spaCy/spacy/cli/convert.py

130 lines
4.9 KiB
Python

from pathlib import Path
from wasabi import Printer
import srsly
import re
from .converters import conllu2json, iob2json, conll_ner2json
from .converters import ner_jsonl2json
# Converters are matched by file extension except for ner/iob, which are
# matched by file extension and content. 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": conllu2json,
"conllu": conllu2json,
"conll": conllu2json,
"ner": conll_ner2json,
"iob": iob2json,
"jsonl": ner_jsonl2json,
}
# File types
FILE_TYPES = ("json", "jsonl", "msg")
FILE_TYPES_STDOUT = ("json", "jsonl")
def convert(
# fmt: off
input_file: ("Input file", "positional", None, str),
output_dir: ("Output directory. '-' for stdout.", "positional", None, str) = "-",
file_type: (f"Type of data to produce: {FILE_TYPES}", "option", "t", str, FILE_TYPES) = "json",
n_sents: ("Number of sentences per doc (0 to disable)", "option", "n", int) = 1,
seg_sents: ("Segment sentences (for -c ner)", "flag", "s") = False,
model: ("Model for sentence segmentation (for -s)", "option", "b", str) = None,
morphology: ("Enable appending morphology to tags", "flag", "m", bool) = False,
converter: (f"Converter: {tuple(CONVERTERS.keys())}", "option", "c", str) = "auto",
ner_map_path: ("NER tag mapping (as JSON-encoded dict of entity types)", "option", "N", Path) = None,
lang: ("Language (if tokenizer required)", "option", "l", str) = None,
# fmt: on
):
"""
Convert files into JSON format for use with train command and other
experiment management functions. If no output_dir is specified, the data
is written to stdout, so you can pipe them forward to a JSON file:
$ spacy convert some_file.conllu > some_file.json
"""
no_print = output_dir == "-"
msg = Printer(no_print=no_print)
input_path = Path(input_file)
if file_type not in FILE_TYPES_STDOUT and output_dir == "-":
# TODO: support msgpack via stdout in srsly?
msg.fail(
f"Can't write .{file_type} data to stdout",
"Please specify an output directory.",
exits=1,
)
if not input_path.exists():
msg.fail("Input file not found", input_path, exits=1)
if output_dir != "-" and not Path(output_dir).exists():
msg.fail("Output directory not found", output_dir, exits=1)
input_data = input_path.open("r", encoding="utf-8").read()
if converter == "auto":
converter = input_path.suffix[1:]
if converter == "ner" or converter == "iob":
converter_autodetect = autodetect_ner_format(input_data)
if converter_autodetect == "ner":
msg.info("Auto-detected token-per-line NER format")
converter = converter_autodetect
elif converter_autodetect == "iob":
msg.info("Auto-detected sentence-per-line NER format")
converter = converter_autodetect
else:
msg.warn(
"Can't automatically detect NER format. Conversion may not succeed. See https://spacy.io/api/cli#convert"
)
if converter not in CONVERTERS:
msg.fail(f"Can't find converter for {converter}", exits=1)
ner_map = None
if ner_map_path is not None:
ner_map = srsly.read_json(ner_map_path)
# Use converter function to convert data
func = CONVERTERS[converter]
data = func(
input_data,
n_sents=n_sents,
seg_sents=seg_sents,
use_morphology=morphology,
lang=lang,
model=model,
no_print=no_print,
ner_map=ner_map,
)
if output_dir != "-":
# Export data to a file
suffix = f".{file_type}"
output_file = Path(output_dir) / Path(input_path.parts[-1]).with_suffix(suffix)
if file_type == "json":
srsly.write_json(output_file, data)
elif file_type == "jsonl":
srsly.write_jsonl(output_file, data)
elif file_type == "msg":
srsly.write_msgpack(output_file, data)
msg.good(f"Generated output file ({len(data)} documents): {output_file}")
else:
# Print to stdout
if file_type == "json":
srsly.write_json("-", data)
elif file_type == "jsonl":
srsly.write_jsonl("-", data)
def autodetect_ner_format(input_data):
# guess format from the first 20 lines
lines = input_data.split("\n")[:20]
format_guesses = {"ner": 0, "iob": 0}
iob_re = re.compile(r"\S+\|(O|[IB]-\S+)")
ner_re = re.compile(r"\S+\s+(O|[IB]-\S+)$")
for line in lines:
line = line.strip()
if iob_re.search(line):
format_guesses["iob"] += 1
if ner_re.search(line):
format_guesses["ner"] += 1
if format_guesses["iob"] == 0 and format_guesses["ner"] > 0:
return "ner"
if format_guesses["ner"] == 0 and format_guesses["iob"] > 0:
return "iob"
return None