258 lines
8.6 KiB
Python
258 lines
8.6 KiB
Python
"""
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Fixtures and configuration for pytest tests.
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"""
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import os
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import tempfile
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import pytest
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import pandas as pd
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from unittest.mock import Mock
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import logging
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import warnings
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import os as _os
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# Force a headless-friendly Matplotlib backend in tests
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_os.environ.setdefault("MPLBACKEND", "Agg")
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@pytest.fixture(autouse=True, scope="session")
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def _matplotlib_headless_backend():
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"""Force Matplotlib to use the Agg backend for all tests.
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Doing this at session scope ensures any pyplot usage in code under test
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doesn't try to initialize interactive Tk backends.
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"""
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try:
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import matplotlib as _mpl
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_mpl.use("Agg", force=True)
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except Exception:
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# If Matplotlib isn't available or already configured, ignore.
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pass
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@pytest.fixture(autouse=True)
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def _stub_pyplot_ui_calls(monkeypatch):
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"""No-op pyplot UI calls that can be noisy or slow in CI.
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This reduces flicker and avoids timing issues without changing behavior.
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"""
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try:
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import matplotlib.pyplot as _plt
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monkeypatch.setattr(_plt, "pause", lambda *args, **kwargs: None, raising=False)
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monkeypatch.setattr(_plt, "draw", lambda *args, **kwargs: None, raising=False)
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except Exception:
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pass
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@pytest.fixture(autouse=True, scope="session")
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def _tune_reportlab_for_tests():
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"""Apply small ReportLab tweaks for stable tests without heavy font checks."""
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try:
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from reportlab import rl_config
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# Disable glyph warnings which are irrelevant for our tests
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rl_config.warnOnMissingFontGlyphs = 0 # type: ignore[attr-defined]
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except Exception:
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pass
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# Test-only warning hygiene to keep output clean while preserving behavior
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# - Silence legacy deprecation shims that originate inside package internals
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warnings.filterwarnings(
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"ignore",
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message=r".*search_filter is deprecated.*",
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category=DeprecationWarning,
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)
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# - Silence a Pillow deprecation surfaced via Matplotlib's Tk backend used by tests
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warnings.filterwarnings(
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"ignore",
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message=r".*'mode' parameter is deprecated and will be removed in Pillow 13.*",
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category=DeprecationWarning,
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)
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# - Silence pandas parse fallback warning triggered intentionally by invalid test data
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warnings.filterwarnings(
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"ignore",
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message=r"Could not infer format, so each element will be parsed individually.*",
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category=UserWarning,
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)
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from thechart.managers import MedicineManager, Medicine
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@pytest.fixture
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def temp_csv_file():
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"""Create a temporary CSV file for testing."""
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fd, path = tempfile.mkstemp(suffix='.csv')
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os.close(fd)
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yield path
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# Cleanup
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if os.path.exists(path):
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os.unlink(path)
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@pytest.fixture
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def mock_medicine_manager():
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"""Create a mock medicine manager with default medicines for testing."""
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mock_manager = Mock(spec=MedicineManager)
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# Default medicines matching the original system
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default_medicines = {
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"bupropion": Medicine(
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key="bupropion",
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display_name="Bupropion",
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dosage_info="150/300 mg",
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quick_doses=["150", "300"],
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color="#FF6B6B",
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default_enabled=True
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),
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"hydroxyzine": Medicine(
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key="hydroxyzine",
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display_name="Hydroxyzine",
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dosage_info="25 mg",
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quick_doses=["25", "50"],
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color="#4ECDC4",
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default_enabled=False
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),
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"gabapentin": Medicine(
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key="gabapentin",
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display_name="Gabapentin",
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dosage_info="100 mg",
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quick_doses=["100", "300", "600"],
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color="#45B7D1",
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default_enabled=False
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),
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"propranolol": Medicine(
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key="propranolol",
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display_name="Propranolol",
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dosage_info="10 mg",
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quick_doses=["10", "20", "40"],
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color="#96CEB4",
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default_enabled=True
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),
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"quetiapine": Medicine(
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key="quetiapine",
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display_name="Quetiapine",
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dosage_info="25 mg",
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quick_doses=["25", "50", "100"],
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color="#FFEAA7",
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default_enabled=False
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)
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}
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mock_manager.get_medicine_keys.return_value = list(default_medicines.keys())
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mock_manager.get_all_medicines.return_value = default_medicines
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mock_manager.get_medicine.side_effect = lambda key: default_medicines.get(key)
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mock_manager.get_graph_colors.return_value = {k: v.color for k, v in default_medicines.items()}
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mock_manager.get_quick_doses.side_effect = lambda key: default_medicines.get(key, Medicine("", "", "", [], "", False)).quick_doses
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return mock_manager
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@pytest.fixture
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def mock_pathology_manager():
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"""Create a mock pathology manager with default pathologies for testing."""
