Detailed introduction to the five modules in python

This python crawler encyclopedia provides a detailed analysis of the steps of the crawler, with detailed annotations for each step of the code. You can master the characteristics of the python crawler through this case:

1. Crawler scheduling entrance (crawler_main.py)

# coding:utf-8
from com.wenhy.crawler_baidu_baike import url_manager, html_downloader, html_parser, html_outputer

print "爬虫百度百科调度入口"

# 创建爬虫类
class SpiderMain(object):

    # 初始化 url管理器 html下载器 解析器 输出器
    def __init__(self):
        self.urls = url_manager.UrlManager()
        self.downloader = html_downloader.HtmlDownloader()
        self.parser = html_parser.HtmlParser()
        self.output = html_outputer.HtmlOutput()


def craw(urls, downloader, parser, output, root_url):
    # 计数
    count = 1
    # 添加url到url管理器中
    urls.add_new_url(root_url)
    # 判断是否有新的URL
    while urls.has_new_url():
        try:

            # 获取新的URL
            new_url = urls.get_new_url()
            print 'crawler %d : %s' % (count, new_url)
            # 下载html页面数据
            html_cont = downloader.download(new_url)
            # 解析页面得到新的url列表，新的数据
            new_urls, new_data = parser.parser(new_url, html_cont)
            # 把解析到的url数组批量添加到url管理器中
            urls.add_new_urls(new_urls)
            # 收集数据
            output.collect_data(new_data)
            # 爬虫1000页面
            if count == 500:
                break
            count = count + 1

        except Exception as e:
            print 'Crawler Failed ', e

    output.output_html()


if __name__ == '__main__':
    # 入口URL 百度百科地址
    root_url = "http://baike.baidu.com/item/Python"
    # 创建爬虫
    obj_spider = SpiderMain()
    # 启动爬虫
    craw(obj_spider.urls, obj_spider.downloader, obj_spider.parser, obj_spider.output, root_url)

2、封装URL管理器（url_manager.py）

# coding:utf-8

print "URL管理器"


class UrlManager(object):

    # 初始化url容器（set集合）
    def __init__(self):
        self.new_urls = set()
        self.old_urls = set()

    # 添加一个新的待爬取url
    def add_new_url(self, url):

        if url is None:
            return

        # 判断url不在新的url集合中也不再旧的url集合中 说明是一个全新的url
        if url not in self.new_urls and url not in self.old_urls:
            self.new_urls.add(url)

    # 批量添加解析页面的URL
    def add_new_urls(self, urls):

        if urls is None or len(urls) == 0:
            return
        for url in urls:
            self.add_new_url(url)

    # 判断是否有新的待爬取的url
    def has_new_url(self):
        # 如果新的url集合里面len不等于0 说明有待爬取的url
        return len(self.new_urls) != 0

    # 获得url地址
    def get_new_url(self):
        # 获取url并移除当前url
        new_url = self.new_urls.pop()
        self.old_urls.add(new_url)
        return new_url

3、HTML下载器（html_downloader.py）

# coding:utf-8

import urllib2
print "下载HTML"


class HtmlDownloader(object):

    def download(self, url):
        # 判断是否为空
        if url is None:
            return None
        # 下载url
        response = urllib2.urlopen(url)
        # 判断返回结果是否为200
        if response.getcode() != 200:
            return None
        # 成功 返回页面内容
        return response.read()

4、HTML 解析器(html_parser.py)

# coding:utf-8

from bs4 import BeautifulSoup
import re
import urlparse

print "HTML 解析器"


class HtmlParser(object):

    def _get_new_urls(self, page_url, soup):

        # 创建一个集合保存页面解析出来的所有url
        new_urls = set()
        # /item/  词条url
        links = soup.find_all('a', href=re.compile(r'/item/'))
        for link in links:
            # 获取连接
            new_url = link['href']
            # url拼接
            new_full_url = urlparse.urljoin(page_url, new_url)
            # print 'new_full_url', new_full_url
            # 添加到集合中url
            new_urls.add(new_full_url)
        return new_urls


    def _get_new_data(self, page_url, soup):
        # 定义一个dict 集合
        res_data = {}

        res_data['url'] = page_url
        # < dd class ="lemmaWgt-lemmaTitle-title" >< h1 > 自由软件 < / h1 >
        title_node = soup.find('dd', class_='lemmaWgt-lemmaTitle-title').find('h1')
        res_data['title'] = title_node.get_text()
        # <div class="lemma-summary" label-module="lemmaSummary">
        summary_node = soup.find('div', class_='lemma-summary')
        res_data['summary'] = summary_node.get_text()

        return res_data


    # 解析器
    def parser(self, page_url, html_content):

        if page_url is None or html_content is None:
            return

        # 使用BeautifulSoup 解析html页面
        soup = BeautifulSoup(html_content, 'html.parser', from_encoding='utf-8')
        new_urls = self._get_new_urls(page_url, soup)
        new_data = self._get_new_data(page_url, soup)
        return new_urls, new_data

5、HTML 输出页面（html_outputer.py）

# coding:utf-8

print "HTML 输出页面"


class HtmlOutput(object):

    def __init__(self):
        self.datas = []

    # 收集数据
    def collect_data(self, data):
        if data is None:
            return
        self.datas.append(data)

    # 展示数据
    def output_html(self):

        fout = open('output.html', 'w')

        fout.write('<html>')
        fout.write('<head>')
        fout.write('<meta http-equiv="Content-Type" content="text/html;charset=utf-8">')
        fout.write('</head>')
        fout.write('<body>')
        fout.write('<table border="1">')
        for data in self.datas:
            fout.write('<tr>')
            fout.write('<td><a href = "%s">%s</a></td>' % (data['url'].encode('utf-8'), data['title'].encode('utf-8')))
            fout.write('<td>%s</td>' % data['summary'].encode('utf-8'))
            fout.write('</tr>')
        fout.write('</table>')
        fout.write('</body>')
        fout.write('</html>')

        fout.close()


总结：python爬虫主要就是五个模块：爬虫启动入口模块，URL管理器存放已经爬虫的URL和待爬虫URL列表，html下载器，html解析器，html输出器
     同时可以掌握到urllib2的使用、bs4（BeautifulSoup）页面解析器、re正则表达式、urlparse、python基础知识回顾（set集合操作）等相关内容。

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