Source code for charset_normalizer.models

from encodings.aliases import aliases
from hashlib import sha256
from json import dumps
from typing import Any, Dict, Iterator, List, Optional, Tuple, Union

from .constant import TOO_BIG_SEQUENCE
from .utils import iana_name, is_multi_byte_encoding, unicode_range


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