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627 lines
21 KiB
627 lines
21 KiB
6 months ago
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import logging
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from os import PathLike
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from typing import BinaryIO, List, Optional, Set, Union
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from .cd import (
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coherence_ratio,
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encoding_languages,
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mb_encoding_languages,
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merge_coherence_ratios,
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)
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from .constant import IANA_SUPPORTED, TOO_BIG_SEQUENCE, TOO_SMALL_SEQUENCE, TRACE
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from .md import mess_ratio
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from .models import CharsetMatch, CharsetMatches
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from .utils import (
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any_specified_encoding,
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cut_sequence_chunks,
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iana_name,
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identify_sig_or_bom,
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is_cp_similar,
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is_multi_byte_encoding,
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should_strip_sig_or_bom,
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)
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# Will most likely be controversial
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# logging.addLevelName(TRACE, "TRACE")
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logger = logging.getLogger("charset_normalizer")
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explain_handler = logging.StreamHandler()
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explain_handler.setFormatter(
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logging.Formatter("%(asctime)s | %(levelname)s | %(message)s")
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)
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def from_bytes(
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sequences: Union[bytes, bytearray],
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steps: int = 5,
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chunk_size: int = 512,
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threshold: float = 0.2,
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cp_isolation: Optional[List[str]] = None,
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cp_exclusion: Optional[List[str]] = None,
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preemptive_behaviour: bool = True,
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explain: bool = False,
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language_threshold: float = 0.1,
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enable_fallback: bool = True,
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) -> CharsetMatches:
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"""
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Given a raw bytes sequence, return the best possibles charset usable to render str objects.
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If there is no results, it is a strong indicator that the source is binary/not text.
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By default, the process will extract 5 blocks of 512o each to assess the mess and coherence of a given sequence.
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And will give up a particular code page after 20% of measured mess. Those criteria are customizable at will.
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The preemptive behavior DOES NOT replace the traditional detection workflow, it prioritize a particular code page
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but never take it for granted. Can improve the performance.
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You may want to focus your attention to some code page or/and not others, use cp_isolation and cp_exclusion for that
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purpose.
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This function will strip the SIG in the payload/sequence every time except on UTF-16, UTF-32.
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By default the library does not setup any handler other than the NullHandler, if you choose to set the 'explain'
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toggle to True it will alter the logger configuration to add a StreamHandler that is suitable for debugging.
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Custom logging format and handler can be set manually.
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"""
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if not isinstance(sequences, (bytearray, bytes)):
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raise TypeError(
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"Expected object of type bytes or bytearray, got: {0}".format(
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type(sequences)
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)
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)
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if explain:
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previous_logger_level: int = logger.level
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logger.addHandler(explain_handler)
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logger.setLevel(TRACE)
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length: int = len(sequences)
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if length == 0:
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logger.debug("Encoding detection on empty bytes, assuming utf_8 intention.")
