• 爬虫大作业


    我爬取的是新浪新闻,打开网页链接http://news.sina.com.cn/china/:

    打开网页获取需要的链接:,然后开始做项目。

    1,获取评论数:

    def getCommentsCounts(newsurl):
        bianhao = re.search('doc-i(.+).shtml', newsurl)
        newsid=bianhao.group(1)
        comment=requests.get(commentURL.format(newsid))
        jd = json.loads(comment.text)
        counts=jd['result']['count']['total']
        return counts
    

    2 获取新闻内容:

    def getNewsDetail(newsurl):
        result = {}
        res=requests.get(newsurl)
        res.encoding='utf-8'
        soup=BeautifulSoup(res.text,'html.parser')
        # 获取标题
        result['title']=soup.select(".main-title")[0].text
        # 来源
        result['newssources'] = soup.select('.source')[0].text
        # 时间
        result['timesource'] = soup.select('.date')[0].text
        # 编辑
        result['editor']=soup.select('.show_author')[0].text.strip('责任编辑:')[-1]
        # 评论数
        result['comments']=getCommentsCounts(url)
        # 内容
        result['contents']= soup.select('.article')[0].text.strip()
        # writeNewsContent(content)
        return str(result['contents'])
    

     3 保存为txt:

    def writeNewsContent(content):
        f=open('news.txt','a',encoding='utf-8')
        f.write(content)
        f.close()
    

      得到txt文本:

    4 词频分析并生成词云:

    for c in sep:
        news = news.replace(c, ' ')
    wordList = list(jieba.cut(news))
    wordDict = {}
    words = list(set(wordList) - exclude)
    
    for w in range(0, len(words)):
        wordDict[words[w]] = news.count(str(words[w]))
    
    dictList = list(wordDict.items())
    dictList.sort(key=lambda x: x[1], reverse=True)
    cy = {}
    f = open('news.txt', 'a', encoding="utf-8")
    for i in range(1000):
        print(dictList[i])
        f.write(dictList[i][0] + ':' + str(dictList[i][1]) + '
    ')
        cy[dictList[i][0]] = dictList[i][1]
    f.close()
    
    font = r'C:WindowsFontswb.ttf'
    image = Image.open('./wordcloud.jpg')
    graph = np.array(image)
    wc = WordCloud(font_path=font, background_color='White', max_words=50, mask=graph)
    wc.generate_from_frequencies(cy)
    image_color = ImageColorGenerator(graph)
    plt.imshow(wc)
    plt.axis("off")
    plt.show()
    

     得到词云图片:

    在做大作业的过程中,遇到的主要问题还是在安装wordcloud上,出现了Fatal error in launcher: Unable to create process using '"'的问题,当然不止这个问题,只是最后才找到这个关键的问题,这个问题后来困扰了我两天时间,于是我开始了与wordcloud的对抗。查了各种资料,最后终于在一篇博文(https://blog.csdn.net/testcs_dn/article/details/54176504)上找到了解决这个问题的答案。先升级pip,嗯,第一遍不知道为啥不成功,还好又试了一个,很好,成功了。

    然后,就下载whl,接着安装,这里就不说了哈,百度上有。最后贴上代码:。

    大作业代码:

    import requests
    import json
    import re
    from bs4 import BeautifulSoup
    import jieba
    # 获取评论数
    def getCommentsCounts(newsurl):
        bianhao = re.search('doc-i(.+).shtml', newsurl)
        newsid=bianhao.group(1)
        comment=requests.get(commentURL.format(newsid))
        jd = json.loads(comment.text)
        counts=jd['result']['count']['total']
        return counts
    
    def getNewsDetail(newsurl):
        result = {}
        res=requests.get(newsurl)
        res.encoding='utf-8'
        soup=BeautifulSoup(res.text,'html.parser')
        # 获取标题
        result['title']=soup.select(".main-title")[0].text
        # 来源
        result['newssources'] = soup.select('.source')[0].text
        # 时间
        result['timesource'] = soup.select('.date')[0].text
        # 编辑
        result['editor']=soup.select('.show_author')[0].text.strip('责任编辑:')[-1]
        # 评论数
        result['comments']=getCommentsCounts(url)
        # 内容
        result['contents']= soup.select('.article')[0].text.strip()
        # writeNewsContent(content)
        return str(result['contents'])
    # 保为 txt
    def writeNewsContent(content):
        f=open('news.txt','a',encoding='utf-8')
        f.write(content)
        f.close()
    
    def parseListLinks(url):
        newsdetails=[]
        res=requests.get(url)
        jss = res.text.lstrip('  newsloadercallback(').rstrip(');')
        jd = json.loads(jss)
        for news in jd['result']['data']:
            allURL=news['url']
            newsdetails.append(getNewsDetail(allURL).split())
        writeNewsContent(str(newsdetails))
        return newsdetails
    
    commentURL = 'http://comment5.news.sina.com.cn/page/info?version=1
        &format=json&channel=gn&newsid=comos-{}&group=undefined&
        compress=0&ie=utf-8&oe=utf-8&page=1&page_size=3'
    url='http://news.sina.com.cn/c/zj/2018-04-20/doc-ifzihneq2559172.shtml'
    listURL='http://api.roll.news.sina.com.cn/zt_list?channel=news&cat_1=gnxw&cat_2==gdxw1||=gatxw||=zs-pl||=mtjj&level==1||=2&show_ext=1&show_all=1&show_num=22&tag=1&format=json&page={}&
    callback=newsloadercallback&_=1524705663198'
    news_total=[]
    for i in range(1,2):
        newssurl=listURL.format(i)
        newsary=parseListLinks(newssurl)
        news_total.extend(newsary)
    print(len(news_total))


       

    import jieba
    from PIL import Image
    import numpy as np
    import matplotlib.pyplot as plt
    from wordcloud import WordCloud,ImageColorGenerator
    
    f = open('content.txt', 'r', encoding='utf-8')
    news = f.read()
    f.close()
    
    sep = ''',。‘’“”:;()!?、《》[] '''
    exclude = {'的','下','中','就','是','■'}
    
    jieba.add_word('中国芯')
    jieba.add_word('倪光南')
    jieba.add_word('梁宁')
    jieba.add_word('沈静文')
    jieba.add_word('宋爽')
    jieba.add_word('冯志远')
    jieba.add_word('霍宇昂')
    jieba.add_word('杨冠宇')
    jieba.add_word('杨渡')
    
    for c in sep:
        news = news.replace(c, ' ')
    wordList = list(jieba.cut(news))
    wordDict = {}
    words = list(set(wordList) - exclude)
    
    for w in range(0, len(words)):
        wordDict[words[w]] = news.count(str(words[w]))
    
    dictList = list(wordDict.items())
    dictList.sort(key=lambda x: x[1], reverse=True)
    cy = {}
    f = open('news.txt', 'a', encoding="utf-8")
    for i in range(1000):
        print(dictList[i])
        f.write(dictList[i][0] + ':' + str(dictList[i][1]) + '
    ')
        cy[dictList[i][0]] = dictList[i][1]
    f.close()
    
    font = r'C:WindowsFontswb.ttf'
    image = Image.open('./wordcloud.jpg')
    graph = np.array(image)
    wc = WordCloud(font_path=font, background_color='White', max_words=50, mask=graph)
    wc.generate_from_frequencies(cy)
    image_color = ImageColorGenerator(graph)
    plt.imshow(wc)
    plt.axis("off")
    plt.show()
    

     词云底片:

    生成的词云:

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  • 原文地址:https://www.cnblogs.com/Runka/p/8963876.html
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