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uchardet/script/BuildLangModel.py

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#!/bin/python3
# -*- coding: utf-8 -*-
# ##### BEGIN LICENSE BLOCK #####
# Version: MPL 1.1/GPL 2.0/LGPL 2.1
#
# The contents of this file are subject to the Mozilla Public License Version
# 1.1 (the "License"); you may not use this file except in compliance with
# the License. You may obtain a copy of the License at
# http://www.mozilla.org/MPL/
#
# Software distributed under the License is distributed on an "AS IS" basis,
# WITHOUT WARRANTY OF ANY KIND, either express or implied. See the License
# for the specific language governing rights and limitations under the
# License.
#
# 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):
# Jehan <jehan@girinstud.io>
#
# Alternatively, the contents of this file may be used under the terms of
# either the GNU General Public License Version 2 or later (the "GPL"), or
# the GNU Lesser General Public License Version 2.1 or later (the "LGPL"),
# in which case the provisions of the GPL or the LGPL are applicable instead
# of those above. If you wish to allow use of your version of this file only
# under the terms of either the GPL or the LGPL, and not to allow others to
# use your version of this file under the terms of the MPL, indicate your
# decision by deleting the provisions above and replace them with the notice
# and other provisions required by the GPL or the LGPL. If you do not delete
# the provisions above, a recipient may use your version of this file under
# the terms of any one of the MPL, the GPL or the LGPL.
#
# ##### END LICENSE BLOCK #####
# Third party modules.
import unicodedata
import wikipedia
import importlib
import optparse
import datetime
import operator
import requests
import sys
import re
import os
# Custom modules.
import charsets.db
from charsets.codepoints import *
# Command line processing.
usage = 'Usage: {} <LANG-CODE>\n' \
'\nEx: `{} fr`'.format(__file__, __file__)
description = "Internal tool for uchardet to generate language data."
cmdline = optparse.OptionParser(usage, description = description)
cmdline.add_option('--max-page',
help = 'Maximum number of Wikipedia pages to parse (useful for debugging).',
action = 'store', type = 'int', dest = 'max_page', default = None)
cmdline.add_option('--max-depth',
help = 'Maximum depth when following links from start page (default: 2).',
action = 'store', type = 'int',
dest = 'max_depth', default = 2)
(options, langs) = cmdline.parse_args()
if len(langs) < 1:
print("Please select at least one language code.\n")
exit(1)
if len(langs) > 1:
print("This script is meant to generate data for one language at a time.\n")
exit(1)
lang = langs[0]
# Load the language data.
sys_path_backup = sys.path
current_dir = os.path.dirname(os.path.realpath(__file__))
sys.path = [current_dir + '/langs']
try:
lang = importlib.import_module(lang.lower())
except ImportError:
print('Unknown language code "{}": '
'file "langs/{}.py" does not exist.'.format(lang, lang.lower()))
exit(1)
sys.path = sys_path_backup
charsets = charsets.db.load(lang.charsets)
if not hasattr(lang, 'start_pages') or lang.start_pages is None or \
lang.start_pages == []:
# Let's start with the main page, assuming it should have links
# to relevant pages. In locale wikipedia, this page is usually redirected
# to a relevant page.
print("Warning: no `start_pages` set for '{}'. Using ['Main_Page'].\n"
" If you don't get good data, it is advised to set a "
"start_pages` variable yourself.".format(lang.code))
lang.start_pages = ['Main_Page']
if not hasattr(lang, 'wikipedia_code') or lang.wikipedia_code is None:
lang.wikipedia_code = lang.code
if not hasattr(lang, 'clean_wikipedia_content') or lang.clean_wikipedia_content is None:
lang.clean_wikipedia_content = None
if hasattr(lang, 'case_mapping'):
lang.case_mapping = bool(lang.case_mapping)
else:
lang.case_mapping = False
if not hasattr(lang, 'custom_case_mapping'):
lang.custom_case_mapping = None
if not hasattr(lang, 'alphabet') or lang.alphabet is None:
lang.alphabet = None
def local_lowercase(text, lang):
lowercased = ''
for l in text:
if lang.custom_case_mapping is not None and \
l in lang.custom_case_mapping:
lowercased += lang.custom_case_mapping[l]
elif l.isupper() and \
lang.case_mapping and \
len(unicodedata.normalize('NFC', l.lower())) == 1:
lowercased += l.lower()
else:
lowercased += l
return lowercased
if lang.alphabet is not None:
# Allowing to provide an alphabet in string format rather than list.
lang.alphabet = list(lang.alphabet)
if lang.use_ascii:
lang.alphabet += [chr(l) for l in range(65, 91)] + [chr(l) for l in range(97, 123)]
if lang.case_mapping or lang.custom_case_mapping is not None:
lang.alphabet = [local_lowercase(l, lang) for l in lang.alphabet]
#alphabet = []
#for l in lang.alphabet:
#if l.isupper() and \
#lang.custom_case_mapping is not None and \
#l in lang.custom_case_mapping:
#alphabet.append(lang.custom_case_mapping[l])
#elif l.isupper() and \
#lang.case_mapping and \
#len(unicodedata.normalize('NFC', l.lower())) == 1:
#alphabet.append(l.lower())
#else:
#alphabet.append(l)
lang.alphabet = list(set(lang.alphabet))
# Starting processing.
wikipedia.set_lang(lang.wikipedia_code)
visited_pages = []
# The full list of letter characters.
# The key is the unicode codepoint,
# and the value is the occurrence count.
characters = {}
# Sequence of letters.
# The key is the couple (char1, char2) in unicode codepoint,
# the value is the occurrence count.
sequences = {}
prev_char = None
def process_text(text, lang):
global charsets
global characters
global sequences
global prev_char
if lang.clean_wikipedia_content is not None:
content = lang.clean_wikipedia_content(text)
# Clean multiple spaces. Newlines and such are normalized to spaces,
# since they have basically a similar role in the purpose of uchardet.
content = re.sub(r'\s+', ' ', content)
if lang.case_mapping or lang.custom_case_mapping is not None:
content = local_lowercase(content, lang)
# In python 3, strings are UTF-8.
# Looping through them return expected characters.
for char in content:
is_letter = False
if ord(char) in characters:
characters[ord(char)] += 1
is_letter = True
else:
# We save the character if it is at least in one of the
# language encodings and its not a special character.
for charset in charsets:
# Does the character exist in the charset?
codepoint = char.encode(charset, 'ignore')
if codepoint == b'':
continue
# ord() is said to return the unicode codepoint.
# But it turns out it also gives the codepoint for other
# charsets if I turn the string to encoded bytes first.
# Not sure if that is a bug or expected.
codepoint = ord(codepoint)
if charsets[charset].charmap[codepoint] == LET:
characters[ord(char)] = 1
is_letter = True
break
if is_letter:
if prev_char is not None:
if (prev_char, ord(char)) in sequences:
sequences[(prev_char, ord(char))] += 1
else:
sequences[(prev_char, ord(char))] = 1
prev_char = ord(char)
else:
prev_char = None
def visit_pages(titles, depth, lang, logfd):
global visited_pages
global options
if len(titles) == 0:
return
next_titles = []
for title in titles:
if options.max_page is not None and \
len(visited_pages) > options.max_page:
return
if title in visited_pages:
continue
visited_pages += [title]
try:
page = wikipedia.page(title)
except (wikipedia.exceptions.PageError,
wikipedia.exceptions.DisambiguationError):
# Let's just discard a page when I get an exception.
print("Discarding page {}.\n".format(title))
continue
logfd.write("\n{} (revision {})".format(title, page.revision_id))
process_text(page.content, lang)
next_titles += page.links
if depth >= options.max_depth:
return
visit_pages (next_titles, depth + 1, lang, logfd)
language_c = lang.name.replace('-', '_').title()
build_log = current_dir + '/BuildLangModelLogs/Lang{}Model.log'.format(language_c)
logfd = open(build_log, 'w')
logfd.write('= Logs of language model for {} ({}) =\n'.format(lang.name, lang.code))
logfd.write('\n- Generated by {}'.format(os.path.basename(__file__)))
logfd.write('\n- Started: {}'.format(str(datetime.datetime.now())))
logfd.write('\n- Maximum depth: {}'.format(options.max_depth))
if options.max_page is not None:
logfd.write('\n- Max number of pages: {}'.format(options.max_page))
logfd.write('\n\n== Parsed pages ==\n')
try:
visit_pages(lang.start_pages, 0, lang, logfd)
except requests.exceptions.ConnectionError:
print('Error: connection to Wikipedia failed. Aborting\n')
exit(1)
logfd.write('\n\n== End of Parsed pages ==')
logfd.write('\n\n- Wikipedia parsing ended at: {}\n'.format(str(datetime.datetime.now())))
