421 lines
12 KiB
Python
421 lines
12 KiB
Python
from __future__ import annotations
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import importlib
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import logging
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import unicodedata
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from bisect import bisect_right
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from codecs import IncrementalDecoder
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from encodings.aliases import aliases
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from functools import lru_cache
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from re import findall
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from typing import Generator
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from _multibytecodec import ( # type: ignore[import-not-found,import]
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MultibyteIncrementalDecoder,
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)
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from .constant import (
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ENCODING_MARKS,
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IANA_SUPPORTED_SIMILAR,
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RE_POSSIBLE_ENCODING_INDICATION,
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UNICODE_RANGES_COMBINED,
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UNICODE_SECONDARY_RANGE_KEYWORD,
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UTF8_MAXIMAL_ALLOCATION,
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COMMON_CJK_CHARACTERS,
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_LATIN,
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_CJK,
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_HANGUL,
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_KATAKANA,
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_HIRAGANA,
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_THAI,
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_ARABIC,
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_ARABIC_ISOLATED_FORM,
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_ACCENT_KEYWORDS,
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_ACCENTUATED,
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)
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@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
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def _character_flags(character: str) -> int:
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"""Compute all name-based classification flags with a single unicodedata.name() call."""
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try:
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desc: str = unicodedata.name(character)
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except ValueError:
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return 0
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flags: int = 0
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if "LATIN" in desc:
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flags |= _LATIN
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if "CJK" in desc:
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flags |= _CJK
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if "HANGUL" in desc:
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flags |= _HANGUL
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if "KATAKANA" in desc:
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flags |= _KATAKANA
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if "HIRAGANA" in desc:
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flags |= _HIRAGANA
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if "THAI" in desc:
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flags |= _THAI
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if "ARABIC" in desc:
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flags |= _ARABIC
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if "ISOLATED FORM" in desc:
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flags |= _ARABIC_ISOLATED_FORM
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for kw in _ACCENT_KEYWORDS:
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if kw in desc:
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flags |= _ACCENTUATED
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break
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return flags
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@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
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def is_accentuated(character: str) -> bool:
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return bool(_character_flags(character) & _ACCENTUATED)
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@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
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def remove_accent(character: str) -> str:
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decomposed: str = unicodedata.decomposition(character)
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if not decomposed:
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return character
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codes: list[str] = decomposed.split(" ")
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return chr(int(codes[0], 16))
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# Pre-built sorted lookup table for O(log n) binary search in unicode_range().
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# Each entry is (range_start, range_end_exclusive, range_name).
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_UNICODE_RANGES_SORTED: list[tuple[int, int, str]] = sorted(
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(ord_range.start, ord_range.stop, name)
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for name, ord_range in UNICODE_RANGES_COMBINED.items()
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)
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_UNICODE_RANGE_STARTS: list[int] = [e[0] for e in _UNICODE_RANGES_SORTED]
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@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
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def unicode_range(character: str) -> str | None:
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"""
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Retrieve the Unicode range official name from a single character.
