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docs: update progress.txt with iteration 11 completion

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Andrew Charlwood
2026-02-04 18:45:59 +00:00
parent ec8f8dc198
commit a749514889
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@@ -473,7 +473,7 @@ Use `rx.cond(condition, true_value, false_value)` not Python `if`.
### Files changed:
- Modified: pathways_app/app_v2.py (+80 lines - load_data method, on_load handler, Path import)
- Modified: IMPLEMENTATION_PLAN.md (marked 3.2 subtasks complete)
### Committed: [pending]
### Committed: f38ccfc "feat: implement data loading from SQLite (Task 3.2)"
### Patterns discovered:
- Reflex on_load: Use `app.add_page(..., on_load=AppState.method_name)` to trigger method on page load
- SQLite in Reflex state: Import sqlite3 inside method to avoid issues with state serialization
@@ -491,3 +491,163 @@ Use `rx.cond(condition, true_value, false_value)` not Python `if`.
- May need to store raw_data list in state or re-query SQLite based on filters
### Blocked items:
- None
## Iteration 9 - 2026-02-04
### Task: 3.3 Filter Logic
### Why this task:
- Previous iteration (8) explicitly recommended continuing with Task 3.3
- Filter logic is foundational for KPI calculations (Task 3.4) and chart generation (Phase 4)
- Natural progression through Phase 3: State Management
- Bridges data loading with reactive UI updates
### Status: COMPLETE
### What was done:
- Created `apply_filters()` method that queries SQLite with current filter state
- Implemented patient-level date filtering using CTE (Common Table Expression):
- "Initiated" filter: MIN(intervention_date) per patient within date range
- "Last Seen" filter: MAX(intervention_date) per patient within date range
- Implemented drug and directorate multi-select filters using SQL IN clauses
- Dynamic WHERE clause building based on which filters have selections
- Updated KPI values (unique_patients, total_drugs, total_cost) from filtered results
- Added apply_filters() calls to all filter event handlers:
- toggle_initiated_filter(), toggle_last_seen_filter()
- set_initiated_from/to(), set_last_seen_from/to()
- toggle_drug(), toggle_directorate()
- select_all_drugs(), clear_all_drugs()
- select_all_directorates(), clear_all_directorates()
- Called apply_filters() after initial data load in load_data()
- Note: Indication filter not implemented at DB level (indications are derived from drug mappings)
### Validation results:
- Tier 1 (Code):
- `python -m py_compile pathways_app/app_v2.py` PASSED
- `python -c "from pathways_app.app_v2 import app, AppState"` PASSED
- AppState.apply_filters exists and is callable
- Tier 2 (Visual): Deferred - requires running app with modified config
- Tier 3 (Functional): SQL query patterns tested directly against database:
- Total unique patients: 35,032
- With Last Seen filter (last 6 months): 19,849 patients, 461 drugs, £211.5M
- ADALIMUMAB only: 2,839 patients, 1 drug, £14.4M
- RHEUMATOLOGY only: 3,540 patients, 104 drugs, £45.8M
### Files changed:
- Modified: pathways_app/app_v2.py (+167 lines - apply_filters method, event handler updates)
- Modified: IMPLEMENTATION_PLAN.md (marked 3.3 subtasks complete)
### Committed: cd15ab6 "feat: implement filter logic with reactive KPI updates (Task 3.3)"
### Patterns discovered:
- CTE pattern for patient-level aggregation: Use WITH clause to compute per-patient first/last dates, then JOIN back to get full records
- Dynamic SQL building: Build WHERE clauses incrementally, use HAVING for aggregated conditions
- COALESCE for null handling: `COALESCE(SUM(price_actual), 0)` prevents None when no records match
- Directory names in DB are UPPERCASE: "RHEUMATOLOGY" not "Rheumatology"
- SQLite IN clause with list: Use `",".join("?" * len(items))` for placeholder generation
### Next iteration should:
- Continue with Task 3.4: KPI Calculations
- The KPI calculations are already done inside apply_filters() - Task 3.4 may already be complete
- Review if any additional computed properties are needed:
- Currently: unique_patients, total_drugs, total_cost updated in apply_filters()
- indication_match_rate still shows "—" (match rate calculation not implemented)
- Consider implementing indication match rate calculation (requires Snowflake GP data lookup)
- OR if 3.4 is effectively complete, move to Phase 4: Interactive Chart (4.1 Chart Data Preparation)
### Blocked items:
- indication_match_rate calculation requires GP diagnosis data from Snowflake (not currently available in SQLite)
- Visual validation still blocked until rxconfig is updated to point to app_v2
## Iteration 10 - 2026-02-04
### Task: 3.4 (review) + 4.1 Chart Data Preparation
### Why this task:
- Previous iteration (9) noted that Task 3.4 might already be complete since KPIs are computed in apply_filters()
- Reviewed Task 3.4: unique_patients, total_drugs, total_cost all implemented and reactive
- Only incomplete item (indication_match_rate) is blocked by Snowflake GP data
- Marked 3.4 complete and moved to Phase 4: Interactive Chart
- Task 4.1 is next logical step: prepare data for Plotly icicle chart
