Skip to main content

Quick Start

Create your first program with the Guido Racing SDK in minutes.

First Program​

1. Create the Project​

mkdir my-racing-app && cd my-racing-app

2. CMakeLists.txt File​

Create a CMakeLists.txt file:

cmake_minimum_required(VERSION 3.20)
project(MyRacingApp)

# Find Guido SDK
find_package(GuidoRacingSDK REQUIRED)

# Create executable
add_executable(my_app main.cpp)

# Link SDK
target_link_libraries(my_app PRIVATE GuidoRacing::guido_racing_sdk)

# C++20 required
set_target_properties(my_app PROPERTIES CXX_STANDARD 20)

3. Source Code (main.cpp)​

Create a main.cpp file:

#include <guido_racing/sdk.hpp>
#include <iostream>

int main() {
    std::cout << "Guido Racing SDK - Quick Start\n";
    
    // Initialize the SDK
    guido_racing::SDK sdk;
    
    std::cout << "SDK Version: " << sdk.version() << "\n";
    std::cout << "✓ SDK initialized successfully!\n";
    
    return 0;
}

4. Build and Run​

mkdir build && cd build
cmake ..
cmake --build .
./my_app

Expected output:

Guido Racing SDK - Quick Start
SDK Version: 1.0.0
✓ SDK initialized successfully!

Load GPS Data​

Example of GPS data import and analysis:

#include <guido_racing/sdk.hpp>
#include <iostream>
#include <vector>

int main() {
    guido_racing::SDK sdk;
    
    // Load a GPX file
    try {
        auto session = sdk.loadGPX("session-spa.gpx");
        
        std::cout << "Session loaded:\n";
        std::cout << "  Duration: " << session.duration() << "s\n";
        std::cout << "  Distance: " << session.distance() << "m\n";
        std::cout << "  Laps detected: " << session.lapCount() << "\n";
        
        // Display lap times
        auto laps = session.getLaps();
        for (size_t i = 0; i < laps.size(); ++i) {
            std::cout << "  Lap " << (i + 1) << ": " 
                      << laps[i].time << "s\n";
        }
        
    } catch (const std::exception& e) {
        std::cerr << "Error: " << e.what() << "\n";
        return 1;
    }
    
    return 0;
}

Analyze a Session​

Complete analysis example with recommendations:

#include <guido_racing/sdk.hpp>
#include <iostream>

int main() {
    guido_racing::SDK sdk;
    
    // Load and analyze
    auto session = sdk.loadGPX("session-spa.gpx");
    auto analysis = sdk.analyzeSession(session);
    
    // Display summary
    std::cout << "Session analysis:\n";
    std::cout << "━━━━━━━━━━━━━━━━━━━━\n";
    std::cout << "Best lap: " << analysis.bestLap().time << "s\n";
    std::cout << "Average lap: " << analysis.averageLap().time << "s\n";
    std::cout << "Consistency: " << analysis.consistency() << "%\n";
    
    // AI Recommendations
    auto recommendations = analysis.getRecommendations();
    
    std::cout << "\n📊 Recommendations:\n";
    std::cout << "━━━━━━━━━━━━━━━━━━━━\n";
    
    for (const auto& rec : recommendations) {
        std::cout << "📍 " << rec.location << "\n";
        std::cout << "   " << rec.message << "\n";
        std::cout << "   Potential gain: " << rec.potentialGain << "s\n";
        std::cout << "   Priority: " << rec.priority << "\n\n";
    }
    
    return 0;
}

Example output:

Session analysis:
━━━━━━━━━━━━━━━━━━━━
Best lap: 127.34s
Average lap: 129.12s
Consistency: 92.5%

📊 Recommendations:
━━━━━━━━━━━━━━━━━━━━
📍 Turn 7 (La Source)
   Braking too early by 12m
   Potential gain: 0.28s
   Priority: High

📍 Exit Turn 15 (Raidillon)
   Late re-acceleration
   Potential gain: 0.15s
   Priority: Medium

Optimal Trajectory​

Calculate and display the ideal trajectory:

#include <guido_racing/sdk.hpp>
#include <iostream>

int main() {
    guido_racing::SDK sdk;
    
    auto session = sdk.loadGPX("session-spa.gpx");
    
    // Calculate optimal trajectory
    auto optimalPath = sdk.calculateOptimalPath(session);
    
    std::cout << "Optimal trajectory calculated\n";
    std::cout << "Points: " << optimalPath.points.size() << "\n";
    std::cout << "Theoretical time: " << optimalPath.theoreticalTime << "s\n";
    
    // Compare with your best lap
    auto bestLap = session.getBestLap();
    auto comparison = sdk.comparePaths(bestLap.path, optimalPath);
    
    std::cout << "\nComparison:\n";
    for (const auto& zone : comparison.differenceZones) {
        std::cout << "  Zone " << zone.name << ": ";
        std::cout << (zone.deviation > 0 ? "+" : "") 
                  << zone.deviation << "m\n";
    }
    
    // Export for visualization
    sdk.exportPathToKML(optimalPath, "optimal-path.kml");
    std::cout << "\nTrajectory exported to optimal-path.kml\n";
    
    return 0;
}

Advanced Configuration​

Customize SDK behavior:

#include <guido_racing/sdk.hpp>

int main() {
    // Custom configuration
    guido_racing::Config config;
    config.gps_frequency = 10; // Hz
    config.smoothing_factor = 0.8;
    config.lap_detection_threshold = 0.95;
    config.enable_ai_coaching = true;
    
    guido_racing::SDK sdk(config);
    
    // Use the configured SDK
    auto session = sdk.loadGPX("session.gpx");
    auto analysis = sdk.analyzeSession(session);
    
    return 0;
}

Next Steps​

Need Help?​