mirror of
https://gitlab.freedesktop.org/uchardet/uchardet.git
synced 2025-12-06 16:56:40 +08:00
3e5d37a6b5
I.e. horizontally or "breadth first" rather than vertical tree traversal. This allows to make sure all the start pages in particular are searched, when using max_page option.
447 lines
16 KiB
Python
Executable File
447 lines
16 KiB
Python
Executable File
#!/bin/python3
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# -*- coding: utf-8 -*-
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# ##### BEGIN LICENSE BLOCK #####
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# Version: MPL 1.1/GPL 2.0/LGPL 2.1
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#
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# The contents of this file are subject to the Mozilla Public License Version
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# 1.1 (the "License"); you may not use this file except in compliance with
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# the License. You may obtain a copy of the License at
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# http://www.mozilla.org/MPL/
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#
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# Software distributed under the License is distributed on an "AS IS" basis,
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# WITHOUT WARRANTY OF ANY KIND, either express or implied. See the License
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# for the specific language governing rights and limitations under the
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# License.
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#
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# The Original Code is Mozilla Universal charset detector code.
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#
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# The Initial Developer of the Original Code is
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# Netscape Communications Corporation.
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# Portions created by the Initial Developer are Copyright (C) 2001
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# the Initial Developer. All Rights Reserved.
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#
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# Contributor(s):
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# Jehan <jehan@girinstud.io>
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#
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# Alternatively, the contents of this file may be used under the terms of
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# either the GNU General Public License Version 2 or later (the "GPL"), or
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# the GNU Lesser General Public License Version 2.1 or later (the "LGPL"),
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# in which case the provisions of the GPL or the LGPL are applicable instead
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# of those above. If you wish to allow use of your version of this file only
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# under the terms of either the GPL or the LGPL, and not to allow others to
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# use your version of this file under the terms of the MPL, indicate your
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# decision by deleting the provisions above and replace them with the notice
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# and other provisions required by the GPL or the LGPL. If you do not delete
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# the provisions above, a recipient may use your version of this file under
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# the terms of any one of the MPL, the GPL or the LGPL.
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#
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# ##### END LICENSE BLOCK #####
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# Third party modules.
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import wikipedia
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import importlib
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import optparse
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import datetime
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import operator
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import requests
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import sys
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import re
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import os
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# Custom modules.
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import charsets.db
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from charsets.codepoints import *
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# Command line processing.
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usage = 'Usage: {} <LANG-CODE>\n' \
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'\nEx: `{} fr`'.format(__file__, __file__)
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description = "Internal tool for uchardet to generate language data."
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cmdline = optparse.OptionParser(usage, description = description)
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cmdline.add_option('--max-page',
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help = 'Maximum number of Wikipedia pages to parse (useful for debugging).',
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action = 'store', type = 'int', dest = 'max_page', default = None)
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cmdline.add_option('--max-depth',
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help = 'Maximum depth when following links from start page (default: 2).',
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action = 'store', type = 'int',
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dest = 'max_depth', default = 2)
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(options, langs) = cmdline.parse_args()
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if len(langs) < 1:
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print("Please select at least one language code.\n")
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exit(1)
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if len(langs) > 1:
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print("This script is meant to generate data for one language at a time.\n")
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exit(1)
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lang = langs[0]
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# Load the language data.
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sys_path_backup = sys.path
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current_dir = os.path.dirname(os.path.realpath(__file__))
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sys.path = [current_dir + '/langs']
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try:
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lang = importlib.import_module(lang.lower())
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except ImportError:
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print('Unknown language code "{}": '
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'file "langs/{}.py" does not exist.'.format(lang, lang.lower()))
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exit(1)
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sys.path = sys_path_backup
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charsets = charsets.db.load(lang.charsets)
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if not hasattr(lang, 'start_pages') or lang.start_pages is None or \
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lang.start_pages == []:
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# Let's start with the main page, assuming it should have links
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# to relevant pages. In locale wikipedia, this page is usually redirected
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# to a relevant page.
