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Rate limits are enforced per API key. Exceeding them returns 429 Too Many Requests.

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Limits

The Retail API enforces a global rate limit of 20 requests per second per API key across all endpoints.
LimitValue
Global (all authenticated endpoints)20 requests per second per API key
Public (unauthenticated)20 requests per second per IP

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When you’re rate limited

{ "status": 429, "message": "Too Many Requests" }
Stop immediately, wait at least 1 second, then retry with exponential backoff: 
import time

def make_request_with_retry(fn, max_retries=3):
    for attempt in range(max_retries):
        response = fn()
        if response.status_code != 429:
            return response
        time.sleep(2 ** attempt)
    raise Exception("Max retries exceeded")

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Use WebSocket instead of polling

The single most effective way to stay within limits is to stop polling and use WebSocket streams. One persistent connection replaces hundreds of repeated REST calls.
Don’t pollUse instead
GET /v1/orders/open repeatedly/v1/ws/private - SUBSCRIPTION_TYPE_ORDER
GET /v1/portfolio/positions repeatedly/v1/ws/private - SUBSCRIPTION_TYPE_POSITION
GET /v1/account/balances repeatedly/v1/ws/private - SUBSCRIPTION_TYPE_ACCOUNT_BALANCE
GET /v1/markets/{slug}/bbo repeatedly/v1/ws/markets - SUBSCRIPTION_TYPE_MARKET_DATA_LITE
GET /v1/markets/{slug}/book repeatedly/v1/ws/markets - SUBSCRIPTION_TYPE_MARKET_DATA

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Cache reference data

Market and event metadata changes infrequently. Fetch it once on startup and refresh periodically rather than on every request. 
import time

class MarketCache:
    def __init__(self, client, ttl=300):
        self._client = client
        self._cache = {}
        self._ttl = ttl
        self._last_refresh = None

    def get(self, slug):
        if self._needs_refresh():
            self._refresh()
        return self._cache.get(slug)

    def _needs_refresh(self):
        return not self._last_refresh or (time.time() - self._last_refresh) > self._ttl

    def _refresh(self):
        markets = self._client.markets.list({"limit": 100, "active": True})
        self._cache = {m["slug"]: m for m in markets["markets"]}
        self._last_refresh = time.time()

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For automated systems

If you’re running an automated trading system and need higher limits for production:
  1. Document your use case and expected request volume
  2. Email support@polymarket.us
  3. Include which endpoints you need higher limits for