load_import.py
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# -*- coding: utf-8 -*-
import json
from django.db.models import Max
from django.core.management.base import BaseCommand
from django.db.transaction import atomic
from common.util import no_history, debug, uniopen
from dictionary.models import Lexeme, Inflection, PartOfSpeech, Vocabulary, \
InflectionCharacteristic, CrossReference, CrossReferenceType, \
ClassificationValue
from patterns.models import Pattern
START_ID = 500000
END_ID = 1000000
next_id = Lexeme.objects.filter(
pk__gte=START_ID, pk__lt=END_ID).aggregate(Max('id'))['id__max']
next_id = next_id + 1 if next_id else START_ID
class Command(BaseCommand):
args = '<nazwa pliku wejściowego> <nazwa słownika> <nazwa źródła>'
help = 'Load prepared lexeme data'
def handle(self, input_file, vocab_name, source, **options):
raise Exception('stale code')
#load_morfologik(input_file, vocab_name, source)
source = None
vocab = None # brzydko, ale nie chce mi się przerabiać wszystkiego
parts_of_speech = PartOfSpeech.objects.all()
pos_table = {}
for part_of_speech in parts_of_speech:
pos_table[part_of_speech.symbol] = part_of_speech
ic_list = InflectionCharacteristic.objects.all()
ic_table = {}
for ic in ic_list:
ic_table[(ic.symbol, ic.part_of_speech.symbol)] = ic
pattern_list = Pattern.objects.all()
pattern_table = {}
for p in pattern_list:
pattern_table[p.name] = p
def associate(l):
created = vocab.add_lexeme(l)
if not created and l.part_of_speech.symbol not in ('ppas', 'pact', 'ger'):
debug(l.entry, u'wielokrotne przypisanie leksemu do słownika!')
def add_cr(l_from, l_to, symbol):
cr_type = CrossReferenceType.objects.get(
symbol=symbol, from_pos=l_from.part_of_speech,
to_pos=l_to.part_of_speech)
CrossReference(from_lexeme=l_from, to_lexeme=l_to, type=cr_type).save()
def create_lexeme(entry, part_of_speech, status, comment, commonness=None):
global next_id
l = Lexeme.objects.create(
id=next_id, entry=entry, part_of_speech=part_of_speech,
source=source, status=status, comment=comment,
owner_vocabulary=vocab)
l.fix_homonym_number()
if commonness:
ClassificationValue.objects.get(label=commonness).add_lexeme(l)
associate(l)
next_id += 1
return l
def create_negated(l):
lneg = create_lexeme(
u"nie" + l.entry, l.part_of_speech,
"cand" if l.status == "cand" else "desc", '')
for lip in l.inflection_set.all():
if lip.inflection_characteristic.symbol != "0-":
ic = ic_table[("0-", "adj")]
else:
ic = lip.inflection_characteristic
Inflection(lexeme=lneg, index=lip.index,
pattern=lip.pattern, root=u"nie" + lip.root,
inflection_characteristic=ic).save()
add_cr(l, lneg, "adjnie")
add_cr(lneg, l, "nieadj")
def check_der(verb, pos, entry, patterns):
lips = verb.inflection_set.all()
if not lips:
return None
ic = lips[0].inflection_characteristic.symbol
matched = []
for l in Lexeme.objects.filter(
entry=entry, part_of_speech__symbol=pos,
inflection__inflection_characteristic__symbol=ic):
l_lips = l.inflection_set.all()
if l_lips[0].inflection_characteristic.symbol == ic:
l_patterns = set(l.patterns.values_list('name', flat=True))
if l_patterns == set(patterns):
matched.append(l)
if len(matched) > 1:
debug(entry, u'niejednoznaczny derywat')
if len(matched) > 0:
return matched[0]
else:
return None
def create_derived(l, pos, entry, patterns):
old_der = check_der(l, pos, entry, patterns)
if old_der:
if vocab not in old_der.vocabularies.all():
associate(old_der)
lder = old_der
else:
lder = create_lexeme(entry, pos_table[pos], l.status, u'')
for lip in l.inflection_set.all():
if lip.pattern.name in patterns:
ic = lip.inflection_characteristic.symbol.lstrip("q")
Inflection(lexeme=lder, index=lip.index,
pattern=lip.pattern, root=lip.root,
inflection_characteristic=ic_table[
(ic, pos)]).save()
add_cr(l, lder, "ver" + pos)
add_cr(lder, l, pos + "ver")
@atomic
def load_morfologik(filename, vocab_name, source_):
global vocab, source
vocab = Vocabulary.objects.get(id=vocab_name)
source = source_
no_history()
for line in uniopen(filename):
data = json.loads(line)
if data['lexeme']['source'] == 'sgjp':
l = Lexeme.objects.get(pk=data['lexeme']['id'])
associate(l)
elif data['lexeme']['source'] == 'morfologik':
l_data = data['lexeme']
l = create_lexeme(l_data['entry'],
pos_table[l_data['part_of_speech']],
l_data['status'], l_data['comment'],
l_data.get('commonness'))
for lip_data in data['lips']:
pattern = pattern_table[lip_data['pattern']]
ic = ic_table[tuple(lip_data['ic'])]
if lip_data['root']['type'] == 'string':
root = lip_data['root']['root']
elif lip_data['root']['type'] == 'compute':
root = l.get_root(pattern, ic)
Inflection(lexeme=l, index=lip_data['ind'],
pattern=pattern, root=root,
inflection_characteristic=ic).save()
if 'derived' in data:
for pos, entry, patterns in data['derived']:
create_derived(l, pos, entry, patterns)
if 'negated' in data:
create_negated(l)