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| import pytest | |
| import os | |
| import sys | |
| import pandas as pd | |
| backend_dir = os.path.abspath(os.path.join(os.path.dirname(__file__), '../backend')) | |
| if backend_dir not in sys.path: | |
| sys.path.insert(0, backend_dir) | |
| from dataset_analytics import get_dataset_profile, get_paginated_rows | |
| def sample_dataset(tmp_path_factory): | |
| fn = tmp_path_factory.mktemp("data") / "test_corpus.csv" | |
| df = pd.DataFrame({ | |
| 'Patient Number': list(range(1, 101)), | |
| 'Heart Rate (bpm)': [70 + (i % 50) for i in range(100)], | |
| 'SpO2 Level (%)': [95 + (i % 5) for i in range(100)], | |
| 'Systolic Blood Pressure (mmHg)': [110 + (i % 60) for i in range(100)], | |
| 'Diastolic Blood Pressure (mmHg)': [70 + (i % 30) for i in range(100)], | |
| 'Body Temperature (°C)': [36.5 + ((i % 15) * 0.1) for i in range(100)], | |
| 'Fall Detection': ['No' if i % 10 != 0 else 'Yes' for i in range(100)], | |
| 'Predicted Disease': [ | |
| 'Healthy' if i % 4 == 0 else ('Heart Disease' if i % 4 == 1 else ('Hypertension' if i % 4 == 2 else 'Asthma')) | |
| for i in range(100) | |
| ], | |
| 'Data Accuracy (%)': [98 for _ in range(100)], | |
| 'Heart Rate Alert': ['NORMAL' for _ in range(100)], | |
| 'SpO2 Level Alert': ['NORMAL' for _ in range(100)], | |
| 'Blood Pressure Alert': ['NORMAL' for _ in range(100)], | |
| 'Temperature Alert': ['NORMAL' for _ in range(100)] | |
| }) | |
| df.to_csv(fn, index=False) | |
| return str(fn) | |
| def test_get_dataset_profile_valid(sample_dataset): | |
| profile = get_dataset_profile(sample_dataset) | |
| assert profile is not None | |
| assert isinstance(profile, dict) | |
| # Required keys | |
| assert "summary" in profile | |
| assert profile["summary"]["total_records"] == 100 | |
| assert "target_distribution" in profile | |
| assert len(profile["target_distribution"]) == 4 | |
| assert "correlation_matrix" in profile | |
| assert "labels" in profile["correlation_matrix"] | |
| assert "matrix" in profile["correlation_matrix"] | |
| assert "feature_stats" in profile | |
| def test_get_dataset_profile_caching(sample_dataset): | |
| # Verify in-memory caching returns identical object reference | |
| p1 = get_dataset_profile(sample_dataset) | |
| p2 = get_dataset_profile(sample_dataset) | |
| assert p1 is p2 | |
| def test_get_dataset_profile_nonexistent(): | |
| prof = get_dataset_profile("non_existent_path_xyz.csv") | |
| assert prof is None | |
| def test_get_paginated_rows_default(sample_dataset): | |
| res = get_paginated_rows(sample_dataset, page=1, limit=25) | |
| assert res["total"] == 100 | |
| assert res["page"] == 1 | |
| assert res["limit"] == 25 | |
| assert res["total_pages"] == 4 | |
| assert len(res["rows"]) == 25 | |
| def test_get_paginated_rows_boundary_clamps(sample_dataset): | |
| # Page <= 0 should clamp to 1 | |
| res_zero = get_paginated_rows(sample_dataset, page=0, limit=10) | |
| assert res_zero["page"] == 1 | |
| assert len(res_zero["rows"]) == 10 | |
| res_neg = get_paginated_rows(sample_dataset, page=-5, limit=10) | |
| assert res_neg["page"] == 1 | |
| assert len(res_neg["rows"]) == 10 | |
| def test_get_paginated_rows_out_of_bounds_page(sample_dataset): | |
| res = get_paginated_rows(sample_dataset, page=9999, limit=25) | |
| assert res["total"] == 100 | |
| assert res["rows"] == [] | |
| def test_get_paginated_rows_disease_filtering(sample_dataset): | |
| # Case insensitive exact match | |
| res_hd = get_paginated_rows(sample_dataset, page=1, limit=50, disease="heart disease") | |
| assert res_hd["total"] == 25 | |
| for r in res_hd["rows"]: | |
| assert r["Predicted Disease"].lower() == "heart disease" | |
| # Non-matching disease | |
| res_unknown = get_paginated_rows(sample_dataset, page=1, limit=50, disease="alien syndrome") | |
| assert res_unknown["total"] == 0 | |
| assert res_unknown["rows"] == [] | |
| def test_get_paginated_rows_search_filtering(sample_dataset): | |
| # Search by patient ID substring | |
| res_search = get_paginated_rows(sample_dataset, page=1, limit=50, search="42") | |
| assert res_search["total"] >= 1 | |
| assert any(r["Patient Number"] == 42 for r in res_search["rows"]) | |