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341 lines
11 KiB
341 lines
11 KiB
from encodings.aliases import aliases
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from hashlib import sha256
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from json import dumps
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from typing import Any, Dict, Iterator, List, Optional, Tuple, Union
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from .constant import TOO_BIG_SEQUENCE
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from .utils import iana_name, is_multi_byte_encoding, unicode_range
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class CharsetMatch:
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def __init__(
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self,
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payload: bytes,
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guessed_encoding: str,
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mean_mess_ratio: float,
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has_sig_or_bom: bool,
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languages: "CoherenceMatches",
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decoded_payload: Optional[str] = None,
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):
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self._payload: bytes = payload
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self._encoding: str = guessed_encoding
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self._mean_mess_ratio: float = mean_mess_ratio
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self._languages: CoherenceMatches = languages
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self._has_sig_or_bom: bool = has_sig_or_bom
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self._unicode_ranges: Optional[List[str]] = None
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self._leaves: List[CharsetMatch] = []
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self._mean_coherence_ratio: float = 0.0
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self._output_payload: Optional[bytes] = None
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self._output_encoding: Optional[str] = None
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self._string: Optional[str] = decoded_payload
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def __eq__(self, other: object) -> bool:
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if not isinstance(other, CharsetMatch):
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raise TypeError(
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"__eq__ cannot be invoked on {} and {}.".format(
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str(other.__class__), str(self.__class__)
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)
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)
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return self.encoding == other.encoding and self.fingerprint == other.fingerprint
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def __lt__(self, other: object) -> bool:
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"""
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Implemented to make sorted available upon CharsetMatches items.
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"""
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if not isinstance(other, CharsetMatch):
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raise ValueError
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chaos_difference: float = abs(self.chaos - other.chaos)
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coherence_difference: float = abs(self.coherence - other.coherence)
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# Below 1% difference --> Use Coherence
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if chaos_difference < 0.01 and coherence_difference > 0.02:
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return self.coherence > other.coherence
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elif chaos_difference < 0.01 and coherence_difference <= 0.02:
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# When having a difficult decision, use the result that decoded as many multi-byte as possible.
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# preserve RAM usage!
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if len(self._payload) >= TOO_BIG_SEQUENCE:
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return self.chaos < other.chaos
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return self.multi_byte_usage > other.multi_byte_usage
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return self.chaos < other.chaos
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@property
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def multi_byte_usage(self) -> float:
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return 1.0 - (len(str(self)) / len(self.raw))
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def __str__(self) -> str:
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# Lazy Str Loading
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if self._string is None:
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self._string = str(self._payload, self._encoding, "strict")
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return self._string
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def __repr__(self) -> str:
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return "<CharsetMatch '{}' bytes({})>".format(self.encoding, self.fingerprint)
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def add_submatch(self, other: "CharsetMatch") -> None:
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if not isinstance(other, CharsetMatch) or other == self:
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raise ValueError(
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"Unable to add instance <{}> as a submatch of a CharsetMatch".format(
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other.__class__
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)
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)
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other._string = None # Unload RAM usage; dirty trick.
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self._leaves.append(other)
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@property
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def encoding(self) -> str:
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return self._encoding
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@property
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def encoding_aliases(self) -> List[str]:
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"""
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Encoding name are known by many name, using this could help when searching for IBM855 when it's listed as CP855.
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"""
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also_known_as: List[str] = []
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for u, p in aliases.items():
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if self.encoding == u:
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also_known_as.append(p)
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elif self.encoding == p:
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also_known_as.append(u)
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return also_known_as
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@property
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def bom(self) -> bool:
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return self._has_sig_or_bom
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@property
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def byte_order_mark(self) -> bool:
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return self._has_sig_or_bom
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@property
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def languages(self) -> List[str]:
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"""
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Return the complete list of possible languages found in decoded sequence.
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Usually not really useful. Returned list may be empty even if 'language' property return something != 'Unknown'.
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"""
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return [e[0] for e in self._languages]
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@property
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def language(self) -> str:
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"""
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Most probable language found in decoded sequence. If none were detected or inferred, the property will return
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"Unknown".
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"""
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if not self._languages:
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# Trying to infer the language based on the given encoding
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# Its either English or we should not pronounce ourselves in certain cases.
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if "ascii" in self.could_be_from_charset:
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return "English"
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# doing it there to avoid circular import
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from charset_normalizer.cd import encoding_languages, mb_encoding_languages
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languages = (
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mb_encoding_languages(self.encoding)
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if is_multi_byte_encoding(self.encoding)
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else encoding_languages(self.encoding)
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)
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if len(languages) == 0 or "Latin Based" in languages:
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return "Unknown"
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return languages[0]
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return self._languages[0][0]
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@property
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def chaos(self) -> float:
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return self._mean_mess_ratio
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@property
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def coherence(self) -> float:
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if not self._languages:
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return 0.0
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return self._languages[0][1]
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@property
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def percent_chaos(self) -> float:
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return round(self.chaos * 100, ndigits=3)
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@property
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def percent_coherence(self) -> float:
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return round(self.coherence * 100, ndigits=3)
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@property
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def raw(self) -> bytes:
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"""
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Original untouched bytes.
