243 lines
9.9 KiB
Python
243 lines
9.9 KiB
Python
import json
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import xml.etree.ElementTree as ET
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from langcodes.util import data_filename
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from langcodes.registry_parser import parse_registry
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def read_cldr_supplemental(dataname):
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cldr_supp_path = data_filename('cldr-json/cldr-json/cldr-core/supplemental')
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filename = data_filename(f'{cldr_supp_path}/{dataname}.json')
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fulldata = json.load(open(filename, encoding='utf-8'))
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if dataname == 'aliases':
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data = fulldata['supplemental']['metadata']['alias']
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else:
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data = fulldata['supplemental'][dataname]
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return data
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def read_iana_registry_suppress_scripts():
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scripts = {}
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for entry in parse_registry():
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if entry['Type'] == 'language' and 'Suppress-Script' in entry:
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scripts[entry['Subtag']] = entry['Suppress-Script']
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return scripts
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def read_iana_registry_scripts():
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scripts = set()
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for entry in parse_registry():
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if entry['Type'] == 'script':
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scripts.add(entry['Subtag'])
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return scripts
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def read_iana_registry_macrolanguages():
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macros = {}
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for entry in parse_registry():
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if entry['Type'] == 'language' and 'Macrolanguage' in entry:
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macros[entry['Subtag']] = entry['Macrolanguage']
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return macros
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def read_iana_registry_replacements():
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replacements = {}
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for entry in parse_registry():
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if entry['Type'] == 'language' and 'Preferred-Value' in entry:
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# Replacements for language codes
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replacements[entry['Subtag']] = entry['Preferred-Value']
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elif 'Tag' in entry and 'Preferred-Value' in entry:
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# Replacements for entire tags
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replacements[entry['Tag'].lower()] = entry['Preferred-Value']
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return replacements
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def write_python_dict(outfile, name, d):
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print(f"{name} = {{", file=outfile)
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for key in sorted(d):
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value = d[key]
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print(f" {key!r}: {value!r},", file=outfile)
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print("}", file=outfile)
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def write_python_set(outfile, name, s):
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print(f"{name} = {{", file=outfile)
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for key in sorted(set(s)):
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print(f" {key!r},", file=outfile)
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print("}", file=outfile)
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GENERATED_HEADER = "# This file is generated by build_data.py."
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def read_validity_regex():
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validity_options = []
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for codetype in ('language', 'region', 'script', 'variant'):
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validity_path = data_filename(f'cldr/common/validity/{codetype}.xml')
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root = ET.fromstring(open(validity_path).read())
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matches = root.findall('./idValidity/id')
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for match in matches:
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for item in match.text.strip().split():
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if '~' in item:
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assert item[-2] == '~'
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prefix = item[:-3]
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range_start = item[-3]
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range_end = item[-1]
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option = f"{prefix}[{range_start}-{range_end}]"
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validity_options.append(option)
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else:
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validity_options.append(item)
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options = '|'.join(validity_options)
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return f'^({options})$'
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def read_language_distances():
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language_info_path = data_filename('cldr/common/supplemental/languageInfo.xml')
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root = ET.fromstring(open(language_info_path).read())
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matches = root.findall(
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'./languageMatching/languageMatches[@type="written_new"]/languageMatch'
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)
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tag_distances = {}
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for match in matches:
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attribs = match.attrib
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n_parts = attribs['desired'].count('_') + 1
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if n_parts < 3:
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if attribs.get('oneway') == 'true':
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pairs = [(attribs['desired'], attribs['supported'])]
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else:
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pairs = [
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(attribs['desired'], attribs['supported']),
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(attribs['supported'], attribs['desired']),
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]
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for (desired, supported) in pairs:
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desired_distance = tag_distances.setdefault(desired, {})
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desired_distance[supported] = int(attribs['distance'])
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# The 'languageInfo' data file contains distances for the unnormalized
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# tag 'sh', but we work mostly with normalized tags, and they don't
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# describe at all how to cope with this.
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#
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# 'sh' normalizes to 'sr-Latn', and when we're matching languages we
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# aren't matching scripts yet, so when 'sh' appears we'll add a
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# corresponding match for 'sr'.
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#
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# Then because we're kind of making this plan up, add 1 to the distance
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# so it's a worse match than ones that are actually clearly defined
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# in languageInfo.
