歌词词云可视化

    # -*- 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)