示例#1
0
def cli_coverage(arguments: List[str]):
    parser = argparse.ArgumentParser(
        description="Embedded detection success coverage script checker for Charset-Normalizer"
    )

    parser.add_argument('-p', '--with-preemptive', action="store_true", default=False, dest='preemptive',
                        help='Enable the preemptive scan behaviour during coverage check')
    parser.add_argument('-c', '--coverage', action="store", default=90, type=int, dest='coverage',
                        help="Define the minimum acceptable coverage to succeed")

    args = parser.parse_args(arguments)

    if not isdir("./char-dataset"):
        print("This script require https://github.com/Ousret/char-dataset to be cloned on package root directory")
        exit(1)

    success_count = 0
    total_count = 0

    for tbt_path in sorted(glob("./char-dataset/**/*.*")):

        expected_encoding = tbt_path.split(sep)[-2]
        total_count += 1

        results = from_path(
            tbt_path,
            preemptive_behaviour=args.preemptive
        )

        if expected_encoding == "None" and len(results) == 0:
            print("✅✅ '{}'".format(tbt_path))
            success_count += 1
            continue

        if len(results) == 0:
            print("⚡⚡ '{}' (nothing)".format(tbt_path))
            continue

        result = results.best()

        if expected_encoding in result.could_be_from_charset or iana_name(expected_encoding) in result.could_be_from_charset:
            print("✅✅ '{}'".format(tbt_path))
            success_count += 1
            continue

        calc_eq = calc_equivalence(result.raw, expected_encoding, result.encoding)

        if calc_eq >= 0.98:
            success_count += 1
            print("️✅ ️'{}' (got '{}' but equivalence {} %)".format(tbt_path, result.encoding, round(calc_eq * 100., 3)))
            continue

        print("⚡ '{}' (got '{}')".format(tbt_path, result.encoding))

    success_ratio = round(success_count / total_count, 2) * 100.

    print("Total EST coverage = {} % ({} / {} files)".format(success_ratio, success_count, total_count))

    return 0 if success_ratio >= args.coverage else 1
示例#2
0
 def __getitem__(self, item) -> 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 cli_bc(arguments: List[str]):
    parser = argparse.ArgumentParser(
        description="BC script checker for Charset-Normalizer with Chardet")

    parser.add_argument(
        '-c',
        '--coverage',
        action="store",
        default=85,
        type=int,
        dest='coverage',
        help="Define the minimum acceptable coverage to succeed")

    args = parser.parse_args(arguments)

    if not isdir("./char-dataset"):
        print(
            "This script require https://github.com/Ousret/char-dataset to be cloned on package root directory"
        )
        exit(1)

    success_count = 0
    total_count = 0

    for tbt_path in sorted(glob("./char-dataset/**/*.*")):
        total_count += 1

        with open(tbt_path, "rb") as fp:
            content = fp.read()

        chardet_result = chardet_detect(content)
        chardet_encoding = chardet_result['encoding']

        charset_normalizer_result = tbt_detect(content)
        charset_normalizer_encoding = charset_normalizer_result['encoding']

        if [chardet_encoding, charset_normalizer_encoding].count(None) == 1:
            print("⚡⚡ '{}' (BC-Break) New('{}') vs Legacy('{}')".format(
                tbt_path, charset_normalizer_encoding, chardet_encoding))
            continue

        if charset_normalizer_encoding == chardet_encoding:
            success_count += 1
            print("✅✅ '{}' (BC)".format(tbt_path))
            continue

        if (chardet_encoding is None and charset_normalizer_encoding is None
            ) or (iana_name(chardet_encoding)
                  == iana_name(charset_normalizer_encoding)):
            success_count += 1
            print("✅✅ '{}' (BC)".format(tbt_path))
            continue

        calc_eq = calc_equivalence(content, chardet_encoding,
                                   charset_normalizer_encoding)

        if calc_eq >= 0.98:
            success_count += 1
            print("️✅ ️'{}' (got '{}' but eq {} WITH {} %)".format(
                tbt_path, charset_normalizer_encoding, chardet_encoding,
                round(calc_eq * 100., 3)))
            continue

        print("⚡⚡ '{}' (BC-Break) New('{}') vs Legacy('{}')".format(
            tbt_path, charset_normalizer_encoding, chardet_encoding))

    success_ratio = round(success_count / total_count, 2) * 100.

