from os.path import splitext, basename from typing import List, BinaryIO, Optional, Set, Union try: from os import PathLike except ImportError: PathLike = Union[str, 'os.PathLike[str]'] # type: ignore from charset_normalizer.constant import TOO_SMALL_SEQUENCE, TOO_BIG_SEQUENCE, IANA_SUPPORTED from charset_normalizer.md import mess_ratio from charset_normalizer.models import CharsetMatches, CharsetMatch from warnings import warn import logging from charset_normalizer.utils import any_specified_encoding, is_multi_byte_encoding, identify_sig_or_bom, \ should_strip_sig_or_bom, is_cp_similar, iana_name from charset_normalizer.cd import coherence_ratio, encoding_languages, mb_encoding_languages, merge_coherence_ratios logger = logging.getLogger("charset_normalizer") logger.setLevel(logging.DEBUG) handler = logging.StreamHandler() handler.setFormatter(logging.Formatter('%(asctime)s | %(levelname)s | %(message)s')) logger.addHandler(handler) 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. By default, the process will extract 5 blocs of 512o each to assess the mess and coherence of a given sequence. And will give up a particular code page after 20% of measured mess. Those criteria are customizable at will. The preemptive behavior DOES NOT replace the traditional detection workflow, it prioritize a particular code page but never take it for granted. Can improve the performance. You may want to focus your attention to some code page or/and not others, use cp_isolation and cp_exclusion for that purpose. This function will strip the SIG in the payload/sequence every time except on UTF-16, UTF-32. """ 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] fallback_ascii = None # type: Optional[CharsetMatch] fallback_u8 = None # type: Optional[CharsetMatch] fallback_specified = None # type: Optional[CharsetMatch] 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)] if strip_sig_or_bom is False else sequences[len(sig_payload):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.', 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)) # Preparing those fallbacks in case we got nothing. if encoding_iana in ["ascii", "utf_8", specified_encoding]: fallback_entry = CharsetMatch( sequences, encoding_iana, threshold, False, [], decoded_payload ) if encoding_iana == specified_encoding: fallback_specified = fallback_entry elif encoding_iana == "ascii": fallback_ascii = fallback_entry else: fallback_u8 = fallback_entry 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[encoding_iana]._languages ) if len(results) == 0: if fallback_u8 or fallback_ascii or fallback_specified: logger.warning("Nothing got out of the detection process. Using ASCII/UTF-8/Specified fallback.") if fallback_specified: logger.warning("%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_u8.fingerprint != fallback_ascii.fingerprint): logger.warning("utf_8 will be used as a fallback match") results.append(fallback_u8) elif fallback_ascii: logger.warning("ascii will be used as a fallback match") results.append(fallback_ascii) return results def from_fp( fp: BinaryIO, steps: int = 5, chunk_size: int = 512, threshold: float = 0.20, cp_isolation: List[str] = None, cp_exclusion: List[str] = None, preemptive_behaviour: bool = True, explain: bool = False ) -> 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 ) def from_path( path: PathLike, steps: int = 5, chunk_size: int = 512, threshold: float = 0.20, cp_isolation: List[str] = None, cp_exclusion: List[str] = None, preemptive_behaviour: bool = True, explain: bool = False ) -> 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) def normalize(path: PathLike, steps: int = 5, chunk_size: int = 512, threshold: float = 0.20, cp_isolation: List[str] = None, cp_exclusion: List[str] = None, preemptive_behaviour: bool = True) -> CharsetMatch: """ Take a (text-based) file path and try to create another file next to it, this time using UTF-8. """ results = from_path( path, steps, chunk_size, threshold, cp_isolation, cp_exclusion, preemptive_behaviour ) filename = basename(path) target_extensions = list(splitext(filename)) if len(results) == 0: raise IOError('Unable to normalize "{}", no encoding charset seems to fit.'.format(filename)) result = results.best() target_extensions[0] += '-' + result.encoding # type: ignore with open('{}'.format(path.replace(filename, ''.join(target_extensions))), 'wb') as fp: fp.write( result.output() # type: ignore ) return result # type: ignore