Prumo

Economic indicators dashboard built with FastAPI + DuckDB + ECharts, serving 11 interactive sections with data from 9 official statistical sources.

Open-source docs

• �️ Documentation Map — Quick navigation guide for all resources
• �📚 Full Documentation Index — Central guide to all project docs
• Contribution guide: CONTRIBUTING.md
• Formal source registry: SOURCES.md
• Design resources: docs/design/ — design inspiration notes and open-source implementations (no copyrighted book files)
• AI agent guidelines: copilot-instructions.md

Português (pt-PT)

Documentação complementar em português está disponível em docs/ e em notas de projeto como SETUP_NOTES.md. O README principal mantém-se em inglês para o público open-source internacional.

Architecture

prumo/
├── app/                          # FastAPI application
│   ├── main.py                   # App entrypoint, CORS, static mount, healthcheck
│   ├── config.py                 # Environment variables and paths
│   ├── database.py               # Thread-safe DuckDB connection pool
│   ├── constants/                # Static data (catalog, events, country lists)
│   │   ├── catalog.py            # CATALOG — 9 sources, ~380 indicators
│   │   ├── events.py             # CHART_EVENTS, BRIEFING/SUMMARY indicator lists
│   │   ├── countries.py          # COMPARE_COUNTRIES, COMPARE_DATASETS
│   │   └── mappings.py           # USED_IN, FRED_SERIES, WB_CODES, SOURCE_META
│   ├── routes/
│   │   ├── api.py                # /api/* endpoints (thin handlers → services)
│   │   └── pages.py              # GET / — serves dashboard via Jinja2
│   └── services/                 # Business logic, one module per section
│       ├── helpers.py            # Shared: YoY, trend, sparkline, period utils
│       ├── resumo.py             # Resumo KPIs
│       ├── industria.py          # Industrial production (IPI)
│       ├── energia.py            # Energy (REN, E-REDES, DGEG)
│       ├── emprego.py            # Employment (IEFP, INE)
│       ├── macro.py              # Macro indicators (GDP, inflation, trade)
│       ├── ficha.py              # Data sheet / DB stats
│       ├── fosso.py              # EU convergence gap
│       ├── produtividade.py      # Productivity metrics
│       ├── analysis.py           # Automated trend analysis
│       ├── explorador.py         # Data explorer catalog
│       ├── series.py             # Generic time series queries + country compare
│       └── briefing.py           # Auto-generated briefing + summary
├── templates/
│   └── dashboard.html            # SPA shell (Jinja2, hash router, ECharts)
├── static/
│   ├── css/
│   │   ├── swd-theme.css         # Storytelling with Data theme
│   │   └── sections.css          # Section-specific styles
│   └── js/
│       ├── app.js                # Hash router + lazy section loading
│       ├── api.js                # Fetch wrappers with 5-min cache
│       ├── swd-charts.js         # SWD chart factory (ECharts)
│       └── sections/             # 11 section initializers (one per tab)
├── collectors/                   # Data source clients (CLI tools)
│   ├── ine.py                    # INE — Instituto Nacional de Estatística
│   ├── eurostat.py               # Eurostat
│   ├── fred.py                   # FRED — Federal Reserve Economic Data
│   ├── oecd.py                   # OECD
│   ├── bportugal.py              # Banco de Portugal
│   ├── ren.py                    # REN — Rede Energética Nacional
│   ├── eredes.py                 # E-REDES — electricity distribution
│   ├── dgeg_fuel_api.py          # DGEG — fuel prices
│   └── worldbank.py              # World Bank
├── stats_lib/                    # Shared data layer for collectors
├── scripts/
│   ├── cae-collect               # Main collection orchestrator
│   └── cae-v4-backfill.py        # Historical data backfill
├── analise-content.html          # Pre-rendered analysis content
├── analise-metadata.json         # Analysis metadata
├── requirements.txt              # Python dependencies
└── Dockerfile                    # Python 3.12 + uvicorn

Data Sources

Source	Provider	Data
INE	Instituto Nacional de Estatística	Industrial production, employment, GDP, trade
Eurostat	European Commission	Cross-country comparisons (manufacturing, GDP, unemployment)
FRED	Federal Reserve Bank of St. Louis	US interest rates, global benchmarks
OECD	Organisation for Economic Co-operation	Composite leading indicators, productivity
BdP	Banco de Portugal	Monetary/financial indicators
REN	Rede Energética Nacional	Electricity consumption/production
E-REDES	Electricity distribution	Grid distribution data
DGEG	Direcção-Geral de Energia e Geologia	Fuel prices
World Bank	World Bank Group	Long-term development indicators

For provider URLs, cadence and terms/caveats notes, see SOURCES.md.

