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What are the steps of python web crawler

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Release: 2023-01-03 09:29:07
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Python web crawler steps: first prepare the required libraries and write the crawler scheduler; then write the url manager and web page downloader; then write the web page parser; and finally write the web page outputter.

What are the steps of python web crawler

The operating environment of this tutorial: Windows 7 system, python version 3.9, DELL G3 computer.

python web crawler steps

(1) Prepare the required libraries

We need to prepare a software called BeautifulSoup ( Web page parsing) is an open source library that is used to parse downloaded web pages. We use the PyCharm compilation environment, so we can download the open source library directly.

The steps are as follows:

Select File->Settings

Open the Project interpreter under Project:PythonProject

Click the plus sign to add a new library

Enter bs4, select bs4 and click Install Packge to download

(2) Write a crawler scheduler

The bike_spider here is the four classes introduced by the project name, corresponding to the following four sections of code url manager, url downloader, url parser, url outputter.

# 爬虫调度程序
from bike_spider import url_manager, html_downloader, html_parser, html_outputer


# 爬虫初始化
class SpiderMain(object):
    def __init__(self):
        self.urls = url_manager.UrlManager()
        self.downloader = html_downloader.HtmlDownloader()
        self.parser = html_parser.HtmlParser()
        self.outputer = html_outputer.HtmlOutputer()

    def craw(self, my_root_url):
        count = 1
        self.urls.add_new_url(my_root_url)
        while self.urls.has_new_url():
            try:
                new_url = self.urls.get_new_url()
                print("craw %d : %s" % (count, new_url))
                # 下载网页
                html_cont = self.downloader.download(new_url)
                # 解析网页
                new_urls, new_data = self.parser.parse(new_url, html_cont)
                self.urls.add_new_urls(new_urls)
                # 网页输出器收集数据
                self.outputer.collect_data(new_data)
                if count == 10:
                    break
                count += 1
            except:
                print("craw failed")

        self.outputer.output_html()


if __name__ == "__main__":
    root_url = "http://baike.baidu.com/item/Python/407313"
    obj_spider = SpiderMain()
    obj_spider.craw(root_url)
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(3) Write url manager

We store the URLs that have been crawled and the URLs that have not been crawled separately so that we will not repeat them Crawl some already crawled web pages.

# url管理器
class UrlManager(object):
    def __init__(self):
        self.new_urls = set()
        self.old_urls = set()

    def add_new_url(self, url):
        if url is None:
            return
        if url not in self.new_urls and url not in self.old_urls:
            self.new_urls.add(url)

    def add_new_urls(self, urls):
        if urls is None or len(urls) == 0:
            return
        for url in urls:
            self.new_urls.add(url)

    def get_new_url(self):
        # pop方法会帮我们获取一个url并且移除它
        new_url = self.new_urls.pop()
        self.old_urls.add(new_url)
        return new_url

    def has_new_url(self):
        return len(self.new_urls) != 0
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(4) Write a web page downloader

Download the page through a network request

# 网页下载器
import urllib.request


class HtmlDownloader(object):

    def download(self, url):
        if url is None:
            return None
        response = urllib.request.urlopen(url)
        # code不为200则请求失败
        if response.getcode() != 200:
            return None
        return response.read()
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(5) Write a web page Parser

When parsing a web page, we need to know what characteristics the content we want to query has. We can open a web page, right-click and inspect the elements to understand the commonalities of the content we are querying.

# 网页解析器
import re
from bs4 import BeautifulSoup
from urllib.parse import urljoin


class HtmlParser(object):

    def parse(self, page_url, html_cont):
        if page_url is None or html_cont is None:
            return
        soup = BeautifulSoup(html_cont, "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

    def _get_new_data(self, page_url, soup):
        res_data = {"url": page_url}
        # 获取标题
        title_node = soup.find("dd", class_="lemmaWgt-lemmaTitle-title").find("h1")
        res_data["title"] = title_node.get_text()
        summary_node = soup.find("p", class_="lemma-summary")
        res_data["summary"] = summary_node.get_text()
        return res_data

    def _get_new_urls(self, page_url, soup):
        new_urls = set()
        # 查找出所有符合下列条件的url
        links = soup.find_all("a", href=re.compile(r"/item/"))
        for link in links:
            new_url = link['href']
            # 获取到的url不完整,学要拼接
            new_full_url = urljoin(page_url, new_url)
            new_urls.add(new_full_url)
        return new_urls
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(6) Write a web page outputter

There are many output formats. We choose to output in the form of html so that we can get a html page.

# 网页输出器
class HtmlOutputer(object):

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

    def collect_data(self, data):
        if data is None:
            return
        self.datas.append(data)

    # 我们以html表格形式进行输出
    def output_html(self):
        fout = open("output.html", "w", encoding='utf-8')
        fout.write("<html>")
        fout.write("<meta charset=&#39;utf-8&#39;>")
        fout.write("<body>")
        # 以表格输出
        fout.write("<table>")
        for data in self.datas:
            # 一行
            fout.write("<tr>")
            # 每个单元行的内容
            fout.write("<td>%s</td>" % data["url"])
            fout.write("<td>%s</td>" % data["title"])
            fout.write("<td>%s</td>" % data["summary"])
            fout.write("</tr>")
        fout.write("</table>")
        fout.write("</body>")
        fout.write("</html>")
        # 输出完毕后一定要关闭输出器
        fout.close()
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