🤖 Trading_Bots_with_Python

A collection of automated trading bots built with Python.
Includes different strategies for algorithmic trading, such as:

---

🧠 Contents

1. DQN Trade Bot

• Strategy: Deep Q-Network with neural networks
• Uses: Keras/Tensorflow for decision making
• File: dqn-crypto-trading-bot

2. Q-Learning Trade Bot

• Strategy: Reinforcement Learning (Q-Learning)
• Goal: Learn to trade based on reward/punishment system.
• File: btc-qlearning-tradebot

3. Pairs Trading Bot

• Strategy: Statistical arbitrage using Z-Score & RSI.
• Timeframes: 15m/1h (Bot2), 1h/1d (Bot1)
• Notifications: Telegram alerts on high-confidence signals
• Files:
  • pair_backtest_bot1.py
  • pair_backtest_bot2.py
  • pair_reporter1h.py, pair_reporter15min.py
  • telegram_helper.py

---

⚙️ Installation

git clone https://github.com/OsSyLab/Trading_Bots_with_Python.git cd Trading_Bots_with_Python pip install -r requirements.txt 🚀 Usage Configure .env for Telegram API keys if using signals

Run bots manually or use a scheduler / deployment (e.g. Render.com)

📬 Telegram Alerts To receive real-time trading signals, configure:

TELEGRAM_TOKEN_BOT1

TELEGRAM_TOKEN_BOT2

TELEGRAM_CHAT_ID

📈 Disclaimer This project is for educational purposes only. Not financial advice. Trade at your own risk.

📬 Contact

📱 Follow me on X (Twitter): @OsSy_Lab https://x.com/OsSy_Lab

MIT License
You are free to use, modify, and distribute this code with attribution.

© 2025 Data Solutions Lab. by Osman Uluhan – All rights reserved.