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if explain:
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logger.removeHandler(explain_handler)
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logger.setLevel(previous_logger_level or logging.WARNING)
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return CharsetMatches([CharsetMatch(sequences, "utf_8", 0.0, False, [], "")])
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if cp_isolation is not None:
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logger.log(
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TRACE,
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"cp_isolation is set. use this flag for debugging purpose. "
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"limited list of encoding allowed : %s.",
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", ".join(cp_isolation),
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)
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cp_isolation = [iana_name(cp, False) for cp in cp_isolation]
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else:
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cp_isolation = []
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if cp_exclusion is not None:
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logger.log(
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TRACE,
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"cp_exclusion is set. use this flag for debugging purpose. "
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"limited list of encoding excluded : %s.",
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", ".join(cp_exclusion),
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)
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cp_exclusion = [iana_name(cp, False) for cp in cp_exclusion]
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else:
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cp_exclusion = []
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if length <= (chunk_size * steps):
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logger.log(
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TRACE,
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"override steps (%i) and chunk_size (%i) as content does not fit (%i byte(s) given) parameters.",
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steps,
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chunk_size,
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length,
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)
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steps = 1
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chunk_size = length
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if steps > 1 and length / steps < chunk_size:
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chunk_size = int(length / steps)
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is_too_small_sequence: bool = len(sequences) < TOO_SMALL_SEQUENCE
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is_too_large_sequence: bool = len(sequences) >= TOO_BIG_SEQUENCE
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if is_too_small_sequence:
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logger.log(
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TRACE,
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"Trying to detect encoding from a tiny portion of ({}) byte(s).".format(
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length
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),
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)
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elif is_too_large_sequence:
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logger.log(
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TRACE,
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"Using lazy str decoding because the payload is quite large, ({}) byte(s).".format(
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length
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),
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)
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prioritized_encodings: List[str] = []
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specified_encoding: Optional[str] = (
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any_specified_encoding(sequences) if preemptive_behaviour else None
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)
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if specified_encoding is not None:
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prioritized_encodings.append(specified_encoding)
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logger.log(
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TRACE,
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"Detected declarative mark in sequence. Priority +1 given for %s.",
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specified_encoding,
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)
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tested: Set[str] = set()
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tested_but_hard_failure: List[str] = []
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tested_but_soft_failure: List[str] = []
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fallback_ascii: Optional[CharsetMatch] = None
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fallback_u8: Optional[CharsetMatch] = None
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fallback_specified: Optional[CharsetMatch] = None
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results: CharsetMatches = CharsetMatches()
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sig_encoding, sig_payload = identify_sig_or_bom(sequences)
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if sig_encoding is not None:
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prioritized_encodings.append(sig_encoding)
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logger.log(
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TRACE,
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"Detected a SIG or BOM mark on first %i byte(s). Priority +1 given for %s.",
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len(sig_payload),
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sig_encoding,
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)
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prioritized_encodings.append("ascii")
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if "utf_8" not in prioritized_encodings:
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prioritized_encodings.append("utf_8")
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for encoding_iana in prioritized_encodings + IANA_SUPPORTED:
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if cp_isolation and encoding_iana not in cp_isolation:
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continue
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if cp_exclusion and encoding_iana in cp_exclusion:
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continue
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if encoding_iana in tested:
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continue
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tested.add(encoding_iana)
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decoded_payload: Optional[str] = None
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bom_or_sig_available: bool = sig_encoding == encoding_iana
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strip_sig_or_bom: bool = bom_or_sig_available and should_strip_sig_or_bom(
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encoding_iana
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)
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if encoding_iana in {"utf_16", "utf_32"} and not bom_or_sig_available:
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logger.log(
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TRACE,
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"Encoding %s won't be tested as-is because it require a BOM. Will try some sub-encoder LE/BE.",
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encoding_iana,
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)
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continue
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if encoding_iana in {"utf_7"} and not bom_or_sig_available:
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logger.log(
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TRACE,
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"Encoding %s won't be tested as-is because detection is unreliable without BOM/SIG.",
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encoding_iana,
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)
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continue
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try:
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is_multi_byte_decoder: bool = is_multi_byte_encoding(encoding_iana)
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except (ModuleNotFoundError, ImportError):
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logger.log(
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TRACE,
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"Encoding %s does not provide an IncrementalDecoder",
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encoding_iana,
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)
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continue
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try:
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if is_too_large_sequence and is_multi_byte_decoder is False:
