Add comprehensive tests for dose tracking functionality
- Implemented `test_dose_parsing_simple.py` to validate the dose parsing workflow. - Created `test_dose_save.py` to verify the saving functionality of dose tracking. - Added `test_dose_save_simple.py` for programmatic testing of dose saving without UI interaction. - Developed `test_final_workflow.py` to test the complete dose tracking workflow, ensuring doses are preserved during edits. - Enhanced `conftest.py` with a mock pathology manager for testing. - Updated `test_data_manager.py` to include pathology manager in DataManager tests and ensure compatibility with new features.
This commit is contained in:
William Valentin
@@ -8,16 +8,21 @@ from matplotlib.axes import Axes
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from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
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from medicine_manager import MedicineManager
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from pathology_manager import PathologyManager
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class GraphManager:
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"""Handle all graph-related operations for the application."""
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def __init__(
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self, parent_frame: ttk.LabelFrame, medicine_manager: MedicineManager
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self,
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parent_frame: ttk.LabelFrame,
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medicine_manager: MedicineManager,
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pathology_manager: PathologyManager,
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) -> None:
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self.parent_frame: ttk.LabelFrame = parent_frame
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self.medicine_manager = medicine_manager
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self.pathology_manager = pathology_manager
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# Configure graph frame to expand
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self.parent_frame.grid_rowconfigure(0, weight=1)
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@@ -28,13 +33,13 @@ class GraphManager:
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def _initialize_toggle_vars(self) -> None:
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"""Initialize toggle variables for chart elements."""
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# Initialize symptom toggles (always shown by default)
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self.toggle_vars: dict[str, tk.BooleanVar] = {
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"depression": tk.BooleanVar(value=True),
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"anxiety": tk.BooleanVar(value=True),
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"sleep": tk.BooleanVar(value=True),
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"appetite": tk.BooleanVar(value=True),
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}
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self.toggle_vars: dict[str, tk.BooleanVar] = {}
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# Initialize pathology toggles dynamically
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for pathology_key in self.pathology_manager.get_pathology_keys():
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pathology = self.pathology_manager.get_pathology(pathology_key)
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default_value = pathology.default_enabled if pathology else True
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self.toggle_vars[pathology_key] = tk.BooleanVar(value=default_value)
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# Add medicine toggles dynamically
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for medicine_key in self.medicine_manager.get_medicine_keys():
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@@ -77,25 +82,20 @@ class GraphManager:
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side="left", padx=5
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)
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# Symptoms toggles
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symptoms_frame = ttk.LabelFrame(self.control_frame, text="Symptoms")
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symptoms_frame.pack(side="left", padx=5, pady=2)
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# Pathologies toggles - dynamic based on pathology manager
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pathologies_frame = ttk.LabelFrame(self.control_frame, text="Pathologies")
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pathologies_frame.pack(side="left", padx=5, pady=2)
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symptom_configs = [
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("depression", "Depression"),
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("anxiety", "Anxiety"),
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("sleep", "Sleep"),
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("appetite", "Appetite"),
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]
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for key, label in symptom_configs:
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checkbox = ttk.Checkbutton(
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symptoms_frame,
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text=label,
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variable=self.toggle_vars[key],
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command=self._handle_toggle_changed,
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)
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checkbox.pack(side="left", padx=3)
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for pathology_key in self.pathology_manager.get_pathology_keys():
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pathology = self.pathology_manager.get_pathology(pathology_key)
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if pathology:
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checkbox = ttk.Checkbutton(
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pathologies_frame,
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text=pathology.display_name,
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variable=self.toggle_vars[pathology_key],
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command=self._handle_toggle_changed,
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)
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checkbox.pack(side="left", padx=3)
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# Medicines toggles - dynamic based on medicine manager
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medicines_frame = ttk.LabelFrame(self.control_frame, text="Medicines")
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@@ -135,35 +135,26 @@ class GraphManager:
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# Track if any series are plotted
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has_plotted_series = False
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# Plot data series based on toggle states
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if self.toggle_vars["depression"].get():
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self._plot_series(
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df, "depression", "Depression (0:good, 10:bad)", "o", "-"
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)
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has_plotted_series = True
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if self.toggle_vars["anxiety"].get():
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self._plot_series(df, "anxiety", "Anxiety (0:good, 10:bad)", "o", "-")
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has_plotted_series = True
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if self.toggle_vars["sleep"].get():
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self._plot_series(df, "sleep", "Sleep (0:bad, 10:good)", "o", "dashed")
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has_plotted_series = True
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if self.toggle_vars["appetite"].get():
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self._plot_series(
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df, "appetite", "Appetite (0:bad, 10:good)", "o", "dashed"
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)
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has_plotted_series = True
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# Plot pathology data series based on toggle states
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for pathology_key in self.pathology_manager.get_pathology_keys():
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if self.toggle_vars[pathology_key].get():
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pathology = self.pathology_manager.get_pathology(pathology_key)
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if pathology and pathology_key in df.columns:
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label = f"{pathology.display_name} ({pathology.scale_info})"
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linestyle = (
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"dashed"
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if pathology.scale_orientation == "inverted"
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else "-"
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)
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self._plot_series(df, pathology_key, label, "o", linestyle)
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has_plotted_series = True
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# Plot medicine dose data
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# Get medicine colors from medicine manager
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medicine_colors = self.medicine_manager.get_graph_colors()
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medicines = [
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"bupropion",
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"hydroxyzine",
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"gabapentin",
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"propranolol",
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"quetiapine",
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]
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# Get medicines dynamically from medicine manager
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medicines = self.medicine_manager.get_medicine_keys()
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# Track medicines with and without data for legend
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medicines_with_data = []
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