"""
This module aims to provide facilities for accessing some examples of mtsamples files
available on this repository: https://github.com/neurazlab/mtsamplesFR
Refer to the repository for more information.
This repository contains:
* **a version of mtsamples.csv**
Source: https://www.kaggle.com/datasets/tboyle10/medicaltranscriptions
license: CC0: Public Domain
* **a mtsamples_translation.json file which is a translation to french**
Date: 08/04/2022
"""
__all__ = ["load_mtsamples", "convert_mtsamples_to_medkit"]
import csv
import json
import urllib.request
from pathlib import Path
from typing import List, Optional, Union
from medkit.core.text import TextDocument
from medkit.io.medkit_json import save_text_documents
_REPO_URL: str = "https://raw.githubusercontent.com/aneuraz/mtsamplesFR/master/data/"
_MTSAMPLES_FILE: str = "mtsamples.csv"
_MTSAMPLES_TRANSLATED_FILE: str = "mtsamples_translated.json"
[docs]def load_mtsamples(
cache_dir: Union[Path, str] = ".cache",
translated: bool = True,
nb_max: Optional[int] = None,
) -> List[TextDocument]:
"""
Function loading mtsamples data into medkit text documents
Parameters
----------
cache_dir
Directory where to store mtsamples file. Default: .cache
translated
If True (default), `mtsamples_translated.json` file is used (FR).
If False, `mtsamples.csv` is used (EN)
nb_max
Maximum number of documents to load
Returns
-------
List[TextDocument]
The medkit text documents corresponding to mtsamples data
"""
if translated:
mtsamples_url = _REPO_URL + _MTSAMPLES_TRANSLATED_FILE
cache_file = Path(cache_dir) / Path(_MTSAMPLES_TRANSLATED_FILE)
else:
mtsamples_url = _REPO_URL + _MTSAMPLES_FILE
cache_file = Path(cache_dir) / Path(_MTSAMPLES_FILE)
if not cache_file.exists():
cache_file.parent.mkdir(exist_ok=True, parents=True)
urllib.request.urlretrieve(
mtsamples_url,
cache_file,
)
with open(cache_file) as f:
if translated:
mtsamples = json.load(f)
else:
mtsamples = csv.DictReader(f)
if nb_max is not None:
mtsamples = mtsamples[:nb_max]
return [
TextDocument(
text=(
sample["transcription_translated"]
if translated
else sample["transcription"]
),
metadata=dict(
id=sample["id"] if translated else sample[""],
description=sample["description"],
medical_specialty=sample["medical_specialty"],
sample_name=sample["sample_name"],
keywords=sample["keywords"],
),
)
for sample in mtsamples
]
[docs]def convert_mtsamples_to_medkit(
output_file: Union[Path, str],
encoding: Optional[str] = "utf-8",
cache_dir: Union[Path, str] = ".cache",
translated: bool = True,
):
"""
Convert mtsamples data into a medkit file
Parameters
----------
output_file
Path to the medkit jsonl file to generate
encoding
Encoding of the medkit file to generate
cache_dir
Directory where mtsamples file is cached. Default: .cache
translated
If True (default), `mtsamples_translated.json` file is used (FR).
If False, `mtsamples.csv` is used (EN)
"""
docs = load_mtsamples(cache_dir, translated)
save_text_documents(docs=docs, output_file=output_file, encoding=encoding)
