> ## Documentation Index
> Fetch the complete documentation index at: https://docs.datadocked.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Rate Limits

> Understanding API rate limits and best practices

## Rate Limiting

To ensure fair usage and API stability, Data Docked implements rate limiting on all endpoints.

## Default Limit

| Limit                      | Scope                  |
| -------------------------- | ---------------------- |
| **15 requests per minute** | Per endpoint, per user |

## Endpoint-Specific Limits

| Endpoint                           | Rate Limit       |
| ---------------------------------- | ---------------- |
| `get-vessel-location`              | 100 requests/min |
| `my-credits`                       | 50 requests/min  |
| `get-vessel-particulars`           | 50 requests/min  |
| `get-vessel-engine-data`           | 50 requests/min  |
| `get-vessel-management-data`       | 50 requests/min  |
| `vessels-by-name`                  | 50 requests/min  |
| `get-vessels-by-area`              | 50 requests/min  |
| `get-vessel-info`                  | 15 requests/min  |
| `get-vessel-weather`               | 15 requests/min  |
| `port-calls-by-vessel`             | 15 requests/min  |
| `vessel-mou`                       | 15 requests/min  |
| `port-calls-by-port`               | 15 requests/min  |
| `get-vessels-location-bulk-search` | 15 requests/min  |
| `get-vessel-historical-data`       | 15 requests/min  |

## Rate Limit Exceeded

If you exceed the rate limit, you'll receive a `429 Too Many Requests` response:

```json theme={null}
{
  "error": "Rate limit exceeded",
  "message": "You have exceeded the rate limit of 15 requests per minute"
}
```

## Best Practices

### Implement Exponential Backoff

When you receive a 429 response, wait before retrying:

```python theme={null}
import time
import requests

def make_request_with_backoff(url, headers, max_retries=5):
    for attempt in range(max_retries):
        response = requests.get(url, headers=headers)

        if response.status_code == 429:
            wait_time = 2 ** attempt  # 1, 2, 4, 8, 16 seconds
            time.sleep(wait_time)
            continue

        return response

    raise Exception("Max retries exceeded")
```

### Use Bulk Endpoints

Instead of making many individual requests, use bulk endpoints when available:

```python theme={null}
# Instead of this (10 requests):
for imo in ["9247431", "9184419", "9465411", ...]:
    get_vessel_location(imo)

# Do this (1 request):
get_vessels_location_bulk("9247431,9184419,9465411,...")
```

### Cache Responses

AIS data updates every few minutes. Cache responses to reduce unnecessary requests:

```python theme={null}
from functools import lru_cache
import time

@lru_cache(maxsize=1000)
def get_cached_location(imo, timestamp):
    # timestamp rounded to 5-minute intervals
    return get_vessel_location(imo)

# Use with 5-minute cache
current_interval = int(time.time() / 300) * 300
location = get_cached_location("9247431", current_interval)
```

## Need Higher Limits?

Contact us at [datadocked.com/contact](https://datadocked.com/contact) to discuss enterprise rate limits.