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"""
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character_ord: int = ord(character)
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# Binary search: find the rightmost range whose start <= character_ord
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idx = bisect_right(_UNICODE_RANGE_STARTS, character_ord) - 1
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if idx >= 0:
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start, stop, name = _UNICODE_RANGES_SORTED[idx]
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if character_ord < stop:
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return name
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return None
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@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
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def is_latin(character: str) -> bool:
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return bool(_character_flags(character) & _LATIN)
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@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
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def is_punctuation(character: str) -> bool:
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character_category: str = unicodedata.category(character)
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if "P" in character_category:
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return True
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character_range: str | None = unicode_range(character)
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if character_range is None:
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return False
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return "Punctuation" in character_range
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@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
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def is_symbol(character: str) -> bool:
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character_category: str = unicodedata.category(character)
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if "S" in character_category or "N" in character_category:
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return True
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character_range: str | None = unicode_range(character)
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if character_range is None:
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return False
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return "Forms" in character_range and character_category != "Lo"
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@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
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def is_emoticon(character: str) -> bool:
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character_range: str | None = unicode_range(character)
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if character_range is None:
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return False
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return "Emoticons" in character_range or "Pictographs" in character_range
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@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
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def is_separator(character: str) -> bool:
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if character.isspace() or character in {"｜", "+", "<", ">"}:
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return True
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character_category: str = unicodedata.category(character)
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return "Z" in character_category or character_category in {"Po", "Pd", "Pc"}
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@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
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def is_case_variable(character: str) -> bool:
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return character.islower() != character.isupper()
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@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
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def is_cjk(character: str) -> bool:
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return bool(_character_flags(character) & _CJK)
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@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
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def is_hiragana(character: str) -> bool:
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return bool(_character_flags(character) & _HIRAGANA)
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@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
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def is_katakana(character: str) -> bool:
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return bool(_character_flags(character) & _KATAKANA)
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@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
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def is_hangul(character: str) -> bool:
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return bool(_character_flags(character) & _HANGUL)
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@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
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def is_thai(character: str) -> bool:
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return bool(_character_flags(character) & _THAI)
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@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
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def is_arabic(character: str) -> bool:
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return bool(_character_flags(character) & _ARABIC)
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@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
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def is_arabic_isolated_form(character: str) -> bool:
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return bool(_character_flags(character) & _ARABIC_ISOLATED_FORM)
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@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
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def is_cjk_uncommon(character: str) -> bool:
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return character not in COMMON_CJK_CHARACTERS
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@lru_cache(maxsize=len(UNICODE_RANGES_COMBINED))
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def is_unicode_range_secondary(range_name: str) -> bool:
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return any(keyword in range_name for keyword in UNICODE_SECONDARY_RANGE_KEYWORD)
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@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
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def is_unprintable(character: str) -> bool:
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return (
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character.isspace() is False # includes \n \t \r \v
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and character.isprintable() is False
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and character != "\x1a" # Why? Its the ASCII substitute character.
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and character != "\ufeff" # bug discovered in Python,
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# Zero Width No-Break Space located in Arabic Presentation Forms-B, Unicode 1.1 not acknowledged as space.
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)
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def any_specified_encoding(sequence: bytes, search_zone: int = 8192) -> str | None:
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"""
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Extract using ASCII-only decoder any specified encoding in the first n-bytes.
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"""
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if not isinstance(sequence, (bytes, bytearray)):
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raise TypeError
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seq_len: int = len(sequence)
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results: list[str] = findall(
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RE_POSSIBLE_ENCODING_INDICATION,
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sequence[: min(seq_len, search_zone)].decode("ascii", errors="ignore"),
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)
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if len(results) == 0:
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return None
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for specified_encoding in results:
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specified_encoding = specified_encoding.lower().replace("-", "_")
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encoding_alias: str
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encoding_iana: str
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for encoding_alias, encoding_iana in aliases.items():
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if encoding_alias == specified_encoding:
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return encoding_iana
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if encoding_iana == specified_encoding:
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return encoding_iana
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return None
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@lru_cache(maxsize=128)
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def is_multi_byte_encoding(name: str) -> bool:
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"""
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Verify is a specific encoding is a multi byte one based on it IANA name
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"""
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return name in {
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"utf_8",
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"utf_8_sig",
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"utf_16",
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"utf_16_be",
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"utf_16_le",
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"utf_32",
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"utf_32_le",
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"utf_32_be",
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"utf_7",
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} or issubclass(
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importlib.import_module(f"encodings.{name}").IncrementalDecoder,
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MultibyteIncrementalDecoder,
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)
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def identify_sig_or_bom(sequence: bytes) -> tuple[str | None, bytes]:
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"""
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Identify and extract SIG/BOM in given sequence.