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"""
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return self._payload
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@property
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def submatch(self) -> List["CharsetMatch"]:
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return self._leaves
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@property
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def has_submatch(self) -> bool:
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return len(self._leaves) > 0
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@property
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def alphabets(self) -> List[str]:
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if self._unicode_ranges is not None:
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return self._unicode_ranges
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# list detected ranges
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detected_ranges: List[Optional[str]] = [
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unicode_range(char) for char in str(self)
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]
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# filter and sort
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self._unicode_ranges = sorted(list({r for r in detected_ranges if r}))
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return self._unicode_ranges
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@property
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def could_be_from_charset(self) -> List[str]:
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"""
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The complete list of encoding that output the exact SAME str result and therefore could be the originating
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encoding.
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This list does include the encoding available in property 'encoding'.
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"""
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return [self._encoding] + [m.encoding for m in self._leaves]
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def output(self, encoding: str = "utf_8") -> bytes:
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"""
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Method to get re-encoded bytes payload using given target encoding. Default to UTF-8.
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Any errors will be simply ignored by the encoder NOT replaced.
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"""
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if self._output_encoding is None or self._output_encoding != encoding:
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self._output_encoding = encoding
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self._output_payload = str(self).encode(encoding, "replace")
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return self._output_payload # type: ignore
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@property
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def fingerprint(self) -> str:
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"""
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Retrieve the unique SHA256 computed using the transformed (re-encoded) payload. Not the original one.
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"""
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return sha256(self.output()).hexdigest()
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class CharsetMatches:
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"""
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Container with every CharsetMatch items ordered by default from most probable to the less one.
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Act like a list(iterable) but does not implements all related methods.
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"""
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def __init__(self, results: Optional[List[CharsetMatch]] = None):
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self._results: List[CharsetMatch] = sorted(results) if results else []
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def __iter__(self) -> Iterator[CharsetMatch]:
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yield from self._results
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def __getitem__(self, item: Union[int, str]) -> CharsetMatch:
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"""
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Retrieve a single item either by its position or encoding name (alias may be used here).
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Raise KeyError upon invalid index or encoding not present in results.
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"""
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if isinstance(item, int):
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return self._results[item]
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if isinstance(item, str):
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item = iana_name(item, False)
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for result in self._results:
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if item in result.could_be_from_charset:
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return result
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raise KeyError
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def __len__(self) -> int:
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return len(self._results)
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def __bool__(self) -> bool:
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return len(self._results) > 0
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def append(self, item: CharsetMatch) -> None:
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"""
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Insert a single match. Will be inserted accordingly to preserve sort.
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Can be inserted as a submatch.
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"""
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if not isinstance(item, CharsetMatch):
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raise ValueError(
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"Cannot append instance '{}' to CharsetMatches".format(
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str(item.__class__)
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)
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)
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# We should disable the submatch factoring when the input file is too heavy (conserve RAM usage)
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if len(item.raw) <= TOO_BIG_SEQUENCE:
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for match in self._results:
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if match.fingerprint == item.fingerprint and match.chaos == item.chaos:
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match.add_submatch(item)
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return
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self._results.append(item)
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self._results = sorted(self._results)
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def best(self) -> Optional["CharsetMatch"]:
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"""
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Simply return the first match. Strict equivalent to matches[0].
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"""
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if not self._results:
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return None
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return self._results[0]
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def first(self) -> Optional["CharsetMatch"]:
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"""
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Redundant method, call the method best(). Kept for BC reasons.
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"""
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return self.best()
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CoherenceMatch = Tuple[str, float]
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CoherenceMatches = List[CoherenceMatch]
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class CliDetectionResult:
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def __init__(
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self,
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path: str,
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encoding: Optional[str],
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encoding_aliases: List[str],
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alternative_encodings: List[str],
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language: str,
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alphabets: List[str],
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has_sig_or_bom: bool,
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chaos: float,
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coherence: float,
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unicode_path: Optional[str],
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is_preferred: bool,
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):
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self.path: str = path
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self.unicode_path: Optional[str] = unicode_path
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self.encoding: Optional[str] = encoding
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self.encoding_aliases: List[str] = encoding_aliases
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self.alternative_encodings: List[str] = alternative_encodings
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self.language: str = language
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self.alphabets: List[str] = alphabets
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self.has_sig_or_bom: bool = has_sig_or_bom
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self.chaos: float = chaos
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self.coherence: float = coherence
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self.is_preferred: bool = is_preferred
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@property
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def __dict__(self) -> Dict[str, Any]: # type: ignore
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return {
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"path": self.path,
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"encoding": self.encoding,
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"encoding_aliases": self.encoding_aliases,
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"alternative_encodings": self.alternative_encodings,
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"language": self.language,
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"alphabets": self.alphabets,
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"has_sig_or_bom": self.has_sig_or_bom,
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"chaos": self.chaos,
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"coherence": self.coherence,
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"unicode_path": self.unicode_path,
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"is_preferred": self.is_preferred,
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}
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def to_json(self) -> str:
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return dumps(self.__dict__, ensure_ascii=True, indent=4)
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