Trading: Data Cloud + Broker

Get a Datafye Data Cloud with broker connectivity running in under 5 minutes. Connect your algos to synthetic market data and Alpaca paper trading.

What you'll have:

• Data Cloud with synthetic market data

• Broker Connector configured for Alpaca paper trading

• Your algo trading on paper account

Prerequisites:

• Docker Desktop installed and running

• 8GB+ RAM available

• Alpaca paper trading account (free - sign up here)

• Python 3.7+ (optional - for testing)

Windows users: You need WSL to install the CLI. Click here for instructions

Setting up WSL for Windows

If you don't already have WSL installed, follow these steps:

1. Install WSL: Open PowerShell or Windows Command Prompt in administrator mode and run:

   wsl --install

   This will install Ubuntu by default.

2. Restart your computer when prompted

3. Launch WSL: Open the Start menu, search for "Ubuntu" (or your chosen Linux distribution), and click to launch

4. Complete initial setup: Create a username and password when prompted

Once WSL is installed and running, continue with the installation instructions below (WSL provides a Linux environment, so follow the Linux instructions).

For more details, see Microsoft's WSL installation guide.

Tip: Consider using Windows Terminal for a better terminal experience.

Step 1: Install the Datafye CLI

curl -fsSL https://downloads.n5corp.com/datafye/cli/latest/install.sh | sudo bash

Verify installation:

datafye

Expected output:

Datafye -- Institutional Grade Trading for Everyone

Datafye CLI is Datafye's command line tool. Try:

datafye help commands        list the top level commands
datafye help <command>       help on a specific command

No sudo access? See CLI Installation for alternative installation methods.

Step 2: Get Alpaca Credentials

1. Sign up for a free Alpaca paper trading account at alpaca.markets

2. Navigate to your paper trading dashboard

3. Copy your API Key ID and Secret Key

Set as environment variables:

export ALPACA_API_KEY="your-api-key-id"
export ALPACA_SECRET_KEY="your-secret-key"

Step 3: Download Deployment Descriptor

curl -o quickstart.yaml https://downloads.n5corp.com/datafye/quickstarts/latest/trading-data-cloud-broker.yaml

This descriptor configures:

• Synthetic dataset with 10 symbols:

  • Tech: AAPL, MSFT, GOOGL, AMZN, NVDA

  • Growth: TSLA, META, NFLX, AMD, INTC

• Trades and quotes (tick data)

• 1-minute OHLC bars

• 90 days of historical data

• Alpaca Broker Connector (paper trading mode)

• No additional API keys required (besides Alpaca)

Step 4: Provision the Environment

datafye trading local provision --descriptor quickstart.yaml

Sneak Preview Note: This quickstart shows the expected workflow and interface. During the preview period, provisioning is not yet available and this command will display a "not yet implemented" message. This is expected behavior for the preview.

Expected Output (when available):

🚀 Provisioning Datafye Trading (Data Cloud + Broker)...
✓ Validating descriptor
✓ Pulling Docker images
✓ Starting Data Cloud
✓ Starting Broker Connector
✓ Connecting to Alpaca (Paper)
✓ Loading synthetic data

✅ Environment ready!

📊 Endpoints:
   Data Cloud:  http://localhost:8080/datafye-api/v1
   Broker API:  http://localhost:8082/broker-api/v1

🔗 Broker: Alpaca (Paper Trading)

Provisioning takes 3-5 minutes.

What Just Happened?

The deployment descriptor configured:

• Data Cloud - Normalized market data service with REST and WebSocket APIs

• Broker Connector - Integration with Alpaca for paper trading

• Synthetic Dataset - 10 symbols with 90 days of historical data:

  • Tech: AAPL, MSFT, GOOGL, AMZN, NVDA

  • Growth: TSLA, META, NFLX, AMD, INTC

• Data Types - Trades, quotes, and 1-minute OHLC bars

What's running:

• Data Cloud container at http://localhost:8080

• Broker Connector container at http://localhost:8082

• Connected to your Alpaca paper trading account

• Ready to accept trading algos that consume data and place orders

About the Synthetic Dataset: The Synthetic dataset attempts to generate realistic market data and is appropriate for demo and API testing purposes. It is NOT suitable for actual algo development - use real market data providers (Polygon, Alpaca, etc.) for developing and validating production algorithms.

Step 5: Verify Services

Option A: Python Test Script (Recommended)

# Download test script (verifies Data Cloud, Broker Connector, and Alpaca connection)
curl -o test-trading.py https://downloads.n5corp.com/datafye/quickstarts/test-trading.py
python3 test-trading.py

Output:

✓ Data Cloud is healthy
✓ Broker Connector is healthy
✓ Connected to Alpaca (Paper)
✓ Account balance: $100,000.00
✓ Current positions: None
✓ Market data streaming: AAPL @ $195.34

Option B: CLI Commands

# Check services
curl http://localhost:8080/datafye-api/v1/health
curl http://localhost:8082/broker-api/v1/health

# Check broker connection
curl http://localhost:8082/broker-api/v1/account

# View account balance
datafye trading broker account

Step 6: Run Paper Trading Algo

Download and run the example paper trading algo:

# Download paper trading algo (simple momentum strategy that places orders via Alpaca)
curl -o paper-trade-algo.py https://downloads.n5corp.com/datafye/quickstarts/paper-trade-algo.py
python3 paper-trade-algo.py

Output:

🔌 Connected to Datafye Data Cloud and Broker
📊 Subscribing to AAPL bars...
🟢 BUY signal: AAPL @ $195.34
   → Placed order: BUY 10 shares AAPL
✓ Order filled: 10 AAPL @ $195.35
💼 Position: +10 AAPL (avg: $195.35)

Your algo is now paper trading through Alpaca!

Monitor Your Trades

# View current positions
datafye trading broker positions

# View order history
datafye trading broker orders

# View account activity
datafye trading broker activity

Manage Your Deployment

datafye trading local stop        # Stop all services
datafye trading local start       # Restart all services
datafye trading local deprovision # Remove deployment

Next Steps

Build custom trading algos:

• Building Your First Algo - Own Container

• Paper Trading Your Algo

Understand broker integration:

• Broker Connector Concepts

• Broker Descriptors Reference

Add backtesting:

• Trading: Full Stack - Add backtesting and AI assistance

Move to live trading:

• Transitioning to Live Trading

Troubleshooting

Docker not running: Start Docker Desktop and retry.

Broker connection failed: Verify your ALPACA_API_KEY and ALPACA_SECRET_KEY environment variables are set correctly.

Port conflicts: Stop conflicting services or see CLI Reference for custom ports.

Order rejected: Check your Alpaca account status and ensure paper trading is enabled.

Last updated: 2025-01-23