mirror of
https://github.com/explosion/spaCy.git
synced 2025-11-04 09:57:26 +03:00
94 lines
2.7 KiB
Python
Executable File
94 lines
2.7 KiB
Python
Executable File
#!/usr/bin/env python
|
|
|
|
from __future__ import unicode_literals, print_function
|
|
|
|
import plac
|
|
import joblib
|
|
from os import path
|
|
import os
|
|
import bz2
|
|
import ujson
|
|
from preshed.counter import PreshCounter
|
|
from joblib import Parallel, delayed
|
|
import io
|
|
|
|
from spacy.en import English
|
|
from spacy.strings import StringStore
|
|
from spacy.attrs import ORTH
|
|
from spacy.tokenizer import Tokenizer
|
|
from spacy.vocab import Vocab
|
|
|
|
|
|
def iter_comments(loc):
|
|
with bz2.BZ2File(loc) as file_:
|
|
for line in file_:
|
|
yield ujson.loads(line)
|
|
|
|
|
|
def count_freqs(input_loc, output_loc):
|
|
print(output_loc)
|
|
vocab = English.default_vocab(get_lex_attr=None)
|
|
tokenizer = Tokenizer.from_dir(vocab,
|
|
path.join(English.default_data_dir(), 'tokenizer'))
|
|
|
|
counts = PreshCounter()
|
|
for json_comment in iter_comments(input_loc):
|
|
doc = tokenizer(json_comment['body'])
|
|
doc.count_by(ORTH, counts=counts)
|
|
|
|
with io.open(output_loc, 'w', 'utf8') as file_:
|
|
for orth, freq in counts:
|
|
string = tokenizer.vocab.strings[orth]
|
|
if not string.isspace():
|
|
file_.write('%d\t%s\n' % (freq, string))
|
|
|
|
|
|
def parallelize(func, iterator, n_jobs):
|
|
Parallel(n_jobs=n_jobs)(delayed(func)(*item) for item in iterator)
|
|
|
|
|
|
def merge_counts(locs, out_loc):
|
|
string_map = StringStore()
|
|
counts = PreshCounter()
|
|
for loc in locs:
|
|
with io.open(loc, 'r', encoding='utf8') as file_:
|
|
for line in file_:
|
|
freq, word = line.strip().split('\t', 1)
|
|
orth = string_map[word]
|
|
counts.inc(orth, int(freq))
|
|
with io.open(out_loc, 'w', encoding='utf8') as file_:
|
|
for orth, count in counts:
|
|
string = string_map[orth]
|
|
file_.write('%d\t%s\n' % (count, string))
|
|
|
|
|
|
@plac.annotations(
|
|
input_loc=("Location of input file list"),
|
|
freqs_dir=("Directory for frequency files"),
|
|
output_loc=("Location for output file"),
|
|
n_jobs=("Number of workers", "option", "n", int),
|
|
skip_existing=("Skip inputs where an output file exists", "flag", "s", bool),
|
|
)
|
|
def main(input_loc, freqs_dir, output_loc, n_jobs=2, skip_existing=False):
|
|
tasks = []
|
|
outputs = []
|
|
for input_path in open(input_loc):
|
|
input_path = input_path.strip()
|
|
if not input_path:
|
|
continue
|
|
filename = input_path.split('/')[-1]
|
|
output_path = path.join(freqs_dir, filename.replace('bz2', 'freq'))
|
|
outputs.append(output_path)
|
|
if not path.exists(output_path) or not skip_existing:
|
|
tasks.append((input_path, output_path))
|
|
|
|
if tasks:
|
|
parallelize(count_freqs, tasks, n_jobs)
|
|
|
|
print("Merge")
|
|
merge_counts(outputs, output_loc)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
plac.call(main)
|