CryptoApi2 0.1.0

CryptoAPI is a powerful Python library designed to simplify interaction with various cryptocurrency APIs. (Binance REST and WebSockets)

CryptoApi

CryptoAPI is a powerful Python library designed to simplify interaction with various cryptocurrency APIs.

It offers a user-friendly typed interface to .

1. fetch real-time market data
2. historical data
3. execute trades.

Key Features:

• Real-time Data: Access to real-time market data, including prices, volumes, and order books.
• Historical Data: Retrieve historical price and trading data.
• WebSockets: Establish persistent connections for live updates and event-driven programming.
• REST API: Interact with RESTful APIs for flexible data retrieval with typed responses and parameters.
• Asynchronous Support: Efficiently handle multiple API requests concurrently.
• Error Handling: Robust error handling and informative error messages. -**Typed API -Responeses of requests are returned as pydantic types

** EXAMPLE app.py ** import numpy as np from binance_client.BinanceAuth import BinanceAuth from binance_client.BinanceFuturesClient import BinanceFuturesClient from binance_client.BinanceTrader import BinanceTrader

api_key=os.environ['BINANCE_API_KEY'] # you can store your credintials in environment variables
api_secret=os.environ['BINANCE_API_SECRET']

auth_data=BinanceAuth(api_key,api_secret) #pass your binance credintials

symbols = ["BTCUSDT", "ADAUSDT"] # choose symbols
trader=BinanceTrader(auth_data,symbols,is_paper_trading=True) # create BinanceTrader so you have access to trading functionality



def run_test_cases(trader: BinanceTrader):

    def log_hedge(row:TicketRow): #function which reacts to price changes
        print(row)
        prices_dict=row.prices
        keys=trader.symbols
        betas=[1,-1]


        order_dict=row.prices.copy()

        sum=0.0

        for i in range(0,len(keys) -1) :
            key=keys[i]
            price=np.log(prices_dict[key])* abs(betas[i])
            order_dict[key]=price
            sum+=price

        
        for i in range(0,len(keys) -1) :
            v=order_dict[key]
            v/=sum
            v= v if betas[i]>1 else -v
            order_dict[key]=v


        print("order_dict")
        print(order_dict)
        return trader.modify_order(order_dict)
    
    def getBetas()->tuple[float,float]:{
        1,-1 
    }
    
    trader.setSingleOnNextUpdate(log_hedge)

    trader.run()

You have just written a simple function that reacts to prices, of course you can refine it, e.g. calculate beta coefficients from regression and add additional explaination variables eg.inflation . After entering the quantity in modify_order, the difference from the current orders is converted into market orders.

Stages of development

1. fetch real-time market data execute trades (binance,REST)
2. websocket support , hedging positions