### Status: COMPLETE
### What was done:
- Reviewed Task 3.4: Confirmed KPI calculations already implemented in apply_filters()
- Marked Task 3.4 complete in IMPLEMENTATION_PLAN.md
- Implemented `prepare_chart_data()` method in AppState:
- Queries filtered data from SQLite
- Builds hierarchical structure: Root → Trust → Directory → Drug
- Calculates patient counts and costs at each level
- Computes colour values (proportions) for visualization
- Stores result in `chart_data` (list of dicts) for Reflex serialization
- Added `chart_data` and `chart_title` state variables
- Implemented `_generate_chart_title()` helper for dynamic titles
- Called `prepare_chart_data()` from `apply_filters()` for reactive updates
- Fixed SQL query to use correct column names (provider_code, org_name from fact_interventions)
### Validation results:
- Tier 1 (Code):
- `python -m py_compile pathways_app/app_v2.py` PASSED
- `python -c "from pathways_app.app_v2 import app, AppState"` PASSED
- Methods exist: prepare_chart_data, _generate_chart_title
- Tier 2 (Visual): Deferred - requires Plotly integration (Task 4.3)
- Tier 3 (Functional): SQL query tested directly - returns correct hierarchical data:
- Sample: "Norfolk and Norwich University | OPHTHALMOLOGY | RANIBIZUMAB | 1801 patients | £9.4M"
### Files changed:
- Modified: pathways_app/app_v2.py (+280 lines - prepare_chart_data, _generate_chart_title, chart_data/chart_title vars)
- Modified: IMPLEMENTATION_PLAN.md (marked 3.4 and 4.1 complete)
### Committed: 14f970d "feat: implement chart data preparation (Task 4.1)"
### Patterns discovered:
- fact_interventions already has org_name column - no need to join ref_organizations
- Column is provider_code not org_code in fact_interventions
- Chart data stored as list[dict[str, Any]] for Reflex serialization (DataFrames don't work)
- Color values computed as proportion of parent total (value/parent_total)
### Next iteration should:
- Continue with Task 4.2: Reactive Plotly Integration
- Create `generate_icicle_chart()` computed property that returns Plotly Figure
- Use chart_data from state to build go.Icicle()
- Configure chart colors using design system palette (may need to convert colour to proper colorscale)
- Set responsive sizing
- Reference visualization/plotly_generator.py for working go.Icicle() patterns
### Blocked items:
- indication_match_rate still blocked (Snowflake GP data)
- Visual validation blocked until Plotly integration complete
## Iteration 11 - 2026-02-04
### Task: 4.2 Reactive Plotly Integration
### Why this task:
- Previous iteration (10) explicitly recommended continuing with Task 4.2
- Natural progression through Phase 4: Interactive Chart
- Chart data preparation (Task 4.1) is complete, now need figure generation
- Task 4.3 (Chart Component) depends on 4.2 being complete
### Status: COMPLETE
### What was done:
- Added `import plotly.graph_objects as go` to app_v2.py
- Created `icicle_figure` computed property (@rx.var) in AppState
- Implementation:
- Extracts lists from chart_data (parents, ids, labels, values, costs, colours)
- Uses NHS-inspired blue gradient colorscale:
- [0.0, "#003087"] Heritage Blue
- [0.25, "#0066CC"] Primary Blue
- [0.5, "#1E88E5"] Vibrant Blue
- [0.75, "#4FC3F7"] Sky Blue
- [1.0, "#E3F2FD"] Pale Blue
- Creates go.Icicle with customdata for hover (values, colours, costs)
- Text template shows label + patient count
- Hover template shows full details (patients, percentage of parent, cost)
- Layout configured with Inter font family, transparent background, 600px height
- Maintains hierarchy order with sort=False
- Returns empty go.Figure() when chart_data is empty
### Validation results:
- Tier 1 (Code):
- `python -m py_compile pathways_app/app_v2.py` PASSED
- `python -c "from pathways_app.app_v2 import app, AppState"` PASSED
- `hasattr(AppState, 'icicle_figure')` returns True
- Tested figure creation with sample data - creates valid go.Figure
- Tier 2 (Visual): Deferred to Task 4.3 — requires rx.plotly() integration
- Tier 3 (Functional): Figure generation tested with mock chart_data
### Files changed:
- Modified: pathways_app/app_v2.py (+111 lines - plotly import, icicle_figure computed property)
- Modified: IMPLEMENTATION_PLAN.md (marked 4.2 complete)
### Committed: ec8f8dc "feat: implement reactive Plotly icicle chart generation (Task 4.2)"
### Patterns discovered:
- @rx.var decorated properties can return Plotly Figure objects
- Custom colorscale: list of [position, color] pairs where position is 0.0-1.0
- customdata=list(zip(...)) works for packaging multiple values for hover template
- Transparent background: paper_bgcolor="rgba(0,0,0,0)" and plot_bgcolor="rgba(0,0,0,0)"
### Next iteration should:
- Continue with Task 4.3: Chart Component
- Replace chart_ready_placeholder() with actual rx.plotly() component
- Pass AppState.icicle_figure to rx.plotly()
- Test with real data by running reflex (may need to update rxconfig or __init__.py)
- Handle edge cases: empty figure, loading state transitions
- Verify chart updates when filters change
### Blocked items:
- indication_match_rate still blocked (Snowflake GP data)
- Visual validation still needs running app (Task 4.3 will enable this)