alpaca-trade-api-python is a python library for the Alpaca trade API.
It allows rapid trading algo development easily, with support for the
both REST and streaming interfaces. For details of each API behavior,
please see the online API document.
Note this module supports only python version 3.5 and above, due to the async/await keyword use.
$ pip3 install alpaca-trade-apiIn order to call Alpaca's trade API, you need to obtain API key pairs. Replace <key_id> and <secret_key> with what you get from the web console.
import alpaca_trade_api as tradeapi
api = tradeapi.REST('<key_id>', '<secret_key>')
account = api.get_account()
api.list_positions()The HTTP API document is located in https://docs.alpaca.markets/
The Alpaca API requires API key ID and secret key, which you can obtain from the
web console after you sign in. You can pass key_id and secret_key to the initializers of
REST or StreamConn as arguments, or set up environment variables as
follows.
- APCA_API_KEY_ID: key ID
- APCA_API_SECRET_KEY: secret key
The base URL for API calls defaults to https://api.alpaca.markets/. This endpoint
is for live trading. You can change the base URL to https://paper-api.alpaca.markets
for paper trading. You can specify the API URL with the environment variable APCA_API_BASE_URL.
The environment variable APCA_API_DATA_URL can also be changed to configure the
endpoint for returning data from the /bars endpoint. By default, it will use
https://data.alpaca.markets.
The REST class is the entry point for the API request. The instance of this
class provides all REST API calls such as account, orders, positions,
and bars.
Each returned object is wrapped by a subclass of Entity class (or a list of it).
This helper class provides property access (the "dot notation") to the
json object, backed by the original object stored in the _raw field.
It also converts certain types to the appropriate python object.
import alpaca_trade_api as tradeapi
api = tradeapi.REST()
account = api.get_account()
account.status
=> 'ACTIVE'The Entity class also converts timestamp string field to a pandas.Timestamp
object. Its _raw property returns the original raw primitive data unmarshaled
from the response JSON text.
When a REST API call sees the 429 or 504 status code, this library retries 3 times by default, with 3 seconds apart between each call. These are configurable with the following environment variables.
- APCA_RETRY_MAX: the number of subsequent API calls to retry, defaults to 3
- APCA_RETRY_WAIT: seconds to wait between each call, defaults to 3
- APCA_RETRY_CODES: comma-separated HTTP status code for which retry is attempted
If the retry exceeds, or other API error is returned, alpaca_trade_api.rest.APIError is raised.
You can access the following information through this object.
- the API error code:
.codeproperty - the API error message:
str(error) - the original request object:
.requestproperty - the original response objecgt:
.responseproperty - the HTTP status code:
.status_codeproperty
Calls GET /account and returns an Account entity.
Calls GET /orders and returns a list of Order entities.
after and until need to be string format, which you can obtain by pd.Timestamp().isoformat()
REST.submit_order(symbol, qty, side, type, time_in_force, limit_price=None, stop_price=None, client_order_id=None)
Calls POST /orders and returns an Order entity.
Calls GET /orders with client_order_id and returns an Order entity.
Calls GET /orders/{order_id} and returns an Order entity.
Calls DELETE /orders/{order_id}.
Calls GET /positions and returns a list of Position entities.
Calls GET /positions/{symbol} and returns a Position entity.
Calls GET /assets and returns a list of Asset entities.
Calls GET /assets/{symbol} and returns an Asset entity.
Calls GET /bars/{timeframe} for the given symbols, and returns a Barset with limit Bar objects
for each of the the requested symbols.
timeframe can be one of minute, 1Min, 5Min, 15Min, day or 1D. minute is an alias
of 1Min. Similarly, day is an alias of 1D.
start, end, after, and until need to be string format, which you can obtain with
pd.Timestamp().isoformat()
after cannot be used with start and until cannot be used with end.
Calls GET /clock and returns a Clock entity.
Calls GET /calendar and returns a Calendar entity.
The StreamConn class provides WebSocket/NATS-based event-driven
interfaces. Using the on decorator of the instance, you can
define custom event handlers that are called when the pattern
is matched on the channel name. Once event handlers are set up,
call the run method which runs forever until a critical exception
is raised. This module itself does not provide any threading
capability, so if you need to consume the messages pushed from the
server, you need to run it in a background thread.
This class provides a unique interface to the two interfaces, both
Alpaca's account/trade updates events and Polygon's price updates.
