From 7e63e6ea45f8d85d4ed5a6ec011735ef0d515f01 Mon Sep 17 00:00:00 2001 From: Andrew Charlwood Date: Mon, 9 Feb 2026 14:53:22 +0000 Subject: [PATCH] feat: add desktop packaging (pywebview + PyInstaller) - resource_path.py: frozen/dev path resolution for bundled data files - app_desktop.py: pywebview entry point (Dash in daemon thread) - app.spec: PyInstaller onedir config with data files and hidden imports - Updated queries.py, card_browser.py, app.py to use get_resource_path() - Added pywebview + pyinstaller to project dependencies - Fixed unresolved merge conflict in .gitignore - Removed stale 01_nhs_classic.html and AdditionalAnalytics.md --- .gitignore | 6 - 01_nhs_classic.html | 551 ---------------------------------- AdditionalAnalytics.md | 154 ---------- app.spec | 137 +++++++++ app_desktop.py | 62 ++++ dash_app/app.py | 12 +- dash_app/data/card_browser.py | 5 +- dash_app/data/queries.py | 4 +- pyproject.toml | 2 + src/core/resource_path.py | 18 ++ uv.lock | 260 ++++++++++++++++ 11 files changed, 491 insertions(+), 720 deletions(-) delete mode 100644 01_nhs_classic.html delete mode 100644 AdditionalAnalytics.md create mode 100644 app.spec create mode 100644 app_desktop.py create mode 100644 src/core/resource_path.py diff --git a/.gitignore b/.gitignore index 1bd9d3b..a38a9db 100644 --- a/.gitignore +++ b/.gitignore @@ -36,16 +36,10 @@ logs/*.jsonl .web/ .states/ -<<<<<<< Updated upstream -# SQLite database (will contain local data) -#*.db -#*.sqlite -======= # SQLite databases (except pathways.db which contains pre-computed data) *.db !data/pathways.db *.sqlite ->>>>>>> Stashed changes # Snowflake result cache data/cache/ diff --git a/01_nhs_classic.html b/01_nhs_classic.html deleted file mode 100644 index 6362d0a..0000000 --- a/01_nhs_classic.html +++ /dev/null @@ -1,551 +0,0 @@ - - - - - -HCD Analysis — NHS Classic - - - - - - -
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HCD Analysis
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- Dashboard › Pathway Analysis -
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- 656,247 records - Last updated: 2h ago -
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Unique Patients
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37,842
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across all trusts
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Drug Types
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89
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high-cost drugs tracked
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Total Cost
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£145.2M
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current period spend
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Indication Match
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93%
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GP diagnosis confirmed
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- - -
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- View -
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- Initiated - -
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- Last seen - -
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- Drugs - -
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- Directorates - -
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Patient Pathway Visualization
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Trust → Directorate → Drug → Patient Pathway
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- - - - - - - diff --git a/AdditionalAnalytics.md b/AdditionalAnalytics.md deleted file mode 100644 index a3558de..0000000 --- a/AdditionalAnalytics.md +++ /dev/null @@ -1,154 +0,0 @@ -# Additional Analytics Charts — Implementation Plan - -## UI Approach: Tabbed Chart Area -Extend existing `chart_card.py` tab bar. Currently has Icicle (active), Sankey (disabled), Timeline (disabled). Replace/extend with new tabs. - -## Charts to Build (Priority Order) - -### Tab 1: Icicle (existing — no change) - -### Tab 2: First-Line Market Share — Horizontal Bar Chart -**What**: % of patients starting on each first-line drug, grouped by directorate or indication -**Data source**: `pathway_nodes WHERE