Dashboard Sections

Section	Route	API	Description
Resumo	#resumo	/api/resumo	Overview KPIs with sparklines and trends
Indústria	#industria	/api/industria	Industrial Production Index (IPI) by sector
Europa	#europa	/api/europa	PT vs EU country comparisons
Energia	#energia	/api/energia	Energy consumption and production
Emprego	#emprego	/api/emprego	Employment, unemployment, job offers
Macro	#macro	/api/macro	GDP, inflation, trade balance
Análise	#analise	/api/analysis	Automated trend analysis
Fosso	#fosso	/api/fosso	EU convergence gap
Produtividade	#produtividade	/api/produtividade	Labour productivity metrics
Explorador	#explorador	/api/explorador	Data explorer (all indicators)
Ficha Técnica	#ficha	/api/ficha	Data sheet, DB stats, sources

API Endpoints

All endpoints are under /api/ and return JSON.

Endpoint	Method	Parameters	Description
/api/resumo	GET	—	Summary KPIs
/api/industria	GET	period (int, default 5)	IPI sectors data
/api/europa	GET	dataset, countries, months, indicator, source, since	Country comparison
/api/energia	GET	—	Energy data
/api/emprego	GET	—	Employment data
/api/macro	GET	—	Macro indicators
/api/ficha	GET	—	DB stats and source metadata
/api/fosso	GET	—	EU convergence gap
/api/produtividade	GET	—	Productivity metrics
/api/analysis	GET	—	Automated trend analysis
/api/explorador	GET	—	Full indicator catalog
/api/briefing	GET	—	Auto-generated briefing
/api/summary	GET	—	Executive summary
/api/series	GET	source, indicator, from, to	Raw time series query
/api/compare	GET	dataset, countries, months, indicator, source, since	Country comparison (alias for europa)
/api/data	GET	—	Full dataset dump
/api/kpis	GET	—	Latest value per indicator
/api/catalog	GET	—	CATALOG enriched with DB stats
/api/events	GET	—	Historical event markers
/healthz	GET	—	Health check
/docs	GET	—	Swagger UI (auto-generated)

Environment Variables

Variable	Default	Description
CAE_DB_PATH	/data/cae-data.duckdb	Path to main DuckDB database
CAE_PORT	8080	Server port
CAE_BASE_PATH	""	URL base path (for subpath serving)
SKILLS_DIR	/home/node/.openclaw/workspace/skills/cae-reports	Path to OpenClaw skills directory
TZ	—	Timezone (from compose)

Local server-env workflow (non-commit)

For machine-specific setup, use a local folder at stacks/jarbas/images/prumo/server-env/.

• server-env/ is intentionally ignored by git and must never be committed.
• Keep all local-only links/files inside server-env/ (for example symlinks to root-level resources such as .bash_aliases, .env, and selected folders under md/).
• Preferred pattern is symlink-based references from server-env/ so local server context is available without changing tracked deployment/configuration files.

Example local setup:

mkdir -p stacks/jarbas/images/prumo/server-env
ln -s ../../../../../.bash_aliases stacks/jarbas/images/prumo/server-env/bash_aliases
ln -s ../../../../../.env stacks/jarbas/images/prumo/server-env/env
ln -s ../../../../../md stacks/jarbas/images/prumo/server-env/md

This workflow is local-only and does not change compose behavior or deployment semantics.

Data Volume & First-Run Initialization

On its first run, the container will automatically initialize the /data volume with default configuration (site.json) and ideology defaults if they don't already exist. The DuckDB database is not included in the image; if one is not mounted, the system will place a README-DB.txt indicating that data needs to be populated via the collection scripts or mounted externally. This ensures safe, idempotent bootstrapping without overwriting existing data.

Deployment

The dashboard runs as a Docker container behind Traefik reverse proxy.

Compose layering (Phase 2)

Prumo is now split into two compose layers under stacks/jarbas/compose/:

• prumo.base.yml: portable/OSS app defaults (build, runtime env, healthcheck).
• prumo.yml: server override (Traefik routes, proxy cert chain, server networks, bind mounts used on this host).

The stack loader in stacks/jarbas/compose.yml includes base first and override second so current server behavior remains unchanged while keeping a reusable base.

Build and deploy

dc-jarbas-up cae-dashboard

Routes

• Primary: https://cae.joao.date — direct access
• Subpath: https://joao.date/dados — served under subpath with Traefik StripPrefix

The subpath route uses Traefik's StripPrefix middleware which sets X-Forwarded-Prefix: /dados. The app reads this header to inject the correct BASE_PATH into the template, so all static asset and API URLs resolve correctly.

Collect data

docker exec cae-dashboard ./scripts/cae-collect

Technical Notes

• Single worker: Uvicorn runs with --workers 1 because DuckDB connections are not thread-safe. FastAPI's thread pool handles concurrent requests via per-thread connection reuse.
• No auth: Dashboard is public (chain-no-auth@file middleware in Traefik).
• SPA routing: The frontend uses hash-based routing (#section). All navigation is client-side; the server only serves the single HTML shell.
• Chart library: ECharts 5.5.0 (CDN) with a custom SWD (Storytelling with Data) theme.
• Caching: api.js caches API responses in memory for 5 minutes to reduce DB load during tab switching.
• Database: DuckDB in read-only mode. Data is collected externally by the cae-collect script and written to the database separately.