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print("Warning: no `start_pages` set for '{}'. Using ['Main_Page'].\n"
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" If you don't get good data, it is advised to set a "
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"start_pages` variable yourself.".format(lang.code))
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lang.start_pages = ['Main_Page']
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if not hasattr(lang, 'wikipedia_code') or lang.wikipedia_code is None:
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lang.wikipedia_code = lang.code
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if not hasattr(lang, 'clean_wikipedia_content') or lang.clean_wikipedia_content is None:
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lang.clean_wikipedia_content = None
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if hasattr(lang, 'case_mapping'):
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lang.case_mapping = bool(lang.case_mapping)
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else:
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lang.case_mapping = False
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if not hasattr(lang, 'alphabet') or lang.alphabet is None:
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lang.alphabet = None
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if lang.alphabet is not None:
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if lang.use_ascii:
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lang.alphabet += [chr(l) for l in range(65, 91)] + [chr(l) for l in range(97, 123)]
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if lang.case_mapping:
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lang.alphabet = list(set([ l.lower() for l in lang.alphabet ]))
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lang.alphabet = list(set(lang.alphabet))
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# Starting processing.
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wikipedia.set_lang(lang.wikipedia_code)
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visited_pages = []
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# The full list of letter characters.
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# The key is the unicode codepoint,
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# and the value is the occurrence count.
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characters = {}
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# Sequence of letters.
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# The key is the couple (char1, char2) in unicode codepoint,
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# the value is the occurrence count.
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sequences = {}
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prev_char = None
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def process_text(text, clean_text, case_mapping):
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global charsets
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global characters
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global sequences
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global prev_char
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if clean_text is not None:
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content = clean_text(text)
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# Clean multiple spaces. Newlines and such are normalized to spaces,
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# since they have basically a similar role in the purpose of uchardet.
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content = re.sub(r'\s+', ' ', content)
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if case_mapping:
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content = content.lower()
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# In python 3, strings are UTF-8.
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# Looping through them return expected characters.
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for char in content:
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is_letter = False
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if ord(char) in characters:
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characters[ord(char)] += 1
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is_letter = True
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else:
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# We save the character if it is at least in one of the
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# language encodings and its not a special character.
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for charset in charsets:
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# Does the character exist in the charset?
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codepoint = char.encode(charset, 'ignore')
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if codepoint == b'':
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continue
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# ord() is said to return the unicode codepoint.
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# But it turns out it also gives the codepoint for other
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# charsets if I turn the string to encoded bytes first.
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# Not sure if that is a bug or expected.
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codepoint = ord(codepoint)
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if charsets[charset].charmap[codepoint] == LET:
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characters[ord(char)] = 1
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is_letter = True
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break
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if is_letter:
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if prev_char is not None:
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if (prev_char, ord(char)) in sequences:
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sequences[(prev_char, ord(char))] += 1
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else:
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sequences[(prev_char, ord(char))] = 1
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prev_char = ord(char)
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else:
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prev_char = None
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def visit_pages(titles, depth, lang, logfd):
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global visited_pages
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global options
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if len(titles) == 0:
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return
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next_titles = []
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for title in titles:
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if options.max_page is not None and \
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len(visited_pages) > options.max_page:
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return
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if title in visited_pages:
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continue
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visited_pages += [title]
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try:
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page = wikipedia.page(title)
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except (wikipedia.exceptions.PageError,
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wikipedia.exceptions.DisambiguationError):
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# Let's just discard a page when I get an exception.
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continue
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logfd.write("\n{} (revision {})".format(title, page.revision_id))
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process_text(page.content,
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lang.clean_wikipedia_content,
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lang.case_mapping)
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next_titles += page.links
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if depth >= options.max_depth:
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return
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visit_pages (next_titles, depth + 1, lang, logfd)
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build_log = current_dir + '/BuildLangModelLogs/LangFrenchModel.log'
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logfd = open(build_log, 'w')
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logfd.write('= Logs of language model for {} ({}) =\n'.format(lang.name, lang.code))
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logfd.write('\n- Generated by {}'.format(os.path.basename(__file__)))
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logfd.write('\n- Started: {}'.format(str(datetime.datetime.now())))
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logfd.write('\n- Maximum depth: {}'.format(options.max_depth))
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if options.max_page is not None:
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logfd.write('\n- Max number of pages: {}'.format(options.max_page))
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logfd.write('\n\n== Parsed pages ==\n')
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try:
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visit_pages(lang.start_pages, 0, lang, logfd)
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except requests.exceptions.ConnectionError:
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print('Error: connection to Wikipedia failed. Aborting\n')
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exit(1)
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logfd.write('\n\n== End of Parsed pages ==')
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logfd.write('\n\n- Wikipedia parsing ended at: {}\n'.format(str(datetime.datetime.now())))
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########### CHARACTERS ###########
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# Character ratios.
