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convert_language_model.py
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#!/usr/bin/env python ######################## BEGIN LICENSE BLOCK ######################## # Contributor(s): # 10.02.2015 - helour - first attempt # 08.08.2016 - Dan Blanchard - first usable release # # 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, write to the Free Software # Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA # 02110-1301 USA # ######################### END LICENSE BLOCK ######################### """ Convert old style SBCS model to new """ import os import sys from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser from string import ascii_letters import chardet from chardet import __version__ from chardet.metadata.languages import LANGUAGES from chardet.sbcharsetprober import SingleByteCharSetModel # Turn ascii_letters into a set to make other ops easier ascii_letters = set(ascii_letters) def normalize_name(charset_name): """Convert name to proper Python constant format""" # Title case to start charset_name = charset_name.upper() # Underscores instead of hyphens charset_name = charset_name.replace("-", "_") return charset_name def convert_sbcs_model(old_model, alphabet): """Create a SingleByteCharSetModel object representing the charset.""" # Setup tables necessary for computing transition frequencies for model char_to_order = dict(enumerate(old_model["char_to_order_map"])) pos_ratio = old_model["typical_positive_ratio"] keep_ascii_letters = old_model["keep_english_letter"] curr_model = SingleByteCharSetModel( charset_name=old_model["charset_name"], language=old_model["language"], char_to_order_map=char_to_order, # language_model is filled in later language_model=None, typical_positive_ratio=pos_ratio, keep_ascii_letters=keep_ascii_letters, alphabet=alphabet, ) return curr_model def print_char_to_order(var_name, order_map, charset_name, output_file): print(f"{var_name} = {{", file=output_file) for char, order in sorted(order_map.items()): char_bytes = bytes(bytearray((char,))) try: unicode_char = char_bytes.decode(charset_name) except UnicodeError: unicode_char = None print(f" {char!r}: {order!r}, # {unicode_char!r}", file=output_file) print("}\n", file=output_file) def print_language_model(var_name, language_model, output_file, char_ranks): print( "# 3: Positive\n# 2: Likely\n# 1: Unlikely\n# 0: Negative\n", file=output_file, ) print(f"{var_name} = {{", file=output_file) for first_char, sub_dict in sorted(language_model.items()): # Skip empty sub_dicts if not sub_dict or first_char not in char_ranks: continue print(f" {char_ranks[first_char]!r}: {{ # {first_char!r}", file=output_file) for second_char, likelihood in sorted(sub_dict.items()): if second_char not in char_ranks: continue print( f" {char_ranks[second_char]!r}: {likelihood!r}, # " f"{second_char!r}", file=output_file, ) print(" },", file=output_file) print("}\n", file=output_file) def convert_models_for_lang(language): """Convert old SingleByteCharSetModels for the given language""" # Validate language language = language.title() lang_metadata = LANGUAGES.get(language) if not lang_metadata: raise ValueError( f"Unknown language: {language}. If you are adding a model for a" " new language, you must first update metadata/" "languages.py" ) lang_mod_name = f"lang{language.lower()}model" if not os.path.exists(os.path.join("chardet", lang_mod_name + ".py")): print(f"Skipping {language} because it does not have an old model.") return lang_mod = getattr(chardet, lang_mod_name) print( f"\n{language}\n----------------------------------------------------------------" ) print(f"Keep ASCII Letters: {lang_metadata.use_ascii}") print(f"Alphabet: {lang_metadata.alphabet}") # Create char-to-order maps (aka char-to-rank dicts) charset_models = {} char_ranks = {} order_to_chars = {} for var_name in dir(lang_mod): if not ("Model" in var_name and "LangModel" not in var_name): continue old_model = getattr(lang_mod, var_name) charset_name = old_model["charset_name"] print(f"Converting charset model for {charset_name}") sys.stdout.flush() charset_models[charset_name] = convert_sbcs_model( old_model, lang_metadata.alphabet ) # Since we don't know which charsets have which characters, we have to # try to reconstruct char_ranks (for letters only, since that's all # the old language models contain) for byte_hex, order in charset_models[charset_name].char_to_order_map.items(): # order 64 was basically ignored before because of the off by one # error, but it's hard to know if training took that into account if order > 64: continue # Convert to bytes in Python 2 and 3 char = bytes(bytearray((byte_hex,))) try: unicode_char = char.decode(charset_name) except UnicodeDecodeError: continue if unicode_char not in char_ranks: char_ranks[unicode_char] = order order_to_chars[order] = unicode_char elif char_ranks[unicode_char] != order: raise ValueError(f"Unstable character ranking for {unicode_char}") old_lang_model = getattr(lang_mod, f"{language.title()}LangModel") language_model = {} # Preserve off-by-one error here by ignoring first column and row for i in range(1, 64): if i not in order_to_chars: continue lang_char = order_to_chars[i] language_model[lang_char] = {} for j in range(1, 64): if j not in order_to_chars: continue lang_char2 = order_to_chars[j] language_model[lang_char][lang_char2] = old_lang_model[(i * 64) + j] # Write output files print(f"Writing output file for {language}\n\n") sys.stdout.flush() with open(f"lang{language.lower()}model.py", "w", encoding="utf-8") as output_file: upper_lang = language.upper() # print header to set encoding print( "from chardet.sbcharsetprober import SingleByteCharSetModel\n\n", file=output_file, ) lm_name = f"{upper_lang}_LANG_MODEL" print_language_model(lm_name, language_model, output_file, char_ranks) print( "# 255: Undefined characters that did not exist in training text\n" "# 254: Carriage/Return\n" "# 253: symbol (punctuation) that does not belong to word\n" "# 252: 0 - 9\n" "# 251: Control characters\n\n" "# Character Mapping Table(s):", file=output_file, ) for charset_name, sbcs_model in charset_models.items(): normal_name = normalize_name(charset_name) char_to_order_name = f"{normal_name}_{upper_lang}_CHAR_TO_ORDER" print_char_to_order( char_to_order_name, sbcs_model.char_to_order_map, charset_name, output_file, ) sbcs_model_name = f"{normal_name}_{upper_lang}_MODEL" sbcs_model.char_to_order_map.clear() sbcs_model_repr = ( repr(sbcs_model) .replace("None", lm_name) .replace("{}", char_to_order_name) .replace(", ", (",\n" + " " * (len(sbcs_model_name) + 26))) ) print(f"{sbcs_model_name} = {sbcs_model_repr}\n", file=output_file) def main(): parser = ArgumentParser( description=__doc__, formatter_class=ArgumentDefaultsHelpFormatter ) parser.add_argument( "language", help="The name of the language the input documents are " "in. Also the name of the language the generated " "model will detect. If no language is specified, " "models for all languages known to chardet will be" " trained.", nargs="*", ) parser.add_argument("--version", action="version", version=__version__) args = parser.parse_args() if not args.language: args.language = list(sorted(LANGUAGES.keys())) for language in args.language: convert_models_for_lang(language) if __name__ == "__main__": main()