一條爬蟲抓取一個小網站所有數據

​ 今天閑來無事，寫一個爬蟲來玩玩。在網上衝浪的時候發現了一個搞笑的段子網，發現裡面的內容還是比較有意思的，於是心血來潮，就想著能不能寫一個Python程式，抓取幾條數據下來看看，一不小心就把這個網站的所有數據都拿到了。

​ 這個網站主要的數據都是詳情在HTML裡面的，可以採用lxml模塊的xpath對HTML標簽的內容解析，獲取到自己想要的數據，然後再保存在本地文件中，整個過程是一氣呵成的。能夠抓取到一頁的數據之後，加一個迴圈就可以抓取到所有頁的數據，下麵的就是數據展示。

廢話少說，直接上Python代碼

import requests
import csv
from lxml import etree
import time


class Page:

    def __init__(self):
        self.pre_url = "https://www.biedoul.com"
        self.start_page = 1
        self.end_page = 15233

    def askHTML(self, current_page, opportunity):
        print(
            "=============================== current page => " + str(current_page) + "===============================")
        try:

            pre_url = self.pre_url + "/index/" + str(current_page)
            page = requests.get(url=pre_url)
            html = etree.HTML(page.content)
            articles = html.xpath('/html/body/div/div/div/dl')
            return articles
        except Exception as e:
            if opportunity > 0:
                time.sleep(500)
                print(
                    "=============================== retry => " + str(opportunity) + "===============================")
                return self.askHTML(current_page, opportunity - 1)
            else:
                return None

    def analyze(self, articles):
        lines = []
        for article in articles:
            data = {}
            data["link"] = article.xpath("./span/dd/a/@href")[0]
            data["title"] = article.xpath("./span/dd/a/strong/text()")[0]
            data["content"] = self.analyze_content(article)
            picture_links = article.xpath("./dd/img/@src")
            if (picture_links is not None and len(picture_links) > 0):
                # print(picture_links)
                data["picture_links"] = picture_links
            else:
                data["picture_links"] = []

            # data["good_zan"] = article.xpath("./div/div/a[@class='pinattn good']/p/text()")[0]
            # data["bad_bs"] = article.xpath("./div/div/a[@class='pinattn bad']/p/text()")[0]
            data["good_zan"] = self.analyze_zan(article, "good")
            # article.xpath("./div/div/a[@class='pinattn good']/p/text()")[0]
            data["bad_bs"] = self.analyze_zan(article, "bad")
            # article.xpath("./div/div/a[@class='pinattn bad']/p/text()")[0]
            lines.append(data)
        return lines

    # 解析文章內容
    def analyze_content(self, article):
        # 1. 判斷dd標簽下是否為文本內容
        content = article.xpath("./dd/text()")
        if content is not None and len(content) > 0 and not self.is_empty_list(content):
            return content

        content = []
        p_list = article.xpath("./dd")
        for p in p_list:
            # 2. 判斷dd/.../font標簽下是否為文本內容
            if len(content) <= 0 or content is None:
                fonts = p.xpath(".//font")
                for font_html in fonts:
                    font_content = font_html.xpath("./text()")
                    if font_content is not None and len(font_content) > 0:
                        content.append(font_content)

            # 3. 判斷dd/.../p標簽下是否為文本內容
            if len(content) <= 0 or content is None:
                fonts = p.xpath(".//p")
                for font_html in fonts:
                    font_content = font_html.xpath("./text()")
                    if font_content is not None and len(font_content) > 0:
                        content.append(font_content)

        return content

    def analyze_zan(self, article, type):
        num = article.xpath("./div/div/a[@class='pinattn " + type + "']/p/text()")
        if num is not None and len(num) > 0:
            return num[0]
        return 0

    def do_word(self):
        fieldnames = ['index', 'link', 'title', 'content', 'picture_links', 'good_zan', 'bad_bs']
        with open('article.csv', 'a', encoding='UTF8', newline='') as f:
            writer = csv.DictWriter(f, fieldnames=fieldnames)
            # writer.writeheader()
            for i in range(self.start_page, self.end_page):
                articles = self.askHTML(i, 3)
                if articles is None:
                    continue
                article_list = self.analyze(articles)
                self.save(writer, article_list)

    # 保存到文件中
    def save(self, writer, lines):
        print("##### 保存中到文件中...")
        # python2可以用file替代open
        print(lines)
        writer.writerows(lines)
        print("##### 保存成功...")

    def is_empty_list(self, list):
        for l in list:
            if not self.empty(l):
                return False
        return True

    def empty(self, content):
        result = content.replace("\r", "").replace("\n", "")
        if result == "":
            return True
        return False

    # 遞歸解析文章內容
    def analyze_font_content(self, font_html, depth):
        content = []
        print(depth)
        font_content_list = font_html.xpath("./font/text()")
        if font_content_list is not None and len(font_content_list) > 0 and not self.is_empty_list(font_content_list):
            for font_content in font_content_list:
                content.append(font_content)
        else:
            if depth < 0:
                return []
            return self.analyze_font_content(font_html.xpath("./font"), depth - 1)

        return content


if __name__ == '__main__':
    page = Page()
    page.do_word()

在運行下麵的代碼之前，需要先按照好requests、lxml兩個模塊，安裝命令為：

pip installl requests
pip install lxml

大家對這個爬蟲有什麼疑問，歡迎給我留言。如果大家對於我這個爬蟲創意還不錯的話，記得關註微信公眾號【智享學習】喲，後續我會分享更多有意思的編程項目。

本文由博客一文多發平臺 OpenWrite 發佈！