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ratios = {}
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n_char = len(characters)
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occurrences = sum(characters.values())
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logfd.write("\n{} characters appeared {} times.\n".format(n_char, occurrences))
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for char in characters:
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ratios[char] = characters[char] / occurrences
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#logfd.write("Character '{}' usage: {} ({} %)\n".format(chr(char),
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# characters[char],
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# ratios[char] * 100))
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sorted_ratios = sorted(ratios.items(), key=operator.itemgetter(1),
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reverse=True)
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# Accumulated ratios of the frequent chars.
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accumulated_ratios = 0
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# If there is no alphabet defined, we just use the first 64 letters, which was
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# the original default.
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# If there is an alphabet, we make sure all the alphabet characters are in the
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# frequent list, and we stop then. There may therefore be more or less than
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# 64 frequent characters depending on the language.
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if lang.alphabet is None:
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freq_count = 64
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else:
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freq_count = 0
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for order, (char, ratio) in enumerate(sorted_ratios):
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if len(lang.alphabet) == 0:
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break
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if chr(char) in lang.alphabet:
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lang.alphabet.remove(chr(char))
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freq_count += 1
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else:
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if len(lang.alphabet) > 0:
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print("Error: alphabet characters are absent from data collection"
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"\n Please check the configuration or the data."
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"\n Missing characters: {}".format(", ".join(lang.alphabet)))
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exit(1)
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logfd.write('\nFirst {} characters:'.format(freq_count))
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for order, (char, ratio) in enumerate(sorted_ratios):
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if order >= freq_count:
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break
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logfd.write("\n[{:2}] Char {}: {} %".format(order, chr(char), ratio * 100))
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accumulated_ratios += ratio
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logfd.write("\n\nThe first {} characters have an accumulated ratio of {}.\n".format(freq_count, accumulated_ratios))
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with open(current_dir + '/header-template.cpp', 'r') as header_fd:
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c_code = header_fd.read()
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c_code += '\n/********* Language model for: {} *********/\n\n'.format(lang.name)
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c_code += '/**\n * Generated by {}\n'.format(os.path.basename(__file__))
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c_code += ' * On: {}\n'.format(str(datetime.datetime.now()))
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c_code += ' **/\n'
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c_code += \
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"""
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/* Character Mapping Table:
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* ILL: illegal character.
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* CTR: control character specific to the charset.
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* RET: carriage/return.
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* SYM: symbol (punctuation) that does not belong to word.
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* NUM: 0 - 9.
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*
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* Other characters are ordered by probabilities
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* (0 is the most common character in the language).
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*
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* Orders are generic to a language. So the codepoint with order X in
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* CHARSET1 maps to the same character as the codepoint with the same
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* order X in CHARSET2 for the same language.
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* As such, it is possible to get missing order. For instance the
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* ligature of 'o' and 'e' exists in ISO-8859-15 but not in ISO-8859-1
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* even though they are both used for French. Same for the euro sign.