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"""
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for iana_encoding in ENCODING_MARKS:
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marks: bytes | list[bytes] = ENCODING_MARKS[iana_encoding]
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if isinstance(marks, bytes):
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marks = [marks]
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for mark in marks:
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if sequence.startswith(mark):
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return iana_encoding, mark
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return None, b""
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def should_strip_sig_or_bom(iana_encoding: str) -> bool:
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return iana_encoding not in {"utf_16", "utf_32"}
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def iana_name(cp_name: str, strict: bool = True) -> str:
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"""Returns the Python normalized encoding name (Not the IANA official name)."""
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cp_name = cp_name.lower().replace("-", "_")
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encoding_alias: str
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encoding_iana: str
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for encoding_alias, encoding_iana in aliases.items():
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if cp_name in [encoding_alias, encoding_iana]:
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return encoding_iana
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if strict:
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raise ValueError(f"Unable to retrieve IANA for '{cp_name}'")
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return cp_name
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def cp_similarity(iana_name_a: str, iana_name_b: str) -> float:
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if is_multi_byte_encoding(iana_name_a) or is_multi_byte_encoding(iana_name_b):
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return 0.0
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decoder_a = importlib.import_module(f"encodings.{iana_name_a}").IncrementalDecoder
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decoder_b = importlib.import_module(f"encodings.{iana_name_b}").IncrementalDecoder
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id_a: IncrementalDecoder = decoder_a(errors="ignore")
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id_b: IncrementalDecoder = decoder_b(errors="ignore")
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character_match_count: int = 0
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for i in range(256):
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to_be_decoded: bytes = bytes([i])
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if id_a.decode(to_be_decoded) == id_b.decode(to_be_decoded):
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character_match_count += 1
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return character_match_count / 256
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def is_cp_similar(iana_name_a: str, iana_name_b: str) -> bool:
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"""
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Determine if two code page are at least 80% similar. IANA_SUPPORTED_SIMILAR dict was generated using
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the function cp_similarity.
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"""
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return (
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iana_name_a in IANA_SUPPORTED_SIMILAR
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and iana_name_b in IANA_SUPPORTED_SIMILAR[iana_name_a]
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)
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def set_logging_handler(
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name: str = "charset_normalizer",
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level: int = logging.INFO,
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format_string: str = "%(asctime)s | %(levelname)s | %(message)s",
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) -> None:
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logger = logging.getLogger(name)
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logger.setLevel(level)
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handler = logging.StreamHandler()
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handler.setFormatter(logging.Formatter(format_string))
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logger.addHandler(handler)
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def cut_sequence_chunks(
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sequences: bytes,
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encoding_iana: str,
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offsets: range,
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chunk_size: int,
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bom_or_sig_available: bool,
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strip_sig_or_bom: bool,
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sig_payload: bytes,
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is_multi_byte_decoder: bool,
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decoded_payload: str | None = None,
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) -> Generator[str, None, None]:
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if decoded_payload and is_multi_byte_decoder is False:
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for i in offsets:
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chunk = decoded_payload[i : i + chunk_size]
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if not chunk:
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break
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yield chunk
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else:
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for i in offsets:
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chunk_end = i + chunk_size
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if chunk_end > len(sequences) + 8:
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continue
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cut_sequence = sequences[i : i + chunk_size]
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if bom_or_sig_available and strip_sig_or_bom is False:
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cut_sequence = sig_payload + cut_sequence
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chunk = cut_sequence.decode(
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encoding_iana,
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errors="ignore" if is_multi_byte_decoder else "strict",
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)
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# multi-byte bad cutting detector and adjustment
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# not the cleanest way to perform that fix but clever enough for now.
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if is_multi_byte_decoder and i > 0:
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chunk_partial_size_chk: int = min(chunk_size, 16)
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if (
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decoded_payload
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and chunk[:chunk_partial_size_chk] not in decoded_payload
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):
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for j in range(i, i - 4, -1):
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cut_sequence = sequences[j:chunk_end]
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if bom_or_sig_available and strip_sig_or_bom is False:
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cut_sequence = sig_payload + cut_sequence
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chunk = cut_sequence.decode(encoding_iana, errors="ignore")
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if chunk[:chunk_partial_size_chk] in decoded_payload:
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break
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yield chunk
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