def main():
parser = argparse.ArgumentParser(
description='Look up japanese words via EDict.')
parser.add_argument('words',
nargs='*',
help='Words to attempt stemming on')
args = parser.parse_args()
edict_path = os.path.join(os.path.dirname(os.path.abspath(__file__)),
'JMdict_e.gz')
dictionary = etree.parse(edict_path)
for word in args.words:
#best practice: to decode early, encode late
word = word.decode('utf-8')
hiragana = romaji2hiragana(word)
results = lookup(hiragana, dictionary)
if not results:
print(u'No initial results found for query {q}'.format(q=hiragana))
alternatives = guess_stem(hiragana)
if alternatives:
for alternative in alternatives:
alternate_results = lookup(alternative, dictionary)
if alternate_results:
print(u'Perhaps you meant {r}?'.format(r=alternative))
else:
print(u'No results or possible results found for query {q}'.
format(q=hiragana))
else:
for result in results:
format_entry(result)
def main():
parser = argparse.ArgumentParser(description='Look up japanese words via EDict.')
parser.add_argument('words', nargs='*', help='Words to attempt stemming on')
args = parser.parse_args()
edict_path = os.path.join(os.path.dirname(os.path.abspath(__file__)),'JMdict_e.gz')
dictionary = etree.parse(edict_path)
for word in args.words:
#best practice: to decode early, encode late
word = word.decode('utf-8')
hiragana = romaji2hiragana(word)
results = lookup(hiragana, dictionary)
if not results:
print(u'No initial results found for query {q}'.format(q=hiragana))
alternatives = guess_stem(hiragana)
if alternatives:
for alternative in alternatives:
alternate_results = lookup(alternative, dictionary)
if alternate_results:
print(u'Perhaps you meant {r}?'.format(r=alternative))
else:
print(u'No results or possible results found for query {q}'.format(q=hiragana))
else:
for result in results:
format_entry(result)
def guess_stem(word):
"""given single input word, try to discern japanese word stem
"""
#ensure input is a unicode string
if not isinstance(word, unicode):
raise NonUnicodeInputException(
'Input argument {word} is not unicode.'.format(word=word))
#1. input word should have no spaces
word = word.strip().lower()
#2b Convert filtered word to hiragana via romkan
hiragana = romaji2hiragana(word)
results = [hiragana]
#3: We've got a simple single word in hiragana. First test against adjectival endings
for tx in AdjectivalTransforms:
negative = tx.Negative(hiragana)
if negative: results.append(negative)
past = tx.Past(hiragana)
if past: results.append(past)
past = tx.Past(hiragana)
if past: results.append(past)
#4: No hits for adjetive stem, test against verbal endings
for tx in VerbalTransforms:
polite = tx.Polite(hiragana)
if polite: results.append(polite)
negative = tx.Negative(hiragana)
if negative: results.append(negative)
te = tx.Te(hiragana)
if te: results.append(te)
perfect = tx.Perfect(hiragana)
if perfect: results.append(perfect)
#5: Return input word and candidate stems as tuple, to do dictionary lookups on all.
#The best hit will be the longest(?) exact match of a suggested stem
return tuple(results)
def guess_stem(word):
"""given single input word, try to discern japanese word stem
"""
#ensure input is a unicode string
if not isinstance(word, unicode):
raise NonUnicodeInputException('Input argument {word} is not unicode.'.format(word=word))
#1. input word should have no spaces
word = word.strip().lower()
#2b Convert filtered word to hiragana via romkan
hiragana = romaji2hiragana(word)
results = [hiragana]
#3: We've got a simple single word in hiragana. First test against adjectival endings
for tx in AdjectivalTransforms:
negative = tx.Negative(hiragana)
if negative: results.append(negative)
past = tx.Past(hiragana)
if past: results.append(past)
past = tx.Past(hiragana)
if past: results.append(past)
#4: No hits for adjetive stem, test against verbal endings
for tx in VerbalTransforms:
polite = tx.Polite(hiragana)
if polite: results.append(polite)
negative = tx.Negative(hiragana)
if negative: results.append(negative)
te = tx.Te(hiragana)
if te: results.append(te)
perfect = tx.Perfect(hiragana)
if perfect: results.append(perfect)
#5: Return input word and candidate stems as tuple, to do dictionary lookups on all.
#The best hit will be the longest(?) exact match of a suggested stem
return tuple(results)
