Alpaca offers brokerage services for equities and crypto. Equity trading is commission free while crypto trading fees are tiered. Alpaca-py allows you to place orders and manage your positions on your Alpaca brokerage account.

Paper Trading#

Alpaca offers a paper trading sandbox environment so you can test out the API or paper trade your strategy before you go live. The paper trading environment is free to use. You can learn more about paper trading on the Alpaca API documentation.

To use paper trading, you will need to set the paper parameter to True when instantiating the TradingClient. Make sure the keys you are providing correspond to a paper account.

from import TradingClient

# paper=True enables paper trading
trading_client = TradingClient('api-key', 'secret-key', paper=True)

Retrieving Account Details#

You can access details about your brokerage account like how much buying power you have, whether you’ve been flagged by as a pattern day trader, your total equity.

from import TradingClient

trading_client = TradingClient('api-key', 'secret-key')

account = trading_client.get_account()


The assets API serves a list of assets available on Alpaca for trading and data consumption. It is important to note that not all assets are tradable on Alpaca, and those assets will be marked with tradable=False. To learn more about Assets, visit the Alpaca API documentation.

Getting All Assets#

Retrieves a list of assets that matches the search parameters. If there is not any search parameters provided, a list of all available assets will be returned. Search parameters for assets are defined by the GetAssetsRequest model, which allows filtering by AssetStatus, AssetClass, and AssetExchange.

from import TradingClient
from import GetAssetsRequest
from import AssetClass

trading_client = TradingClient('api-key', 'secret-key')

# search for crypto assets
search_params = GetAssetsRequest(asset_class=AssetClass.CRYPTO)

assets = trading_client.get_all_assets(search_params)


The orders API allows you to submit orders and then manage those orders. You can customize your order with various order types, order time in forces or by creating multi-leg orders. To learn more about orders, visit the Alpaca API documentation.

Creating an Order#

To create on order on Alpaca-py you must use an OrderRequest object. There are different OrderRequest objects based on the type of order you want to make. For market orders, there is MarketOrderRequest, limit orders have LimitOrderRequest, stop orders StopOrderRequest, and trailing stop orders have TrailingStopOrderRequest. Each order type have their own required parameters for a successful order.


For stocks, the notional parameter can only be used with Market orders. For crypto, the notional parameter can be used with any order type.

Market Order

A market order is an order to buy or sell a stock at the best available price. Generally, this type of order will be executed immediately. However, the price at which a market order will be executed is not guaranteed.

Market orders allow the trade of fractional shares for stocks. Fractional shares must be denoted either with a non-integer qty value or with the use of the notional parameter. The notional parameter allows you to denote the amount you wish to trade in units of the quote currency. For example, instead of trading 1 share of SPY, we can trade $200 of SPY. notional orders are inherently fractional orders.

from import TradingClient
from import MarketOrderRequest
from import OrderSide, TimeInForce

trading_client = TradingClient('api-key', 'secret-key', paper=True)

# preparing orders
market_order_data = MarketOrderRequest(

# Market order
market_order = trading_client.submit_order(

Limit Order

A limit order is an order to buy or sell a stock at a specific price or better. You can use the LimitOrderRequest model to prepare your order details.

from import TradingClient
from import LimitOrderRequest
from import OrderSide, TimeInForce

trading_client = TradingClient('api-key', 'secret-key', paper=True)

limit_order_data = LimitOrderRequest(

# Limit order
limit_order = trading_client.submit_order(

Getting All Orders#

We can query all the orders associated with our account. It is possible to narrow the query by passing in parameters through the GetOrdersRequest model.

from import TradingClient
from import GetOrdersRequest
from import OrderSide, QueryOrderStatus

trading_client = TradingClient('api-key', 'secret-key', paper=True)

# params to filter orders by
request_params = GetOrdersRequest(

# orders that satisfy params
orders = trading_client.get_orders(filter=request_params)

Cancel All Orders#

We can attempt to cancel all open orders with this method. The method takes no parameters and returns a list of CancelOrderResponse objects. The cancellation of an order is not guaranteed. The CancelOrderResponse objects contain information about the cancel status of each attempted order cancellation.

from import TradingClient

trading_client = TradingClient('api-key', 'secret-key', paper=True)

# attempt to cancel all open orders
cancel_statuses = trading_client.cancel_orders()


The positions endpoints lets you track and manage open positions in your portfolio. Learn more about the positions endpoints in the API docs.

Getting All Positions#

This method requires no parameters and returns all open positions in your portfolio. It will return a list of Position objects.

from import TradingClient

trading_client = TradingClient('api-key', 'secret-key')


Close All Positions#

This method closes all your open positions. If you set the cancel_orders parameter to True, the method will also cancel all open orders, preventing you from entering into a new position.

from import TradingClient

trading_client = TradingClient('api-key', 'secret-key')

# closes all position AND also cancels all open orders

Streaming Trade Updates#

There is also a TradingStream websocket client which allows you to stream order updates. Whenever an order is submitted, filled, cancelled, etc, you will receive a response on the client.

You can learn more on the API documentation

Here is an example

from import TradingStream

trading_stream = TradingStream('api-key', 'secret-key', paper=True)

async def update_handler(data):
    # trade updates will arrive in our async handler

# subscribe to trade updates and supply the handler as a parameter

# start our websocket streaming