哔哩哔哩怎么使用弹幕字号的大小操作方法

爬取哔哩哔哩的弹幕，http://comment.bilibili.com/6315651.xml

需要知道cid,可以F12,F5刷新，找cid，找到之后拼接url

也可以写代码，解析response获取cid,然后再拼接

使用requests或者urllib都可以

我是用requests，请求该链接获取到xml文件

代码：获取xml

def get_data(): res = requests.get('http://comment.bilibili.com/6315651.xml') res.encoding = 'utf8' with open('gugongdanmu.xml', 'a', encoding='utf8') as f: f.writelines(res.text)

解析xml,

def analyze_xml(): f1 = open("gugongdanmu.xml", "r", encoding='utf8') f2 = open("tanmu2.txt", "w", encoding='utf8') count = 0 # 正则匹配解决xml的多余的字符 dr = re.compile(r'u0026lt;[^u0026gt;]+u0026gt;', re.S) while 1: line = f1.readline() if not line: break pass # 匹配到之后用空代替 dd = dr.sub('', line) # dd = re.findall(dr, line) count = count+1 f2.writelines(dd) print(count)

去掉无用的字符和数字，找出所有的汉字

def analyze_hanzi(): f1 = open("tanmu2.txt", "r", encoding='utf8') f2 = open("tanmu3.txt", "w", encoding='utf8') count = 0 # dr = re.compile(r'u0026lt;[^u0026gt;]+u0026gt;',re.S) # 所有的汉字[一-龥] dr = re.compile(r'[一-龥]+',re.S) while 1: line = f1.readline() if not line: break pass # 找出无用的符号和数字 # dd = dr.sub('',line) dd = re.findall(dr, line) count = count+1 f2.writelines(dd) print(count) # pattern = re.compile(r'[一-龥]+')

使用jieba分词，生成词云

def show_sign(): content = read_txt_file() segment = jieba.lcut(content) words_df = pd.DataFrame({'segment': segment}) stopwords = pd.read_csv("stopwords.txt", index_col=False, quoting=3, sep=" ", names=['stopword'], encoding='utf-8') words_df = words_df[~words_df.segment.isin(stopwords.stopword)] print(words_df) print('-------------------------------') words_stat = words_df.groupby(by=['segment'])['segment'].agg(numpy.size) words_stat = words_stat.to_frame() words_stat.columns = ['计数'] words_stat = words_stat.reset_index().sort_values(by=["计数"], ascending=False) # 设置词云属性 color_mask = imread('ciyun.png') wordcloud = WordCloud(font_path="simhei.ttf", # 设置字体可以显示中文 background_color="white", # 背景颜色 max_words=1000, # 词云显示的最大词数 mask=color_mask, # 设置背景图片 max_font_size=100, # 字体最大值 random_state=42, width=1000, height=860, margin=2, # 设置图片默认的大小,但是如果使用背景图片的话, # 那么保存的图片大小将会按照其大小保存,margin为词语边缘距离 ) # 生成词云, 可以用generate输入全部文本,也可以我们计算好词频后使用generate_from_frequencies函数 word_frequence = {x[0]: x[1] for x in words_stat.head(1000).values} print(word_frequence) # for key,value in word_frequence: # write_txt_file(word_frequence) word_frequence_dict = {} for key in word_frequence: word_frequence_dict[key] = word_frequence[key] wordcloud.generate_from_frequencies(word_frequence_dict) # 从背景图片生成颜色值 image_colors = ImageColorGenerator(color_mask) # 重新上色 wordcloud.recolor(color_func=image_colors) # 保存图片 wordcloud.to_file('output.png') plt.imshow(wordcloud) plt.axis("off") plt.show()

运行程序，结果：

统计的结果

完成！

pip的换源，原来的太慢，然后将你自己没有库装上