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mock_manager = Mock()
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# Default pathologies matching the original system
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mock_manager.get_pathology_keys.return_value = ["depression", "anxiety", "sleep", "appetite"]
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return mock_manager
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@pytest.fixture
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def sample_data():
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"""Sample data for testing."""
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return [
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["2024-01-01", 3, 2, 4, 3, 1, "", 0, "", 2, "", 1, "", 0, "", "Test note 1"],
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["2024-01-02", 2, 3, 3, 4, 1, "", 1, "", 2, "", 0, "", 1, "", "Test note 2"],
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["2024-01-03", 4, 1, 5, 2, 0, "", 0, "", 1, "", 1, "", 0, "", ""],
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]
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@pytest.fixture
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def sample_dataframe():
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"""Sample DataFrame for testing."""
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return pd.DataFrame({
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'date': ['2024-01-01', '2024-01-02', '2024-01-03'],
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'depression': [3, 2, 4],
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'anxiety': [2, 3, 1],
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'sleep': [4, 3, 5],
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'appetite': [3, 4, 2],
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'bupropion': [1, 1, 0],
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'bupropion_doses': ['2024-01-01 08:00:00:150mg', '2024-01-02 08:00:00:300mg', ''],
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'hydroxyzine': [0, 1, 0],
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'hydroxyzine_doses': ['', '2024-01-02 20:00:00:25mg', ''],
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'gabapentin': [2, 2, 1],
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'gabapentin_doses': ['2024-01-01 12:00:00:100mg|2024-01-01 20:00:00:100mg',
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'2024-01-02 12:00:00:100mg|2024-01-02 20:00:00:100mg',
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'2024-01-03 12:00:00:100mg'],
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'propranolol': [1, 0, 1],
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'propranolol_doses': ['2024-01-01 12:00:00:10mg', '', '2024-01-03 12:00:00:20mg'],
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'quetiapine': [0, 1, 0],
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'quetiapine_doses': ['', '2024-01-02 22:00:00:50mg', ''],
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'note': ['Test note 1', 'Test note 2', '']
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})
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@pytest.fixture
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def mock_logger():
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"""Mock logger for testing."""
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return Mock(spec=logging.Logger)
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@pytest.fixture
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def temp_log_dir():
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"""Create a temporary directory for log files."""
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with tempfile.TemporaryDirectory() as temp_dir:
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yield temp_dir
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@pytest.fixture
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def mock_env_vars(monkeypatch):
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"""Mock environment variables."""
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monkeypatch.setenv("LOG_LEVEL", "DEBUG")
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monkeypatch.setenv("LOG_PATH", "/tmp/test_logs")
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monkeypatch.setenv("LOG_CLEAR", "False")
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@pytest.fixture
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def sample_dose_data():
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"""Sample dose data for testing dose calculation."""
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return {
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'standard_format': '2025-07-28 18:59:45:150mg|2025-07-28 19:34:19:75mg', # Should sum to 225
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'with_bullets': '• • • • 2025-07-30 07:50:00:300', # Should be 300
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'decimal_doses': '2025-07-28 18:59:45:12.5mg|2025-07-28 19:34:19:7.5mg', # Should sum to 20
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'no_timestamp': '100mg|50mg', # Should sum to 150
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'mixed_format': '• 2025-07-30 22:50:00:10|75mg', # Should sum to 85
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'empty_string': '', # Should be 0
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'nan_value': 'nan', # Should be 0
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'no_units': '2025-07-28 18:59:45:10|2025-07-28 19:34:19:5', # Should sum to 15
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}
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@pytest.fixture
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def legend_test_dataframe():
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"""DataFrame specifically designed for testing legend functionality."""
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return pd.DataFrame({
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'date': ['2024-01-01', '2024-01-02', '2024-01-03'],
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'depression': [3, 2, 4],
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'anxiety': [2, 3, 1],
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'sleep': [4, 3, 5],
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'appetite': [3, 4, 2],
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# Medicine with consistent doses for average testing
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'bupropion': [1, 1, 1],
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'bupropion_doses': ['2024-01-01 08:00:00:100mg',
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'2024-01-02 08:00:00:200mg',
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'2024-01-03 08:00:00:150mg'], # Average: 150mg
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# Medicine with varying doses
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'propranolol': [1, 1, 0],
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'propranolol_doses': ['2024-01-01 12:00:00:10mg',
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'2024-01-02 12:00:00:20mg',
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''], # Average: 15mg (10+20)/2
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# Medicines without dose data
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'hydroxyzine': [0, 0, 0],
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'hydroxyzine_doses': ['', '', ''],
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'gabapentin': [0, 0, 0],
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'gabapentin_doses': ['', '', ''],
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'quetiapine': [0, 0, 0],
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'quetiapine_doses': ['', '', ''],
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'note': ['Test note 1', 'Test note 2', 'Test note 3']
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})
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