معرفی شرکت ها


alpaca-backtrader-api-0.9.5


Card image cap
تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر
Card image cap
تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر
Card image cap
تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر
Card image cap
تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر
Card image cap
تبلیغات ما

مشتریان به طور فزاینده ای آنلاین هستند. تبلیغات می تواند به آنها کمک کند تا کسب و کار شما را پیدا کنند.

مشاهده بیشتر

توضیحات

Alpaca API within backtrader
ویژگی مقدار
سیستم عامل -
نام فایل alpaca-backtrader-api-0.9.5
نام alpaca-backtrader-api
نسخه کتابخانه 0.9.5
نگهدارنده []
ایمیل نگهدارنده []
نویسنده Alpaca
ایمیل نویسنده oss@alpaca.markets
آدرس صفحه اصلی https://github.com/alpacahq/alpaca-backtrader-api
آدرس اینترنتی https://pypi.org/project/alpaca-backtrader-api/
مجوز -
[![PyPI version](https://badge.fury.io/py/alpaca-backtrader-api.svg)](https://badge.fury.io/py/alpaca-backtrader-api) [![CircleCI](https://circleci.com/gh/alpacahq/alpaca-backtrader-api.svg?style=shield)](https://circleci.com/gh/alpacahq/alpaca-backtrader-api) [![Updates](https://pyup.io/repos/github/alpacahq/alpaca-backtrader-api/shield.svg)](https://pyup.io/repos/github/alpacahq/alpaca-backtrader-api/) [![Python 3](https://pyup.io/repos/github/alpacahq/alpaca-backtrader-api/python-3-shield.svg)](https://pyup.io/repos/github/alpacahq/alpaca-backtrader-api/) # alpaca-backtrader-api `alpaca-backtrader-api` is a python library for the Alpaca trade API within `backtrader` framework. 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 underlying library `alpaca-trade-api`. ## Install ```bash $ pip3 install alpaca-backtrader-api ``` ## Example #### These examples only work if you have a funded brokerage account or another means of accessing Polygon data. you can find example strategies in the [samples](https://github.com/alpacahq/alpaca-backtrader-api/tree/master/sample) folder. remember to add you credentials. you can toggle between backtesting and paper trading by changing `ALPACA_PAPER` #### a strategy looks like this: In 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. ```python import alpaca_backtrader_api import backtrader as bt from datetime import datetime ALPACA_API_KEY = <key_id> ALPACA_SECRET_KEY = <secret_key> ALPACA_PAPER = True class SmaCross(bt.SignalStrategy): def __init__(self): sma1, sma2 = bt.ind.SMA(period=10), bt.ind.SMA(period=30) crossover = bt.ind.CrossOver(sma1, sma2) self.signal_add(bt.SIGNAL_LONG, crossover) cerebro = bt.Cerebro() cerebro.addstrategy(SmaCross) store = alpaca_backtrader_api.AlpacaStore( key_id=ALPACA_API_KEY, secret_key=ALPACA_SECRET_KEY, paper=ALPACA_PAPER ) if not ALPACA_PAPER: broker = store.getbroker() # or just alpaca_backtrader_api.AlpacaBroker() cerebro.setbroker(broker) DataFactory = store.getdata # or use alpaca_backtrader_api.AlpacaData data0 = DataFactory(dataname='AAPL', historical=True, fromdate=datetime( 2015, 1, 1), timeframe=bt.TimeFrame.Days) cerebro.adddata(data0) print('Starting Portfolio Value: %.2f' % cerebro.broker.getvalue()) cerebro.run() print('Final Portfolio Value: %.2f' % cerebro.broker.getvalue()) cerebro.plot() ``` ## API Document The HTTP API document is located in https://docs.alpaca.markets/ ## Authentication The Alpaca API requires API key ID and secret key, which you can obtain from the web console after you sign in. You can set them in the AlpacaStore constructor, using 'key_id' and 'secret_key'. ## Paper/Live mode The 'paper' parameter is default to False, which allows live trading. If you set it to True, then you are in the paper trading mode. ## Running Multiple Strategies/Datas There's a way to execute an algorithm with multiple datas or/and execute more than one algorithm.<br> The websocket connection is limited to 1 connection per account. Alpaca backtrader opens a websocket connection for each data you define.<br> For that exact purpose this ![project](https://github.com/shlomikushchi/alpaca-proxy-agent) was created<br> The steps to execute this are: * Run the Alpaca Proxy Agent as described in the project's README * Define this env variable: `DATA_PROXY_WS` to be the address of the proxy agent. (e.g: `DATA_PROXY_WS=ws://192.168.99.100:8765`) * execute your algorithm. it will connect to the servers through the proxy agent allowing you to execute multiple datas/strategies ## Support and Contribution 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.


نیازمندی

مقدار نام
==1.9.76.123 backtrader
==1.4.3 alpaca-trade-api
==3.4 exchange-calendars
==2.2.5 matplotlib
==1.0.2 msgpack
==1.21.2 numpy
==1.3.2 pandas


نحوه نصب


نصب پکیج whl alpaca-backtrader-api-0.9.5:

    pip install alpaca-backtrader-api-0.9.5.whl


نصب پکیج tar.gz alpaca-backtrader-api-0.9.5:

    pip install alpaca-backtrader-api-0.9.5.tar.gz