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lmiranda c9cf744d84 feat: Complete Phase 5 dashboard implementation

Implement full 5-tab Toronto Neighbourhood Dashboard with real data
connectivity:

Dashboard Structure:
- Overview tab with livability scores and rankings
- Housing tab with affordability metrics
- Safety tab with crime statistics
- Demographics tab with population/income data
- Amenities tab with parks, schools, transit

Figure Factories (portfolio_app/figures/):
- bar_charts.py: ranking, stacked, horizontal bars
- scatter.py: scatter plots, bubble charts
- radar.py: spider/radar charts
- demographics.py: donut, age pyramid, income distribution

Service Layer (portfolio_app/toronto/services/):
- neighbourhood_service.py: queries dbt marts for all tab data
- geometry_service.py: generates GeoJSON from PostGIS
- Graceful error handling when database unavailable

Callbacks (portfolio_app/pages/toronto/callbacks/):
- map_callbacks.py: choropleth updates, map click handling
- chart_callbacks.py: supporting chart updates
- selection_callbacks.py: dropdown handlers, KPI updates

Data Pipeline (scripts/data/):
- load_toronto_data.py: orchestration script with CLI flags

Lessons Learned:
- Graceful error handling in service layers
- Modular callback structure for multi-tab dashboards
- Figure factory pattern for reusable charts

Closes: #64, #65, #66, #67, #68, #69, #70

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

2026-01-17 11:46:18 -05:00

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Sprint 9-10 - Graceful Error Handling in Service Layers

Context

Building the Toronto Neighbourhood Dashboard with a service layer that queries PostgreSQL/PostGIS dbt marts to provide data to Dash callbacks.

Problem

Initial service layer implementation let database connection errors propagate as unhandled exceptions. When the PostGIS Docker container was unavailable (common on ARM64 systems where the x86_64 image fails), the entire dashboard would crash instead of gracefully degrading.

Solution

Wrapped database queries in try/except blocks to return empty DataFrames/lists/dicts when the database is unavailable:

def _execute_query(sql: str, params: dict | None = None) -> pd.DataFrame:
    try:
        engine = get_engine()
        with engine.connect() as conn:
            return pd.read_sql(text(sql), conn, params=params)
    except Exception:
        return pd.DataFrame()

This allows:

Dashboard to load and display empty states
Development/testing without running database
Graceful degradation in production

Prevention

Always design service layers with graceful degradation - assume external dependencies can fail
Return empty collections, not exceptions - let UI components handle empty states
Test without database - verify the app doesn't crash when DB is unavailable
Consider ARM64 compatibility - PostGIS images may not support all platforms

1.5 KiB Raw Blame History