Alpaca-py provides an interface for interacting with the API products Alpaca offers. These API products are provided as various REST, WebSocket and SSE endpoints that allow you to do everything from streaming market data to creating your own trading apps. You can learn about the API products Alpaca offers at alpaca.markets.
Alpaca’s APIs allow you to do everything from building algorithmic trading strategies to building a full brokerage experience for your own end users. Here are some things you can do with Alpaca-py.
Market Data API: Access live and historical market data for 5000+ stocks and 20+ crypto.
Trading API: Trade stock and crypto with lightning fast execution speeds.
Broker API & Connect: Build investment apps - from robo-advisors to brokerages.
Alpaca-py is supported on Python 3.7+. You can install Alpaca-py using pip. To learn more about version histories, visit the PyPI page.
To install Alpaca-py, run the following pip command in your terminal.
pip install alpaca-py
Try upgrading your pip before installing if you face errors.
pip install --upgrade pip
If you’re using poetry to manage dependencies in your project. You can add Alpaca-py to your project by running
poetry add alpaca-py
If you’ve used the previous python SDK alpaca-trade-api, there are a few key differences to be aware of.
Alpaca-py lets you use Broker API to start building your investment apps! Learn more at the Broker page.
Alpaca-py uses a more OOP approach to submitting requests compared to the previous SDK. To submit a request, you will most likely need to create a request object containing the desired request data. Generally, there is a unique request model for each method.
Some examples of request models corresponding to methods:
Request Models Usage Example
To get historical bar data for crypto, you will need to provide a CryptoBarsRequest object.
from alpaca.data.historical import CryptoHistoricalDataClient from alpaca.data.requests import CryptoBarsRequest from alpaca.data.timeframe import TimeFrame # no keys required for crypto data client = CryptoHistoricalDataClient() request_params = CryptoBarsRequest( symbol_or_symbols=["BTC/USD", "ETH/USD"], timeframe=TimeFrame.Day, start="2022-07-01" ) bars = client.get_crypto_bars(request_params)
Alpaca-py uses pydantic to validate data models at run-time. This means if you are receiving request data via JSON from a client. You can handle parsing and validation through Alpaca’s request models. All request models can be instantiated by passing in data in dictionary format.
Here is a rough example of what is possible.
@app.route('/post_json', methods=['POST']) def do_trade(): # ... order_data_json = request.get_json() # validate data MarketOrderRequest(**order_data_json) # ...
Alpaca-py has a lot of client classes. There is a client for each API and even
asset class specific clients (
CryptoDataStream). This requires
you to pick and choose clients based on your needs.
Market Data API:
Trading and Market Data API#
In order to use Alpaca’s services you’ll need to sign up for an Alpaca account and retrieve your API keys.
Signing up is completely free and takes only a few minutes. Sandbox environments are available to test
out the API. To use the sandbox environment, you will need to provide sandbox/paper keys. API keys are
passed into Alpaca-py through either
To use the Broker API, you will need to sign up for a broker account and retrieve
your Broker API keys. The API keys can be found on the dashboard once you’ve logged in. Alpaca also provides a sandbox environment to test out Broker API. To use the sandbox mode, provide your
sandbox keys. Once you have your keys, you can pass them into
BrokerClient to get started.