Sync Client

AgentExchangeClient is a synchronous REST client built on httpx. It is thread-safe and can be shared across multiple tools in the same process. All responses are deserialized into frozen dataclasses with Decimal precision for monetary fields.

Import and Construction

from agentexchange import AgentExchangeClient

client = AgentExchangeClient(
    api_key="ak_live_...",
    api_secret="sk_live_...",
    base_url="http://localhost:8000",  # default
    timeout=30.0,                      # default
)

# Or use as a context manager for automatic cleanup
with AgentExchangeClient(api_key="...", api_secret="...") as client:
    price = client.get_price("BTCUSDT")

Always call client.close() when you are done, or use it as a context manager.

Market Data (6 methods)

`get_price(symbol)`

Fetch the current price for one trading pair. Price is sourced from Redis (sub-millisecond) and updated tick-by-tick from Binance.

price = client.get_price("BTCUSDT")
# price.symbol    → "BTCUSDT"
# price.price     → Decimal("64521.30")
# price.timestamp → datetime(...)

Returns: Price dataclass

`get_all_prices()`

Fetch current prices for all 600+ active pairs in a single call. Use this when scanning multiple coins — never loop get_price.

prices = client.get_all_prices()
for p in prices:
    print(f"{p.symbol}: {p.price}")

Returns: list[Price]

`get_candles(symbol, interval, limit=100)`

Fetch historical OHLCV candles for technical analysis.

candles = client.get_candles(
    symbol="ETHUSDT",
    interval="1h",   # 1m, 5m, 15m, 1h, 4h, 1d
    limit=24,
)
for c in candles:
    print(f"{c.open_time}  O:{c.open}  H:{c.high}  L:{c.low}  C:{c.close}  V:{c.volume}")

Returns: list[Candle]

`get_ticker(symbol)`

Fetch 24-hour ticker statistics: open, high, low, close, volume, and percentage change.

ticker = client.get_ticker("SOLUSDT")
print(f"24h change: {ticker.change_pct}%")
print(f"Volume: {ticker.volume}")

Returns: Ticker dataclass

`get_recent_trades(symbol)`

Fetch recent public trades for a symbol.

trades = client.get_recent_trades("BTCUSDT")

Returns: list[Trade]

`get_orderbook(symbol, depth=20)`

Fetch order book bids and asks. Use before large orders to estimate slippage.

ob = client.get_orderbook("BTCUSDT", depth=10)
best_bid = ob.bids[0]  # [price, quantity]
best_ask = ob.asks[0]
print(f"Spread: {best_ask[0] - best_bid[0]}")

Returns: Object with .bids and .asks lists of [Decimal, Decimal] pairs

Trading (9 methods)

Always call get_balance() before placing any order, and get_price() to verify the current price. After opening a new position, immediately place a stop-loss order.

`place_market_order(symbol, side, quantity)`

Place a market order that fills immediately at the current live price. A small slippage factor is applied to simulate real market conditions.

from decimal import Decimal

order = client.place_market_order(
    symbol="BTCUSDT",
    side="buy",           # "buy" or "sell"
    quantity=Decimal("0.01"),
)
print(f"Order: {order.order_id}  Status: {order.status}")
print(f"Filled at: ${order.executed_price}  Fee: ${order.fee}")
print(f"Slippage: {order.slippage_pct}%")