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Freqtrade is a free and open-source crypto trading bot written in Python. It is designed to support all major exchanges and be controlled via Telegram or WebUI. It contains backtesting, plotting, and money management tools as well as strategy optimization by machine learning. Always start by running a trading bot in Dry-run and do not engage money before you understand how it works and what profit/loss you should expect. We strongly recommend you have basic coding skills and Python...

Bitcoin Arbitrage Bot is your all-in-one solution for maximizing crypto trading profits through advanced arbitrage techniques. Designed to identify and execute profitable buy-sell opportunities across multiple exchanges, this bot empowers you to stay ahead in the fast-moving crypto market. Whether you're a seasoned trader or just starting your crypto journey, Bitcoin Arbitrage Bot is the tool you need to automate your trading strategy and achieve consistent results.

...One of the best open-source alternatives to Freqtrade with genuine AI edge: privacy-first self-hosting (no shared API keys), multi-timeframe/symbol backtesting, custom indicators, ML-enhanced signals. Perfect for Python devs, algorithmic traders, high-frequency, trend-following, mean-reversion & arbitrage enthusiasts seeking the top ai crypto trading bot or best crypto trading bot in 2026. Automate your crypto edge — download now & start winning! Join the future of crypto!

TradingVue.js was a hackable charting lib for traders. You could draw literally ANYTHING on top of candlestick charts. If you create trading software, this lib is probably for you. If you like to make custom indicators and think out of the box, this lib is most likely for you. And if you miss the usability of TradingView.com in other open-source libraries and can't stand it, you are definitely in the right place! The process of adding a new indicator is simple, first you define your own data format (should be timestamped though) and display settings. ...

Catalyst is an algorithmic trading library for crypto-assets written in Python, originally developed to let quants and developers design, backtest, and deploy trading strategies in a unified environment. It builds on top of Zipline, extending that ecosystem to support crypto exchanges and high-resolution historical data (daily and minute bars). Users can express strategies in Python, run backtests against historical price data, and analyze performance through built-in metrics and analytics to evaluate profitability, risk, and behavior under different market conditions. ...