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Smartwave/venv/lib/python3.12/site-packages/charset_normalizer/utils.py
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This file contains ambiguous Unicode characters
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from __future__ import annotations
import importlib
import logging
import unicodedata
from bisect import bisect_right
from codecs import IncrementalDecoder
from encodings.aliases import aliases
from functools import lru_cache
from re import findall
from typing import Generator
from .constant import (
ENCODING_MARKS,
IANA_SUPPORTED_SIMILAR,
RE_POSSIBLE_ENCODING_INDICATION,
UNICODE_RANGES_COMBINED,
_SECONDARY_RANGE_NAMES,
UTF8_MAXIMAL_ALLOCATION,
COMMON_CJK_CHARACTERS,
_LATIN,
_CJK,
_HANGUL,
_KATAKANA,
_HIRAGANA,
_THAI,
_ARABIC,
_ARABIC_ISOLATED_FORM,
_ACCENT_KEYWORDS,
_ACCENTUATED,
)
def _character_flags(character: str) -> int:
"""Compute all name-based classification flags with a single unicodedata.name() call."""
try:
desc: str = unicodedata.name(character)
except ValueError:
return 0
flags: int = 0
if "LATIN" in desc:
flags |= _LATIN
if "CJK" in desc:
flags |= _CJK
if "HANGUL" in desc:
flags |= _HANGUL
if "KATAKANA" in desc:
flags |= _KATAKANA
if "HIRAGANA" in desc:
flags |= _HIRAGANA
if "THAI" in desc:
flags |= _THAI
if "ARABIC" in desc:
flags |= _ARABIC
if "ISOLATED FORM" in desc:
flags |= _ARABIC_ISOLATED_FORM
for kw in _ACCENT_KEYWORDS:
if kw in desc:
flags |= _ACCENTUATED
break
return flags
def is_accentuated(character: str) -> bool:
return bool(_character_flags(character) & _ACCENTUATED)
@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
def remove_accent(character: str) -> str:
decomposed: str = unicodedata.decomposition(character)
if not decomposed:
return character
codes: list[str] = decomposed.split(" ")
return chr(int(codes[0], 16))
# Pre-built sorted lookup table for O(log n) binary search in unicode_range().
# Each entry is (range_start, range_end_exclusive, range_name).
_UNICODE_RANGES_SORTED: list[tuple[int, int, str]] = sorted(
(ord_range.start, ord_range.stop, name)
for name, ord_range in UNICODE_RANGES_COMBINED.items()
)
_UNICODE_RANGE_STARTS: list[int] = [e[0] for e in _UNICODE_RANGES_SORTED]
def unicode_range(character: str) -> str | None:
"""
Retrieve the Unicode range official name from a single character.
"""
character_ord: int = ord(character)
# Binary search: find the rightmost range whose start <= character_ord
idx = bisect_right(_UNICODE_RANGE_STARTS, character_ord) - 1
if idx >= 0:
start, stop, name = _UNICODE_RANGES_SORTED[idx]
if character_ord < stop:
return name
return None
def is_latin(character: str) -> bool:
return bool(_character_flags(character) & _LATIN)
def is_punctuation(character: str) -> bool:
character_category: str = unicodedata.category(character)
if "P" in character_category:
return True
character_range: str | None = unicode_range(character)
if character_range is None:
return False
return "Punctuation" in character_range
def is_symbol(character: str) -> bool:
character_category: str = unicodedata.category(character)
if "S" in character_category or "N" in character_category:
return True
character_range: str | None = unicode_range(character)
if character_range is None:
return False
return "Forms" in character_range and character_category != "Lo"
def is_emoticon(character: str) -> bool:
character_range: str | None = unicode_range(character)
if character_range is None:
return False
return "Emoticons" in character_range or "Pictographs" in character_range
def is_separator(character: str) -> bool:
if character.isspace() or character in {"", "+", "<", ">"}:
return True
character_category: str = unicodedata.category(character)
return "Z" in character_category or character_category in {"Po", "Pd", "Pc"}
@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
def is_case_variable(character: str) -> bool:
return character.islower() != character.isupper()
@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
def is_cjk(character: str) -> bool:
return bool(_character_flags(character) & _CJK)
@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
def is_hiragana(character: str) -> bool:
return bool(_character_flags(character) & _HIRAGANA)
@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
def is_katakana(character: str) -> bool:
return bool(_character_flags(character) & _KATAKANA)
@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
def is_hangul(character: str) -> bool:
return bool(_character_flags(character) & _HANGUL)
@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
def is_thai(character: str) -> bool:
return bool(_character_flags(character) & _THAI)
@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
def is_arabic(character: str) -> bool:
return bool(_character_flags(character) & _ARABIC)
@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
def is_arabic_isolated_form(character: str) -> bool:
return bool(_character_flags(character) & _ARABIC_ISOLATED_FORM)
@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
def is_cjk_uncommon(character: str) -> bool:
return character not in COMMON_CJK_CHARACTERS
def is_unicode_range_secondary(range_name: str) -> bool:
return range_name in _SECONDARY_RANGE_NAMES
@lru_cache(maxsize=UTF8_MAXIMAL_ALLOCATION)
def is_unprintable(character: str) -> bool:
return (
not character.isspace() # includes \n \t \r \v
and not character.isprintable()
and character != "\x1a" # Why? Its the ASCII substitute character.
