# 10. 默認請求頭 # 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. 定義pipeline處理請求 # ITEM_PIPELINES = { # 'step8_king.pipelines.JsonPipeline': 700, # 'step8_king.pipelines.FilePipeline': 500, # }# 12. 自定義擴展，基于信號進行調用 # Enable or disable extensions # See http://scrapy.readthedocs.org/en/latest/topics/extensions.html # EXTENSIONS = { # # 'step8_king.extensions.MyExtension': 500, # }# 13. 爬蟲允許的最大深度，可以通過meta查看當前深度；0表示無深度 # DEPTH_LIMIT = 3# 14. 爬取時，0表示深度優先Lifo(默認)；1表示廣度優先FiFo# 后進先出，深度優先 # DEPTH_PRIORITY = 0 # SCHEDULER_DISK_QUEUE = 'scrapy.squeue.PickleLifoDiskQueue' # SCHEDULER_MEMORY_QUEUE = 'scrapy.squeue.LifoMemoryQueue' # 先進先出，廣度優先# DEPTH_PRIORITY = 1 # SCHEDULER_DISK_QUEUE = 'scrapy.squeue.PickleFifoDiskQueue' # SCHEDULER_MEMORY_QUEUE = 'scrapy.squeue.FifoMemoryQueue'# 15. 調度器隊列 # SCHEDULER = 'scrapy.core.scheduler.Scheduler' # from scrapy.core.scheduler import Scheduler# 16. 訪問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. 自動限速算法from scrapy.contrib.throttle import AutoThrottle自動限速設置1. 獲取最小延遲 DOWNLOAD_DELAY2. 獲取最大延遲 AUTOTHROTTLE_MAX_DELAY3. 設置初始下載延遲 AUTOTHROTTLE_START_DELAY4. 當請求下載完成后，獲取其"連接"時間 latency，即：請求連接到接受到響應頭之間的時間5. 用于計算的... AUTOTHROTTLE_TARGET_CONCURRENCYtarget_delay = latency / self.target_concurrencynew_delay = (slot.delay + target_delay) / 2.0 # 表示上一次的延遲時間new_delay = max(target_delay, new_delay)new_delay = min(max(self.mindelay, new_delay), self.maxdelay)slot.delay = new_delay """# 開始自動限速 # AUTOTHROTTLE_ENABLED = True # The initial download delay # 初始下載延遲 # AUTOTHROTTLE_START_DELAY = 5 # The maximum download delay to be set in case of high latencies # 最大下載延遲 # AUTOTHROTTLE_MAX_DELAY = 10 # The average number of requests Scrapy should be sending in parallel to each remote server # 平均每秒并發數 # AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0# Enable showing throttling stats for every response received: # 是否顯示 # 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. 啟用緩存目的用于將已經發送的請求或相應緩存下來，以便以后使用from scrapy.downloadermiddlewares.httpcache import HttpCacheMiddlewarefrom scrapy.extensions.httpcache import DummyPolicyfrom scrapy.extensions.httpcache import FilesystemCacheStorage """ # 是否啟用緩存策略 # HTTPCACHE_ENABLED = True# 緩存策略：所有請求均緩存，下次在請求直接訪問原來的緩存即可 # HTTPCACHE_POLICY = "scrapy.extensions.httpcache.DummyPolicy" # 緩存策略：根據Http響應頭：Cache-Control、Last-Modified 等進行緩存的策略 # HTTPCACHE_POLICY = "scrapy.extensions.httpcache.RFC2616Policy"# 緩存超時時間 # HTTPCACHE_EXPIRATION_SECS = 0# 緩存保存路徑 # HTTPCACHE_DIR = 'httpcache'# 緩存忽略的Http狀態碼 # HTTPCACHE_IGNORE_HTTP_CODES = []# 緩存存儲的插件 # HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'""" 19. 代理，需要在環境變量中設置from scrapy.contrib.downloadermiddleware.httpproxy import HttpProxyMiddleware方式一：使用默認os.environ{http_proxy:http://root:woshiniba@192.168.11.11:9999/https_proxy:http://192.168.11.11:9999/}方式二：使用自定義下載中間件def to_bytes(text, encoding=None, errors='strict'):if isinstance(text, bytes):return textif 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訪問Https訪問時有兩種情況：1. 要爬取網站使用的可信任證書(默認支持)DOWNLOADER_HTTPCLIENTFACTORY = "scrapy.core.downloader.webclient.ScrapyHTTPClientFactory"DOWNLOADER_CLIENTCONTEXTFACTORY = "scrapy.core.downloader.contextfactory.ScrapyClientContextFactory"2. 要爬取網站使用的自定義證書DOWNLOADER_HTTPCLIENTFACTORY = "scrapy.core.downloader.webclient.ScrapyHTTPClientFactory"DOWNLOADER_CLIENTCONTEXTFACTORY = "step8_king.https.MySSLFactory"# https.pyfrom scrapy.core.downloader.contextfactory import ScrapyClientContextFactoryfrom twisted.internet.ssl import (optionsForClientTLS, CertificateOptions, PrivateCertificate)class MySSLFactory(ScrapyClientContextFactory):def getCertificateOptions(self):from OpenSSL import cryptov1 = 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對象certificate=v2, # X509對象verify=False,method=getattr(self, 'method', getattr(self, '_ssl_method', None)))其他：相關類scrapy.core.downloader.handlers.http.HttpDownloadHandlerscrapy.core.downloader.webclient.ScrapyHTTPClientFactoryscrapy.core.downloader.contextfactory.ScrapyClientContextFactory相關配置DOWNLOADER_HTTPCLIENTFACTORYDOWNLOADER_CLIENTCONTEXTFACTORY"""""" 21. 爬蟲中間件class SpiderMiddleware(object):def process_spider_input(self,response, spider):'''下載完成，執行，然后交給parse處理:param response: :param spider: :return: '''passdef process_spider_output(self,response, result, spider):'''spider處理完成，返回時調用:param response::param result::param spider::return: 必須返回包含 Request 或 Item 對象的可迭代對象(iterable)'''return resultdef process_spider_exception(self,response, exception, spider):'''異常調用:param response::param exception::param spider::return: None,繼續交給后續中間件處理異常；含 Response 或 Item 的可迭代對象(iterable)，交給調度器或pipeline'''return Nonedef process_start_requests(self,start_requests, spider):'''爬蟲啟動時調用:param start_requests::param spider::return: 包含 Request 對象的可迭代對象'''return start_requests內置爬蟲中間件：'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. 下載中間件class DownMiddleware1(object):def process_request(self, request, spider):'''請求需要被下載時，經過所有下載器中間件的process_request調用:param request::param spider::return:None,繼續后續中間件去下載；Response對象，停止process_request的執行，開始執行process_responseRequest對象，停止中間件的執行，將Request重新調度器raise IgnoreRequest異常，停止process_request的執行，開始執行process_exception'''passdef process_response(self, request, response, spider):'''spider處理完成，返回時調用:param response::param result::param spider::return:Response 對象：轉交給其他中間件process_responseRequest 對象：停止中間件，request會被重新調度下載raise IgnoreRequest 異常：調用Request.errback'''print('response1')return responsedef process_exception(self, request, exception, spider):'''當下載處理器(download handler)或 process_request() (下載中間件)拋出異常:param response::param exception::param spider::return:None：繼續交給后續中間件處理異常；Response對象：停止后續process_exception方法Request對象：停止中間件，request將會被重新調用下載'''return None默認下載中間件{'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, # }此文為轉載https://www.cnblogs.com/wupeiqi/articles/6229292.html
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