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e09401b81a
* Optimize encoding detection * Use a threshold based system
51 lines
1.4 KiB
Python
51 lines
1.4 KiB
Python
from typing import Union, Tuple
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from charset_normalizer import from_bytes
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from charset_normalizer.constant import TOO_SMALL_SEQUENCE
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UTF8 = 'utf-8'
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ContentBytes = Union[bytearray, bytes]
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def detect_encoding(content: ContentBytes) -> str:
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"""
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We default to UTF-8 if text too short, because the detection
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can return a random encoding leading to confusing results
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given the `charset_normalizer` version (< 2.0.5).
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>>> too_short = ']"foo"'
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>>> detected = from_bytes(too_short.encode()).best().encoding
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>>> detected
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'ascii'
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>>> too_short.encode().decode(detected)
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']"foo"'
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"""
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encoding = UTF8
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if len(content) > TOO_SMALL_SEQUENCE:
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match = from_bytes(bytes(content)).best()
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if match:
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encoding = match.encoding
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return encoding
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def smart_decode(content: ContentBytes, encoding: str) -> Tuple[str, str]:
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"""Decode `content` using the given `encoding`.
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If no `encoding` is provided, the best effort is to guess it from `content`.
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Unicode errors are replaced.
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"""
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if not encoding:
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encoding = detect_encoding(content)
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return content.decode(encoding, 'replace'), encoding
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def smart_encode(content: str, encoding: str) -> bytes:
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"""Encode `content` using the given `encoding`.
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Unicode errors are replaced.
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"""
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return content.encode(encoding, 'replace')
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