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Getting Started with GitFlow Analytics

Welcome! This section will help you get GitFlow Analytics up and running quickly.

🚀 Quick Path to Success

1. Installation

First, install GitFlow Analytics on your system: → Installation Guide

2. Quick Tutorial

Run through a 5-minute tutorial to see GitFlow Analytics in action: → Quick Start Tutorial

3. Your First Analysis

Analyze your first repository and understand the output: → Your First Analysis

📋 What You'll Learn

By the end of this section, you'll be able to:

✅ Install GitFlow Analytics on your system
✅ Configure basic authentication (GitHub tokens)
✅ Run your first repository analysis
✅ Understand the generated reports
✅ Interpret key metrics and insights

🎯 Prerequisites

Before you begin, make sure you have:

Python 3.8+ installed on your system
Git installed and accessible from command line
GitHub account with repositories you want to analyze
Basic familiarity with command-line tools

⏱️ Time Investment

Installation: 5-10 minutes
Quick Tutorial: 5 minutes
First Analysis: 10-15 minutes
Total: ~20-30 minutes

🤔 Need Help?

If you run into issues during setup:

🔄 What's Next?

After completing the getting started guide, you might want to:

Customize Configuration - Learn about advanced options
Enable ML Features - Set up machine learning categorization
Explore Examples - See real-world usage scenarios
Set Up Organization Analysis - Analyze multiple repositories

Ready to begin? Start with Installation!