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cryptofeed

Cryptofeed - Real-time cryptocurrency market data feeds from 40+ exchanges. WebSocket streaming, normalized data, order books, trades, tickers. Python library for algorithmic trading and market data analysis.

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name cryptofeed description Cryptofeed - Real-time cryptocurrency market data feeds from 40+ exchanges. WebSocket streaming, normalized data, order books, trades, tickers. Python library for algorithmic trading and market data analysis. Cryptofeed Skill Comprehensive assistance with Cryptofeed development - a Python library for handling cryptocurrency exchange data feeds with normalized and standardized results. When to Use This Skill This skill should be triggered when: Working with real-time cryptocurrency market data Implementing WebSocket streaming from crypto exchanges Building algorithmic trading systems Processing order book updates, trades, or ticker data Connecting to 40+ cryptocurrency exchanges Using normalized exchange APIs Implementing market data backends (Redis, MongoDB, Kafka, etc.) Quick Reference Installation # Basic installation pip install cryptofeed # With all optional backends pip install cryptofeed[ all ] Basic Usage Pattern from cryptofeed import FeedHandler from cryptofeed.exchanges import Coinbase, Bitfinex from cryptofeed.defines import TICKER, TRADES, L2_BOOK # Define callbacks def ticker_callback ( data ): print ( f"Ticker: {data} " ) def trade_callback ( data ): print ( f"Trade: {data} " ) # Create feed handler fh = FeedHandler() # Add exchange feeds fh.add_feed(Coinbase( symbols=[ 'BTC-USD' ], channels=[TICKER], callbacks={TICKER: ticker_callback} )) fh.add_feed(Bitfinex( symbols=[ 'BTC-USD' ], channels=[TRADES], callbacks={TRADES: trade_callback} )) # Start receiving data fh.run() National Best Bid/Offer (NBBO) from cryptofeed import FeedHandler from cryptofeed.exchanges import Coinbase, Gemini, Kraken def nbbo_update ( symbol, bid, bid_size, ask, ask_size, bid_feed, ask_feed ): print ( f'Pair: {symbol} Bid: {bid: .2 f} ( {bid_size: .6 f} ) from {bid_feed} ' ) print ( f'Ask: {ask: .2 f} ( {ask_size: .6 f} ) from {ask_feed} ' ) f = FeedHandler() f.add_nbbo([Coinbase, Kraken, Gemini], [ 'BTC-USD' ], nbbo_update) f.run() Supported Exchanges (40+) Major Exchanges Binance (Spot, Futures, Delivery, US) Coinbase , Kraken (Spot, Futures), Bitfinex Gemini , OKX , Bybit Huobi (Spot, DM, Swap), Gate.io (Spot, Futures) KuCoin , Deribit , BitMEX , dYdX Additional Exchanges AscendEX, Bequant, bitFlyer, Bithumb, Bitstamp, Blockchain.com, Bit.com, Bitget, Crypto.com, Delta, EXX, FMFW.io, HitBTC, Independent Reserve, OKCoin, Phemex, Poloniex, ProBit, Upbit Supported Data Channels Market Data (Public) L1_BOOK - Top of order book L2_BOOK - Price aggregated sizes L3_BOOK - Price aggregated orders TRADES - Executed trades (taker side) TICKER - Price ticker updates FUNDING - Funding rate data OPEN_INTEREST - Open interest statistics LIQUIDATIONS - Liquidation events INDEX - Index price data CANDLES - Candlestick/K-line data Authenticated Channels (Private) ORDER_INFO - Order status updates TRANSACTIONS - Deposits and withdrawals BALANCES - Wallet balance updates FILLS - User's executed trades Supported Backends Write data directly to storage: Redis (Streams and Sorted Sets) Arctic - Time-series database ZeroMQ , InfluxDB v2 , MongoDB Kafka , RabbitMQ , PostgreSQL QuasarDB , GCP Pub/Sub , QuestDB UDP/TCP/Unix Sockets Key Features Real-time Data Normalization Cryptofeed normalizes data across all exchanges, providing consistent: Symbol formatting Timestamp handling Data structures Channel names WebSocket + REST Fallback Primarily uses WebSockets for real-time data Falls back to REST polling when WebSocket unavailable Automatic reconnection handling NBBO Aggregation Create synthetic National Best Bid/Offer feeds by aggregating data across multiple exchanges to find arbitrage opportunities. Backend Integration Direct data writing to various storage systems without custom integration code. Requirements Python : 3.8 or higher Installation : Via pip or from source Optional Dependencies : Install backends as needed Common Use Cases Multi-Exchange Price Monitoring fh = FeedHandler() fh.add_feed(Binance(symbols=[ 'BTC-USDT' ], channels=[TICKER], callbacks=ticker_cb)) fh.add_feed(Coinbase(symbols=[ 'BTC-USD' ], channels=[TICKER], callbacks=ticker_cb)) fh.add_feed(Kraken(symbols=[ 'BTC-USD' ], channels=[TICKER], callbacks=ticker_cb)) fh.run() Order Book Depth Analysis def book_callback ( book, receipt_timestamp ): print ( f"Bids: { len (book.book.bids)} | Asks: { len (book.book.asks)} " ) fh.add_feed(Coinbase( symbols=[ 'BTC-USD' ], channels=[L2_BOOK], callbacks={L2_BOOK: book_callback} )) Trade Flow Analysis def trade_callback ( trade, receipt_timestamp ): print ( f" {trade.exchange} - {trade.symbol} : {trade.side} {trade.amount} @ {trade.price} " ) fh.add_feed(Binance( symbols=[ 'BTC-USDT' , 'ETH-USDT' ], channels=[TRADES], callbacks={TRADES: trade_callback} )) Reference Files This skill includes documentation in references/ : getting_started.md - Installation and basic usage README.md - Complete overview and examples Use view to read specific reference files when detailed information is needed. Working with This Skill For Beginners Start with basic FeedHandler setup and single exchange connections before adding multiple feeds. For Advanced Users Explore NBBO feeds, authenticated channels, and backend integrations for production systems. For Code Examples See the quick reference section above and the reference files for complete working examples. Resources Repository : https://github.com/bmoscon/cryptofeed PyPI : https://pypi.python.org/pypi/cryptofeed Examples : https://github.com/bmoscon/cryptofeed/tree/master/examples Documentation : https://github.com/bmoscon/cryptofeed/blob/master/docs/README.md Discord : https://discord.gg/zaBYaGAYfR Related : Cryptostore (containerized data storage) Notes Requires Python 3.8+ WebSocket-first approach with REST fallback Normalized data across all exchanges Active development and community support 40+ supported exchanges and growing
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