前言

B站作为一个弹幕视频网站，有着所谓的弹幕文化，那么接下来我们看看，一个视频中出现最多的弹幕是什么？

知识点：

1. 爬虫基本流程

2. 正则

3. requests

4. jieba

5. csv

6. wordcloud

开发环境：

Python 3.6

Pycharm

Python部分

步骤：

import re
import requests
import csv

1、确定爬取的url路径，headers参数

 

 

代码：

url = 'https://api.bilibili.com/x/v1/dm/list.so?oid=186803402'
headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.108 Safari/537.36'}

 

2、模拟浏览器发送请求，获取相应内容

headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/78.0.3904.108 Safari/537.36'}
resp = requests.get(url)
#乱码
print(resp.content.decode('utf-8'))

3、解析网页 提取数据

#按照要求提取网页数据
res = re.compile('<d.*?>(.*?)</d>')
danmu = re.findall(res,html_doc)
print(danmu)

4、保存数据

for i in danmu:
	with open('C:/Users/Administrator/Desktop/B站弹幕.csv','a',newline='',encoding='utf-8-sig') as f:
        writer = csv.writer(f)
        danmu = []
        danmu.append(i)
        writer.writerow(danmu)

 

 

显示数据

导入词云制作库wordcloud和中文分词库jieba

import jieba
import wordcloud

导入imageio库中的imread函数，并用这个函数读取本地图片，作为词云形状图片

import imageio

mk = imageio.imread(r"拳头.png")
headers = {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/71.0.3578.98 Safari/537.36",
}

response = requests.get("https://api.bilibili.com/x/v1/dm/list.so?oid=186803402", headers=headers)
# print(response.text)
html_doc = response.content.decode('utf-8')
# soup = BeautifulSoup(html_doc,'lxml')
format = re.compile("<d.*?>(.*?)</d>")
DanMu = format.findall(html_doc)

for i in DanMu:
    with open('C:/Users/Mark/Desktop/b站弹幕.csv', "a", newline='', encoding='utf-8-sig') as csvfile:
        writer = csv.writer(csvfile)
        danmu = []
        danmu.append(i)
        writer.writerow(danmu)

构建并配置词云对象w，注意要加stopwords集合参数，将不想展示在词云中的词放在stopwords集合里，这里去掉“曹操”和“孔明”两个词

w = wordcloud.WordCloud(width=1000,
                        height=700,
                        background_color='white',
                        font_path='msyh.ttc',
                        mask=mk,
                        scale=15,
                        stopwords={' '},
                        contour_width=5,
                        contour_color='red')

对来自外部文件的文本进行中文分词，得到string

f = open('C:/Users/Mark/Desktop/b站弹幕.csv', encoding='utf-8')
txt = f.read()
txtlist = jieba.lcut(txt)
string = " ".join(txtlist)

将string变量传入w的generate()方法，给词云输入文字

w.generate(string)

将词云图片导出到当前文件夹

w.to_file('C:/Users/Mark/Desktop/output2-threekingdoms.png')

效果如下：