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if desired == 'sh' or supported == 'sh':
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if desired == 'sh':
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desired = 'sr'
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if supported == 'sh':
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supported = 'sr'
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if desired != supported:
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# don't try to define a non-zero distance for sr <=> sr
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desired_distance = tag_distances.setdefault(desired, {})
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desired_distance[supported] = int(attribs['distance']) + 1
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return tag_distances
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def build_data():
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lang_scripts = read_iana_registry_suppress_scripts()
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all_scripts = read_iana_registry_scripts()
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macrolanguages = read_iana_registry_macrolanguages()
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iana_replacements = read_iana_registry_replacements()
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language_distances = read_language_distances()
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alias_data = read_cldr_supplemental('aliases')
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likely_subtags = read_cldr_supplemental('likelySubtags')
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replacements = {}
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# Aliased codes can still have alpha3 codes, and there's no unified source
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# about what they are. It depends on whether the alias predates or postdates
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# ISO 639-2, which nobody should have to care about. So let's set all the
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# alpha3 codes for aliased alpha2 codes here.
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alpha3_mapping = {
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'tl': 'tgl', # even though it normalizes to 'fil'
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'in': 'ind',
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'iw': 'heb',
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'ji': 'yid',
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'jw': 'jav',
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'sh': 'hbs',
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}
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alpha3_biblio = {}
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norm_macrolanguages = {}
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for alias_type in ['languageAlias', 'scriptAlias', 'territoryAlias']:
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aliases = alias_data[alias_type]
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# Initially populate 'languageAlias' with the aliases from the IANA file
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if alias_type == 'languageAlias':
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replacements[alias_type] = iana_replacements
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replacements[alias_type]['root'] = 'und'
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else:
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replacements[alias_type] = {}
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for code, value in aliases.items():
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# Make all keys lowercase so they can be looked up
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# case-insensitively
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code = code.lower()
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# If there are multiple replacements, take the first one. For example,
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# we just replace the Soviet Union (SU) with Russia (RU), instead of
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# trying to do something context-sensitive and poorly standardized
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# that selects one of the successor countries to the Soviet Union.
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replacement = value['_replacement'].split()[0]
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if value['_reason'] == 'macrolanguage':
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norm_macrolanguages[code] = replacement
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else:
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# CLDR tries to oversimplify some codes as it assigns aliases.
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# For example, 'nor' is the ISO alpha3 code for 'no', but CLDR
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# would prefer you use 'nb' over 'no', so it makes 'nor' an
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# alias of 'nb'. But 'nb' already has an alpha3 code, 'nob'.
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#
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# We undo this oversimplification so that we can get a
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# canonical mapping between alpha2 and alpha3 codes.
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if code == 'nor':
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replacement = 'no'
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elif code == 'mol':
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replacement = 'mo'
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elif code == 'twi':
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replacement = 'tw'
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elif code == 'bih':
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replacement = 'bh'
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replacements[alias_type][code] = replacement
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if alias_type == 'languageAlias':
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if value['_reason'] == 'overlong':
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if replacement in alpha3_mapping:
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raise ValueError(
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"{code!r} is an alpha3 for {replacement!r}, which"
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" already has an alpha3: {orig!r}".format(
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code=code,
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replacement=replacement,
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orig=alpha3_mapping[replacement],
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)
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)
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alpha3_mapping[replacement] = code
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elif value['_reason'] == 'bibliographic':
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alpha3_biblio[replacement] = code
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validity_regex = read_validity_regex()
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# Write the contents of data_dicts.py.
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with open('data_dicts.py', 'w', encoding='utf-8') as outfile:
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print(GENERATED_HEADER, file=outfile)
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print("import re\n", file=outfile)
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write_python_dict(outfile, 'DEFAULT_SCRIPTS', lang_scripts)
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write_python_dict(
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outfile, 'LANGUAGE_REPLACEMENTS', replacements['languageAlias']
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)
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write_python_dict(outfile, 'LANGUAGE_ALPHA3', alpha3_mapping)
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write_python_dict(outfile, 'LANGUAGE_ALPHA3_BIBLIOGRAPHIC', alpha3_biblio)
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write_python_dict(outfile, 'SCRIPT_REPLACEMENTS', replacements['scriptAlias'])
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write_python_set(outfile, 'ALL_SCRIPTS', all_scripts)
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write_python_dict(
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outfile, 'TERRITORY_REPLACEMENTS', replacements['territoryAlias']
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)
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write_python_dict(outfile, 'MACROLANGUAGES', macrolanguages)
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write_python_dict(outfile, 'NORMALIZED_MACROLANGUAGES', norm_macrolanguages)
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write_python_dict(outfile, 'LIKELY_SUBTAGS', likely_subtags)
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write_python_dict(outfile, 'LANGUAGE_DISTANCES', language_distances)
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print(f"VALIDITY = re.compile({validity_regex!r})", file=outfile)
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if __name__ == '__main__':
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build_data()
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