StockAPIS for Developers

from stockapis import StockAPIS
 
api = StockAPIS(api_key='your_api_key')
 
def best_bid_ask(symbol, exchanges):
    quotes = []
 
    for exchange in exchanges:
        q = api.platforms.crypto_exchanges.get_ticker(
            exchange=exchange,
            symbol=symbol
        )
        quotes.append({
            'exchange': exchange,
            'bid': q.bid,
            'ask': q.ask,
            'volume_24h': q.volume_24h
        })
 
    best_bid = max(quotes, key=lambda x: x['bid'])
    best_ask = min(quotes, key=lambda x: x['ask'])
    spread = best_ask['ask'] - best_bid['bid']
 
    print(f"Best Bid: {best_bid['bid']} ({best_bid['exchange']})")
    print(f"Best Ask: {best_ask['ask']} ({best_ask['exchange']})")
    print(f"Cross-Exchange Spread: {spread:.2f}")
 
    return quotes
 
best_bid_ask('BTC-USD', ['binance', 'coinbase', 'kraken'])

def load_candles(symbol, interval='1h', limit=500):
    candles = api.platforms.financial_data_apis.get_ohlcv(
        source='polygon',
        symbol=symbol,
        interval=interval,
        limit=limit
    )
 
    closes = [c.close for c in candles]
    highest = max(c.high for c in candles)
    lowest = min(c.low for c in candles)
 
    print(f"OHLCV - {symbol} ({interval})")
    print(f"Candles: {len(candles)}")
    print(f"Period High: {highest}")
    print(f"Period Low: {lowest}")
    print(f"Last Close: {closes[-1]}")
 
    return candles

def order_book_imbalance(symbol, depth=20):
    book = api.platforms.crypto_exchanges.get_order_book(
        exchange='binance',
        symbol=symbol,
        depth=depth
    )
 
    bid_volume = sum(level.size for level in book.bids)
    ask_volume = sum(level.size for level in book.asks)
    imbalance = bid_volume / (bid_volume + ask_volume)
 
    print(f"Order Book - {symbol}")
    print(f"Top Bid: {book.bids[0].price} x {book.bids[0].size}")
    print(f"Top Ask: {book.asks[0].price} x {book.asks[0].size}")
    print(f"Bid/Ask Imbalance: {imbalance:.1%}")
 
    if imbalance > 0.6:
        print("→ Buy-side pressure")
    elif imbalance < 0.4:
        print("→ Sell-side pressure")
 
    return book

def get_quotes(symbols):
    results = []
 
    for sym in symbols:
        q = api.quote(symbol=sym)  # routes to the right source automatically
        results.append({
            'symbol': sym,
            'asset_class': q.asset_class,
            'price': q.price,
            'change_pct': q.change_pct
        })
 
    print("Unified Quotes:")
    for r in results:
        print(f"  {r['symbol']:10} [{r['asset_class']:7}] "
              f"{r['price']:>12,.2f}  {r['change_pct']:+.2f}%")
 
    return results
 
# Equities and crypto in one list — no per-source code
get_quotes(['AAPL', 'BTC-USD', 'TSLA', 'ETH-USD'])

def signal_digest(symbol):
    news = api.platforms.financial_news.search(
        sources=['bloomberg', 'reuters'],
        symbol=symbol,
        published_in_last_hours=24
    )
 
    sentiment = api.platforms.social_signals.get_sentiment(
        symbol=symbol,
        window='24h'
    )
 
    print(f"Signal Digest - {symbol}")
    print(f"Headlines (24h): {len(news)}")
    print(f"Social Sentiment: {sentiment.score:+.2f} "
          f"({sentiment.label})")
    print(f"Mentions: {sentiment.mentions:,}")
 
    print("\nTop Headlines:")
    for item in news[:3]:
        print(f"  [{item.source}] {item.title}")
 
    return news, sentiment

from stockapis import StockAPIS
 
api = StockAPIS(api_key='your_api_key')
 
# One call, normalized across every source
ticker = api.platforms.crypto_exchanges.get_ticker(
    exchange='binance',
    symbol='BTC-USD'
)
 
print(f"Price: {ticker.last:,.2f}")
print(f"24h Change: {ticker.change_pct:+.2f}%")
print(f"24h Volume: {ticker.volume_24h:,.0f}")
print(f"Bid/Ask: {ticker.bid:,.2f} / {ticker.ask:,.2f}")