pyccxt 0.1.0

Python lib for accessing ccxt

pyccxt

A Python library for accessing cryptocurrency exchange data via CCXT. Get ticker prices and market volumes across different exchanges with aggregated analysis capabilities.

Overview

pyccxt provides a unified interface to access cryptocurrency market data from multiple exchanges. Built on top of the popular CCXT library, it offers:

• Price aggregation across multiple exchanges
• Volume analysis by market and currency
• CLI tools for quick market data access
• Market comparison and analysis
• Exchange filtering by features and supported pairs

Installation

pip install pyccxt

Development Installation

git clone https://github.com/holgern/pyccxt.git
cd pyccxt
pip install -e .

Quick Start

Python API

from pyccxt import Exchange

# Initialize exchange
exchange = Exchange("binance")

# Get market volumes
volumes = exchange.get_market_volumes(
    filter_base="BTC",
    normalize_to="USD",
    limit=10,
)
for volume_data in volumes:
    print(
        f"{volume_data['symbol']}: "
        f"{volume_data['normalizedVolume']:.2f} "
        f"{volume_data['normalizedCurrency']}"
    )

# Get price for specific pair
market = exchange.get_market("BTC/USDT")
if market:
    ticker = market.get_ticker()
    print(f"BTC/USDT: ${ticker.last:.2f}")

Command Line Interface

# Get price for a trading pair
pyccxt price BTC USD --market binance

# Render an OHLCV-derived ASCII chart
pyccxt chart BTC USDT --market kraken --timeframe 1h --limit 60

# Fetch OHLCV candles and print the table
pyccxt ohlcv BTC USDT --market kraken --timeframe 4h --limit 90 --table

# Show market volumes
pyccxt volume --market binance --limit 10

# List available exchanges
pyccxt exchanges

# Filter exchanges by features
pyccxt exchanges --features --filter fetchOHLCV

Features

Exchange Data Access

• Multiple Exchange Support: Access 100+ cryptocurrency exchanges
• Unified API: Consistent interface across all exchanges
• Market Data: Real-time prices, volumes, and market info
• OHLC Data: Historical price data with multiple timeframes

Volume Analysis

from pyccxt import Exchange, get_market_volumes_for_pair

volumes = get_market_volumes_for_pair("BTC", "USDT", max_exchanges=5)
for vol in volumes:
    print(
        f"{vol['exchange']}: {vol['normalizedVolume']:.2f} "
        f"{vol['normalizedCurrency']}"
    )

Market Filtering

# Get markets by base currency
btc_markets = exchange.get_markets_by_base("BTC")

# Get markets by quote currency
usd_markets = exchange.get_markets_by_quote("USD")

# Filter by minimum volume
high_volume = exchange.get_market_volumes(normalize_to="USD", min_volume=1000000)

CLI Usage

Price Commands

# Basic price lookup
pyccxt price BTC USD

# Specify exchange
pyccxt price ETH EUR --market kraken

# Get detailed price info with spread and 24h change
pyccxt price BTC USDT --market binance

Volume Commands

# Show top volumes for an exchange
pyccxt volume --market binance --normalize-to USD --limit 20

# Filter by quote currency
pyccxt volume --market coinbase --quote USD --normalize-to USD --limit 15

# Compare volumes across exchanges
pyccxt volume --market binance,kraken,coinbase --base BTC --compare --normalize-to USD

Chart Commands

# Plot close prices derived from fetched OHLCV candles
pyccxt chart BTC USDT --market kraken --timeframe 1h --limit 60

# Plot a different OHLC-derived series and print the underlying price rows
pyccxt chart ETH USD --market coinbase --timeframe 15m --limit 80 --price-type high --table

# Fetch candles, render a close-price plot, and print OHLCV rows
pyccxt ohlcv BTC USDT --market kraken --timeframe 4h --limit 90 --table

# Plot the typical price while keeping candle output optional
pyccxt ohlcv ETH EUR --market kraken --timeframe 1d --limit 30 --plot-price typical

• chart fetches OHLCV data first and plots one derived price series.
• ohlcv uses the same OHLCV fetch path, plots one selected series, and can print full candle rows.
• --table prints the underlying rows used by each command.

