爬虫采用python3 windows平台上

chapter 网页抓取

1、背景调查

包含内容： (1、检查robots.txt 大多数网站都会定义robots.txt文件，了解具体有哪些限制。主要方式，URL/robots.txt查看 (2、检查网站地图，sitemap 通过robots.txt中，提供的sitemap。不过一般网站没有提供，用处不大。 (3、估算网站大小 估算网站大小，经常通过搜索引擎搜索下目标网页，会显示查到的数量，能够得到大致网页数量。 (4、识别网站所用的技术 应用builtwith包，可以输出网站所用的技术和，然后我们根据网站所用的技术去分析网页。 import builtwith builtwith.parse(‘https://www.cnblogs.com/ironstark/p/5303924.html’) 废话不多说，开始写爬虫了。

2、爬取网页的基本方法

直接上代码

import urllib.request as rq import re import itertools import urllib.parse as urlparse import urllib.robotparser def download(url, user_agent='wswp', proxy =None ,num_retries=2): print('Downloading:',url) headers = {'User-agent':user_agent} #使用代理 request = rq.Request(url,headers=headers) opener = rq.build_opener() #使用绝对路径访问 if proxy : #使用支持的代理 proxy_params = {rq.urlparse(url).scheme:proxy} opener.add_handler(rq.ProxyHandler(proxy_params)) try: html = opener.open(request).read() except rq.URLError as e: print('Download error :' ,e.reason) html = None if num_retries >0: #当访问网页出现504等由于网页延迟等原因，重新下载，默认2次 if hasattr(e,'code') and 500 <= e.code <600: html = download(url,user_agent,proxy,num_retries-1) return html

3、偏离爬虫

（1）ID遍历法 id遍历法适用于，id是数值且id之间相隔不远，有一定规律的网页。

#maxnum number of consecutive download errors allowed max_error = 5 #current number of consecutive download error n = 0 num_error = 0 for page in itertools.count(1): url = 'http://example.webscraping.com/view/-%d' %page html = download(url) if html is None: num_error +=1 if num_error == max_error: break else: num_error = 0 n +=1 if n>=5: break print('download success')

(2) 链接爬取 优点：通过链接爬虫可以更像用户登录一样，这样可以让网页爬虫更好的工作，可以爬一些不能连续的网页 确定：会下载一些我们不需要的网页

def link_crawler(seed_url,link_regex): crawl_queue = [seed_url] seen = set(crawl_queue) #去除重复下载 while crawl_queue: url = crawl_queue.pop() html = download(url) for link in get_links(html): if re.match(like_regex,link): link = urlparse.urljoin(seed_url,link) if link not in seen: seen.add(link) crawl_queue.append(link) def get_links(html): #获取链接的url webpage_regex = re.compile('<a[^>]+href=["\'](.*?)["\']') return webpage_regex.findall(html)

4、爬虫的高级功能

（1）解析robots.txt文件，避免下载禁止爬取的url，使用 import urllib.robotparser 可以在

def link_crawler(seed_url,link_regex): crawl_queue = [seed_url] seen = set(crawl_queue) #去除重复下载 while crawl_queue: url = crawl_queue.pop() html = download(url) for link in get_links(html): if re.match(like_regex,link): link = urlparse.urljoin(seed_url,link) if link not in seen: seen.add(link) crawl_queue.append(link) def get_links(html): #获取链接的url webpage_regex = re.compile('<a[^>]+href=["\'](.*?)["\']') return webpage_regex.findall(html)