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str(
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sequences[: int(50e4)]
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if strip_sig_or_bom is False
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else sequences[len(sig_payload) : int(50e4)],
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encoding=encoding_iana,
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)
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else:
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decoded_payload = str(
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sequences
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if strip_sig_or_bom is False
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else sequences[len(sig_payload) :],
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encoding=encoding_iana,
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)
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except (UnicodeDecodeError, LookupError) as e:
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if not isinstance(e, LookupError):
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logger.log(
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TRACE,
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"Code page %s does not fit given bytes sequence at ALL. %s",
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encoding_iana,
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str(e),
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)
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tested_but_hard_failure.append(encoding_iana)
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continue
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similar_soft_failure_test: bool = False
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for encoding_soft_failed in tested_but_soft_failure:
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if is_cp_similar(encoding_iana, encoding_soft_failed):
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similar_soft_failure_test = True
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break
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if similar_soft_failure_test:
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logger.log(
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TRACE,
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"%s is deemed too similar to code page %s and was consider unsuited already. Continuing!",
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encoding_iana,
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encoding_soft_failed,
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)
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continue
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r_ = range(
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0 if not bom_or_sig_available else len(sig_payload),
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length,
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int(length / steps),
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)
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multi_byte_bonus: bool = (
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is_multi_byte_decoder
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and decoded_payload is not None
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and len(decoded_payload) < length
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)
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if multi_byte_bonus:
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logger.log(
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TRACE,
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"Code page %s is a multi byte encoding table and it appear that at least one character "
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"was encoded using n-bytes.",
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encoding_iana,
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)
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max_chunk_gave_up: int = int(len(r_) / 4)
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max_chunk_gave_up = max(max_chunk_gave_up, 2)
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early_stop_count: int = 0
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lazy_str_hard_failure = False
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md_chunks: List[str] = []
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md_ratios = []
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try:
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for chunk in cut_sequence_chunks(
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sequences,
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encoding_iana,
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r_,
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chunk_size,
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bom_or_sig_available,
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strip_sig_or_bom,
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sig_payload,
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is_multi_byte_decoder,
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decoded_payload,
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):
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md_chunks.append(chunk)
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md_ratios.append(
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mess_ratio(
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chunk,
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threshold,
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explain is True and 1 <= len(cp_isolation) <= 2,
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)
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)
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if md_ratios[-1] >= threshold:
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early_stop_count += 1
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if (early_stop_count >= max_chunk_gave_up) or (
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bom_or_sig_available and strip_sig_or_bom is False
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):
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break
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except (
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UnicodeDecodeError
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) as e: # Lazy str loading may have missed something there
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logger.log(
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TRACE,
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"LazyStr Loading: After MD chunk decode, code page %s does not fit given bytes sequence at ALL. %s",
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encoding_iana,
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str(e),
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)
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early_stop_count = max_chunk_gave_up
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lazy_str_hard_failure = True
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# We might want to check the sequence again with the whole content
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# Only if initial MD tests passes
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if (
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not lazy_str_hard_failure
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and is_too_large_sequence
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and not is_multi_byte_decoder
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):
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try:
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sequences[int(50e3) :].decode(encoding_iana, errors="strict")
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except UnicodeDecodeError as e:
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logger.log(
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TRACE,
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"LazyStr Loading: After final lookup, code page %s does not fit given bytes sequence at ALL. %s",
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encoding_iana,
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str(e),
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)
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tested_but_hard_failure.append(encoding_iana)
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continue
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mean_mess_ratio: float = sum(md_ratios) / len(md_ratios) if md_ratios else 0.0
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if mean_mess_ratio >= threshold or early_stop_count >= max_chunk_gave_up:
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tested_but_soft_failure.append(encoding_iana)
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logger.log(
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TRACE,
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"%s was excluded because of initial chaos probing. Gave up %i time(s). "
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"Computed mean chaos is %f %%.",
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encoding_iana,
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early_stop_count,
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round(mean_mess_ratio * 100, ndigits=3),
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)
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# Preparing those fallbacks in case we got nothing.