Exchange Commands

# List all exchanges
pyccxt exchanges

# Show exchange features
pyccxt exchanges --features

# Filter by supported features
pyccxt exchanges --filter fetchOHLCV,fetchTicker

# Filter by supported trading pairs
pyccxt exchanges --base BTC --quote USD

API Reference

Exchange Class

from pyccxt import Exchange

exchange = Exchange("binance")

Methods

• get_market(symbol) - Get Market instance for symbol
• get_markets_by_base(currency) - Filter by base currency
• get_markets_by_quote(currency) - Filter by quote currency
• get_market_volumes(filter_base=None, filter_quote=None, normalize_to="USD", min_volume=0, limit=None, include_unconverted=True) - Get volume rows with explicit filters and normalization
• fetch_all_tickers() - Get all ticker data
• get_total_volume(filter_base=None, filter_quote=None, normalize_to="USD", min_volume=0, include_unconverted=False) - Get total normalized exchange volume
• get_volume_by_quote_currency() - Get quote-native totals grouped by quote currency
• get_volume_by_base_currency() - Get base-native totals grouped by base currency

Market Class

market = exchange.get_market("BTC/USDT")

Methods

• get_ticker() - Get current price ticker
• get_price() - Get current price
• refresh() - Update market data
• fetch_ohlc(timeframe, limit) - Get OHLC data

Ticker Class

ticker = market.get_ticker()
print(f"Price: {ticker.last}")
print(f"24h Change: {ticker.percentage}%")
print(f"Volume: {ticker.quoteVolume}")

Examples

Market Volume Analysis

from pyccxt import Exchange

def analyze_btc_markets():
    """Analyze BTC trading volumes across top exchanges."""

    # Top exchanges by volume
    exchanges = ["binance", "coinbase", "kraken", "huobi", "okx"]

    total_volumes = {}

    for exchange_name in exchanges:
        try:
            exchange = Exchange(exchange_name)
            btc_volumes = exchange.get_market_volumes(
                filter_base="BTC",
                normalize_to="USD",
                limit=10,
            )

            total_vol = sum(vol["normalizedVolume"] or 0 for vol in btc_volumes)
            total_volumes[exchange_name] = total_vol

            print(f"{exchange_name}: {total_vol:.2f} USD normalized volume")

        except Exception as e:
            print(f"Error with {exchange_name}: {e}")

    # Sort by volume
    sorted_exchanges = sorted(
        total_volumes.items(),
        key=lambda x: x[1],
        reverse=True
    )

    print("\\nTop exchanges by normalized BTC market volume:")
    for exchange, volume in sorted_exchanges:
        print(f"{exchange}: {volume:.2f} USD")

if __name__ == "__main__":
    analyze_btc_markets()

Price Comparison

from pyccxt import Exchange, get_market_volumes_for_pair

def compare_prices(base="BTC", quote="USDT"):
    """Compare prices across multiple exchanges."""

    volumes = get_market_volumes_for_pair(base, quote, max_exchanges=10)

    prices = []
    for vol_data in volumes:
        exchange_name = vol_data["exchange"]
        try:
            exchange = Exchange(exchange_name)
            market = exchange.get_market(f"{base}/{quote}")
            if market:
                ticker = market.get_ticker()
                if ticker and ticker.last:
                    prices.append(
                        {
                            "exchange": exchange_name,
                            "price": ticker.last,
                            "normalizedVolume": vol_data["normalizedVolume"],
                            "normalizedCurrency": vol_data["normalizedCurrency"],
                        }
                    )
        except Exception as e:
            print(f"Error getting price from {exchange_name}: {e}")

    # Sort by price
    prices.sort(key=lambda x: x["price"])

    print(f"\\n{base}/{quote} Price Comparison:")
    for price_data in prices:
        print(
            f"{price_data['exchange']}: ${price_data['price']:.2f} "
            f"(Vol: {price_data['normalizedVolume']:.2f} "
            f"{price_data['normalizedCurrency']})"
        )

if __name__ == "__main__":
    compare_prices("BTC", "USDT")
    compare_prices("ETH", "USD")

Configuration

Exchange Construction

# Supported constructor options
exchange = Exchange("binance", min_refresh_time=60, timeout=30000)

Development

Setup

git clone https://github.com/holgern/pyccxt.git
cd pyccxt
pip install -e .
pip install -r requirements-test.txt

Testing

# Run all tests
pytest

# Run with coverage
pytest --cov=pyccxt

# Run specific test
pytest -k "test_exchange"

Code Quality

# Format and lint
ruff check .
ruff format .

# Run pre-commit hooks
pre-commit run --all-files

Contributing

1. Fork the repository
2. Create a feature branch: git checkout -b feature-name
3. Make your changes and add tests
4. Run the test suite: pytest
5. Run linting: ruff check .
6. Commit your changes: git commit -am 'Add feature'
7. Push to the branch: git push origin feature-name
8. Submit a pull request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Built on top of CCXT - Cryptocurrency trading library
• CLI powered by Typer and Rich
• Inspired by the need for unified cryptocurrency market analysis

Changelog

Latest Changes

• Modern Python type hints with X | None syntax
• Comprehensive CLI with market filtering
• Volume aggregation across exchanges
• Market comparison tools
• Improved error handling and logging

Support

• Issues: GitHub Issues
• Documentation: This README and inline code documentation
• Examples: See the examples/ directory for usage examples

---

Note: This library is for informational purposes only. Always verify data from multiple sources before making trading decisions.