level = 3` (drug level). The `colour` column already holds proportion of parent. `value` = patient count. -**Query**: Filter by `chart_type`, `date_filter_id`, optionally `directory` or `trust_name`. Group by `directory`, then show drugs as bars. -**Viz**: Horizontal grouped bar chart. One cluster per directorate/indication (top N), bars within = drugs, length = % of patients. Sorted by total patients desc. NHS blue palette. -**Interaction**: Responds to all existing filters (date, chart type, trust, drug, directorate). Clicking a directorate cluster could filter the icicle. - -### Tab 3: Pathway Cost Effectiveness — Lollipop/Dot Plot -**What**: Compare annualized cost per patient across complete treatment pathways within a directorate/indication. Highlights most vs least cost-effective pathways. -**Data source**: `pathway_nodes WHERE level >= 4` (pathway nodes). Fields: `cost_pp_pa` (annualized), `value` (patient count), `ids` (parse to get pathway sequence), `directory`. -**Calculation**: `cost_pp_pa` is already computed as `(total_cost / patients) * (365 / avg_days)` — this IS the "total cost over N years / N years" the user described. -**Query**: Filter to a specific directorate/indication, then show all pathway variants ranked by `cost_pp_pa`. -**Viz**: Horizontal lollipop chart (dot on stick). Y-axis = pathway label (e.g., "Adalimumab → Secukinumab → Rituximab"), X-axis = £ per patient per annum. Dot size = patient count. Colour gradient: green (cheap) → amber → red (expensive). -**Interaction**: Directorate/indication selector drives which pathways are shown. Could also compare across directorates at the drug level (level 3). - -**Bonus metric — "Pathway Retention" (fewest switches)**: -- For each 2nd-line pathway (e.g., "Drug A → Drug B"), calculate what % of patients escalate to a 3rd line -- Derivation: `value("Drug A → Drug B") - SUM(value("Drug A → Drug B → *"))` = patients who stayed on 2nd line -- Show as a secondary annotation or companion chart: "Drug B retains 72% of patients (no 3rd-line switch needed)" -- This identifies the most effective 2nd-line choices - -### Tab 4: Cost Waterfall — Waterfall Chart -**What**: Break down £ per patient per annum by directorate, showing relative cost contribution -**Data source**: `pathway_nodes WHERE level = 2` (directorate/indication level). Field: `cost_pp_pa`, `value`. -**Viz**: Plotly waterfall chart. Each bar = one directorate's average cost_pp_pa. Sorted highest to lowest. Running reference line optional. Use NHS colours. -**Note**: User specifically wants cost_pp_pa (annualized), not total cost. -**Interaction**: Responds to chart_type toggle, date filter, trust filter. - -### Tab 5: Drug Switching Sankey — Sankey Diagram -**What**: Flow of patients from 1st-line → 2nd-line → 3rd-line drugs -**Data source**: `pathway_nodes WHERE level >= 3`. Parse `ids` to extract drug transition sequences. -**Parsing**: `ids` format at level 4+: `"TRUST - DIRECTORY - DRUG_A - DRUG_A|DRUG_B"`. Split by " - ", take segments from level 3 onwards, split by "|" to get ordered drug list. -**Viz**: Plotly Sankey. Left nodes = 1st-line drugs, middle = 2nd-line, right = 3rd-line. Link width = patient count. Colour by drug or by directorate. -**Interaction**: Filter by directorate/indication to see switching within a specialty. Filter by trust to compare switching patterns. - -### Tab 6: Dosing Interval Comparison — Grouped Bar Chart -**What**: Compare average dosing frequency/weekly interval for a drug across trusts or directorates -**Data source**: Level 3+ nodes, `average_spacing` (HTML string), `average_administered` (JSON array) -**Parsing needed**: - - `average_spacing`: regex to extract weekly interval number from `"given X times with Y weekly interval"` - - `average_administered`: `json.loads()` to get dose counts -**Viz**: Horizontal grouped bars. Y-axis = trust or directorate, X-axis = weekly interval (or total administrations). One colour per drug if comparing multiple. -**Interaction**: Drug selector to pick which drug to compare. Group-by selector (trust vs directorate). - -### Tab 7: Directorate × Drug Heatmap -**What**: Matrix showing which drugs are used in which directorates, cells coloured by patient count or