def ngramgen(source, *cuttoff_info):
"""Generate n-grams with provided cuttoff"""
try:
fh = open(source, 'r', encoding='UTF-8')
except Exception:
print(f'File not found: {source}')
return
try:
cuttoff_info = map(int, cuttoff_info)
except ValueError:
print('Invalid cuttoff info provided, list of integers needed')
return
if len(list(cuttoff_info)) == 0:
print('Cuttoff info provided is zero length')
return
sent_idx = _cached_sentences_index(source)
fh.seek(0)
lines = (line for line in fh)
isents = text.iter_sentences(lines, sent_idx)
itokens = (t for t, s, tid in text.iter_tokens(isents))
res = ngramgenmod.multi_ngram(itokens, len(list(cuttoff_info)))
fh.close()
res = ngramgenmod.cutt_ngrams(res, cuttoff_info)
for dict_ in res:
for tpl, v in dict_.items():
print(f"{' '.join(tpl)} {unicode(v).encode('utf-8')}")
def ngramgen(source, *cuttoff_info):
"""Generate n-grams with provided cuttoff"""
try:
fh = open(source, 'r')
except Exception:
print 'File not found:', source
return
try:
cuttoff_info = map(int, cuttoff_info)
except ValueError:
print 'Invalid cuttoff info provided, list of integers needed'
return
if len(cuttoff_info) == 0:
print 'Cuttoff info provided is zero length'
return
sent_idx = _cached_sentences_index(source)
fh.seek(0)
lines = (line.decode('utf-8') for line in fh)
isents = text.iter_sentences(lines, sent_idx)
itokens = (t for t, s, tid in text.iter_tokens(isents))
res = ngramgenmod.multi_ngram(itokens, len(cuttoff_info))
fh.close()
res = ngramgenmod.cutt_ngrams(res, cuttoff_info)
for dict_ in res:
for tpl, v in dict_.iteritems():
print (' '.join(tpl) + ' ' + unicode(v)).encode('utf-8')
def _cached_vocab(filepath):
sig = _cache_sig(filepath)
try:
with open('%s/%s.vocab' % (_CACHE, sig), 'rb') as f:
vocab_bin = f.read()
except IOError:
sent_idx = _cached_sentences_index(filepath)
with open(filepath, 'r') as fh:
lines = (line.decode('utf-8') for line in fh)
vocab = text.vocabulary(text.iter_tokens(text.iter_sentences(lines, sent_idx)))
vocab_bin = compress(json.dumps(vocab))
with open('%s/%s.vocab' % (_CACHE, sig), 'wb') as f:
f.write(vocab_bin)
else:
vocab = json.loads(decompress(vocab_bin))
return vocab
def _cached_vocab(filepath):
sig = _cache_sig(filepath)
try:
with open('{_CACHE}/{sig}.vocab', 'rb') as f:
vocab_bin = f.read()
except IOError:
sent_idx = _cached_sentences_index(filepath)
with open(filepath, 'r') as fh:
lines = (line for line in fh)
vocab = text.vocabulary(
text.iter_tokens(text.iter_sentences(lines, sent_idx)))
vocab_bin = compress(json.dumps(vocab))
with open('{_CACHE}/{sig.vocab}', 'wb') as f:
f.write(vocab_bin)
else:
vocab = json.loads(decompress(vocab_bin))
return vocab
