Get Alpaca Market Data Without the Connection Constantly Dying on You

The Problem with Hammering APIs Every Second

Look, I get it. You wrote a nice little script that calls requests.get() every second to check if TSLA moved. Congrats, you've built the digital equivalent of asking "Are we there yet?" on repeat. That worked fine when you were trading your lunch money, but now you're missing moves faster than your ex ghosted you.

Here's what actually happens with REST API polling: Stock jumps 2%, you find out 30 seconds later because that's when your next API call fires. By then, the move's over and you're buying at the top like everyone else who discovered the news on Twitter.

WebSocket gives you the data the moment it happens. No delays, no missed moves, no more refreshing your screen like a psychopath watching your portfolio die.

The WebSocket Connection That Actually Stays Connected

Alpaca's WebSocket feeds work like this: You connect once, it pushes data to you in real-time. Think push notifications but for stock prices and without the battery drain.

The endpoints you need:

• Market data: wss://data.alpaca.markets
• Your account updates: wss://paper-api.alpaca.markets/stream

Don't try to be clever and use both in the same connection. They're separate for a reason.

What Breaks and How to Fix It

Connection drops every 10 minutes? That's your firewall being helpful. Configure keep-alive or use a VPS that doesn't hate persistent connections.

Auth failures? You're probably using paper trading keys on the live endpoint or vice versa. Yes, this breaks in production at the worst possible moment.

Data stops flowing during volatility? Your message handler is too slow. When TSLA announces another "funding secured" tweet, you'll get 1000 messages per second. If your handler can't keep up, messages get dropped and you miss the move.

The fix is simple: Queue the data, process it asynchronously. Don't try to calculate your entire portfolio's net worth inside the message handler.

async def handle_trade(trade):
    # Don't do this - will break during volatility
    # complex_calculation(trade)
    
    # Do this instead
    await trade_queue.put(trade)

Free vs $99/month Data: Choose Your Pain

IEX (Free): Only gets you data from one exchange. Great for testing, useless for serious trading. You'll miss moves that happen on NYSE while only watching NASDAQ.

SIP ($99/month): All exchanges, all the time. Used to be $49 but they jacked up the price. Still worth it if you're trading more than coffee money - the extra data coverage pays for itself the first time you catch a move that IEX users missed.

Crypto runs 24/7 and never sleeps. Your connection management needs to handle weekends, holidays, and that random Tuesday when Bitcoin decides to crash at 3am because someone mentioned "regulation" in a tweet.

When It All Goes to Hell

Your WebSocket will die. Not if, when. Networks fail, servers restart, cosmic rays flip bits. Plan for it.

The connection will drop right before the most important announcement of the year. It's like Murphy's Law but specifically designed to cost you money.

Set up monitoring that screams at you when data stops flowing. I learned this the hard way when my bot sat silent for 2 hours during an earnings announcement because the connection died and I was too busy feeling smart about my "automated" system.

Keep historical data APIs handy for backfilling gaps when you reconnect. Yes, this means more code complexity. No, you can't skip it and hope for the best.

Now that you understand what can go wrong, let's build something that actually handles these problems properly. The difference between a broken bot that loses money and one that stays profitable comes down to handling the edge cases that everyone else ignores.

A Streaming Setup That Won't Die Every 5 Minutes

Here are those edge case handlers I mentioned. Stop copying examples that were clearly written by someone who never ran this in production. Here's what actually works when you're trading real money and the connection decides to crap out during the FOMC announcement.

Using alpaca-py Without Losing Your Mind

The alpaca-py SDK (current version 0.42.1) handles most of the WebSocket bullshit for you. Finally, someone wrote a library that doesn't immediately break when you look at it wrong. Unlike the old alpaca-trade-api that everyone's still using in outdated Stack Overflow answers:

Critical Bug Alert - Versions 0.41.0 - 0.42.1: If you're running your bot inside an existing asyncio event loop, stream.run() will crash with "RuntimeError: asyncio.run() cannot be called from a running event loop". This is a known issue - the library tries to call asyncio.run() internally when you're already in an async context. Use await stream._run_forever() instead of stream.run() as a workaround until they fix it.