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if (
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enable_fallback
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and encoding_iana in ["ascii", "utf_8", specified_encoding]
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and not lazy_str_hard_failure
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):
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fallback_entry = CharsetMatch(
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|
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sequences, encoding_iana, threshold, False, [], decoded_payload
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)
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if encoding_iana == specified_encoding:
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fallback_specified = fallback_entry
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elif encoding_iana == "ascii":
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fallback_ascii = fallback_entry
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else:
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fallback_u8 = fallback_entry
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continue
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logger.log(
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TRACE,
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"%s passed initial chaos probing. Mean measured chaos is %f %%",
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encoding_iana,
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round(mean_mess_ratio * 100, ndigits=3),
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|
)
|
||
|
|
|
||
|
|
if not is_multi_byte_decoder:
|
||
|
|
target_languages: List[str] = encoding_languages(encoding_iana)
|
||
|
|
else:
|
||
|
|
target_languages = mb_encoding_languages(encoding_iana)
|
||
|
|
|
||
|
|
if target_languages:
|
||
|
|
logger.log(
|
||
|
|
TRACE,
|
||
|
|
"{} should target any language(s) of {}".format(
|
||
|
|
encoding_iana, str(target_languages)
|
||
|
|
),
|
||
|
|
)
|
||
|
|
|
||
|
|
cd_ratios = []
|
||
|
|
|
||
|
|
# We shall skip the CD when its about ASCII
|
||
|
|
# Most of the time its not relevant to run "language-detection" on it.
|
||
|
|
if encoding_iana != "ascii":
|
||
|
|
for chunk in md_chunks:
|
||
|
|
chunk_languages = coherence_ratio(
|
||
|
|
chunk,
|
||
|
|
language_threshold,
|
||
|
|
",".join(target_languages) if target_languages else None,
|
||
|
|
)
|
||
|
|
|
||
|
|
cd_ratios.append(chunk_languages)
|
||
|
|
|
||
|
|
cd_ratios_merged = merge_coherence_ratios(cd_ratios)
|
||
|
|
|
||
|
|
if cd_ratios_merged:
|
||
|
|
logger.log(
|
||
|
|
TRACE,
|
||
|
|
"We detected language {} using {}".format(
|
||
|
|
cd_ratios_merged, encoding_iana
|
||
|
|
),
|
||
|
|
)
|
||
|
|
|
||
|
|
results.append(
|
||
|
|
CharsetMatch(
|
||
|
|
sequences,
|
||
|
|
encoding_iana,
|
||
|
|
mean_mess_ratio,
|
||
|
|
bom_or_sig_available,
|
||
|
|
cd_ratios_merged,
|
||
|
|
decoded_payload,
|
||
|
|
)
|
||
|
|
)
|
||
|
|
|
||
|
|
if (
|
||
|
|
encoding_iana in [specified_encoding, "ascii", "utf_8"]
|
||
|
|
and mean_mess_ratio < 0.1
|
||
|
|
):
|
||
|
|
logger.debug(
|
||
|
|
"Encoding detection: %s is most likely the one.", encoding_iana
|
||
|
|
)
|
||
|
|
if explain:
|
||
|
|
logger.removeHandler(explain_handler)
|
||
|
|
logger.setLevel(previous_logger_level)
|
||
|
|
