这是人人车的价格加密后，进行破解的方法：

import base64
from fontTools.ttLib import TTFont
'''
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'''

def create_ttf():
    b64_code = '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'

    with open('./font.ttf','wb') as f:
        f.write(base64.decodebytes(b64_code.encode()))

def decode_ttf(ttf_path):
    ttf = TTFont(ttf_path)
   # 输出数字与uni编码之间的关系 元素下标就是数字，元素内容是uni编码
    li = ttf.getGlyphOrder()[1:]
    # 输出uni编码与数字之间的关系，输出类型为字典，特殊字符的acill值:uni编码
    dic = ttf.getBestCmap()

    new_dict = {}
    for k, v in dic.items():
        # chr(k) 转成特殊字符   li.index(v) 找到uni编码所对应的下标(即对应数字)
        new_dict[chr(k)] = li.index(v)
    return new_dict
 
if __name__ == '__main__':
    # 生成ttf文件
    create_ttf()
    # 进行内容解析测试
    ttf_path = './font.ttf'  # 人人车加密价格的TTF字体文件路径
    encrypted_text = '-.%起'  # 需要解密的加密文本
    decrypted_text = decode_ttf(ttf_path)
    # 输出：人人车价格解密结果
    ans = ''
    for char in encrypted_text:
        if char == '.':
            ans += '.'
        else:
            ans += str(decrypted_text[char])
    print(ans)

老师，我有个疑问：

上一节视频说的大O（也就是函数渐近上界）和这一节咋不一样啊。上一结中说的是2n^2+8n+5的渐近上界是3n^2，这里怎么时间复杂度取的又是n^2啊。

3n^2在n增长时恒大于2n^2+8n+5，这可以理解。忽略低次项保留最高项（去系数）也可理解，就是不明白啥时候取3n^2，啥时候取n^2啊

为什么底层文件会报错

点击Admin无法访问 ，phpmyadmin访问被拒 ，怎么解决？

z这个怎么处理？

报错怎么解决

 按照视频里敲的，连接不上是啥原因

这里既然是加载数值型数据，为啥也能fen.get(key)呢

这里为啥可以使用count[r],count的类型不应该是个数字吗

老师，我敲完 yum install vim -y之后是这种情况，应该怎么解决

ENGINE=InnoDB DEFAULT CHARSET=utf8;

老师这句sql语句表示的是什么意思 前面好像没有讲过

a.sort()

last=a[-1]

for i in range(len(a)-2,-1,-1):

    if last==a[i]:

        del a[i]

    else:

        last=a[i]

print(a)

老师这段代码不理解，能解释一下吗

写一个函数, 输入一个字符串, 返回倒序排列的结果:用递归怎么写啊

def string_reverse5(text='abcdef'):

    if len(text)<=1:

        return text

    else:

        return string_reverse5(text[1:]+text[0])

报错

[Previous line repeated 996 more times]

RecursionError: maximum recursion depth exceeded

老师 加载模型也需要传入模型吗？

(3,2)< (‘a’,‘b’)

是比较ascill值吗