🂡 Blackjack Simulation (Python + JavaScript)

Welcome to my Blackjack simulation project! This repository contains both a Python-based simulation and a JavaScript browser game interface.

This project was originally inspired while I was practicing a Kaggle exercise related to blackjack: 🔗 https://www.kaggle.com/code/sunlongngouv/exercise-working-with-external-libraries/edit

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🎯 Project Purpose

• Simulate a complete Blackjack game between a human player and an automated dealer
• Practice algorithmic thinking and randomization using Python
• Build a functional static web version using HTML/CSS/JavaScript
• Experiment with probability-driven decisions and dynamic Ace evaluation
• Host and publish the game through GitHub Pages

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🃏 Game Rules

The following standard Blackjack rules apply:

• A deck contains 52 cards
• Numbered cards = face value
• J, Q, K = 10
• Ace = 11 or 1 depending on total
• Both player and dealer start with two cards
• Player actions:
  • Hit → draw another card
  • Stand → stop drawing
• If total > 21 → BUST
• Closest to 21 wins
• Dealer wins if scores tie

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🤖 Dealer (AI) Logic

The dealer follows deterministic decision logic:

Decision Rules

• If total < 17 → dealer hits
• If total ≥ 17 → dealer stands
• Aces are dynamically converted:
  • Count as 11 unless total exceeds 21
  • Otherwise count as 1

Example Ace Logic

Hand: {A, A, 9}

• Ace (11) + Ace (1) + 9 = 21
• Dealer stands

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🧩 Technical Implementation - Python Notebook for CLI Game

Url: https://github.com/SunlongNgouv/blackjack_simulation/blob/master/Blackjack%20Simulation.ipynb

Local file: Blackjack Simulation.ipynb

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🚀 Deployment - UI JS Simulation

Url: https://sunlongngouv.github.io/blackjack_simulation/

Local files: index.html, style.css, script.js

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🧠 Future Enhancements

• Deck memory (prevent card reuse)
• Display visible card history
• Add probabilistic recommendation (e.g., “Best move: Hit”)
• Basic card-counting logic
• Animated chip and bet system
• Multiplayer simulation
• Win-loss statistics tracking

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🙌 Acknowledgments

This project was inspired by the blackjack exercise I practiced on Kaggle: 🔗 https://www.kaggle.com/code/sunlongngouv/exercise-working-with-external-libraries/edit

Thanks to the Kaggle community for motivating this deeper exploration into game logic and probabilistic modelling.

📩 Feedback & Contribution

Feel free to open issues or submit pull requests — feedback and collaboration are welcome!