spaCy/spacy/tests/training/test_corpus.py

import tempfile
from contextlib import contextmanager
from pathlib import Path
from typing import IO, Generator, Iterable, List, TextIO, Tuple

import pytest

from spacy.lang.en import English
from spacy.training import Example, PlainTextCorpus
from spacy.util import make_tempdir

# Intentional newlines to check that they are skipped.
PLAIN_TEXT_DOC = """

This is a doc. It contains two sentences.
This is another doc.

A third doc.

"""

PLAIN_TEXT_DOC_TOKENIZED = [
    [
        "This",
        "is",
        "a",
        "doc",
        ".",
        "It",
        "contains",
        "two",
        "sentences",
        ".",
    ],
    ["This", "is", "another", "doc", "."],
    ["A", "third", "doc", "."],
]


@pytest.mark.parametrize("min_length", [0, 5])
@pytest.mark.parametrize("max_length", [0, 5])
def test_plain_text_reader(min_length, max_length):
    nlp = English()
    with _string_to_tmp_file(PLAIN_TEXT_DOC) as file_path:
        corpus = PlainTextCorpus(
            file_path, min_length=min_length, max_length=max_length
        )

        check = [
            doc
            for doc in PLAIN_TEXT_DOC_TOKENIZED
            if len(doc) >= min_length and (max_length == 0 or len(doc) <= max_length)
        ]
        reference, predicted = _examples_to_tokens(corpus(nlp))

        assert reference == check
        assert predicted == check


@contextmanager
def _string_to_tmp_file(s: str) -> Generator[Path, None, None]:
    with make_tempdir() as d:
        file_path = Path(d) / "string.txt"
        with open(file_path, "w", encoding="utf-8") as f:
            f.write(s)
        yield file_path


def _examples_to_tokens(
    examples: Iterable[Example],
) -> Tuple[List[List[str]], List[List[str]]]:
    reference = []
    predicted = []

    for eg in examples:
        reference.append([t.text for t in eg.reference])
        predicted.append([t.text for t in eg.predicted])

    return reference, predicted