Add geiger_counter_visualizer/tests/test_core.py

geiger_counter_visualizer/tests/test_core.py

@@ -0,0 +1,53 @@
+import pytest
+import pandas as pd
+from datetime import datetime
+from geiger_counter_visualizer import core
+
+
+@pytest.fixture
+def sample_data_points():
+    return [
+        core.DataPoint(timestamp="2024-01-01T00:00:00", count=10, frequency=1.2),
+        core.DataPoint(timestamp="2024-01-01T00:00:01", count=15, frequency=1.4),
+        core.DataPoint(timestamp="2024-01-01T00:00:02", count=9, frequency=1.1)
+    ]
+
+
+def test_datapoint_initialization(sample_data_points):
+    dp = sample_data_points[0]
+    assert isinstance(dp.timestamp, str)
+    assert dp.count == 10
+    assert dp.frequency == pytest.approx(1.2)
+    # Valid ISO timestamp
+    parsed = datetime.fromisoformat(dp.timestamp)
+    assert isinstance(parsed, datetime)
+
+
+def test_datapoint_type_validation():
+    with pytest.raises((TypeError, ValueError)):
+        core.DataPoint(timestamp=123, count="a", frequency="b")
+
+
+def test_visualize_data_monkeypatch(sample_data_points, monkeypatch):
+    calls = {}
+
+    def fake_show():
+        calls["called"] = True
+    monkeypatch.setattr("matplotlib.pyplot.show", fake_show)
+
+    result = core.visualize_data(sample_data_points)
+    assert result is None
+    assert calls.get("called", False) is True
+
+
+def test_visualize_data_empty(monkeypatch):
+    monkeypatch.setattr("matplotlib.pyplot.show", lambda: None)
+    # visualize_data should handle empty list gracefully
+    result = core.visualize_data([])
+    assert result is None
+
+
+def test_visualize_data_invalid_input(monkeypatch):
+    monkeypatch.setattr("matplotlib.pyplot.show", lambda: None)
+    with pytest.raises((AssertionError, TypeError)):
+        core.visualize_data([{"timestamp": "2024-01-01", "count": 3, "frequency": 0.5}])