From 98642f49e4a13628e4c60177e8987fd38d91cca5 Mon Sep 17 00:00:00 2001
From: Mika <kontakt@donau2space.de>
Date: Thu, 5 Mar 2026 15:48:02 +0000
Subject: [PATCH] Add data_analysis/tests/test_core.py

---
 data_analysis/tests/test_core.py | 54 ++++++++++++++++++++++++++++++++
 1 file changed, 54 insertions(+)
 create mode 100644 data_analysis/tests/test_core.py

diff --git a/data_analysis/tests/test_core.py b/data_analysis/tests/test_core.py
new file mode 100644
index 0000000..05c7d7d
--- /dev/null
+++ b/data_analysis/tests/test_core.py
@@ -0,0 +1,54 @@
+import pytest
+from data_analysis import core
+
+
+def test_analyze_data_nominal_case():
+    data = [
+        {"context": "near_expiry", "pinned_status": "unpinned", "delta_t": -0.5, "warn": True},
+        {"context": "near_expiry", "pinned_status": "unpinned", "delta_t": 1.0, "warn": False},
+        {"context": "fresh", "pinned_status": "unpinned", "delta_t": 0.5, "warn": False},
+        {"context": "fresh", "pinned_status": "pinned", "delta_t": -0.2, "warn": True},
+    ]
+    result = core.analyze_data(data)
+    assert isinstance(result, dict)
+    assert set(result.keys()) == {"near_expiry_count", "fresh_count", "warn_rate"}
+    assert result["near_expiry_count"] == 2
+    assert result["fresh_count"] == 1
+    total_records = len(data)
+    expected_warn_rate = 2 / total_records
+    assert pytest.approx(result["warn_rate"], rel=1e-3) == expected_warn_rate
+
+
+def test_analyze_data_empty_input():
+    result = core.analyze_data([])
+    assert isinstance(result, dict)
+    assert result["near_expiry_count"] == 0
+    assert result["fresh_count"] == 0
+    assert result["warn_rate"] == 0.0
+
+
+def test_analyze_data_invalid_structure():
+    bad_data = [{"context": "near_expiry", "delta_t": -1.0}]  # missing keys
+    with pytest.raises((KeyError, ValueError, TypeError)):
+        core.analyze_data(bad_data)
+
+
+def test_analyze_data_delta_t_negative_detection():
+    data = [
+        {"context": "near_expiry", "pinned_status": "unpinned", "delta_t": -0.3, "warn": False},
+        {"context": "fresh", "pinned_status": "unpinned", "delta_t": -0.5, "warn": True},
+    ]
+    result = core.analyze_data(data)
+    # both are unpinned, so should register counts
+    assert result["near_expiry_count"] == 1
+    assert result["fresh_count"] == 1
+    expected_warn_rate = 1 / 2
+    assert pytest.approx(result["warn_rate"], rel=1e-3) == expected_warn_rate
+
+
+def test_analyze_data_type_validation():
+    data = [
+        {"context": "fresh", "pinned_status": "unpinned", "delta_t": "NaN", "warn": True}
+    ]
+    with pytest.raises((TypeError, ValueError)):
+        core.analyze_data(data)