import os

import datasets as ds
import pytest


@pytest.fixture
def dataset_path() -> str:
    return "CAMERA.py"


def test_load_dataset_without_lp_images(
    dataset_path: str,
    expected_train_num_rows: int = 12395,
    expected_val_num_rows: int = 3098,
    expected_test_num_rows: int = 872,
):
    dataset = ds.load_dataset(path=dataset_path, name="without-lp-images")

    assert dataset["train"].num_rows == expected_train_num_rows  # type: ignore
    assert dataset["validation"].num_rows == expected_val_num_rows  # type: ignore
    assert dataset["test"].num_rows == expected_test_num_rows  # type: ignore


@pytest.mark.skipif(
    bool(os.environ.get("CI", False)),
    reason="Because this test downloads a large data set, we will skip running it on CI.",
)
def test_load_dataset_with_lp_images(
    dataset_path: str,
    expected_train_num_rows: int = 12395,
    expected_val_num_rows: int = 3098,
    expected_test_num_rows: int = 872,
):
    dataset = ds.load_dataset(path=dataset_path, name="with-lp-images")

    assert dataset["train"].num_rows == expected_train_num_rows  # type: ignore
    assert dataset["validation"].num_rows == expected_val_num_rows  # type: ignore
    assert dataset["test"].num_rows == expected_test_num_rows  # type: ignore

    assert "lp_image" in dataset["train"].column_names