One connection is established when the subscribe() is called with
the corresponding channel names. For example, if you subscribe to
account_updates, a WebSocket connects to Alpaca stream API, and
if AM.* given to the subscribe() method, a NATS connection is
established to Polygon's interface.
The run method is a short-cut to start subscribing to channels and
runnnig forever. The call will be blocked forever until a critical
exception is raised, and each event handler is called asynchronously
upon the message arrivals.
The run method tries to reconnect to the server in the event of
connection failure. In this case you may want to reset your state
which is best in the connect event. The method still raises
exception in the case any other unknown error happens inside the
event loop.
The msg object passed to each handler is wrapped by the entity
helper class if the message is from the server.
Each event handler has to be a marked as async. Otherwise,
a ValueError is raised when registering it as an event handler.
conn = StreamConn()
@conn.on(r'account_updates')
async def on_account_updates(conn, channel, account):
print('account', account)
@conn.on(r'^AM.')
def on_bars(conn, channel, bar):
print('bars', bar)
# blocks forever
conn.run(['account_updates', 'AM.*'])You will likely call the run method in a thread since it will keep running
unless an exception is raised.
Request "listen" to the server. channels must be a list of string channel names.
Goes into an infinite loop and awaits for messages from the server. You should
set up event listeners using the on or register method before calling run.
As in the above example, this is a decorator method to add an event handler function.
channel_pat is used as a regular expression pattern to filter stream names.
Registers a function as an event handler that is triggered by the stream events
that match with channel_path regular expression. Calling this method with the
same channel_pat will overwrite the old handler.
Deregisters the event handler function that was previously registered via on or
register method.
Alpaca's API key ID can be used to access Polygon API whose document is found here.
This python SDK wraps their API service and seamlessly integrates with Alpaca API.
alpaca_trade_api.REST.polygon will be the REST object for Polygon.
The example below gives AAPL daily OHLCV data in a DataFrame format.
import alpaca_trade_api as tradeapi
api = tradeapi.REST()
aapl = api.polygon.historic_agg('day', 'AAPL', limit=1000).dfIt is initialized through alpaca REST object.
Returns a list of Exchange entity.
Returns a SymbolTypeMap object.
Returns a Trades which is a list of Trade entities.
dateis a date string such as '2018-2-2'. The returned quotes are from this day onyl.offsetis an integer in Unix Epoch millisecond as the lower bound filter, inclusive.limitis an integer for the number of ticks to return. Default and max is 30000.
Returns a pandas DataFrame object with the ticks returned by the historic_trades.
Returns a Quotes which is a list of Quote entities.
dateis a date string such as '2018-2-2'. The returned quotes are from this day only.offsetis an integer in Unix Epoch millisecond as the lower bound filter, inclusive.limitis an integer for the number of ticks to return. Default and max is 30000.
Returns a pandas DataFrame object with the ticks returned by the historic_quotes.
Returns an Aggs which is a list of Agg entities. Aggs.df gives you the DataFrame
object.
_fromis an Eastern Time timestamp string that filters the result for the lower bound, inclusive.tois an Eastern Time timestamp string that filters the result for the upper bound, inclusive.limitis an integer to limit the number of results. 3000 is the default and max value.
Specify the _from parameter if you specify the to parameter since when to is
specified _from is assumed to be the beginning of history. Otherwise, when you
use only the limit or no parameters, the result is returned from the latest point.
The returned entities have fields relabeled with the longer name instead of shorter ones.
For example, the o field is renamed to open.
Returns a pandas DataFrame object with the ticks returned by the hitoric_agg.
Returns a Trade entity representing the last trade for the symbol.
Returns a Quote entity representing the last quote for the symbol.
Returns a ConditionMap entity.
Returns a Company entity if symbol is string, or a
dict[symbol -> Company] if symbol is a list of string.
Returns a Dividends entity if symbol is string, or a
dict[symbol -> Dividends] if `symbol is a list of string.
Returns a Splits entity for the symbol.
Returns an Earnings entity if symbol is string, or a
dict[symbol -> Earnings] if symbol is a list of string.
Returns an Financials entity if symbol is string, or a
dict[symbol -> Financials] if symbol is a list of string.
Returns a NewsList entity for the symbol.
For technical issues particular to this module, please report the issue on this GitHub repository. Any API issues can be reported through Alpaca's customer support.
New features, as well as bug fixes, by sending pull request is always welcomed.