return CharsetMatches([results[encoding_iana]])
|
||
|
|
|
||
|
|
if encoding_iana == sig_encoding:
|
||
|
|
logger.debug(
|
||
|
|
"Encoding detection: %s is most likely the one as we detected a BOM or SIG within "
|
||
|
|
"the beginning of the sequence.",
|
||
|
|
encoding_iana,
|
||
|
|
)
|
||
|
|
if explain:
|
||
|
|
logger.removeHandler(explain_handler)
|
||
|
|
logger.setLevel(previous_logger_level)
|
||
|
|
return CharsetMatches([results[encoding_iana]])
|
||
|
|
|
||
|
|
if len(results) == 0:
|
||
|
|
if fallback_u8 or fallback_ascii or fallback_specified:
|
||
|
|
logger.log(
|
||
|
|
TRACE,
|
||
|
|
"Nothing got out of the detection process. Using ASCII/UTF-8/Specified fallback.",
|
||
|
|
)
|
||
|
|
|
||
|
|
if fallback_specified:
|
||
|
|
logger.debug(
|
||
|
|
"Encoding detection: %s will be used as a fallback match",
|
||
|
|
fallback_specified.encoding,
|
||
|
|
)
|
||
|
|
results.append(fallback_specified)
|
||
|
|
elif (
|
||
|
|
(fallback_u8 and fallback_ascii is None)
|
||
|
|
or (
|
||
|
|
fallback_u8
|
||
|
|
and fallback_ascii
|
||
|
|
and fallback_u8.fingerprint != fallback_ascii.fingerprint
|
||
|
|
)
|
||
|
|
or (fallback_u8 is not None)
|
||
|
|
):
|
||
|
|
logger.debug("Encoding detection: utf_8 will be used as a fallback match")
|
||
|
|
results.append(fallback_u8)
|
||
|
|
elif fallback_ascii:
|
||
|
|
logger.debug("Encoding detection: ascii will be used as a fallback match")
|
||
|
|
results.append(fallback_ascii)
|
||
|
|
|
||
|
|
if results:
|
||
|
|
logger.debug(
|
||
|
|
"Encoding detection: Found %s as plausible (best-candidate) for content. With %i alternatives.",
|
||
|
|
results.best().encoding, # type: ignore
|
||
|
|
len(results) - 1,
|
||
|
|
)
|
||
|
|
else:
|
||
|
|
logger.debug("Encoding detection: Unable to determine any suitable charset.")
|
||
|
|
|
||
|
|
if explain:
|
||
|
|
logger.removeHandler(explain_handler)
|
||
|
|
logger.setLevel(previous_logger_level)
|
||
|
|
|
||
|
|
return results
|
||
|
|
|
||
|
|
|
||
|
|
def from_fp(
|
||
|
|
fp: BinaryIO,
|
||
|
|
steps: int = 5,
|
||
|
|
chunk_size: int = 512,
|
||
|
|
threshold: float = 0.20,
|
||
|
|
cp_isolation: Optional[List[str]] = None,
|
||
|
|
cp_exclusion: Optional[List[str]] = None,
|
||
|
|
preemptive_behaviour: bool = True,
|
||
|
|
explain: bool = False,
|
||
|
|
language_threshold: float = 0.1,
|
||
|
|
enable_fallback: bool = True,
|
||
|
|
) -> CharsetMatches:
|
||
|
|
"""
|
||
|
|
Same thing than the function from_bytes but using a file pointer that is already ready.
|
||
|
|
Will not close the file pointer.
|
||
|
|
"""
|
||
|
|
return from_bytes(
|
||
|
|
fp.read(),
|
||
|
|
steps,
|
||
|
|
chunk_size,
|
||
|
|
threshold,
|
||
|
|
cp_isolation,
|
||
|
|
cp_exclusion,
|
||
|
|
preemptive_behaviour,
|
||
|
|
explain,
|
||
|
|
language_threshold,
|
||
|
|
enable_fallback,
|
||
|
|
)
|
||
|
|
|
||
|
|
|
||
|
|
def from_path(
|
||
|
|
path: Union[str, bytes, PathLike], # type: ignore[type-arg]
|
||
|
|
steps: int = 5,
|
||
|
|
chunk_size: int = 512,
|
||
|
|
threshold: float = 0.20,
|
||
|
|
cp_isolation: Optional[List[str]] = None,
|
||
|
|
cp_exclusion: Optional[List[str]] = None,
|
||
|
|
preemptive_behaviour: bool = True,
|
||
|
|
explain: bool = False,
|
||
|
|
language_threshold: float = 0.1,
|
||
|
|
enable_fallback: bool = True,
|
||
|
|
) -> CharsetMatches:
|
||
|
|
"""
|
||
|
|
Same thing than the function from_bytes but with one extra step. Opening and reading given file path in binary mode.