cost_pp_pa -**Data source**: Level 3 nodes, pivot `directory` × drug (parsed from `labels` or `ids`) -**Viz**: Plotly heatmap. Rows = directorates (sorted by total patients), columns = drugs (sorted by frequency). Cell colour = patient count or cost. Hover shows details. -**Interaction**: Toggle between patient count / cost / cost_pp_pa colouring. - -### Tab 8: Treatment Duration Bars -**What**: Compare average treatment durations across drugs within a directorate -**Data source**: Level 3 nodes, `avg_days` field -**Viz**: Horizontal bar chart. Y-axis = drug, X-axis = average days. Colour intensity by patient count. -**Interaction**: Directorate filter drives which drugs are shown. - ---- - -## Data Layer Changes - -### New query functions needed (in `src/data_processing/pathway_queries.py`): - -```python -def get_drug_market_share(db_path, date_filter_id, chart_type, directory=None, trust=None): - """Level 3 nodes grouped by directory, returning drug, value, colour.""" - -def get_pathway_costs(db_path, date_filter_id, chart_type, directory=None): - """Level 4+ nodes with cost_pp_pa, parsed pathway labels, patient counts.""" - -def get_cost_waterfall(db_path, date_filter_id, chart_type, trust=None): - """Level 2 nodes with cost_pp_pa per directorate/indication.""" - -def get_drug_transitions(db_path, date_filter_id, chart_type, directory=None): - """Level 3+ nodes parsed into source→target drug transitions with patient counts.""" - -def get_dosing_intervals(db_path, date_filter_id, chart_type, drug=None): - """Level 3 nodes for a specific drug, parsed average_spacing by trust/directory.""" - -def get_drug_directory_matrix(db_path, date_filter_id, chart_type): - """Level 3 nodes pivoted as directory × drug with value/cost metrics.""" - -def get_treatment_durations(db_path, date_filter_id, chart_type, directory=None): - """Level 3 nodes with avg_days by drug within a directorate.""" -``` - -### Parsing utilities needed: - -```python -def parse_average_spacing(spacing_html: str) -> dict: - """Extract drug_name, dose_count, weekly_interval, total_weeks from HTML string.""" - -def parse_pathway_drugs(ids: str, level: int) -> list[str]: - """Extract ordered drug list from ids column at level 4+.""" - -def calculate_retention_rate(nodes: list[dict]) -> dict: - """For each N-drug pathway, calculate % not escalating to N+1 drugs.""" -``` - ---- - -## Callback Architecture - -Each tab gets its own callback triggered by `chart-data` store + `active-tab` state: - -``` -active-tab change → render selected chart -chart-data change → re-render active chart -``` - -Only the active tab's chart is computed (lazy rendering). Store the active tab in `app-state`. - -New callback per chart type in `dash_app/callbacks/`: -- `market_share.py` — builds bar chart from level 3 data -- `pathway_costs.py` — builds lollipop + retention annotations -- `cost_waterfall.py` — builds waterfall from level 2 data -- `sankey.py` — builds Sankey from parsed transitions -- `dosing.py` — builds grouped bars from parsed spacing -- `heatmap.py` — builds heatmap from pivoted matrix -- `duration.py` — builds bar chart from avg_days - ---- - -## Implementation Order - -1. **Data parsing utilities** — shared parsing for spacing, pathway drugs, retention -2. **Query functions** — one per chart type in pathway_queries.py -3. **Tab infrastructure** — extend chart_card.py with all tab labels, lazy rendering -4. **Charts one at a time** (in priority order): - - First-Line Market Share (simplest, validates the tab pattern) - - Pathway Cost Effectiveness + Retention (user's key insight) - - Cost Waterfall - - Drug Switching Sankey - - Dosing Interval - - Heatmap - - Treatment Duration - ---- - -## Verification - -- Run `python run_dash.py` after each chart addition -- Verify each chart responds to filter changes (date, chart type, trust, directorate, drug) -- Test with both "directory" and "indication" chart types -- Verify icicle chart still works correctly (no regressions) -- Check tab switching is smooth with no unnecessary recomputation diff --git a/app.spec b/app.spec new file mode 100644 index 0000000..52770ff --- /dev/null +++ b/app.spec @@ -0,0 +1,137 @@ +# -*- mode: python ; coding: utf-8 -*- +"""PyInstaller