Add data_analysis/tests/test_core.py

data_analysis/tests/test_core.py

@@ -0,0 +1,57 @@
+import json
+import pandas as pd
+import pytest
+from pathlib import Path
+
+import src.data_analysis.core as core
+
+
+@pytest.fixture()
+def sample_data(tmp_path):
+    # Create a temporary CSV to simulate realistic temperature data
+    csv_path = tmp_path / "test_temperature_data.csv"
+    data = [
+        ["Beton", 18.5, 0.95, "2024-08-01T22:00:00"],
+        ["Wasser", 17.1, 0.98, "2024-08-01T22:00:00"],
+        ["Luft", 19.0, 0.99, "2024-08-01T22:00:00"],
+        ["Beton", 17.8, 0.95, "2024-08-01T23:00:00"],
+        ["Wasser", 16.9, 0.98, "2024-08-01T23:00:00"],
+        ["Luft", 19.3, 0.99, "2024-08-01T23:00:00"],
+    ]
+    df = pd.DataFrame(data, columns=["surface", "temperature_c", "emissivity", "timestamp"])
+    df.to_csv(csv_path, index=False)
+    return pd.read_csv(csv_path)
+
+
+def test_analyze_temperature_data_returns_analysisresult(sample_data):
+    result = core.analyze_temperature_data(sample_data)
+    assert isinstance(result, core.AnalysisResult)
+    assert hasattr(result, "temperature_differences")
+    assert hasattr(result, "pattern_recognition")
+
+
+def test_analysisresult_to_json_valid(sample_data):
+    result = core.analyze_temperature_data(sample_data)
+    json_output = result.to_json()
+    parsed = json.loads(json_output)
+    assert isinstance(parsed, dict)
+    assert "temperature_differences" in parsed
+    assert "pattern_recognition" in parsed
+
+
+def test_analyze_temperature_data_edge_empty_dataframe():
+    empty_df = pd.DataFrame(columns=["surface", "temperature_c", "emissivity", "timestamp"])
+    with pytest.raises(ValueError):
+        core.analyze_temperature_data(empty_df)
+
+
+def test_analysisresult_strict_type_validation():
+    # Ensure that AnalysisResult enforces correct types or fails gracefully
+    with pytest.raises((TypeError, ValueError)):
+        _ = core.AnalysisResult(temperature_differences="wrong_type", pattern_recognition=123)
+
+
+def test_pattern_recognition_nonempty(sample_data):
+    result = core.analyze_temperature_data(sample_data)
+    assert isinstance(result.pattern_recognition, str)
+    assert len(result.pattern_recognition) > 0