feat: add directorate card tree builder for drug browser drawer (Task 1.2)

IMPLEMENTATION_PLAN.md

@@ -107,12 +107,12 @@ Drawer selection → update_drug_selection → app-state store → load_pathway_
 - **Checkpoint**: `python -c "from dash_app.data.queries import load_initial_data; print(load_initial_data())"` returns valid data
 
 ### 1.2 Build directorate card tree from DimSearchTerm.csv
-- [ ] Create `dash_app/data/card_browser.py` with:
+- [x] Create `dash_app/data/card_browser.py` with:
   - `build_directorate_tree()` → dict structured as `{PrimaryDirectorate: {Search_Term: [drug_fragment, ...]}}`
   - Loads `data/DimSearchTerm.csv`, groups by PrimaryDirectorate → Search_Term → split CleanedDrugName by pipe
   - Applies SEARCH_TERM_MERGE_MAP from `data_processing.diagnosis_lookup` (merge asthma variants)
   - `get_all_drugs()` → sorted flat list of all unique drug labels from `pathway_nodes` level 3
-- **Checkpoint**: `python -c "from dash_app.data.card_browser import build_directorate_tree; import json; print(json.dumps(build_directorate_tree(), indent=2))"` returns valid tree
+- **Checkpoint**: `python -c "from dash_app.data.card_browser import build_directorate_tree; import json; print(json.dumps(build_directorate_tree(), indent=2))"` returns valid tree ✓
 
 ---
 

dash_app/data/card_browser.py

@@ -0,0 +1,83 @@
+"""
+Directorate card tree builder for the drug browser drawer.
+
+Loads DimSearchTerm.csv and builds a nested structure:
+    {PrimaryDirectorate: {Search_Term: [drug_fragment, ...]}}
+
+Also provides get_all_drugs() for the flat "All Drugs" card.
+"""
+
+import csv
+from collections import defaultdict
+from pathlib import Path
+
+from data_processing.diagnosis_lookup import SEARCH_TERM_MERGE_MAP
+
+DATA_DIR = Path(__file__).resolve().parents[2] / "data"
+DIM_SEARCH_TERM_PATH = DATA_DIR / "DimSearchTerm.csv"
+
+
+def build_directorate_tree() -> dict[str, dict[str, list[str]]]:
+    """
+    Build a nested dict from DimSearchTerm.csv grouped by directorate.
+
+    Returns:
+        {
+            "CARDIOLOGY": {
+                "acute coronary syndrome": ["ABCIXIMAB", "CLOPIDOGREL", ...],
+                "atrial fibrillation": ["APIXABAN", "DABIGATRAN", ...],
+                ...
+            },
+            "CLINICAL HAEMATOLOGY": { ... },
+            ...
+        }
+
+    Search_Term values are normalized via SEARCH_TERM_MERGE_MAP
+    (e.g. "allergic asthma" → "asthma"). Drug fragments within
+    merged terms are combined and deduplicated.
+    """
+    # directorate → search_term → set of drug fragments
+    tree: dict[str, dict[str, set[str]]] = defaultdict(lambda: defaultdict(set))
+
+    with open(DIM_SEARCH_TERM_PATH, newline="", encoding="utf-8") as f:
+        reader = csv.DictReader(f)
+        for row in reader:
+            search_term = (row.get("Search_Term") or "").strip().lower()
+            drug_names_raw = row.get("CleanedDrugName") or ""
+            directorate = (row.get("PrimaryDirectorate") or "").strip().upper()
+
+            if not search_term or not directorate:
+                continue
+
+            # Apply merge map (e.g. "allergic asthma" → "asthma")
+            search_term = SEARCH_TERM_MERGE_MAP.get(search_term, search_term)
+
+            fragments = [
+                frag.strip().upper()
+                for frag in drug_names_raw.split("|")
+                if frag.strip()
+            ]
+
+            tree[directorate][search_term].update(fragments)
+
+    # Convert sets → sorted lists and sort at every level
+    result: dict[str, dict[str, list[str]]] = {}
+    for directorate in sorted(tree):
+        result[directorate] = {
+            term: sorted(tree[directorate][term])
+            for term in sorted(tree[directorate])
+        }
+
+    return result
+
+
+def get_all_drugs() -> list[str]:
+    """
+    Return a sorted flat list of all unique drug labels from pathway_nodes level 3.
+
+    Delegates to load_initial_data() which already queries the database.
+    """
+    from dash_app.data.queries import load_initial_data
+
+    data = load_initial_data()
+    return data.get("available_drugs", [])

