######################## BEGIN LICENSE BLOCK ######################## # The Original Code is Mozilla Universal charset detector code. # # The Initial Developer of the Original Code is # Netscape Communications Corporation. # Portions created by the Initial Developer are Copyright (C) 2001 # the Initial Developer. All Rights Reserved. # # Contributor(s): # Mark Pilgrim - port to Python # Shy Shalom - original C code # # This library is free software; you can redistribute it and/or # modify it under the terms of the GNU Lesser General Public # License as published by the Free Software Foundation; either # version 2.1 of the License, or (at your option) any later version. # # This library is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU # Lesser General Public License for more details. # # You should have received a copy of the GNU Lesser General Public # License along with this library; if not, see # . ######################### END LICENSE BLOCK ######################### """ Module containing the UniversalDetector detector class, which is the primary class a user of ``chardet`` should use. :author: Mark Pilgrim (initial port to Python) :author: Shy Shalom (original C code) :author: Dan Blanchard (major refactoring for 3.0) :author: Ian Cordasco """ import codecs import logging import re from typing import Optional, Union from .charsetgroupprober import CharSetGroupProber from .charsetprober import CharSetProber from .enums import EncodingEra, InputState, LanguageFilter, ProbingState from .escprober import EscCharSetProber from .mbcsgroupprober import MBCSGroupProber from .metadata.charsets import get_charset, is_unicode_encoding from .resultdict import ResultDict from .sbcsgroupprober import ISO_WIN_MAP, SBCSGroupProber from .utf1632prober import UTF1632Prober class UniversalDetector: """ The ``UniversalDetector`` class underlies the ``chardet.detect`` function and coordinates all of the different charset probers. To get a ``dict`` containing an encoding and its confidence, you can simply run: .. code:: u = UniversalDetector() u.feed(some_bytes) u.close() detected = u.result """ MINIMUM_THRESHOLD = 0.20 HIGH_BYTE_DETECTOR = re.compile(b"[\x80-\xff]") ESC_DETECTOR = re.compile(b"(\033|~{)") # Threshold for "very close" confidence scores where era preference applies VERY_CLOSE_THRESHOLD = 0.005 # 0.5% # Map ISO encodings to their Windows equivalents (imported from sbcsgroupprober) ISO_WIN_MAP = ISO_WIN_MAP # Based on https://encoding.spec.whatwg.org/#names-and-labels # Maps legacy encoding names to their modern/superset equivalents. # Uses Python's canonical codec names (case-insensitive). LEGACY_MAP = { "ascii": "Windows-1252", # ASCII is subset of Windows-1252 "euc-kr": "CP949", # EUC-KR extended by CP949 (aka Windows-949) "iso-8859-1": "Windows-1252", # Latin-1 extended by Windows-1252 "iso-8859-2": "Windows-1250", # Central European "iso-8859-5": "Windows-1251", # Cyrillic "iso-8859-6": "Windows-1256", # Arabic "iso-8859-7": "Windows-1253", # Greek "iso-8859-8": "Windows-1255", # Hebrew "iso-8859-9": "Windows-1254", # Turkish "iso-8859-11": "CP874", # Thai, extended by CP874 (aka Windows-874) "iso-8859-13": "Windows-1257", # Baltic "tis-620": "CP874", # Thai, equivalent to Windows-874 } def __init__( self, lang_filter: LanguageFilter = LanguageFilter.ALL, should_rename_legacy: bool | None = None, encoding_era: EncodingEra = EncodingEra.MODERN_WEB, max_bytes: int = 200_000, ) -> None: self._esc_charset_prober: Optional[EscCharSetProber] = None self._utf1632_prober: Optional[UTF1632Prober] = None self._charset_probers: list[CharSetProber] = [] self.result: ResultDict = { "encoding": None, "confidence": 0.0, "language": None, } self.done = False self._got_data = False self._input_state = InputState.PURE_ASCII self._last_char = b"" self.lang_filter = lang_filter self.logger = logging.getLogger(__name__) if should_rename_legacy is None: should_rename_legacy = encoding_era == EncodingEra.MODERN_WEB self.should_rename_legacy = should_rename_legacy self.encoding_era = encoding_era self._total_bytes_fed = 0 self.max_bytes = max_bytes self.reset() @property def input_state(self) -> int: return self._input_state @property def has_win_bytes(self) -> bool: """Check if Windows-specific bytes were detected by the SBCS prober.""" for prober in self._charset_probers: if isinstance(prober, SBCSGroupProber): return prober._has_win_bytes return False @property def charset_probers(self) -> list[CharSetProber]: return self._charset_probers @property def nested_probers(self) -> list[CharSetProber]: """Get a flat list of all nested charset probers.""" nested = [] for prober in self._charset_probers: if isinstance(prober, CharSetGroupProber): nested.extend(getattr(prober, "probers", [])) else: nested.append(prober) return nested @property def active_probers(self) -> list[CharSetProber]: """Get a flat list of all active (not falsey and not in NOT_ME state) nested charset probers.""" return [prober for prober in self.nested_probers if prober and prober.active] def _apply_encoding_heuristics( self, charset_name: str, confidence: float, winning_prober: CharSetProber ) -> tuple[str, float]: """ Apply heuristic adjustments to the winning encoding based on: 1. Encoding era preferences (prefer newer/Unicode encodings) 2. Mac/Windows/ISO byte pattern disambiguation Collects all close-confidence alternatives in a single pass and picks the best one by era preference and Unicode preference. Returns: (adjusted_charset_name, adjusted_confidence) """ lower_charset_name = charset_name.lower() winner_charset = get_charset(lower_charset_name) winner_era = winner_charset.encoding_era.value winner_is_unicode = is_unicode_encoding(lower_charset_name) min_confidence = confidence * (1 - self.VERY_CLOSE_THRESHOLD) # Collect all close-confidence alternatives that would be preferred best_alt_name = None best_alt_confidence = confidence best_alt_era = winner_era best_alt_is_unicode = winner_is_unicode for prober in self._charset_probers: if not prober or not prober.active or prober == winning_prober: continue alt_charset_name = (prober.charset_name or "").lower() if not alt_charset_name: continue alt_confidence = prober.get_confidence() if alt_confidence < min_confidence: continue alt_charset = get_charset(alt_charset_name) alt_era = alt_charset.encoding_era.value alt_is_unicode = is_unicode_encoding(alt_charset_name) # Check if this alternative is preferred over the current best prefer_over_best = False if alt_era < best_alt_era: prefer_over_best = True elif alt_era == best_alt_era and alt_is_unicode and not best_alt_is_unicode: prefer_over_best = True if prefer_over_best: best_alt_name = alt_charset_name best_alt_confidence = alt_confidence best_alt_era = alt_era best_alt_is_unicode = alt_is_unicode if best_alt_name is not None: self.logger.debug( "Era preference: %s (era %s, unicode=%s) preferred over %s", best_alt_name, best_alt_era, best_alt_is_unicode, charset_name, ) charset_name = best_alt_name confidence = best_alt_confidence return charset_name, confidence def _get_utf8_prober(self) -> Optional[CharSetProber]: """ Get the UTF-8 prober from the charset probers. Returns None if not found. """ for prober in self.nested_probers: if prober.charset_name and "utf-8" in prober.charset_name.lower(): return prober return None def reset(self) -> None: """ Reset the UniversalDetector and all of its probers back to their initial states. This is called by ``__init__``, so you only need to call this directly in between analyses of different documents. """ self.result = {"encoding": None, "confidence": 0.0, "language": None} self.done = False self._got_data = False self._input_state = InputState.PURE_ASCII self._last_char = b"" self._total_bytes_fed = 0 if self._esc_charset_prober: self._esc_charset_prober.reset() if self._utf1632_prober: self._utf1632_prober.reset() for prober in self._charset_probers: prober.reset() def feed(self, byte_str: Union[bytes, bytearray]) -> None: """ Takes a chunk of a document and feeds it through all of the relevant charset probers. After calling ``feed``, you can check the value of the ``done`` attribute to see if you need to continue feeding the ``UniversalDetector`` more data, or if it has made a prediction (in the ``result`` attribute). .. note:: You should always call ``close`` when you're done feeding in your document if ``done`` is not already ``True``. """ if self.done: return if not byte_str: return if not isinstance(byte_str, bytearray): byte_str = bytearray(byte_str) # First check for known BOMs, since these are guaranteed to be correct if not self._got_data: # If the data starts with BOM, we know it is UTF if byte_str.startswith(codecs.BOM_UTF8): # EF BB BF UTF-8 with BOM self.result = { "encoding": "UTF-8-SIG", "confidence": 1.0, "language": "", } elif