spec for NHS Pathway Analysis desktop app.""" + +import os + +block_cipher = None + +# Project root (where this spec file lives) +ROOT = os.path.abspath(os.path.dirname(SPECPATH)) if 'SPECPATH' in dir() else os.path.abspath('.') + +a = Analysis( + ['app_desktop.py'], + pathex=[os.path.join(ROOT, 'src')], + binaries=[], + datas=[ + ('data/pathways.db', 'data'), + ('data/DimSearchTerm.csv', 'data'), + ('data/defaultTrusts.csv', 'data'), + ('dash_app/assets/nhs.css', 'dash_app/assets'), + ], + hiddenimports=[ + # Dash internals + 'dash', + 'dash.dash', + 'dash.dcc', + 'dash.html', + 'dash.exceptions', + 'dash._utils', + 'dash.dependencies', + 'dash_mantine_components', + # Plotly + 'plotly', + 'plotly.graph_objects', + 'plotly.io', + 'plotly.express', + 'plotly.subplots', + # Data + 'pandas', + 'pandas._libs.tslibs', + 'numpy', + 'sqlite3', + # App packages (src/ on pathex) + 'core', + 'core.config', + 'core.models', + 'core.logging_config', + 'core.resource_path', + 'data_processing', + 'data_processing.database', + 'data_processing.schema', + 'data_processing.pathway_queries', + 'data_processing.parsing', + 'data_processing.diagnosis_lookup', + 'analysis', + 'analysis.pathway_analyzer', + 'analysis.statistics', + 'visualization', + 'visualization.plotly_generator', + # Dash app + 'dash_app', + 'dash_app.app', + 'dash_app.data', + 'dash_app.data.queries', + 'dash_app.data.card_browser', + 'dash_app.callbacks', + 'dash_app.callbacks.filters', + 'dash_app.callbacks.chart', + 'dash_app.callbacks.modals', + 'dash_app.callbacks.navigation', + 'dash_app.callbacks.trust_comparison', + 'dash_app.callbacks.kpi', + 'dash_app.callbacks.trends', + 'dash_app.components', + 'dash_app.components.header', + 'dash_app.components.sub_header', + 'dash_app.components.sidebar', + 'dash_app.components.filter_bar', + 'dash_app.components.chart_card', + 'dash_app.components.footer', + 'dash_app.components.modals', + 'dash_app.components.trust_comparison', + 'dash_app.components.trends', + # pywebview backend + 'webview', + 'clr', + 'pythonnet', + # Flask (Dash's server) + 'flask', + 'flask.json', + 'flask.json.provider', + ], + hookspath=[], + hooksconfig={}, + runtime_hooks=[], + excludes=[ + 'snowflake', + 'snowflake.connector', + 'cli', + 'pytest', + 'tests', + 'tkinter', + 'matplotlib', + 'IPython', + 'jupyter', + ], + win_no_prefer_redirects=False, + win_private_assemblies=False, + cipher=block_cipher, + noarchive=False, +) + +pyz = PYZ(a.pure, a.zipped_data, cipher=block_cipher) + +exe = EXE( + pyz, + a.scripts, + [], + exclude_binaries=True, + name='NHS_Pathway_Analysis', + debug=False, + bootloader_ignore_signals=False, + strip=False, + upx=True, + console=False, # --windowed (no console) + icon=None, +) + +coll = COLLECT( + exe, + a.binaries, + a.zipfiles, + a.datas, + strip=False, + upx=True, + upx_exclude=[], + name='NHS_Pathway_Analysis', +) diff --git a/app_desktop.py b/app_desktop.py new file mode 100644 index 0000000..34cca9c --- /dev/null +++ b/app_desktop.py @@ -0,0 +1,62 @@ +"""Desktop entry point: Dash app inside a pywebview native window.""" + +import sys +import socket +import threading +import time +from pathlib import Path + +# Ensure src/ is on sys.path so that core/, data_processing/, etc. are importable +_src_dir = str(Path(__file__).resolve().parent / "src") +if _src_dir not in sys.path: + sys.path.insert(0, _src_dir) + +import webview +from dash_app.app import app + + +def find_free_port(start: int = 8050) -> int: + """Find the first available port starting from *start*.""" + for port in range(start, start + 100): + with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: + try: + s.bind(("127.0.0.1", port)) + return port + except OSError: + continue + raise RuntimeError("No free port found") + + +def wait_for_server(port: int, timeout: float = 30.0) -> None: + """Block until the Dash server accepts connections.""" + deadline = time.monotonic() + timeout + while time.monotonic() < deadline: + with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as s: + if s.connect_ex(("127.0.0.1", port)) == 0: + return + time.sleep(0.1) + raise TimeoutError(f"Server did not start within {timeout}s") + + +def main() -> None: + port = find_free_port() + + server_thread = threading.Thread( + target=app.run, + kwargs={"debug": False, "port": port, "use_reloader": False}, + daemon=True, + ) + server_thread.start() + wait_for_server(port) + + webview.create_window( + "NHS Pathway Analysis", + f"http://127.0.0.1:{port}", + width=1400, + height=900, + ) + webview.start() + + +if __name__ == "__main__": + main() diff --git a/dash_app/app.py b/dash_app/app.py index 6d0129d..fd3c8a4 100644 --- a/dash_app/app.py +++ b/dash_app/app.py @@ -1,7 +1,10 @@ """Dash application entry point with layout root and state stores.""" +import sys + from dash import Dash, html, dcc import dash_mantine_components as dmc +from core.resource_path import get_resource_path from dash_app.components.header import make_header from dash_app.components.sub_header import make_sub_header from dash_app.components.sidebar import make_sidebar @@ -12,10 +15,11 @@ from dash_app.components.modals import make_modals from dash_app.components.trust_comparison import make_tc_landing, make_tc_dashboard from dash_app.components.trends import make_trends_landing, make_trends_detail -app = Dash( - __name__, - suppress_callback_exceptions=True, -) +_app_kwargs = {"suppress_callback_exceptions": True} +if getattr(sys, "frozen", False): + _app_kwargs["assets_folder"] = str(get_resource_path("dash_app/assets")) + +app = Dash(__name__, **_app_kwargs) app.layout = dmc.MantineProvider( children=[ diff --git a/dash_app/data/card_browser.py b/dash_app/data/card_browser.py index 685a37c..f88e879 100644 --- a/dash_app/data/card_browser.py +++ b/dash_app/data/card_browser.py @@ -9,12 +9,11 @@ Also provides get_all_drugs() for the flat "All Drugs" card. import csv from collections import defaultdict -from pathlib import Path +from core.resource_path import get_resource_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" +DIM_SEARCH_TERM_PATH = get_resource_path("data/DimSearchTerm.csv") def build_directorate_tree() -> dict[str, dict[str, list[str]]]: diff --git a/dash_app/data/queries.py b/dash_app/data/queries.py index a088966..e6af843 100644 --- a/dash_app/data/queries.py +++ b/dash_app/data/queries.py @@ -5,9 +5,9 @@ Resolves the database path relative to this file's location and delegates to the shared functions in src/data_processing/pathway_queries.py. """ -from pathlib import Path from typing import Optional +from core.resource_path import get_resource_path from data_processing.pathway_queries import ( load_initial_data as _load_initial_data, load_pathway_nodes as _load_pathway_nodes, @@ -33,7 +33,7 @@ from data_processing.pathway_queries import ( get_trend_data as _get_trend_data, ) -DB_PATH = Path(__file__).resolve().parents[2] / "data" / "pathways.db" +DB_PATH = get_resource_path("data/pathways.db") def load_initial_data() -> dict: diff --git a/pyproject.toml b/pyproject.toml index d233c11..405f449 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -13,6 +13,8 @@ dependencies = [ "pillow>=10.0.0", "plotly>=5.15.0", "pyarrow>=20.0.0", + "pyinstaller>=6.18.0", + "pywebview>=6.1", "snowflake-connector-python>=3.0.0", "tomli>=2.0.0", ] diff --git a/src/core/resource_path.py b/src/core/resource_path.py new file mode 100644 index 0000000..d5fbb09 --- /dev/null +++ b/src/core/resource_path.py @@ -0,0 +1,18 @@ +"""Resolve file paths for both development and PyInstaller frozen modes.""" + +import sys +from pathlib import Path + + +def get_resource_path(relative_path: str) -> Path: + """Return absolute path to a bundled resource. + + In frozen mode (PyInstaller), resolves from sys._MEIPASS. + In dev mode, resolves from the project root (3 parents up from this file: + src/core/resource_path.py → src/core → src → project root). + """ + if getattr(sys, "frozen", False): + base = Path(sys._MEIPASS) + else: + base = Path(__file__).resolve().parents[2] + return base / relative_path diff --git a/uv.lock b/uv.lock index a812a72..bc7bd20 100644 --- a/uv.lock +++ b/uv.lock @@ -5,6 +5,15 @@ resolution-markers = [ "python_full_version < '3.11'", ] +[[package]] +name = "altgraph" +version = "0.17.5" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/7e/f8/97fdf103f38fed6792a1601dbc16cc8aac56e7459a9fff08c812d8ae177a/altgraph-0.17.5.tar.gz", hash = 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