Crypto API (Go)

A lightweight crypto data API written in Go, focused on simplicity, performance, and clarity.

The API is read-only and does not require authentication.

This project aggregates crypto-related data (prices, chains, protocols) from external sources and exposes a clean, versioned HTTP API with in-memory caching and test coverage.

Built as part of Skeletor Labs to demonstrate backend engineering, API design, and Web3 infrastructure skills.

Features

• 🚀 Fast HTTP API: Built with Go's standard library for maximum performance.
• 🧠 Generic Cache: Type-safe in-memory caching using Go Generics (Get[T]/Set[T]).
• 📈 Intelligence Engine: Derived metrics including BTC/M2 Valuation and Statistical Correlation.
• 🧪 Test Driven: High coverage for handlers, engines, and data sources.
• 🔢 API Versioning: Clean routing under /v1.
• 🧼 Standardized Responses: Consistent metadata envelope (meta.updatedAt, meta.cached).
• 🛡️ Multi-Provider Resilience: Price aggregation with automated fallback (Binance → Coinbase → Kraken → CoinGecko).
• 🔌 Unified Data Engine: Standardized HTTP fetching with generic JSON decoding and automated retries.

API Endpoints

All endpoints are versioned under /v1.

Response Metadata
Most endpoints return a standard response envelope containing metadata.

{
  "meta": {
    "updatedAt": "2026-01-31T21:14:00Z",
    "cached": false
  },
  "data": { ... }
}

---

Health Check

GET /v1/health
Intentionally excluded from the standard response format.

Example:

curl http://localhost:8080/v1/health

Response:

{
  "status": "ok"
}

Status code:

200 OK

---

Token Price

GET /v1/price/<token>

• token is case-insensitive, token identifier (e.g., bitcoin) or common ticker symbols (e.g., btc).
• Resilient Sourcing: The API implements a prioritized fallback strategy: Binance → Coinbase → Kraken → CoinGecko.
• Internally normalized to lowercase.
• Returned token-name is always lowercase.

Example:

curl http://localhost:8080/v1/price/bitcoin

Response:

{
  "meta": {
    "updatedAt": "2026-01-31T21:14:00Z",
    "cached": false
  },
  "token": "bitcoin",
  "usd": 87723
}

---

Chains

GET /v1/chains
Returns a list of supported chains with basic metrics.

Example:

curl http://localhost:8080/v1/chains

Response:

{
  "meta": {
    "updatedAt": "2026-01-31T21:14:00Z",
    "cached": false
  },
  "data": [
    {
      "name": "Ethereum",
      "tvl": 123456789,
      "symbol": "ETH"
    }
  ]
}

---

Protocols

GET /v1/protocols

Optional query parameters:

• chain
• category

Example:

curl "http://localhost:8080/v1/protocols?chain=Ethereum"

Response:

{
  "meta": {
    "updatedAt": "2026-01-31T21:14:00Z",
    "cached": false
  },
  "data": [
    {
      "name": "Lido",
      "slug": "lido",
      "tvl": 123456,
      "chain": "Ethereum",
      "category": "Liquid Staking"
    }
  ]
}

---

Bitcoin Fees

GET /v1/bitcoin/fees
Returns recommended Bitcoin transaction fees based on current mempool conditions.

Example:

curl http://localhost:8080/v1/bitcoin/fees

Response:

{
  "meta": {
    "updatedAt": "2026-01-31T21:14:00Z",
    "cached": false
  },
  "fastestFee": 42,
  "halfHourFee": 28,
  "hourFee": 18
}

---

Bitcoin Network

GET /v1/bitcoin/network
Returns live network metrics, including Trend analysis and Halving projections.

Example:

curl http://localhost:8080/v1/bitcoin/network

Response:

{
  "meta": {
    "updatedAt": "2026-02-04T23:40:21Z",
    "cached": false
  },
  "blockHeight": 935051,
  "hashrateTHs": 920496599.65,
  "difficulty": 141668107417558.2,
  "avgBlockTimeSeconds": 719.77,
  "trend": "Stable",
  "halving": {
    "currentBlock": 935051,
    "nextHalvingBlock": 1050000,
    "blocksRemaining": 114949,
    "progressPercent": 45.26,
    "estimatedDate": "2028-09-19T14:22:21Z"
  }
}

trend indicates short-term network behavior:

• Improving
• Stable
• Worsening

---

Bitcoin Mempool

GET /v1/bitcoin/mempool
Returns current Bitcoin mempool congestion metrics.

Example:

curl http://localhost:8080/v1/bitcoin/mempool

Response:

{
  "meta": {
    "updatedAt": "2026-01-31T21:14:00Z",
    "cached": false
  },
  "count": 31468,
  "vsize": 15577951,
  "totalFee": 2587922
}

---

Bitcoin Valuation

GET /v1/bitcoin/valuation
Analyzes Bitcoin price relative to global M2 money supply.

