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Direktori : /proc/thread-self/root/opt/cloudlinux/venv/lib/python3.11/site-packages/charset_normalizer/ |
Current File : //proc/thread-self/root/opt/cloudlinux/venv/lib/python3.11/site-packages/charset_normalizer/api.py |
import logging import warnings from os import PathLike from os.path import basename, splitext from typing import Any, BinaryIO, List, Optional, Set from .cd import ( coherence_ratio, encoding_languages, mb_encoding_languages, merge_coherence_ratios, ) from .constant import IANA_SUPPORTED, TOO_BIG_SEQUENCE, TOO_SMALL_SEQUENCE, TRACE from .md import mess_ratio from .models import CharsetMatch, CharsetMatches from .utils import ( any_specified_encoding, cut_sequence_chunks, iana_name, identify_sig_or_bom, is_cp_similar, is_multi_byte_encoding, should_strip_sig_or_bom, ) # Will most likely be controversial # logging.addLevelName(TRACE, "TRACE") logger = logging.getLogger("charset_normalizer") explain_handler = logging.StreamHandler() explain_handler.setFormatter( logging.Formatter("%(asctime)s | %(levelname)s | %(message)s") ) def from_bytes( sequences: bytes, steps: int = 5, chunk_size: int = 512, threshold: float = 0.2, cp_isolation: Optional[List[str]] = None, cp_exclusion: Optional[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. By default the library does not setup any handler other than the NullHandler, if you choose to set the 'explain' toggle to True it will alter the logger configuration to add a StreamHandler that is suitable for debugging. Custom logging format and handler can be set manually. """ if not isinstance(sequences, (bytearray, bytes)): raise TypeError( "Expected object of type bytes or bytearray, got: {0}".format( type(sequences) ) ) if explain: previous_logger_level: int = logger.level logger.addHandler(explain_handler) logger.setLevel(TRACE) length: int = len(sequences) if length == 0: logger.debug("Encoding detection on empty bytes, assuming utf_8 intention.") if explain: logger.removeHandler(explain_handler) logger.setLevel(previous_logger_level or logging.WARNING) return CharsetMatches([CharsetMatch(sequences, "utf_8", 0.0, False, [], "")]) if cp_isolation is not None: logger.log( TRACE, "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.log( TRACE, "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.log( TRACE, "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: bool = len(sequences) < TOO_SMALL_SEQUENCE is_too_large_sequence: bool = len(sequences) >= TOO_BIG_SEQUENCE if is_too_small_sequence: logger.log( TRACE, "Trying to detect encoding from a tiny portion of ({}) byte(s).".format( length ), ) elif is_too_large_sequence: logger.log( TRACE, "Using lazy str decoding because the payload is quite large, ({}) byte(s).".format( length ), ) prioritized_encodings: List[str] = [] specified_encoding: Optional[str] = ( any_specified_encoding(sequences) if preemptive_behaviour else None ) if specified_encoding is not None: prioritized_encodings.append(specified_encoding) logger.log( TRACE, "Detected declarative mark in sequence. Priority +1 given for %s.", specified_encoding, ) tested: Set[str] = set() tested_but_hard_failure: List[str] = [] tested_but_soft_failure: List[str] = [] fallback_ascii: Optional[CharsetMatch] = None fallback_u8: Optional[CharsetMatch] = None fallback_specified: Optional[CharsetMatch] = None results: CharsetMatches = CharsetMatches() sig_encoding, sig_payload = identify_sig_or_bom(sequences) if sig_encoding is not None: prioritized_encodings.append(sig_encoding) logger.log( TRACE, "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: Optional[str] = None bom_or_sig_available: bool = sig_encoding == encoding_iana strip_sig_or_bom: bool = bom_or_sig_available and should_strip_sig_or_bom( encoding_iana ) if encoding_iana in {"utf_16", "utf_32"} and not bom_or_sig_available: logger.log( TRACE, "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: bool = is_multi_byte_encoding(encoding_iana) except (ModuleNotFoundError, ImportError): logger.log( TRACE, "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, LookupError) as e: if not isinstance(e, LookupError): logger.log( TRACE, "Code page %s does not fit given bytes sequence at ALL. %s", encoding_iana, str(e), ) tested_but_hard_failure.append(encoding_iana) continue similar_soft_failure_test: bool = False 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.log( TRACE, "%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 not bom_or_sig_available else len(sig_payload), length, int(length / steps), ) multi_byte_bonus: bool = ( is_multi_byte_decoder and decoded_payload is not None and len(decoded_payload) < length ) if multi_byte_bonus: logger.log( TRACE, "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 = int(len(r_) / 4) max_chunk_gave_up = max(max_chunk_gave_up, 2) early_stop_count: int = 0 lazy_str_hard_failure = False md_chunks: List[str] = [] md_ratios = [] try: for chunk in cut_sequence_chunks( sequences, encoding_iana, r_, chunk_size, bom_or_sig_available, strip_sig_or_bom, sig_payload, is_multi_byte_decoder, decoded_payload, ): 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 except UnicodeDecodeError as e: # Lazy str loading may have missed something there logger.log( TRACE, "LazyStr Loading: After MD chunk decode, code page %s does not fit given bytes sequence at ALL. %s", encoding_iana, str(e), ) early_stop_count = max_chunk_gave_up lazy_str_hard_failure = True # We might want to check the sequence again with the whole content # Only if initial MD tests passes if ( not lazy_str_hard_failure and is_too_large_sequence and not is_multi_byte_decoder ): try: sequences[int(50e3) :].decode(encoding_iana, errors="strict") except UnicodeDecodeError as e: logger.log( TRACE, "LazyStr Loading: After final lookup, code page %s does not fit given bytes sequence at ALL. %s", encoding_iana, str(e), ) tested_but_hard_failure.append(encoding_iana) continue mean_mess_ratio: float = sum(md_ratios) / len(md_ratios) if md_ratios else 0.0 if mean_mess_ratio >= threshold or early_stop_count >= max_chunk_gave_up: tested_but_soft_failure.append(encoding_iana) logger.log( TRACE, "%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] and not lazy_str_hard_failure ): 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.log( TRACE, "%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: 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, 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.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, ) -> 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[Any]", 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, ) -> 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[Any]", 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, ) -> CharsetMatch: """ Take a (text-based) file path and try to create another file next to it, this time using UTF-8. """ warnings.warn( "normalize is deprecated and will be removed in 3.0", DeprecationWarning, ) 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(str(path).replace(filename, "".join(target_extensions))), "wb" ) as fp: fp.write(result.output()) # type: ignore return result # type: ignore