spaCy/spacy/cli/convert.py
2018-08-14 14:04:32 +02:00

52 lines
1.9 KiB
Python

# coding: utf8
from __future__ import unicode_literals
import plac
from pathlib import Path
from .converters import conllu2json, conllubio2json, iob2json, conll_ner2json
from .converters import ner_jsonl2json
from ._messages import Messages
from ..util import prints
# Converters are matched by file extension. To add a converter, add a new
# entry to this dict with the file extension mapped to the converter function
# imported from /converters.
CONVERTERS = {
'conllubio': conllubio2json,
'conllu': conllu2json,
'conll': conllu2json,
'ner': conll_ner2json,
'iob': iob2json,
'jsonl': ner_jsonl2json
}
@plac.annotations(
input_file=("input file", "positional", None, str),
output_dir=("output directory for converted file", "positional", None, str),
n_sents=("Number of sentences per doc", "option", "n", int),
converter=("Name of converter (auto, iob, conllu or ner)", "option", "c", str),
lang=("Language (if tokenizer required)", "option", "l", str),
morphology=("Enable appending morphology to tags", "flag", "m", bool))
def convert(input_file, output_dir, n_sents=1, morphology=False, converter='auto',
lang=None):
"""
Convert files into JSON format for use with train command and other
experiment management functions.
"""
input_path = Path(input_file)
output_path = Path(output_dir)
if not input_path.exists():
prints(input_path, title=Messages.M028, exits=1)
if not output_path.exists():
prints(output_path, title=Messages.M029, exits=1)
if converter == 'auto':
converter = input_path.suffix[1:]
if converter not in CONVERTERS:
prints(Messages.M031.format(converter=converter),
title=Messages.M030, exits=1)
func = CONVERTERS[converter]
func(input_path, output_path,
n_sents=n_sents, use_morphology=morphology, lang=lang)