from alpaca.data.live import StockDataStream
from alpaca.trading.client import TradingClient
import asyncio
import os

## Basic setup that won't make you want to quit programming
stream = StockDataStream(
    api_key=os.getenv('ALPACA_API_KEY'),
    secret_key=os.getenv('ALPACA_SECRET'),
    feed='iex'  # Free tier - upgrade when you're making money
)

trading_client = TradingClient(
    api_key=os.getenv('ALPACA_API_KEY'), 
    secret_key=os.getenv('ALPACA_SECRET'),
    paper=True  # Keep this True until you're confident
)

@stream.trade
async def on_trade(trade):
    # Do something with the trade data
    # Don't put complex calculations here or you'll miss data
    print(f"{trade.symbol}: ${trade.price}")
    
    # Simple buy signal - replace with your actual strategy
    if should_buy(trade):
        try:
            order = trading_client.submit_order(
                symbol=trade.symbol,
                qty=1,
                side='buy',
                type='market',
                time_in_force='day'
            )
            print(f"Bought {trade.symbol}")
        except Exception as e:
            print(f"Order failed: {e}")

def should_buy(trade):
    # Your strategy logic here
    return False  # Replace with actual conditions

## Start streaming - this will run forever (until it doesn't)
stream.subscribe_trades(on_trade, "AAPL", "GOOGL")
stream.run()

When Your Handler Can't Keep Up (And It Will)

During volatility, you'll get hammered with data faster than you can process it. Your cute little strategy calculation will choke and you'll miss everything important.

trade_queue = asyncio.Queue()

@stream.trade  
async def handle_trade(trade):
    # Don't do complex shit here - just queue it
    await trade_queue.put(trade)

async def process_trades():
    while True:
        try:
            trade = await asyncio.wait_for(trade_queue.get(), timeout=1.0)
            # Now do your expensive calculations
            analyze_and_maybe_trade(trade)
        except asyncio.TimeoutError:
            continue  # No trades in queue
        except Exception as e:
            print(f"Processing failed: {e}")
            # Log it and keep going

## Run both concurrently
async def main():
    await asyncio.gather(
        stream.run(),
        process_trades()
    )

Reconnection That Actually Works

Your connection will drop. Plan for it or cry when it happens at 3pm on earnings day. Check out this GitHub issue for common connection problems and this forum thread for community solutions.

import time

async def run_with_reconnect():
    retries = 0
    max_retries = 10
    
    while retries < max_retries:
        try:
            print(f"Connecting... attempt {retries + 1}")
            
            # Set up your stream subscriptions
            stream.subscribe_trades(handle_trade, "AAPL", "TSLA")
            
            # This blocks until connection dies
            await stream.run()
            
        except Exception as e:
            retries += 1
            wait_time = min(2 ** retries, 60)  # Don't wait more than 1 minute
            
            print(f"Connection died: {e}")
            print(f"Waiting {wait_time}s before retry...")
            
            await asyncio.sleep(wait_time)
    
    print("Gave up reconnecting. Fix your network.")

## Run it
asyncio.run(run_with_reconnect())

Don't Be Stupid About Risk Management

Before you blow up your account, add some basic checks. Learn from this Reddit thread about people who lost money by skipping risk management:

def can_i_afford_this_trade(symbol, quantity):
    account = trading_client.get_account()
    buying_power = float(account.buying_power)
    
    # Get current price (roughly)
    current_price = get_last_price(symbol)  # You implement this
    trade_cost = current_price * quantity
    
    if trade_cost > buying_power * 0.9:  # Don't use all your money
        print("Can't afford this trade")
        return False
    return True

def should_i_even_be_trading_right_now():
    clock = trading_client.get_clock()
    if not clock.is_open:
        print("Market is closed, genius")
        return False
    return True

The Bottom Line

WebSocket streaming is fast but complex. REST polling is simple but slow. Pick your poison based on how much money you're losing to latency vs how much time you want to spend debugging connection issues.

Start with the simple examples above. Add complexity only when you're making enough money to justify the headaches. Check out this comparison and this performance analysis for more technical details.

The decision between WebSocket and REST isn't just about speed - it's about which type of pain you're willing to deal with. Let's break down what each approach actually costs you.