|
||
|
|
Can raise IOError.
|
||
|
|
"""
|
||
|
|
with open(path, "rb") as fp:
|
||
|
|
return from_fp(
|
||
|
|
fp,
|
||
|
|
steps,
|
||
|
|
chunk_size,
|
||
|
|
threshold,
|
||
|
|
cp_isolation,
|
||
|
|
cp_exclusion,
|
||
|
|
preemptive_behaviour,
|
||
|
|
explain,
|
||
|
|
language_threshold,
|
||
|
|
enable_fallback,
|
||
|
|
)
|
||
|
|
|
||
|
|
|
||
|
|
def is_binary(
|
||
|
|
fp_or_path_or_payload: Union[PathLike, str, BinaryIO, bytes], # type: ignore[type-arg]
|
||
|
|
steps: int = 5,
|
||
|
|
chunk_size: int = 512,
|
||
|
|
threshold: float = 0.20,
|
||
|
|
cp_isolation: Optional[List[str]] = None,
|
||
|
|
cp_exclusion: Optional[List[str]] = None,
|
||
|
|
preemptive_behaviour: bool = True,
|
||
|
|
explain: bool = False,
|
||
|
|
language_threshold: float = 0.1,
|
||
|
|
enable_fallback: bool = False,
|
||
|
|
) -> bool:
|
||
|
|
"""
|
||
|
|
Detect if the given input (file, bytes, or path) points to a binary file. aka. not a string.
|
||
|
|
Based on the same main heuristic algorithms and default kwargs at the sole exception that fallbacks match
|
||
|
|
are disabled to be stricter around ASCII-compatible but unlikely to be a string.
|
||
|
|
"""
|
||
|
|
if isinstance(fp_or_path_or_payload, (str, PathLike)):
|
||
|
|
guesses = from_path(
|
||
|
|
fp_or_path_or_payload,
|
||
|
|
steps=steps,
|
||
|
|
chunk_size=chunk_size,
|
||
|
|
threshold=threshold,
|
||
|
|
cp_isolation=cp_isolation,
|
||
|
|
cp_exclusion=cp_exclusion,
|
||
|
|
preemptive_behaviour=preemptive_behaviour,
|
||
|
|
explain=explain,
|
||
|
|
language_threshold=language_threshold,
|
||
|
|
enable_fallback=enable_fallback,
|
||
|
|
)
|
||
|
|
elif isinstance(
|
||
|
|
fp_or_path_or_payload,
|
||
|
|
(
|
||
|
|
bytes,
|
||
|
|
bytearray,
|
||
|
|
),
|
||
|
|
):
|
||
|
|
guesses = from_bytes(
|
||
|
|
fp_or_path_or_payload,
|
||
|
|
steps=steps,
|
||
|
|
chunk_size=chunk_size,
|
||
|
|
threshold=threshold,
|
||
|
|
cp_isolation=cp_isolation,
|
||
|
|
cp_exclusion=cp_exclusion,
|
||
|
|
preemptive_behaviour=preemptive_behaviour,
|
||
|
|
explain=explain,
|
||
|
|
language_threshold=language_threshold,
|
||
|
|
enable_fallback=enable_fallback,
|
||
|
|
)
|
||
|
|
else:
|
||
|
|
guesses = from_fp(
|
||
|
|
fp_or_path_or_payload,
|
||
|
|
steps=steps,
|
||
|
|
chunk_size=chunk_size,
|
||
|
|
threshold=threshold,
|
||
|
|
cp_isolation=cp_isolation,
|
||
|
|
cp_exclusion=cp_exclusion,
|
||
|
|
preemptive_behaviour=preemptive_behaviour,
|
||
|
|
explain=explain,
|
||
|
|
language_threshold=language_threshold,
|
||
|
|
enable_fallback=enable_fallback,
|
||
|
|
)
|
||
|
|
|
||
|
|
return not guesses
|