24 best Python Trading Bot libraries in 2025

Build an end-to-end automated trading application to visualize financial data of stock holdings. Buy/sell stocks automatically using Python trading bot libs.

The key functions of a stock trading bot built using the Python algorithmic trading libraries are getting the data, training the model, entering and exiting trades, placing orders, and getting notified. Through backtesting on historical data and by minimizing human intervention, a Python trading bot can increase the speed of order entry and establish discipline in the volatile stock market to help traders earn profits. Since computer systems react quickly to fluctuating markets, an automated Python-based trading system can produce bids as soon as the defined trading conditions are met.

Browse below to check out the latest and trending Python libraries to build your automated trading bot:

zipline 

• Backtesting and algorithm development framework for trading strategies. 
• Easily integrates with live trading platforms. 
• Provides a range of built-in statistical and risk analysis tools. 

ta-lib 

• Offers over 150 technical analysis indicators. 
• Widely used in financial markets for quantitative analysis. 
• Supports multiple programming languages, including Python. 

freqtrade 

• High-frequency trading bot with a focus on cryptocurrencies. 
• Supports machine learning and AI-based strategy development. 
• Offers an active community and a range of pre-built strategies.

binance-trade-bot 

• Designed specifically for trading on the Binance exchange. 
• Supports various trading pairs and strategies. 
• Offers real-time market data and order execution. 

jesse 

• Python-based framework for cryptocurrency trading strategies. 
• Provides a simple and clean syntax for strategy development. 
• Supports multiple exchanges and backtesting. 

Crypto-Signal 

• Cryptocurrency trading signals and alert system. 
• Offers technical analysis indicators and custom signal creation. 
• Integration with popular cryptocurrency exchanges. 

Binance-volatility-trading-bot 

• Designed for volatility-based trading strategies on Binance. 
• Focuses on profiting from price fluctuations. 
• Offers various trading parameters for customization. 

binance-trader 

• A simple and lightweight Binance trading bot. 
• Supports spot and futures trading on the Binance platform. 
• Suitable for both beginners and experienced traders. 

OctoBot 

• Modular and extensible cryptocurrency trading bot. 
• Provides a web-based dashboard for monitoring and configuration. 
• Supports various technical analysis indicators. 

cointrol 

• Open-source cryptocurrency trading bot with a focus on Bitcoin. 
• Supports multiple exchanges and customizable strategies. 
• Offers risk management and trading performance analysis. 

Cryptocurrency-Trading-Bots-Python-Beginner-Advance 

• A collection of Python trading bot examples for all skill levels. 
• Educational resource with various trading strategies. 
• Suitable for beginners and experienced traders. 

algobot 

• Algorithmic trading bot framework with a range of features. 
• Supports backtesting, live trading, and data analysis. 
• Integrates with various data sources and brokers. 

binance-tutorials 

• Educational resources and tutorials for Binance trading. 
• Covers various aspects of trading on the Binance platform. 
• Suitable for traders looking to learn and improve their skills. 

pybacktest 

• A Python library for backtesting trading strategies. 
• Supports historical price data analysis and strategy optimization. 
• Provides visualizations for performance analysis. 

crypto-trader 

• A simple cryptocurrency trading bot for Bitcoin. 
• Designed for automated trading on various exchanges. 
• Offers basic trading strategies. 

stock-trading-ml 

• Machine learning-based stock trading bot. 
• Uses historical stock data for predictive trading. 
• Suitable for those interested in AI-driven trading. 

tradingview-webhooks-bot 

• A bot that uses TradingView webhooks for automated trading. 
• Integrates with TradingView alerts to trigger trades. 
• Suitable for traders using TradingView for technical analysis. 

crypto-arbitrage 

• Focuses on cryptocurrency arbitrage trading strategies. 
• Aims to profit from price differences on different exchanges. 
• Supports multiple cryptocurrency pairs. 

TensorFlow-Bitcoin-Robot 

• Utilizes TensorFlow for machine learning-based Bitcoin trading. 
• Provides tools for developing and training trading models. 
• Suitable for those with machine learning expertise. 

pyjuque 

• Cryptocurrency trading bot framework with a focus on flexibility. 
• Supports custom strategies and risk management. 
• Designed for traders with coding experience. 

Titan 

• Algorithmic trading bot for various asset classes, including cryptocurrencies. 
• Offers machine learning capabilities and strategy customization. 
• Designed for both beginners and experienced traders. 

PyTrendFollow 

• A trend-following trading bot framework. 
• Focuses on capturing trends in various financial markets. 
• Supports strategy development and live trading. 

Bitcoin-Surge-Trading-Alpha 

• A cryptocurrency trading bot with a focus on capturing surges in Bitcoin prices. 
• Designed for short-term trading strategies. 
• Offers features for risk management and portfolio tracking.

pytrader 

• A simple and lightweight cryptocurrency trading bot. 
• Supports multiple exchanges and basic trading strategies. 
• Suitable for beginners and traders looking for a minimalistic approach. 

FAQ   

1. How to choose a Python trading bot library for backtesting and live trading?   

When choosing a Python trading bot library, consider:- 

1. versatility in strategy development,  

2. access to historical and real-time data, and  

3. support for various order types.  

Seek libraries with intuitive APIs, risk controls, and exchange compatibility. Also, a vibrant community and regular updates are essential for long-term reliability.  

2. Can Python trading bot libraries handle multiple trading pairs?   

Python trading bot libraries are typically flexible and can handle multiple trading pairs. These libraries adapt to diverse markets, including cryptocurrencies, traditional stocks, and more. 

3. How do Python trading bot libraries handle risk management to protect investments?     

Risk management is paramount in Python trading bot libraries. Traders can apply stop-loss, position sizing, and risk controls to protect investments. Users can set preset loss limits, reducing the impact of market downturns. 

4. What tools do Python trading bot libraries provide for performance analysis?   

Python trading bot libraries provide tools for strategy optimization and performance analysis. Traders can backtest their strategies using historical data to fine-tune their algorithms. Performance metrics and visualization tools help assess strategy effectiveness and make informed adjustments.  

5. Can Python trading bot libraries run on cloud servers or require infrastructure?

Python trading bot libraries can be deployed on cloud servers, eliminating hardware needs. This cloud-based approach offers scalability, cost-efficiency, and accessibility for users. Thus making it an attractive option for both beginners and experienced traders.