byte_str.startswith((codecs.BOM_UTF32_LE, codecs.BOM_UTF32_BE)): # FF FE 00 00 UTF-32, little-endian BOM # 00 00 FE FF UTF-32, big-endian BOM self.result = {"encoding": "UTF-32", "confidence": 1.0, "language": ""} elif byte_str.startswith((codecs.BOM_UTF16_LE, codecs.BOM_UTF16_BE)): # FF FE UTF-16, little endian BOM # FE FF UTF-16, big endian BOM self.result = {"encoding": "UTF-16", "confidence": 1.0, "language": ""} else: # Binary file detection - check for excessive null bytes early # But UTF-16/32 have null bytes, so check for patterns first # Check for no-BOM UTF-16/32 patterns (alternating nulls) # UTF-32LE: XX 00 00 00 pattern (every 4th byte is null) # UTF-32BE: 00 00 00 XX pattern (first 3 of 4 bytes are null) # UTF-16LE: XX 00 pattern (every other byte is null in odd positions) # UTF-16BE: 00 XX pattern (every other byte is null in even positions) looks_like_utf16_32 = False # Use larger sample for better pattern detection sample_size = min(len(byte_str), 200) if sample_size >= 50: sample = byte_str[:sample_size] # Count nulls in even and odd positions (for UTF-16 detection) even_nulls = sum( 1 for i in range(0, sample_size, 2) if sample[i] == 0 ) odd_nulls = sum( 1 for i in range(1, sample_size, 2) if sample[i] == 0 ) # Check for UTF-32 patterns (more nulls in groups of 4) # For UTF-32LE: positions 1,2,3 of every 4 bytes might be null # For UTF-32BE: positions 0,1,2 of every 4 bytes might be null if sample_size >= 100: mod1_nulls = sum( 1 for i in range(1, sample_size, 4) if sample[i] == 0 ) mod2_nulls = sum( 1 for i in range(2, sample_size, 4) if sample[i] == 0 ) mod3_nulls = sum( 1 for i in range(3, sample_size, 4) if sample[i] == 0 ) # Strong UTF-32 signal: consistent null pattern in 2+ of the 3 positions utf32_nulls = [mod1_nulls, mod2_nulls, mod3_nulls] if sum(n > sample_size // 8 for n in utf32_nulls) >= 2: looks_like_utf16_32 = True # UTF-16 detection: significant nulls in even OR odd positions # Lower threshold: 12% of positions (24 out of 200) utf16_threshold = sample_size // 16 if even_nulls > utf16_threshold or odd_nulls > utf16_threshold: looks_like_utf16_32 = True if not looks_like_utf16_32: # Sample first 8KB to detect binary files check_size = min(len(byte_str), 8192) null_count = byte_str[:check_size].count(0) if null_count > check_size * 0.1: # >10% null bytes # Likely a binary file, not text self.result = { "encoding": None, "confidence": 0.0, "language": "", } self.done = True return self._got_data = True if self.result["encoding"] is not None: self.done = True return # If none of those matched and we've only see ASCII so far, check # for high bytes and escape sequences if self._input_state == InputState.PURE_ASCII: if self.HIGH_BYTE_DETECTOR.search(byte_str): self._input_state = InputState.HIGH_BYTE elif ( self._input_state == InputState.PURE_ASCII and self.ESC_DETECTOR.search(self._last_char + byte_str) ): self._input_state = InputState.ESC_ASCII self._last_char = byte_str[-1:] # Track total bytes processed self._total_bytes_fed += len(byte_str) # Stop processing after processing enough data # Don't set done=True here, let close() finalize the result if self._total_bytes_fed > self.max_bytes: return # next we will look to see if it is appears to be either a UTF-16 or # UTF-32 encoding if not self._utf1632_prober: self._utf1632_prober = UTF1632Prober() if self._utf1632_prober.state == ProbingState.DETECTING: if self._utf1632_prober.feed(byte_str) == ProbingState.FOUND_IT: self.result = { "encoding": self._utf1632_prober.charset_name, "confidence": self._utf1632_prober.get_confidence(), "language": "", } self.done = True return # If we've seen escape sequences, use the EscCharSetProber, which # uses a simple state machine to check for known escape sequences in # HZ and ISO-2022 encodings, since those are the only encodings that # use such sequences. if self._input_state == InputState.ESC_ASCII: if not self._esc_charset_prober: self._esc_charset_prober = EscCharSetProber(self.lang_filter) if self._esc_charset_prober.feed(byte_str) == ProbingState.FOUND_IT: self.result = { "encoding": self._esc_charset_prober.charset_name, "confidence": self._esc_charset_prober.get_confidence(), "language": self._esc_charset_prober.language, } self.done = True # If we've seen high bytes (i.e., those with values greater than 127), # we need to do more complicated checks using all our multi-byte and # single-byte probers that are left. The single-byte probers # use character bigram distributions to determine the encoding, whereas # the multi-byte probers use a combination of character unigram and # bigram distributions. elif self._input_state == InputState.HIGH_BYTE: if not self._charset_probers: self._charset_probers = [ MBCSGroupProber( lang_filter=self.lang_filter, encoding_era=self.encoding_era ) ] # If we're checking non-CJK encodings, use single-byte prober if self.lang_filter & LanguageFilter.NON_CJK: self._charset_probers.append( SBCSGroupProber( encoding_era=self.encoding_era, lang_filter=self.lang_filter ) ) for prober in self._charset_probers: if prober.feed(byte_str) == ProbingState.FOUND_IT: charset_name = prober.charset_name # Rename legacy encodings if requested if self.should_rename_legacy: charset_name = self.LEGACY_MAP.get( (charset_name or "").lower(), charset_name ) self.result = { "encoding": charset_name, "confidence": prober.get_confidence(), "language": prober.language, } self.done = True break def close(self) -> ResultDict: """ Stop analyzing the current document and come up with a final prediction. :returns: The ``result`` attribute, a ``dict`` with the keys `encoding`, `confidence`, and `language`. """ # Don't bother with checks if we're already done if self.done: return self.result self.done = True if not self._got_data: self.logger.debug("no data received!") # Default to ASCII if it is all we've seen so far elif self._input_state == InputState.PURE_ASCII: self.result = {"encoding": "ascii", "confidence": 1.0, "language": ""} # Check if escape prober found anything elif self._input_state == InputState.ESC_ASCII: if self._esc_charset_prober: charset_name = self._esc_charset_prober.charset_name if charset_name: self.result = { "encoding": charset_name, "confidence": self._esc_charset_prober.get_confidence(), "language": self._esc_charset_prober.language, } else: # ESC prober didn't identify a specific encoding # Since input is pure ASCII + ESC, default to UTF-8 self.result = { "encoding": "utf-8", "confidence": 1.0, "language": "", } # If we have seen non-ASCII, return the best that met MINIMUM_THRESHOLD elif self._input_state == InputState.HIGH_BYTE: prober_confidence = None max_prober_confidence = 0.0 max_prober = None for prober in self._charset_probers: if not prober: continue prober_confidence = prober.get_confidence() if prober_confidence > max_prober_confidence: max_prober_confidence = prober_confidence max_prober = prober if max_prober and (max_prober_confidence > self.MINIMUM_THRESHOLD): charset_name = max_prober.charset_name assert charset_name is not None lower_charset_name = charset_name.lower() confidence = max_prober.get_confidence() # Find the actual winning nested prober (max_prober might be a group prober) winning_nested_prober = None for prober in self.nested_probers: if ( prober and prober.active and prober.charset_name and prober.charset_name.lower() == lower_charset_name and abs(prober.get_confidence() - confidence) < 0.0001 ): winning_nested_prober = prober break # Apply heuristic adjustments in a single pass over active probers charset_name, confidence = self._apply_encoding_heuristics( charset_name, confidence, winning_nested_prober or max_prober ) # Rename legacy encodings with superset encodings if asked if self.should_rename_legacy: charset_name = self.LEGACY_MAP.get( (charset_name or "").lower(), charset_name ) self.result = { "encoding": charset_name, "confidence": confidence, "language": max_prober.language, } else: # Default to UTF-8 if no encoding met threshold AND UTF-8 prober # hasn't determined this is NOT UTF-8 # UTF-8 is now the most common encoding on the web and a superset of ASCII utf8_prober = self._get_utf8_prober() if utf8_prober and utf8_prober.active: # UTF-8 prober didn't rule it out, so default to UTF-8 self.result = { "encoding": utf8_prober.charset_name, "confidence": utf8_prober.get_confidence(), "language": utf8_prober.language, } else: # UTF-8 was ruled out, return None self.result = { "encoding": None, "confidence": 0.0, "language": None, } # Log all prober confidences if none met MINIMUM_THRESHOLD if self.logger.getEffectiveLevel() <= logging.DEBUG: if self.result["encoding"] is None: self.logger.debug("no probers hit minimum threshold") for prober in self.nested_probers: if not prober: continue self.logger.debug( "%s %s confidence = %s", prober.charset_name, prober.language, prober.get_confidence(), ) return self.result