    print("Total EST BC = {} % ({} / {} files)".format(success_ratio,
                                                       success_count,
                                                       total_count))

    return 0 if success_ratio >= args.coverage else 1
示例#4
0
def from_bytes(sequences: bytes,
               steps: int = 5,
               chunk_size: int = 512,
               threshold: float = 0.2,
               cp_isolation: List[str] = None,
               cp_exclusion: List[str] = None,
               preemptive_behaviour: bool = True,
               explain: bool = False) -> CharsetMatches:
    """
    Given a raw bytes sequence, return the best possibles charset usable to render str objects.
    If there is no results, it is a strong indicator that the source is binary/not text.
    """

    if not explain:
        logger.setLevel(logging.CRITICAL)
    else:
        logger.setLevel(logging.INFO)

    length = len(sequences)  # type: int

    if length == 0:
        logger.warning(
            "Given content is empty, stopping the process very early, returning empty utf_8 str match"
        )
        return CharsetMatches(
            [CharsetMatch(sequences, "utf_8", 0., False, [], "")])

    if cp_isolation is not None:
        logger.warning(
            'cp_isolation is set. use this flag for debugging purpose. '
            'limited list of encoding allowed : %s.', ', '.join(cp_isolation))
        cp_isolation = [iana_name(cp, False) for cp in cp_isolation]
    else:
        cp_isolation = []

    if cp_exclusion is not None:
        logger.warning(
            'cp_exclusion is set. use this flag for debugging purpose. '
            'limited list of encoding excluded : %s.', ', '.join(cp_exclusion))
        cp_exclusion = [iana_name(cp, False) for cp in cp_exclusion]
    else:
        cp_exclusion = []

    if length <= (chunk_size * steps):
        logger.warning(
            'override steps (%i) and chunk_size (%i) as content does not fit (%i byte(s) given) parameters.',
            steps, chunk_size, length)
        steps = 1
        chunk_size = length

    if steps > 1 and length / steps < chunk_size:
        chunk_size = int(length / steps)

    is_too_small_sequence = len(sequences) < TOO_SMALL_SEQUENCE  # type: bool
    is_too_large_sequence = len(sequences) >= TOO_BIG_SEQUENCE  # type: bool

    if is_too_small_sequence:
        warn('Trying to detect encoding from a tiny portion of ({}) byte(s).'.
             format(length))

    prioritized_encodings = []  # type: List[str]

    specified_encoding = any_specified_encoding(
        sequences
    ) if preemptive_behaviour is True else None  # type: Optional[str]

    if specified_encoding is not None:
        prioritized_encodings.append(specified_encoding)
        logger.info(
            'Detected declarative mark in sequence. Priority +1 given for %s.',
            specified_encoding)

    tested = set()  # type: Set[str]
    tested_but_hard_failure = []  # type: List[str]
    tested_but_soft_failure = []  # type: List[str]

    single_byte_hard_failure_count = 0  # type: int
    single_byte_soft_failure_count = 0  # type: int

    results = CharsetMatches()  # type: CharsetMatches

    sig_encoding, sig_payload = identify_sig_or_bom(sequences)

    if sig_encoding is not None:
        prioritized_encodings.append(sig_encoding)
        logger.info(
            'Detected a SIG or BOM mark on first %i byte(s). Priority +1 given for %s.',
            len(sig_payload), sig_encoding)

    prioritized_encodings.append("ascii")

    if "utf_8" not in prioritized_encodings:
        prioritized_encodings.append("utf_8")

    for encoding_iana in prioritized_encodings + IANA_SUPPORTED:

        if cp_isolation and encoding_iana not in cp_isolation:
            continue

        if cp_exclusion and encoding_iana in cp_exclusion:
            continue

        if encoding_iana in tested:
            continue

        tested.add(encoding_iana)

        decoded_payload = None  # type: Optional[str]
        bom_or_sig_available = sig_encoding == encoding_iana  # type: bool
        strip_sig_or_bom = bom_or_sig_available and should_strip_sig_or_bom(
            encoding_iana)  # type: bool

        if encoding_iana in {"utf_16", "utf_32"
                             } and bom_or_sig_available is False:
            logger.info(
                "Encoding %s wont be tested as-is because it require a BOM. Will try some sub-encoder LE/BE.",
                encoding_iana)
            continue

        try:
            is_multi_byte_decoder = is_multi_byte_encoding(
                encoding_iana)  # type: bool
        except (ModuleNotFoundError, ImportError):
            logger.debug("Encoding %s does not provide an IncrementalDecoder",
                         encoding_iana)
            continue

