Markets in Motion, Macro Tape Reader
Fuse macro series with FX and crypto ticks to visualize regime shifts and cross market rhythm.
EURUSD (90d) & Crypto Spot
Build goals
Fuse macro series with FX and crypto ticks to visualize regime shifts and cross market rhythm.
Stack
- Frontend: React 18, Mapbox GL or deck.gl when needed, D3 for charts, TanStack Query, Zustand for local state, plain CSS with design tokens. No runtime CSS frameworks.
- API: Python 3.11 FastAPI or Node 20 Fastify (choose per project spec), Pydantic or Zod models, Uvicorn or Node cluster, OpenAPI JSON at /openapi.json.
- Storage: Redis 7 for hot cache, Postgres 15 with PostGIS for spatial and Timescale extension for time series where needed, S3 compatible bucket for tiles and artifacts.
- Ingest: Async fetchers with ETag or Last Modified, paging, retry with backoff and jitter, circuit breakers, structured logs.
- Tiles: Vector tiles for heavy map layers, long cache with ETag, CDN in front.
- Observability: Prometheus metrics, OpenTelemetry traces, structured logs, freshness and error rate alerts.
- Security: Keys server side only, CORS scoped, token bucket rate limits, audit logs for sensitive actions.
Data sources
Source | Endpoint | Cadence | Access | Auth | Notes |
---|---|---|---|---|---|
FRED | api.stlouisfed.org/fred | frequent | REST JSON, CSV | Key | Macro series |
ECB FX reference | ecb.europa.eu/stats/eurofxref | daily | XML, CSV | None | FX rates |
CoinGecko or Coinbase | api.coingecko.com or api.exchange.coinbase.com | real time | REST, WebSocket | Varies | Crypto market data |
Architecture
Node Fastify or Python FastAPI, lag aware joins, WebSocket tick ingestion with backpressure, downsampled tiles for fast zoom, reproducible snapshot endpoints.
Models
Models are expressed in DB tables and mirrored as API schemas. All timestamps are UTC. All coordinates are WGS84. Stable IDs, soft deletes by valid_to when needed.
- series(id, name, ts, value, source)
- tick(ts, symbol, price, venue)
- event_calendar(ts, label, category)
Algorithms
- Rolling correlations and spiral time mapping
- Tick aggregation to 1 s, 5 s, 1 m candles
- Event overlay for policy or macro prints
API surface
- GET /series?q=&since=&until=&granularity=
- GET /ticks?symbol=&since=&until=&agg=
- GET /snapshot?id=
UI and visualization
- Ticker strip and spiral regime chart
- Correlation matrix with brushing
- Scenario bookmarks that freeze view state
Performance budgets
- Tick ingestion sustained 5k msgs per second per core with backpressure
- Chart interactions p95 under 16 ms
- FCP under 2 s on broadband mid tier laptop.
- API p95 under 300 ms for common list endpoints, p99 under 800 ms.
- Map render p95 frame time under 20 ms for target layers and volumes (document per tool).
- Frontend app code under 180 KB gzip excluding map library.
- API memory under 200 MB under normal load.
Accessibility
- WCAG 2.2 AA, automated axe checks clean, no critical issues.
- Keyboard navigable controls, focus rings visible, ARIA roles correct.
- Color contrast at or above 4.5 to 1, colorblind safe palettes.
- Live regions announce dynamic updates, prefers reduced motion honored.
Evidence pack and quality gates
- Contract tests with recorded cassettes for each provider, JSON Schema validation, drift alarms within 15 minutes.
- Load tests with k6, thresholds enforced in CI for p95 and p99.
- Lighthouse performance and a11y reports stored as CI artifacts.
- Golden tests for algorithms with synthetic datasets and expected outputs.
- Cost workbook with cache hit ratios, tile and API egress estimates, retention policies.
CI configuration
name: ci
on: [push, pull_request]
jobs:
api:
runs-on: ubuntu-latest
services:
postgres:
image: postgis/postgis:15-3.3
ports: [ "5432:5432" ]
env: { POSTGRES_PASSWORD: postgres }
redis:
image: redis:7
ports: [ "6379:6379" ]
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with: { node-version: "20" }
- uses: actions/setup-python@v5
with: { python-version: "3.11" }
- run: pip install -e packages/api[dev] || true
- run: psql postgresql://postgres:postgres@localhost:5432/postgres -f packages/api/src/db/schema.sql || true
- run: pytest -q packages/api/src/tests || true
- run: cd packages/web && npm ci && npm run build && npm test --silent
Risks and mitigations
- Burst handling, validate backpressure and queue sizing
- Timezone reproducibility, store UTC and display localized
Acceptance checklist
- CI green on main, all quality gates met.
- Freshness SLOs met for hot regions or feeds.
- Performance budgets met or better.
- A11y audits pass with zero critical findings.
- Provenance and license panels render correct metadata.
- Runbook covers stale feed handling, provider errors, and key rotation.
Implementation sequence
- Implement series and ticks adapters, schemas
- Join service and spiral chart numeric mapping
- Snapshot API and exports
- Evidence pack with k6 and WS soak tests
Runbook
make up # docker compose up db, redis, api, web
make ingest # start ingest workers for this tool
make tiles # build vector tiles if applicable
make test # unit + contract + golden
make e2e # browser tests