and character != "\ufeff" # bug discovered in Python,
# Zero Width No-Break Space located in Arabic Presentation Forms-B, Unicode 1.1 not acknowledged as space.
)
def any_specified_encoding(
sequence: bytes | bytearray, search_zone: int = 8192
) -> str | None:
"""
Extract using ASCII-only decoder any specified encoding in the first n-bytes.
"""
if not isinstance(sequence, (bytes, bytearray)):
raise TypeError
seq_len: int = len(sequence)
decoded_zone: str = sequence[: min(seq_len, search_zone)].decode(
"ascii", errors="ignore"
)
# Cheap literal pre-filter.
lowered_zone: str = decoded_zone.lower()
if "coding" not in lowered_zone and "charset" not in lowered_zone:
return None
results: list[str] = findall(
RE_POSSIBLE_ENCODING_INDICATION,
decoded_zone,
)
if len(results) == 0:
return None
for specified_encoding in results:
specified_encoding = specified_encoding.lower().replace("-", "_")
encoding_alias: str
encoding_iana: str
for encoding_alias, encoding_iana in aliases.items():
if encoding_alias == specified_encoding:
return encoding_iana
if encoding_iana == specified_encoding:
return encoding_iana
return None
@lru_cache(maxsize=128)
def is_multi_byte_encoding(name: str) -> bool:
"""
Verify is a specific encoding is a multi byte one based on it IANA name
"""
if name in {
"utf_8",
"utf_8_sig",
"utf_16",
"utf_16_be",
"utf_16_le",
"utf_32",
"utf_32_le",
"utf_32_be",
"utf_7",
}:
return True
# Besides the Unicode family above, every multibyte codec shipped with
# Python is implemented by _multibytecodec through exactly one of the six
# cjkcodecs providers below. Probing those providers directly (getcodec)
# classifies a name without importing its "encodings.<name>" module:
# classifying the whole IANA_SUPPORTED list would otherwise import many
# modules and dominate "import charset_normalizer" wall time.
# see https://github.com/jawah/charset_normalizer/issues/742
for provider in (
"_codecs_cn",
"_codecs_hk",
"_codecs_iso2022",
"_codecs_jp",
"_codecs_kr",
"_codecs_tw",
):
try:
importlib.import_module(provider).getcodec(name) # type: ignore[attr-defined]
except (ImportError, AttributeError, LookupError): # Defensive: edge cases
continue
return True
return False
def identify_sig_or_bom(sequence: bytes | bytearray) -> tuple[str | None, bytes]:
"""
Identify and extract SIG/BOM in given sequence.
