CCXT Library for Unified Crypto Trading

The CCXT project was first initiated around 2016 by Russian developer Igor Kroitor to tackle the problem of API fragmentation across the rapidly growing number of cryptocurrency exchanges. It provides a consistent interface that abstracts the unique API endpoints of each platform, saving developers from writing and maintaining separate connectors. The library is written in JavaScript and transpiled to support multiple languages, including Python, PHP, C#, and Go, broadening its adoption among developers with different tech stacks. For Python developers, it integrates with `asyncio` for building concurrent, high-performance trading systems. Beyond unified trading commands, CCXT provides access to a full range of public and private endpoints. This includes fetching historical OHLCV data, order books, and tickers for quantitative analysis, as well as managing account balances and executing orders for algorithmic strategies. The library can also normalize data across different exchanges to simplify cross-exchange arbitrage analysis. For developers requiring real-time data for low-latency applications, a premium version called CCXT Pro is available. CCXT Pro extends the core library by adding support for WebSocket streams, providing instant updates for high-frequency trading strategies, a feature not available in the standard REST-based library. In May 2025, the project faced controversy when it was revealed that hard-coded referral IDs were embedded in the code, which captured a portion of users' trading fee rebates without their explicit knowledge. This practice reportedly began around 2018 after a user suggested adding an optional referral ID as a way to support the project's development. The library's architecture includes a feature for "implicit API methods," allowing developers to call exchange-specific endpoints that are not part of the unified API. This provides a powerful escape hatch for accessing unique features, such as staking or dividend history, without abandoning the CCXT framework. The library's widespread adoption has made it a foundational component in the algorithmic trading ecosystem. With over 36,000 stars on GitHub and more than 93 million downloads on PyPI as of 2025, it serves as the engine for thousands of trading bots, data analysis pipelines, and research backends.