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Series 2: Skeleton of the Bot

🎯 Focus: Building the Core Loop

Now that we have the ability to fetch data from YouTube, let's build the core structure of our bot. Think of this as creating the skeleton - the fundamental architecture that everything else will hang on.

📚 Topics Covered

Structuring Code Cleanly

  • Organize code into modules and classes
  • Separation of concerns (API interaction, comment parsing, reply logic)
  • Project structure best practices
  • Configuration management

Parsing Fetched Comments

  • Extract relevant information from raw comment data
  • Filter comments (by date, video, user, etc.)
  • Handle different comment formats and edge cases
  • Clean and normalize data

Setting up State Management

  • Database vs. local state approaches
  • Choosing the right persistence strategy
  • Schema design for tracking processed comments
  • Preventing duplicate replies

Writing a Dummy Text Replier

  • Create a simple rule-based reply generator
  • Test the reply pipeline end-to-end
  • Placeholder for future AI-powered replies
  • Error handling and logging

🚀 What You'll Build

By the end of this series, you'll have: - ✅ A well-structured bot application - ✅ Comment parsing and filtering logic - ✅ State management system to track processed comments - ✅ A complete (albeit simple) bot loop that runs without errors

🏗️ Architecture Overview

YouTube API
    ↓
Fetch Comments
    ↓
Parse & Filter
    ↓
Check State (Already Replied?)
    ↓
Generate Reply (Dummy)
    ↓
Post Reply
    ↓
Update State

📝 Prerequisites

  • Completion of Series 1 (YouTube API Setup)
  • Comfortable with Python data structures
  • Basic database or file I/O knowledge

🎬 Watch & Follow Along

This series builds directly on Series 1. Keep your API credentials handy and follow the video to implement each component.

Next Step: After completing this series, you'll have a working bot skeleton. In Series 3, we'll replace the dummy replies with AI-powered responses.