"""
for iana_encoding in ENCODING_MARKS:
marks: bytes | list[bytes] = ENCODING_MARKS[iana_encoding]
if isinstance(marks, bytes):
marks = [marks]
for mark in marks:
if sequence.startswith(mark):
return iana_encoding, mark
return None, b""
def should_strip_sig_or_bom(iana_encoding: str) -> bool:
return iana_encoding not in {"utf_16", "utf_32"}
def iana_name(cp_name: str, strict: bool = True) -> str:
"""Returns the Python normalized encoding name (Not the IANA official name)."""
cp_name = cp_name.lower().replace("-", "_")
encoding_alias: str
encoding_iana: str
for encoding_alias, encoding_iana in aliases.items():
if cp_name in [encoding_alias, encoding_iana]:
return encoding_iana
if strict:
raise ValueError(f"Unable to retrieve IANA for '{cp_name}'")
return cp_name
def cp_similarity(iana_name_a: str, iana_name_b: str) -> float:
if is_multi_byte_encoding(iana_name_a) or is_multi_byte_encoding(iana_name_b):
return 0.0
decoder_a = importlib.import_module(f"encodings.{iana_name_a}").IncrementalDecoder
decoder_b = importlib.import_module(f"encodings.{iana_name_b}").IncrementalDecoder
id_a: IncrementalDecoder = decoder_a(errors="ignore")
id_b: IncrementalDecoder = decoder_b(errors="ignore")
character_match_count: int = 0
for i in range(256):
to_be_decoded: bytes = bytes([i])
if id_a.decode(to_be_decoded) == id_b.decode(to_be_decoded):
character_match_count += 1
return character_match_count / 256
def is_cp_similar(iana_name_a: str, iana_name_b: str) -> bool:
"""
Determine if two code page are at least 80% similar. IANA_SUPPORTED_SIMILAR dict was generated using
the function cp_similarity.
"""
return (
iana_name_a in IANA_SUPPORTED_SIMILAR
and iana_name_b in IANA_SUPPORTED_SIMILAR[iana_name_a]
)
def set_logging_handler(
name: str = "charset_normalizer",
level: int = logging.INFO,
format_string: str = "%(asctime)s | %(levelname)s | %(message)s",
) -> None:
logger = logging.getLogger(name)
logger.setLevel(level)
handler = logging.StreamHandler()
handler.setFormatter(logging.Formatter(format_string))
logger.addHandler(handler)
def cut_sequence_chunks(
sequences: bytes | bytearray,
encoding_iana: str,
offsets: range,
chunk_size: int,
bom_or_sig_available: bool,
strip_sig_or_bom: bool,
sig_payload: bytes,
is_multi_byte_decoder: bool,
decoded_payload: str | None = None,
deferred_decoding: bool = False,
) -> Generator[str, None, None]:
if decoded_payload and not is_multi_byte_decoder:
for i in offsets:
chunk = decoded_payload[i : i + chunk_size]
if not chunk:
break
yield chunk
elif deferred_decoding:
# Deferred single-byte probing: the whole payload is not decoded
# yet. Single-byte codecs are stateless (1 byte == 1 char), hence
# decode(base)[i:j] == decode(base[i:j]): slicing the raw bytes
# yields exactly the chunks the branch above would have produced,
# short trailing chunks included, and raises UnicodeDecodeError on
# invalid bytes just like the whole-payload decode would.
base_bytes = (
sequences if not strip_sig_or_bom else sequences[len(sig_payload) :]
)
for i in offsets:
cut_sequence = base_bytes[i : i + chunk_size]
if not cut_sequence:
break
yield str(cut_sequence, encoding_iana)
else:
for i in offsets:
chunk_end = i + chunk_size
if chunk_end > len(sequences) + 8:
continue
cut_sequence = sequences[i : i + chunk_size]
if bom_or_sig_available and not strip_sig_or_bom:
cut_sequence = sig_payload + cut_sequence
chunk = cut_sequence.decode(
encoding_iana,
errors="ignore" if is_multi_byte_decoder else "strict",
)
# multi-byte bad cutting detector and adjustment
# not the cleanest way to perform that fix but clever enough for now.
if is_multi_byte_decoder and i > 0:
chunk_partial_size_chk: int = min(chunk_size, 16)
if (
decoded_payload
and chunk[:chunk_partial_size_chk] not in decoded_payload
):
for j in range(i, i - 4, -1):
cut_sequence = sequences[j:chunk_end]
if bom_or_sig_available and not strip_sig_or_bom:
cut_sequence = sig_payload + cut_sequence
chunk = cut_sequence.decode(encoding_iana, errors="ignore")
if chunk[:chunk_partial_size_chk] in decoded_payload:
break
yield chunk