以网易云音乐为例，动态抓取指定明星的歌曲列表，保存歌词文件，去除歌词中的常用词，并对歌词进行词云展示，分析歌曲的作词风格:

# -*- coding:utf-8 -*-
# 网易云音乐 通过歌手ID，生成该歌手的词云
import requests
import sys
import re
import os
from wordcloud import WordCloud
import matplotlib.pyplot as plt
import jieba
from PIL import Image
import numpy as np
from lxml import etree

#头部信息
headers = {
        'Referer'   :'http://music.163.com',
        'Host'      :'music.163.com',
        'Accept'    :'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8',
        'User-Agent':'Chrome/10'
    }

# 获取歌词
def get_song_lyric(headers, lyric_url):
    res = requests.request('GET', lyric_url, headers=headers)
    if 'lrc' in res.json():
        lyric = res.json()['lrc']['lyric']
        new_lyric = re.sub(r'[\d:.[\]]','',lyric)
        return new_lyric
    else:
        return ''

# 去掉停用词
def remove_stop_words(f):
    stop_words = ['作词', '作曲', '编曲', 'Arranger', '录音', '混音', '人声', 'Vocal', '弦乐', 'Keyboard', '键盘', '编辑', '助理', 'Assistants', 'Mixing', 'Editing', 'Recording', '音乐', '制作', 'Producer', '发行', 'produced', 'and', 'distributed']
    for stop_word in stop_words:
        f = f.replace(stop_word, '')
    return f

# 生成词云
def create_word_cloud(f):
    print('根据词频，开始生成词云!')
    f = remove_stop_words(f)
    cut_text = " ".join(jieba.cut(f,cut_all=False, HMM=True))
    wc = WordCloud(
        font_path="./wc.ttf",
        max_words=100,
        width=2000,
        height=1200,
    )
    wordcloud = wc.generate(cut_text)
    # 写词云图片
    wordcloud.to_file("wordcloud.jpg")
    # 显示词云文件
    plt.imshow(wordcloud)
    plt.axis("off")
    plt.show()


# 得到指定歌手页面 热门前50的歌曲ID，歌曲名
def get_songs(artist_id):
    page_url = 'https://music.163.com/artist?id=' + artist_id
    # 获取网页HTML
    res = requests.request('GET', page_url, headers=headers)
    # 用XPath解析 前50首热门歌曲
    html = etree.HTML(res.text)
    href_xpath = "//*[@id='hotsong-list']//a/@href"
    name_xpath = "//*[@id='hotsong-list']//a/text()"
    hrefs = html.xpath(href_xpath)
    names = html.xpath(name_xpath)
    # 设置热门歌曲的ID，歌曲名称
    song_ids = []
    song_names = []
    for href, name in zip(hrefs, names):
        song_ids.append(href[9:])
        song_names.append(name)
    return song_ids, song_names

# 设置歌手ID，毛不易为12138269
artist_id = '12138269'
[song_ids, song_names] = get_songs(artist_id)

# 所有歌词
all_word = ''
# 获取每首歌歌词
for (song_id, song_name) in zip(song_ids, song_names):
    # 歌词API URL
    lyric_url = 'http://music.163.com/api/song/lyric?os=pc&id=' + song_id + '&lv=-1&kv=-1&tv=-1'
    lyric = get_song_lyric(headers, lyric_url)
    all_word = all_word + ' ' + lyric

#根据词频 生成词云
create_word_cloud(all_word)

效果如下：

image.png