（2）限定爬取深度，以免进入爬虫陷阱

5、整合代码

# -*- coding: utf-8 -*- """ Created on Sat May 25 20:09:01 2019 @author: Administrator """ import re import urllib.request as rq import urllib.parse as urlparse import time from datetime import datetime import urllib.robotparser as robotparser import queue def link_crawler(seed_url, link_regex=None, delay=5, max_depth=-1, max_urls=-1, headers=None, user_agent='wswp', proxy=None, num_retries=1): """Crawl from the given seed URL following links matched by link_regex """ # the queue of URL's that still need to be crawled crawl_queue = queue.deque([seed_url]) # the URL's that have been seen and at what depth seen = {seed_url: 0} # track how many URL's have been downloaded num_urls = 0 rp = get_robots(seed_url) throttle = Throttle(delay) headers = headers or {} if user_agent: headers['User-agent'] = user_agent while crawl_queue: url = crawl_queue.pop() # check url passes robots.txt restrictions if rp.can_fetch(user_agent, url): throttle.wait(url) html = download(url, headers, proxy=proxy, num_retries=num_retries) links = [] depth = seen[url] if depth != max_depth: # can still crawl further if link_regex: # filter for links matching our regular expression links.extend(link for link in get_links(html) if re.match(link_regex, link)) for link in links: link = normalize(seed_url, link) # check whether already crawled this link if link not in seen: seen[link] = depth + 1 # check link is within same domain if same_domain(seed_url, link): # success! add this new link to queue crawl_queue.append(link) # check whether have reached downloaded maximum num_urls += 1 if num_urls == max_urls: break else: print ('Blocked by robots.txt:', url) class Throttle: """Throttle downloading by sleeping between requests to same domain """ def __init__(self, delay): # amount of delay between downloads for each domain self.delay = delay # timestamp of when a domain was last accessed self.domains = {} def wait(self, url): domain = urlparse.urlparse(url).netloc last_accessed = self.domains.get(domain) if self.delay > 0 and last_accessed is not None: sleep_secs = self.delay - (datetime.now() - last_accessed).seconds if sleep_secs > 0: time.sleep(sleep_secs) self.domains[domain] = datetime.now() def download(url, headers={}, proxy=None, num_retries=2, data=None): print ('Downloading:', url) request = rq.Request(url, data, headers) opener = rq.build_opener() if proxy: proxy_params = {urlparse.urlparse(url).scheme: proxy} opener.add_handler(rq.ProxyHandler(proxy_params)) try: response = opener.open(request) html = response.read() code = response.code except rq.URLError as e: print ('Download error:', e.reason) html = '' if hasattr(e, 'code'): code = e.code if num_retries > 0 and 500 <= code < 600: # retry 5XX HTTP errors return download(url, headers, proxy, num_retries-1, data) else: code = None return html def normalize(seed_url, link): """Normalize this URL by removing hash and adding domain """ link, _ = urlparse.urldefrag(link) # remove hash to avoid duplicates return urlparse.urljoin(seed_url, link) def same_domain(url1, url2): """Return True if both URL's belong to same domain """ return urlparse.urlparse(url1).netloc == urlparse.urlparse(url2).netloc def get_robots(url): """Initialize robots parser for this domain """ rp = robotparser.RobotFileParser() rp.set_url(urlparse.urljoin(url, '/robots.txt')) rp.read() return rp def get_links(html): """Return a list of links from html """ # a regular expression to extract all links from the webpage webpage_regex = re.compile('<a[^>]+href=["\'](.*?)["\']', re.IGNORECASE) # list of all links from the webpage return webpage_regex.findall(str(html)) if __name__ == '__main__': link_crawler('http://example.webscraping.com', '/(index|view)', delay=0, num_retries=1, user_agent='BadCrawler') link_crawler('http://example.webscraping.com', '/(index|view)', delay=0, num_retries=1, max_depth=1, user_agent='wswp')

chapter 2 数据的抓取

网页抓取了，那怎么抓取网页上的数据呢？抓取数据主要有三种方法，正则表达式、Beautiful Soup和lxml三种方法。

抓取方法性能使用难度优点缺点正则表达式快困难快，使用面广难，程序脆弱Beautiful Soup慢使用简单慢LXML较快较容易使用相对简单，速度快–

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