        try:
            if is_too_large_sequence and is_multi_byte_decoder is False:
                str(sequences[:int(50e4)], encoding=encoding_iana)
            else:
                decoded_payload = str(sequences if strip_sig_or_bom is False
                                      else sequences[len(sig_payload):],
                                      encoding=encoding_iana)
        except UnicodeDecodeError as e:
            logger.warning(
                'Code page %s does not fit given bytes sequence at ALL. %s',
                encoding_iana, str(e))
            tested_but_hard_failure.append(encoding_iana)
            if not is_multi_byte_decoder:
                single_byte_hard_failure_count += 1
            continue
        except LookupError:
            tested_but_hard_failure.append(encoding_iana)
            if not is_multi_byte_decoder:
                single_byte_hard_failure_count += 1
            continue

        similar_soft_failure_test = False  # type: bool

        for encoding_soft_failed in tested_but_soft_failure:
            if is_cp_similar(encoding_iana, encoding_soft_failed):
                similar_soft_failure_test = True
                break

        if similar_soft_failure_test:
            logger.warning(
                "%s is deemed too similar to code page %s and was consider unsuited already. Continuing!",
                encoding_iana, encoding_soft_failed)
            continue

        r_ = range(0 if bom_or_sig_available is False else len(sig_payload),
                   length, int(length / steps))

        multi_byte_bonus = is_multi_byte_decoder and decoded_payload is not None and len(
            decoded_payload) < length  # type: bool

        if multi_byte_bonus:
            logger.info(
                'Code page %s is a multi byte encoding table and it appear that at least one character was encoded using n-bytes. Should not be a coincidence. Priority +1 given.',
                encoding_iana)

        max_chunk_gave_up = int(len(r_) / 4)  # type: int

        if max_chunk_gave_up < 2:
            max_chunk_gave_up = 2

        early_stop_count = 0  # type: int

        md_chunks = []  # type: List[str]
        md_ratios = []

        for i in r_:
            cut_sequence = sequences[i:i + chunk_size]

            if bom_or_sig_available and strip_sig_or_bom is False:
                cut_sequence = sig_payload + cut_sequence

            chunk = cut_sequence.decode(encoding_iana,
                                        errors="ignore")  # type: str

            md_chunks.append(chunk)

            md_ratios.append(mess_ratio(chunk, threshold))

            if md_ratios[-1] >= threshold:
                early_stop_count += 1

            if (early_stop_count >= max_chunk_gave_up) or (
                    bom_or_sig_available and strip_sig_or_bom is False):
                break

        if md_ratios:
            mean_mess_ratio = sum(md_ratios) / len(md_ratios)  # type: float
        else:
            mean_mess_ratio = 0.

        if mean_mess_ratio >= threshold or early_stop_count >= max_chunk_gave_up:
            tested_but_soft_failure.append(encoding_iana)
            if not is_multi_byte_decoder:
                single_byte_soft_failure_count += 1
            logger.warning(
                '%s was excluded because of initial chaos probing. Gave up %i time(s). '
                'Computed mean chaos is %f %%.', encoding_iana,
                early_stop_count, round(mean_mess_ratio * 100, ndigits=3))
            continue

        logger.info(
            '%s passed initial chaos probing. Mean measured chaos is %f %%',
            encoding_iana, round(mean_mess_ratio * 100, ndigits=3))

        if not is_multi_byte_decoder:
            target_languages = encoding_languages(
                encoding_iana)  # type: List[str]
        else:
            target_languages = mb_encoding_languages(encoding_iana)

        if target_languages:
            logger.info("{} should target any language(s) of {}".format(
                encoding_iana, str(target_languages)))

        cd_ratios = []

        for chunk in md_chunks:
            chunk_languages = coherence_ratio(
                chunk, 0.1,
                ",".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.info("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.info("%s is most likely the one. Stopping the process.",
                        encoding_iana)
            return CharsetMatches([results[encoding_iana]])

        if encoding_iana == sig_encoding:
            logger.info(
                "%s is most likely the one as we detected a BOM or SIG within the beginning of the sequence.",
                encoding_iana)
            return CharsetMatches([results[encoding_iana]])

        if results[-1].languages:
            logger.info(
                "Using %s code page we detected the following languages: %s",
                encoding_iana, results[-1]._languages)

    return results