爬虫大作业

1.选一个自己感兴趣的主题。

2.用python 编写爬虫程序，从网络上爬取相关主题的数据。

3.对爬了的数据进行文本分析，生成词云。

4.对文本分析结果进行解释说明。

5.写一篇完整的博客，描述上述实现过程、遇到的问题及解决办法、数据分析思想及结论。

6.最后提交爬取的全部数据、爬虫及数据分析源代码。

       此次实验中，通过爬取网易云音乐-遥远的她网页中的热门评论来做词频分析
爬取热门评论并保存至txt文本的代码：

# -*- coding : UTF-8 -*-
# -*- author : Kamchuen -*-
# -*- file : project1 -*-
# -*- time: 2018/4/28 -*-
# -*- description: 歌曲热门评论获取-*-
# -*- songname: 遥远的她-*-

import requests
import json

def getcomments(musicid):
    url = 'http://music.163.com/weapi/v1/resource/comments/R_SO_4_191232?csrf_token=5594eaee83614ea8ca9017d85cd9d1b3'.format(musicid)
    payload = {
        'params': '5KX6Y3k92jAA0++OK5aeNVeABXbc97L0PMviuChCa4cr1OW3wHCWDSLEtRyQwXdMC2+BbLjG3qA8N9gLOgL5WPBSl2qyIv++7YRnEn3BxO2hq6opl5B3Jgbi/I/PPkxneLfgYuIo71F0VxqAVaoJlMefBej5M/fZ5eO3YkvOKWaAHbtJYL+g17z8XskUfcHm',
        'encSecKey': '5baedada4b87cc31a46b38d0a3893895da30fe3bddaf8a24020ce17fa004f2e646cb15e109c4786e55eca0e88dbd6dc905aa55fd6cd7f4de1e625937d986dd4e1217a19e4f4a2f0e00504763308148ab3215ae25a5ac99e65ba8e46f2f8a734182fc20c5a7281f1d127a513a954b17d66a75f4a06f0044fc6c783dd356b017a7'
    }
    headers = {
        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/65.0.3325.181 Safari/537.36',
        'Referer': 'http://music.163.com/song?id={}'.format(musicid),
        'Host': 'music.163.com',
        'Origin': 'http://music.163.com'
    }

    response = requests.post(url=url, headers=headers, data=payload)
    data = json.loads(response.text)
    hotcomments = []
    for hotcomment in data['hotComments']:
        item = {
            'nickname': hotcomment['user']['nickname'],
            'content': hotcomment['content']
        }
        hotcomments.append(item)

    # 返回热门评论
    return [content['content'] for content in hotcomments]

if __name__ == '__main__':
    hot = getcomments(191232)
    print(hot)
    file = open('hot.txt','w')
    for hotword in hot:
           file.write(hotword+'\n')
    file.close()

打开txt文本生成词云的代码：

# -*- coding : UTF-8 -*-
# -*- author : Kamchuen -*-
# -*- file : wordcloudTest1 -*-
# -*- time: 2018/4/28 -*-
# -*- description: 词云测试-*-
from os import path
from PIL import Image
import numpy as np
import matplotlib.pyplot as plt

from wordcloud import WordCloud, STOPWORDS, ImageColorGenerator

d = path.dirname(__file__)


text = open(path.join(d, 'hot.txt')).read()


alice_coloring = np.array(Image.open(path.join(d, "奥特曼.jpg")))
stopwords = set(STOPWORDS)
stopwords.add("said")

wc = WordCloud(background_color="white", max_words=2000, mask=alice_coloring,
               stopwords=stopwords, max_font_size=85, font_path="STHUPO.TTF",random_state=50)

wc.generate(text)

image_colors = ImageColorGenerator(alice_coloring)

# show
plt.imshow(wc, interpolation="bilinear")
plt.axis("off")
plt.figure()
plt.imshow(wc.recolor(color_func=image_colors), interpolation="bilinear")
plt.axis("off")
plt.figure()
plt.imshow(alice_coloring, cmap=plt.cm.gray, interpolation="bilinear")
plt.axis("off")
plt.show()

结果：