import pytest
from pathlib import Path
from analyzer import is_blurry


def make_test_image(tmp_path, color=(200, 200, 200)):
    from PIL import Image
    img = Image.new("RGB", (100, 100), color=color)
    p = tmp_path / "test.jpg"
    img.save(p)
    return str(p)


def test_solid_color_image_is_blurry(tmp_path):
    path = make_test_image(tmp_path)
    assert is_blurry(path, threshold=100) is True


def test_normal_image_is_not_blurry(tmp_path):
    from PIL import Image, ImageDraw
    img = Image.new("RGB", (100, 100), color=(255, 255, 255))
    draw = ImageDraw.Draw(img)
    for i in range(0, 100, 2):
        draw.line([(i, 0), (i, 100)], fill=(0, 0, 0), width=1)
    p = tmp_path / "sharp.jpg"
    img.save(p)
    assert is_blurry(str(p), threshold=100) is False


from analyzer import is_overexposed, is_underexposed


def test_white_image_is_overexposed(tmp_path):
    path = make_test_image(tmp_path, color=(255, 255, 255))
    assert is_overexposed(path, threshold=240) is True


def test_dark_image_is_underexposed(tmp_path):
    path = make_test_image(tmp_path, color=(10, 10, 10))
    assert is_underexposed(path, threshold=30) is True


def test_normal_image_is_neither(tmp_path):
    path = make_test_image(tmp_path, color=(128, 128, 128))
    assert is_overexposed(path, threshold=240) is False
    assert is_underexposed(path, threshold=30) is False


from analyzer import find_duplicates


def make_gradient_image(tmp_path, name="gradient.jpg"):
    from PIL import Image
    img = Image.new("L", (100, 100))
    pixels = img.load()
    for y in range(100):
        for x in range(100):
            pixels[x, y] = x * 255 // 100
    p = tmp_path / name
    img.convert("RGB").save(p)
    return str(p)


def make_diagonal_image(tmp_path, name="diagonal.jpg"):
    from PIL import Image
    img = Image.new("L", (100, 100))
    pixels = img.load()
    for y in range(100):
        for x in range(100):
            pixels[x, y] = 255 if x > y else 0
    p = tmp_path / name
    img.convert("RGB").save(p)
    return str(p)


def test_identical_images_are_duplicates(tmp_path):
    p1 = make_gradient_image(tmp_path, "img1.jpg")
    import shutil
    p2 = tmp_path / "copy.jpg"
    shutil.copy(p1, p2)
    groups = find_duplicates([p1, str(p2)], threshold=8)
    assert len(groups) == 1
    assert len(groups[0]) == 2


def test_different_images_are_not_duplicates(tmp_path):
    p1 = make_gradient_image(tmp_path, "gradient.jpg")
    p2 = make_diagonal_image(tmp_path, "diagonal.jpg")
    groups = find_duplicates([p1, p2], threshold=8)
    assert len(groups) == 0


from analyzer import analyze_folder


def test_analyze_folder_returns_results(tmp_path):
    make_test_image(tmp_path, color=(128, 128, 128))
    from PIL import Image
    white = tmp_path / "white.jpg"
    Image.new("RGB", (100, 100), color=(255, 255, 255)).save(white)

    results = analyze_folder(
        folder=str(tmp_path),
        blur_threshold=100,
        over_threshold=240,
        under_threshold=30,
        dup_threshold=8,
        use_ai=False,
    )
    reasons_flat = [r for item in results for r in item["reasons"]]
    assert "ueberbelichtet" in reasons_flat