feat(fc-cleanup): audits/single_color.py + tests — Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

tests/test_audits_single_color.py

@@ -0,0 +1,42 @@
+"""Tests for the single-color audit rule.
+
+The rule downsamples + measures the fraction of pixels within `tolerance`
+(Euclidean RGB distance) of the dominant color. Matches if that fraction
+exceeds `threshold`. Single-color content is typically uploaded by
+mistake (placeholder/error/preview images) and should be flagged.
+"""
+
+from PIL import Image
+
+from backend.app.services.audits import single_color
+
+
+def test_single_color_evaluate_true_for_uniform_image():
+    im = Image.new("RGB", (50, 50), (128, 64, 200))
+    assert single_color.evaluate(im, threshold=0.9, tolerance=10) is True
+
+
+def test_single_color_evaluate_false_for_diverse_image():
+    # Half black, half white — no single color dominates.
+    im = Image.new("RGB", (50, 50), (0, 0, 0))
+    for x in range(25):
+        for y in range(50):
+            im.putpixel((x, y), (255, 255, 255))
+    assert single_color.evaluate(im, threshold=0.9, tolerance=10) is False
+
+
+def test_single_color_evaluate_respects_tolerance_widening():
+    # Gradient image: pixels span 0..50 in R channel. Tight tolerance
+    # rejects (no concentration), wide tolerance accepts (all near 25).
+    im = Image.new("RGB", (50, 50), (0, 0, 0))
+    for x in range(50):
+        for y in range(50):
+            im.putpixel((x, y), (x, 0, 0))
+    assert single_color.evaluate(im, threshold=0.9, tolerance=5) is False
+    assert single_color.evaluate(im, threshold=0.9, tolerance=50) is True
+
+
+def test_single_color_evaluate_handles_rgba_input():
+    # Alpha channel should be ignored — only RGB matters for the rule.
+    im = Image.new("RGBA", (50, 50), (100, 100, 100, 128))
+    assert single_color.evaluate(im, threshold=0.9, tolerance=10) is True