########### CHARACTERS ###########
# Character ratios.
ratios = {}
n_char = len(characters)
occurrences = sum(characters.values())
logfd.write("\n{} characters appeared {} times.\n".format(n_char, occurrences))
for char in characters:
ratios[char] = characters[char] / occurrences
#logfd.write("Character '{}' usage: {} ({} %)\n".format(chr(char),
# characters[char],
# ratios[char] * 100))
sorted_ratios = sorted(ratios.items(), key=operator.itemgetter(1),
reverse=True)
# Accumulated ratios of the frequent chars.
accumulated_ratios = 0
# If there is no alphabet defined, we just use the first 64 letters, which was
# the original default.
# If there is an alphabet, we make sure all the alphabet characters are in the
# frequent list, and we stop then. There may therefore be more or less than
# 64 frequent characters depending on the language.
if lang.alphabet is None:
freq_count = 64
else:
freq_count = 0
for order, (char, ratio) in enumerate(sorted_ratios):
if len(lang.alphabet) == 0:
break
if chr(char) in lang.alphabet:
lang.alphabet.remove(chr(char))
freq_count += 1
else:
if len(lang.alphabet) > 0:
print("Error: alphabet characters are absent from data collection"
"\n Please check the configuration or the data."
"\n Missing characters: {}".format(", ".join(lang.alphabet)))
exit(1)
logfd.write('\nFirst {} characters:'.format(freq_count))
for order, (char, ratio) in enumerate(sorted_ratios):
if order >= freq_count:
break
logfd.write("\n[{:2}] Char {}: {} %".format(order, chr(char), ratio * 100))
accumulated_ratios += ratio
logfd.write("\n\nThe first {} characters have an accumulated ratio of {}.\n".format(freq_count, accumulated_ratios))
with open(current_dir + '/header-template.cpp', 'r') as header_fd:
c_code = header_fd.read()
c_code += '\n/********* Language model for: {} *********/\n\n'.format(lang.name)
c_code += '/**\n * Generated by {}\n'.format(os.path.basename(__file__))
c_code += ' * On: {}\n'.format(str(datetime.datetime.now()))
c_code += ' **/\n'
c_code += \
"""
/* Character Mapping Table:
* ILL: illegal character.
* CTR: control character specific to the charset.
* RET: carriage/return.
* SYM: symbol (punctuation) that does not belong to word.
* NUM: 0 - 9.
*
* Other characters are ordered by probabilities
* (0 is the most common character in the language).
*
* Orders are generic to a language. So the codepoint with order X in
* CHARSET1 maps to the same character as the codepoint with the same
* order X in CHARSET2 for the same language.
* As such, it is possible to get missing order. For instance the
* ligature of 'o' and 'e' exists in ISO-8859-15 but not in ISO-8859-1
* even though they are both used for French. Same for the euro sign.
*/
"""
for charset in charsets:
charset_c = charset.replace('-', '_').title()
CTOM_str = 'static const unsigned char {}_CharToOrderMap[]'.format(charset_c)
CTOM_str += ' =\n{'
for line in range(0, 16):
CTOM_str += '\n '
for column in range(0, 16):
cp = line * 16 + column
cp_type = charsets[charset].charmap[cp]
if cp_type == ILL:
CTOM_str += 'ILL,'
elif cp_type == RET:
CTOM_str += 'RET,'
elif cp_type == CTR:
CTOM_str += 'CTR,'
elif cp_type == SYM:
CTOM_str += 'SYM,'
elif cp_type == NUM:
CTOM_str += 'NUM,'
else: # LET
try:
uchar = bytes([cp]).decode(charset)
except UnicodeDecodeError:
print('Unknown character 0X{:X} in {}.'.format(cp, charset))
print('Please verify your charset specification.\n')
exit(1)
#if lang.case_mapping and uchar.isupper() and \
#len(unicodedata.normalize('NFC', uchar.lower())) == 1:
# Unless we encounter special cases of characters with no
# composed lowercase, we lowercase it.
if lang.case_mapping or lang.custom_case_mapping is not None:
uchar = local_lowercase(uchar, lang)
for order, (char, ratio) in enumerate(sorted_ratios):
if char == ord(uchar):
CTOM_str += '{:3},'.format(order)
break
else:
CTOM_str += '{:3},'.format(n_char)
n_char += 1
CTOM_str += ' /* {:X}X */'.format(line)
CTOM_str += '\n};\n/*'
CTOM_str += 'X0 X1 X2 X3 X4 X5 X6 X7 X8 X9 XA XB XC XD XE XF'
CTOM_str += ' */\n\n'
c_code += CTOM_str
########### SEQUENCES ###########
ratios = {}
occurrences = sum(sequences.values())
ratio_512 = 0
ratio_1024 = 0
sorted_seqs = sorted(sequences.items(), key=operator.itemgetter(1),
reverse=True)
for order, ((c1, c2), count) in enumerate(sorted_seqs):
if order < 512:
ratio_512 += count
elif order < 1024:
ratio_1024 += count
else:
break
ratio_512 /= occurrences
ratio_1024 /= occurrences
logfd.write("\n{} sequences found.\n".format(len(sorted_seqs)))
c_code += """
/* Model Table:
* Total sequences: {}
* First 512 sequences: {}
* Next 512 sequences (512-1024): {}
* Rest: {}
* Negative sequences: TODO""".format(len(sorted_seqs),
ratio_512,
ratio_1024,
1 - ratio_512 - ratio_1024)
logfd.write("\nFirst 512 (typical positive ratio): {}".format(ratio_512))
logfd.write("\nNext 512 (512-1024): {}".format(ratio))
logfd.write("\nRest: {}".format(1 - ratio_512 - ratio_1024))
c_code += "\n */\n"
LM_str = 'static const PRUint8 {}LangModel[]'.format(language_c)
LM_str += ' =\n{'
for line in range(0, freq_count):
LM_str += '\n '
for column in range(0, freq_count):
# Let's not make too long lines.
if freq_count > 40 and column == int(freq_count / 2):
LM_str += '\n '
first_order = int(line)
second_order = column
if first_order < len(sorted_ratios) and second_order < len(sorted_ratios):
(first_char, _) = sorted_ratios[first_order]
(second_char, _) = sorted_ratios[second_order]
if (first_char, second_char) in sequences:
for order, (seq, _) in enumerate(sorted_seqs):
if seq == (first_char, second_char):
if order < 512:
LM_str += '3,'
elif order < 1024:
LM_str += '2,'
else:
LM_str += '1,'
break
else:
pass # impossible!
LM_str += '0,'
else:
LM_str += '0,'
else:
# It may indeed happen that we find less than 64 letters used for a
# given language.
LM_str += '0,'
LM_str += '\n};\n'
c_code += LM_str
for charset in charsets:
charset_c = charset.replace('-', '_').title()
SM_str = '\n\nconst SequenceModel {}{}Model ='.format(charset_c, language_c)
SM_str += '\n{\n '
SM_str += '{}_CharToOrderMap,\n {}LangModel,'.format(charset_c, language_c)
SM_str += '\n {},'.format(freq_count)
SM_str += '\n (float){},'.format(ratio_512)
SM_str += '\n {},'.format('PR_TRUE' if lang.use_ascii else 'PR_FALSE')
SM_str += '\n "{}"'.format(charset)
SM_str += '\n};'
c_code += SM_str
lang_model_file = current_dir + '/../src/LangModels/Lang{}Model.cpp'.format(language_c)
with open(lang_model_file, 'w') as cpp_fd:
cpp_fd.write(c_code)
logfd.write('\n\n- Processing end: {}\n'.format(str(datetime.datetime.now())))
logfd.close()
print("The following language model file has been generated: {}"
"\nThe build log is available in: {}"
"\nTest them and commit them.".format(lang_model_file, build_log))
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