Example:

curl http://localhost:8080/v1/bitcoin/valuation

Response:

{
  "meta": {
    "updatedAt": "2026-02-08T10:30:00Z",
    "cached": false
  },
  "btcPrice": 69133,
  "m2SupplyBillions": 21050.5,
  "ratio": 3.28,
  "description": "Bitcoin is trading at 3.28x relative to M2 liquidity..."
}

---

Bitcoin Correlation

GET /v1/bitcoin/correlation
Calculates the Pearson correlation coefficient between BTC and M2 liquidity over a historical window.

Example:

curl http://localhost:8080/v1/bitcoin/correlation

Response:

{
  "meta": {
    "updatedAt": "2026-02-08T10:30:00Z",
    "cached": true
  },
  "coefficient": 0.87,
  "sampleCount": 730,
  "startDate": "2024-02-08T00:00:00Z",
  "endDate": "2026-02-08T00:00:00Z"
}

---

Notes:

• Data sourced from:
  • mempool.space (Network)
  • Binance, Coinbase, Kraken [High-priority] and CoinGecko [Fallback] (Prices)
  • FRED - Federal Reserve Economic Data (Macro/M2)
• Results are managed via Type-safe Generic In-memory caching.
• Network metrics are aggregated from multiple endpoints:
  • Block height
  • Rolling hashrate (TH/s)
  • Current difficulty
  • Average block time
• Intelligence Layer provides advanced analytics (Valuation & Correlation).

---

Project Structure

├── internal
│   ├── cache        # In-memory cache implementation
│   ├── engine       # Domain-specific logic (Halving, Trend calculations)
│   │   └── bitcoin
│   │       ├── correlation  # Pearson statistical correlation analysis
│   │       ├── valuation    # Fair value metrics (M2/BTC ratio)
│   │       ├── halving      # Scarcity and epoch projections
│   │       └── trend        # Network behavior and sentiment analysis
│   ├── filters      # Domain-level filtering logic
│   ├── httpx        # HTTP handlers
│   ├── middleware   # HTTP middleware
│   ├── models       # API response models
│   └── sources      # Upstream providers
│       ├── macro    # FRED API (M2 Money Supply)
│       ├── market   # Price aggregators (Binance, Coinbase, Kraken, Coingecko)
│       └── bitcoin  # Mempool.space API (Fees, Blocks, Mempool)

Running Locally

Requirements

Go 1.21+

Run the server

go run .

Server will start on:

http://localhost:8080

Running with Docker

1. Ensure you have a .env file with your FRED_API_KEY.
2. Run using Docker Compose:

docker-compose up --build

---

Running Tests

Run all tests:

go test ./...

Run tests with gotestsum:

# Run tests with professional formatting (requires gotestsum)
gotestsum --format pkgname-and-test-fails

---

Design Notes

• Handlers are kept small and focused
• External sources are isolated behind a sources layer
• Cache keys and API outputs are normalized for consistency
• API versioning is handled at the routing layer
• No frameworks, minimal dependencies
• Domain-Driven Engines: Complex business logic (like Halving projections and Trend analysis) is isolated in internal/engine. This keeps handlers slim and makes the core logic easily testable without HTTP concerns.
• Stateful Trends: Network trends are computed using a sliding window buffer, allowing - the API to detect sentiment changes rather than just showing raw snapshots.
• Type Safety: Leverage Go Generics in the cache layer to eliminate manual type assertions and runtime panics.
• Separation of Concerns: Analytics are decoupled from HTTP concerns via the engine layer, ensuring core logic is easily testable.
• Resilience: Upstream failures are handled gracefully with cached fallbacks and standardized error codes.
• Statistical Analysis: The correlation engine implements the Pearson Correlation Coefficient to measure the linear relationship between BTC price and M2 supply over a 730-day rolling window.
• Unified Fetching: Replaced redundant HTTP boilerplate with a centralized, generic FetchJSON[T] engine, reducing codebase size and ensuring consistent timeout/retry policies.
• Price Fallback Strategy: Implemented a prioritized provider loop that ensures price availability even if primary exchanges or aggregators face rate limits or downtime.

---

Status

This project is actively used as an internal data layer and technical showcase.

Planned improvements:

• Derived data (Halving & Trends)
• Intelligence Engine (Valuation & Correlation)
• Type-safe Cache implementation
• Docker support
• Multi-provider price aggregation with automated fallback.
• Unified HTTP/JSON fetching engine.
• Persistence layer for historical snapshots

---

License

MIT