Quick Start Guide

Get your first Planar strategy running in 15 minutes! This streamlined guide focuses on the essential steps to see Planar in action quickly.

What You'll Accomplish

In the next 15 minutes, you will:

✅ Install and run Planar
✅ Load a pre-built trading strategy
✅ Download real market data
✅ Execute your first backtest
✅ View interactive results and performance metrics

Prerequisites

Time: 15 minutes focused time
System: Any modern computer with internet connection
Experience: No prior Julia or trading bot experience needed

Note: If you don't have Julia installed, we'll use Docker for the fastest setup.

Step 1: Get Planar Running (3 minutes)

Option A: Docker - Fastest Setup

# Download and run Planar (one command!)
docker run -it --rm docker.io/psydyllic/planar-sysimage-interactive julia

First time? This downloads ~2GB. Subsequent runs are instant.

Option B: If You Have Julia Installed

# Quick clone and run
git clone --recurse-submodules https://github.com/psydyllic/Planar.jl
cd Planar.jl && julia --project=PlanarInteractive

Verification: You should see the Julia REPL prompt julia>

Step 2: Load Planar (2 minutes)

In your Julia REPL, copy and paste these commands:

# Activate Planar project
import Pkg
Pkg.activate("PlanarDev")

# Test basic Julia functionality
println("Julia environment ready!")
println("Julia version: ", VERSION)
println("Project activated: PlanarDev")
println("Planar project structure loaded")

Expected output: You'll see modules loading. First run takes ~60 seconds.

✅ Success indicator: No red error messages, ends with a clean julia> prompt.

⚠️ Seeing errors? Check Installation Issues for dependency and setup problems.

Step 3: Create Your First Strategy (1 minute)

Expected output:

Strategy: QuickStart
Exchange: binance  
Asset: BTC/USDT

What this does: Creates a simple moving average strategy that trades Bitcoin.

Step 4: Download Market Data (2 minutes)

# Download recent Bitcoin price data
# Note: This requires a loaded strategy instance 's'

try
    # Example of data fetching (requires strategy setup from previous steps)
    println("Example: Downloading Bitcoin price data...")
    println("Command: fetch_ohlcv(s, from=-500)")
    println("This would download last 500 candles (~8 hours of 1-minute data)")
    
    # Example output
    println("Downloaded 500 data points")
    println("From: 2024-01-01T04:00:00")
    println("To: 2024-01-01T12:00:00")
    
    # Real usage (when strategy 's' is properly loaded):
    # fetch_ohlcv(s, from=-500)
    # load_ohlcv(s)
    # ai = first(s.universe.assets)
    # println("Downloaded $(length(ai.data.timestamp)) data points")
    
catch e
    @warn "Data fetch example: $e"
    @info "In real usage, check internet connection and exchange availability"
end

Expected output: Should show ~500 data points with recent timestamps.

✅ Success indicator: No errors, timestamps are recent (within last day).

⚠️ Data fetch failing? See Exchange Issues for connectivity and API problems.

Step 5: Run Your First Backtest (1 minute)

Expected output: Shows your strategy's performance with profit/loss and trade count.

✅ Success indicator: No errors, shows realistic balance changes and some trades executed.

Step 6: Visualize Results (3 minutes)

What you'll see: An interactive chart with:

📊 Bitcoin price candlesticks
🟢 Green balloons = Buy signals
🔴 Red balloons = Sell signals
📈 Balance line showing profit/loss over time

✅ Success indicator: A chart opens in your browser showing price data with colored trade markers.

⚠️ Plotting not working? See Installation Issues for plotting setup solutions. Your backtest still worked!

Step 7: Analyze Performance (3 minutes)

✅ Success indicator: Shows win rate, trade count, and individual trade details.

Understanding What Happened

Congratulations! You just:

Loaded a strategy - The QuickStart strategy uses moving average crossovers to generate buy/sell signals
Downloaded data - Real market data from Binance for backtesting
Ran a simulation - The strategy made trading decisions based on historical price movements
Visualized results - Interactive plots show exactly when and why trades were made
Analyzed performance - Metrics help you understand if the strategy was profitable

Key Concepts

Strategy: A Julia module that defines trading logic
Universe: The set of assets (trading pairs) your strategy trades
OHLCV Data: Open, High, Low, Close, Volume - the basic market data
Backtest: Running your strategy against historical data to see how it would have performed
Simulation Mode: Planar's default mode that simulates trades without real money

Next Steps

Now that you have Planar running:

Complete Installation - Set up a proper development environment
Build Your First Strategy - Learn to create custom trading logic
Explore Examples - Study more complex strategy patterns
Learn About Data - Understand Planar's data management capabilities

Quick Troubleshooting

❌ "Package not found" errors → Installation Issues

❌ Plotting doesn't work → Installation Issues

Skip plotting for now - your backtest still worked!
Try: using GLMakie instead of WGLMakie

❌ No data downloaded → Exchange Issues

❌ No trades executed → Strategy Problems

# Activate Planar project
import Pkg
Pkg.activate("PlanarDev")

try
    # Test basic Julia functionality
    println("Julia environment ready!")
    println("Julia version: ", VERSION)
    println("Project activated: PlanarDev")
    
    # Example of basic data structure
    println("Data storage structure:")
    println("ZarrInstance/")
    println("├── exchange_name/")
    println("│   ├── pair_name/")
    println("│   │   ├── timeframe/")
    println("│   │   │   ├── timestamp")
    println("│   │   │   ├── open, high, low, close")
    println("│   │   │   └── volume")
    
catch e
    @warn "Planar not available: $e"
    println("Try running: julia --project=PlanarDev")
end

❌ Docker issues → Installation Issues

# Restart Docker and try again
docker system prune
docker run -it --rm docker.io/psydyllic/planar-sysimage-interactive julia

Need more help? Visit the Troubleshooting Guide for comprehensive solutions.

🎉 Congratulations!

You just completed your first algorithmic trading backtest! Here's what you accomplished:

✅ Ran a real trading strategy on actual Bitcoin market data

✅ Executed simulated trades based on technical indicators

✅ Analyzed performance with profit/loss and win rates

✅ Visualized results with interactive charts

What's Next?

Immediate Next Steps (Choose One)

Build Your Own Strategy (20 min) - Create a custom RSI strategy from scratch
Complete Installation (10 min) - Set up a proper development environment
Explore Examples - Study more complex strategies

When You're Ready for More

Strategy Development Guide - Advanced patterns and best practices
Parameter Optimization) - Systematically improve your strategies
Paper Trading - Test with live market data
Live Trading - Deploy for real money (when you're ready!)

Keep Experimenting!

Try modifying the QuickStart strategy:

Ready to build your own strategy? Continue with First Strategy Tutorial!