如何解压缩已压缩的base64字符串?

时间:2020-11-09 00:00:14

标签: python compression

以下是我要解压缩的字符串:

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

我尝试过zlib:

import zlib
decompressed_data = zlib.decompress(data)

我收到以下错误:

TypeError: a bytes-like object is required, not 'str'

然后我做了:

data = bytes(data, "utf-8")
decompressed_data = zlib.decompress(data)

我再次遇到错误:

Error -3 while decompressing data: incorrect header check

1 个答案:

答案 0 :(得分:3)

您首先需要解码base64,然后zlib解压缩:

import zlib, base64
decompressed_data = zlib.decompress(base64.b64decode(data))

查看您的数据,它似乎是UTF-8编码的XML,所以我们快到了:

xml = decompressed_data.decode("utf-8")