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*/
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"""
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for charset in charsets:
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charset_c = charset.replace('-', '_').title()
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CTOM_str = 'static const unsigned char {}_CharToOrderMap[]'.format(charset_c)
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CTOM_str += ' =\n{'
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for line in range(0, 16):
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CTOM_str += '\n '
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for column in range(0, 16):
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cp = line * 16 + column
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cp_type = charsets[charset].charmap[cp]
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if cp_type == ILL:
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CTOM_str += 'ILL,'
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elif cp_type == RET:
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CTOM_str += 'RET,'
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elif cp_type == CTR:
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CTOM_str += 'CTR,'
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elif cp_type == SYM:
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CTOM_str += 'SYM,'
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elif cp_type == NUM:
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CTOM_str += 'NUM,'
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else: # LET
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uchar = bytes([cp]).decode(charset)
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if lang.case_mapping and uchar.isupper():
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uchar = uchar.lower()
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for order, (char, ratio) in enumerate(sorted_ratios):
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if char == ord(uchar):
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CTOM_str += '{:3},'.format(order)
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break
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else:
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CTOM_str += '{:3},'.format(n_char)
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n_char += 1
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CTOM_str += ' /* {:X}X */'.format(line)
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CTOM_str += '\n};\n/*'
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CTOM_str += 'X0 X1 X2 X3 X4 X5 X6 X7 X8 X9 XA XB XC XD XE XF'
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CTOM_str += ' */\n\n'
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c_code += CTOM_str
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########### SEQUENCES ###########
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ratios = {}
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occurrences = sum(sequences.values())
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ratio_512 = 0
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ratio_1024 = 0
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sorted_seqs = sorted(sequences.items(), key=operator.itemgetter(1),
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reverse=True)
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for order, ((c1, c2), count) in enumerate(sorted_seqs):
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if order < 512:
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ratio_512 += count
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elif order < 1024:
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ratio_1024 += count
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else:
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break
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ratio_512 /= occurrences
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ratio_1024 /= occurrences
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logfd.write("\n{} sequences found.\n".format(len(sorted_seqs)))
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c_code += """
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/* Model Table:
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* Total sequences: {}
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* First 512 sequences: {}
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* Next 512 sequences (512-1024): {}
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* Rest: {}
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* Negative sequences: TODO""".format(len(sorted_seqs),
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ratio_512,
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ratio_1024,
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1 - ratio_512 - ratio_1024)
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logfd.write("\nFirst 512 (typical positive ratio): {}".format(ratio_512))
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logfd.write("\nNext 512 (512-1024): {}".format(ratio))
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logfd.write("\nRest: {}".format(1 - ratio_512 - ratio_1024))
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c_code += "\n */\n"
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language_c = lang.name.replace('-', '_').title()
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LM_str = 'static const PRUint8 {}LangModel[]'.format(language_c)
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LM_str += ' =\n{'
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for line in range(0, freq_count):
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LM_str += '\n '
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for column in range(0, freq_count):
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# Let's not make too long lines.
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if freq_count > 40 and column == int(freq_count / 2):
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LM_str += '\n '
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first_order = int(line)
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second_order = column
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if first_order < len(sorted_ratios) and second_order < len(sorted_ratios):
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(first_char, _) = sorted_ratios[first_order]
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(second_char, _) = sorted_ratios[second_order]
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if (first_char, second_char) in sequences:
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for order, (seq, _) in enumerate(sorted_seqs):
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if seq == (first_char, second_char):
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if order < 512:
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LM_str += '3,'
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elif order < 1024:
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LM_str += '2,'
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else:
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LM_str += '1,'
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break
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else:
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pass # impossible!
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LM_str += '0,'
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else:
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LM_str += '0,'
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else:
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# It may indeed happen that we find less than 64 letters used for a
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# given language.
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LM_str += '0,'
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LM_str += '\n};\n'
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c_code += LM_str
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for charset in charsets:
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charset_c = charset.replace('-', '_').title()
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SM_str = '\n\nconst SequenceModel {}{}Model ='.format(charset_c, language_c)
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SM_str += '\n{\n '
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SM_str += '{}_CharToOrderMap,\n {}LangModel,'.format(charset_c, language_c)
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SM_str += '\n {},'.format(freq_count)
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SM_str += '\n (float){},'.format(ratio_512)
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SM_str += '\n {},'.format('PR_TRUE' if lang.use_ascii else 'PR_FALSE')
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SM_str += '\n "{}"'.format(charset)
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SM_str += '\n};'
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c_code += SM_str
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lang_model_file = current_dir + '/../src/LangModels/LangFrenchModel.cpp'
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with open(lang_model_file, 'w') as cpp_fd:
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cpp_fd.write(c_code)
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logfd.write('\n\n- Processing end: {}\n'.format(str(datetime.datetime.now())))
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logfd.close()
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print("The following language model file has been generated: {}"
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"\nThe build log is available in: {}"
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"\nTest them and commit them.".format(lang_model_file, build_log))
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