separate pipeline

approbot-pipeline/tests/test_pipeline.py

@@ -0,0 +1,57 @@
+"""
+Grundlegende Unit- und Fehler-Tests für approbot_pipeline.
+
+End-to-end-Tests gegen echte Bilder sind in tests/test_e2e.py
+(erfordert fixtures/Scene*-Ordner, nicht im Repo).
+"""
+import os
+from pathlib import Path
+
+import pytest
+
+from approbot_pipeline import PipelineResult, __version__, estimate_from_dir
+
+FIXTURES = Path(__file__).parent / "fixtures"
+
+
+def test_version_format():
+    parts = __version__.split(".")
+    assert len(parts) == 3
+    assert all(p.isdigit() for p in parts)
+
+
+def test_pipeline_result_dataclass():
+    r = PipelineResult(
+        joints={"x": 50.0, "y": -2.0, "z": 94.0, "a": 20.0, "b": 59.0, "c": 9.0, "e": 3.0},
+        confidence={"x": "high", "y": "high", "z": "high", "a": "high", "b": "low", "c": "low", "e": "low"},
+        n_markers=42,
+        residual_rms=1.45,
+        processing_ms=1200.0,
+    )
+    assert r.joints["x"] == 50.0
+    assert r.confidence["b"] == "low"
+    assert r.n_markers == 42
+    assert r.errors == []
+
+
+def test_estimate_raises_on_empty_dir(tmp_path):
+    with pytest.raises(FileNotFoundError, match="render_"):
+        estimate_from_dir(tmp_path, robot_json=FIXTURES / "robot_minimal.json")
+
+
+def test_estimate_raises_without_robot_json(tmp_path):
+    env_backup = os.environ.pop("ROBOT_JSON", None)
+    try:
+        with pytest.raises(ValueError, match="robot_json"):
+            estimate_from_dir(tmp_path, robot_json=None)
+    finally:
+        if env_backup is not None:
+            os.environ["ROBOT_JSON"] = env_backup
+
+
+def test_robot_minimal_json_is_valid():
+    import json
+    data = json.loads((FIXTURES / "robot_minimal.json").read_text())
+    assert "pose_estimation" in data
+    assert "links" in data
+    assert data["pose_estimation"]["method"] == "hybrid"