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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:.2f} ({bid_size:.6f}) from {bid_feed}')
    print(f'Ask: {ask:.2f} ({ask_size:.6f}) 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

Weekly Installs

185

Repository

2025emma/vibe-coding-cn

GitHub Stars

13.8K

First Seen

Jan 22, 2026

Security Audits

Gen Agent Trust HubPassSocketPassSnykPass

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