10_async_api.py

"""
10_async_api.py
---------------
Concept: Asynchronous Programming (async use in API calls)
Context: Efficiently fetching data from multiple exchanges simultaneously.

Note: This concept is crucial for High-Frequency Trading (HFT) or when monitoring many pairs.
"""

import asyncio
import time
import random

# 1. Synchronous (Normal) Approach - Blocking
def get_price_sync(exchange, symbol):
    print(f"[Sync] Requesting {symbol} from {exchange}...")
    time.sleep(1) # Simulating network delay
    print(f"[Sync] Received {symbol} from {exchange}")
    return 100

def run_sync():
    print("--- Starting Synchronous Fetch ---")
    start = time.time()
    get_price_sync("Binance", "BTC/USDT")
    get_price_sync("Coinbase", "BTC/USDT")
    get_price_sync("Kraken", "BTC/USDT")
    end = time.time()
    print(f"Sync Total Time: {end - start:.2f} seconds\n")

# 2. Asynchronous Approach - Non-blocking
async def get_price_async(exchange, symbol):
    print(f"[Async] Requesting {symbol} from {exchange}...")
    await asyncio.sleep(1) # Simulating network delay (non-blocking)
    print(f"[Async] Received {symbol} from {exchange}")
    return random.uniform(20000, 60000)

async def run_async():
    print("--- Starting Asynchronous Fetch ---")
    start = time.time()
    
    # Schedule all 3 calls to run concurrently
    task1 = get_price_async("Binance", "BTC/USDT")
    task2 = get_price_async("Coinbase", "BTC/USDT")
    task3 = get_price_async("Kraken", "BTC/USDT")
    
    # Wait for all of them to complete
    await asyncio.gather(task1, task2, task3)
    
    end = time.time()
    print(f"Async Total Time: {end - start:.2f} seconds")
    print("(Notice it took ~1 second total, not 3!)")

if __name__ == "__main__":
    # Run Sync
    run_sync()
    
    # Run Async
    asyncio.run(run_async())