progress.txt

@@ -132,7 +132,7 @@ Migrating the HCD Analysis frontend from Reflex to Dash (Plotly) + Dash Mantine
 - `src/data_processing/pathway_queries.py` — NEW: shared query functions
 - `dash_app/data/queries.py` — NEW: thin Dash wrapper with DB_PATH resolution
 - `IMPLEMENTATION_PLAN.md` — Task 1.1 marked [x]
-### Committed: (pending)
+### Committed: b71748f "feat: add shared pathway query functions for Dash data access (Task 1.1)"
 ### Patterns discovered:
 - `src/` is on sys.path only when using `uv run` (via .pth file created by setup_dev.py). Running `python` directly won't find `data_processing` module. Always use `uv run python` for testing.
 - `total_records` from `pathway_refresh_log` returns 0 — the refresh log's `source_row_count` field appears empty despite `completed_at` having a value. This is cosmetic — the KPI can use `unique_patients` from chart-data instead.
@@ -145,3 +145,44 @@ Migrating the HCD Analysis frontend from Reflex to Dash (Plotly) + Dash Mantine
 - Remember: drug fragments in CleanedDrugName are UPPERCASE substrings, not exact matches
 ### Blocked items:
 - None
+
+## Iteration 3 — 2026-02-06
+### Task: Phase 1 — Task 1.2 (Build directorate card tree from DimSearchTerm.csv)
+### Why this task:
+- Phase 1 data access layer needs both query functions (done in 1.1) AND the card browser data (this task)
+- Progress.txt from iteration 2 explicitly recommended this task
+- The drawer component (Phase 4) depends on this data structure
+### Status: COMPLETE
+### What was done:
+- Created `dash_app/data/card_browser.py` with two functions:
+  - `build_directorate_tree()` — reads DimSearchTerm.csv, applies SEARCH_TERM_MERGE_MAP, returns nested dict: {PrimaryDirectorate: {Search_Term: [drug_fragment, ...]}}
+  - `get_all_drugs()` — delegates to `load_initial_data()` from queries.py (no SQL duplication)
+- SEARCH_TERM_MERGE_MAP correctly imported from `data_processing.diagnosis_lookup`
+- Asthma variants ("allergic asthma", "severe persistent allergic asthma") merge into single "asthma" entry with combined/deduplicated drug fragments
+- Tree uses sets during construction to deduplicate drug fragments from merged terms, then converts to sorted lists
+### Validation results:
+- Tier 1 (Code): `from dash_app.data.card_browser import build_directorate_tree` — OK
+- Tier 1 (App starts): `from dash_app.app import app` — OK, layout type is MantineProvider
+- Tier 3 (Functional):
+  - `build_directorate_tree()`: 19 directorates, correctly nested dict
+  - CARDIOLOGY has 10 indications, CLINICAL HAEMATOLOGY has many more
+  - Asthma merge verified: only "asthma" present (not "allergic asthma" or "severe persistent allergic asthma"), OMALIZUMAB included in merged drug list
+  - `get_all_drugs()`: 42 drugs from pathway_nodes level 3
+### Files changed:
+- `dash_app/data/card_browser.py` — NEW: directorate tree builder + drug list accessor
+- `IMPLEMENTATION_PLAN.md` — Task 1.2 marked [x]
+### Committed: [pending]
+### Patterns discovered:
+- `get_all_drugs()` uses a lazy import (`from dash_app.data.queries import load_initial_data`) to avoid circular imports since both modules are in `dash_app/data/`
+- Drug fragments in DimSearchTerm.csv are already UPPERCASE in the CSV, but `.upper()` is applied defensively
+- "diabetes" appears twice in DimSearchTerm.csv (DIABETIC MEDICINE and OPHTHALMOLOGY) — this is handled naturally by the directorate grouping (same search_term under two different directorates)
+### Next iteration should:
+- Start Phase 2: Task 2.1 — Header + sidebar components
+- Read `01_nhs_classic.html` to get the exact HTML structure, CSS classes, and SVG icons
+- Create `dash_app/components/header.py` with `make_header()` function
+- Create `dash_app/components/sidebar.py` with `make_sidebar()` function
+- Use CSS classes from nhs.css (`.top-header`, `.sidebar`, etc.) — NOT inline styles
+- Header needs placeholder `html.Span` with IDs for callback updates: `id="header-record-count"`, `id="header-last-updated"`
+- Sidebar needs click targets for drawer open (Drug Selection, Indications items)
+### Blocked items:
+- None