Hello lsr2001,
Understanding NylasSdkTimeoutError and ProtocolError Issues
The issues you’re experiencing are related to timeout handling and connection management in the Nylas Python SDK. Let me break down what’s happening and provide solutions.
What causes NylasSdkTimeoutError?
NylasSdkTimeoutError occurs when the Nylas SDK times out before receiving a response from the server1. This happens when:
-
Network latency - Slow network connections or high server load
-
Large data operations - Processing large amounts of email/calendar data
-
Server-side delays - Provider API limitations (Gmail, Exchange, etc.)
-
Default timeout too low - The default timeout is 90 seconds2, which may not be sufficient for some operations
The error is raised in the HttpClient when requests.exceptions.Timeout occurs3:
except requests.exceptions.Timeout as exc:
raise NylasSdkTimeoutError(url=request["url"], timeout=timeout) from exc
Why you’re getting ProtocolError after adding retry logic
The urllib3.exceptions.ProtocolError: 'Remote end closed connection without response' occurs because:
-
Connection reuse issues: Your retry decorator is reusing HTTP connections that the server has already closed
-
Session management: The underlying requests session keeps connections alive, but the server/proxy closes them between retries
-
Exponential backoff timing: The delays may not account for server connection timeouts
Improved Solutions
1. Configure Timeout Properly
Instead of just retrying, first increase the timeout for operations that need more time:
from nylas import Client
# Initialize with longer timeout
client = Client(
api_key="your-api-key",
timeout=300 # 5 minutes instead of default 90 seconds
)
# Or override timeout per request
messages = client.messages.list(
"grant-id",
overrides={"timeout": 180} # 3 minutes for this specific request
)
2. Enhanced Retry Decorator
Improve your retry logic to handle both timeout and connection errors:
import time
from functools import wraps
from nylas.models.errors import NylasSdkTimeoutError
import urllib3.exceptions
import requests.exceptions
def retry_with_backoff(max_retries=3, backoff=2, max_backoff=60):
def decorator(func):
@wraps(func)
def wrapper(*args, **kwargs):
last_exception = None
for attempt in range(1, max_retries + 1):
try:
return func(*args, **kwargs)
except (NylasSdkTimeoutError,
urllib3.exceptions.ProtocolError,
requests.exceptions.ConnectionError,
requests.exceptions.Timeout) as e:
last_exception = e
if attempt == max_retries:
return {
"success": False,
"code": 504,
"message": f"Request failed after {max_retries} attempts: {str(e)}"
}
# Calculate backoff with jitter and max limit
backoff_time = min(backoff * (2 ** (attempt - 1)), max_backoff)
jitter = backoff_time * 0.1 * (0.5 - random.random()) # ±5% jitter
sleep_time = backoff_time + jitter
print(f"Attempt {attempt} failed: {str(e)}. Retrying in {sleep_time:.2f} seconds...")
time.sleep(sleep_time)
except Exception as e:
# Don't retry on non-network errors
return {
"success": False,
"code": 500,
"message": f"Non-retryable error: {str(e)}"
}
return {
"success": False,
"code": 504,
"message": f"All retry attempts failed. Last error: {str(last_exception)}"
}
return wrapper
return decorator
3. Connection Management Strategy
Create a new client instance for each retry attempt to avoid connection reuse issues:
def get_fresh_client():
return Client(
api_key="your-api-key",
timeout=180 # 3 minutes
)
@retry_with_backoff(max_retries=3, backoff=2)
def fetch_messages_with_fresh_connection(grant_id):
client = get_fresh_client() # Fresh connection each retry
return client.messages.list(grant_id)
4. Request-Level Overrides
Use the built-in request override system for fine-grained control4:
def make_robust_request(client, operation, **kwargs):
overrides = {
"timeout": 300, # 5 minutes
"headers": {"Connection": "close"} # Disable keep-alive
}
try:
return operation(**kwargs, overrides=overrides)
except (NylasSdkTimeoutError, urllib3.exceptions.ProtocolError) as e:
# Handle specific error cases
return handle_connection_error(e)
5. Comprehensive Error Handling
class NylasErrorHandler:
def __init__(self, client):
self.client = client
def execute_with_retry(self, operation, *args, **kwargs):
max_attempts = 3
base_timeout = 90
for attempt in range(max_attempts):
try:
# Increase timeout with each attempt
timeout = base_timeout * (attempt + 1)
overrides = kwargs.get('overrides', {})
overrides['timeout'] = timeout
kwargs['overrides'] = overrides
return operation(*args, **kwargs)
except NylasSdkTimeoutError as e:
if attempt == max_attempts - 1:
return self._handle_timeout_error(e, attempt + 1)
time.sleep(2 ** attempt) # Exponential backoff
except urllib3.exceptions.ProtocolError as e:
if attempt == max_attempts - 1:
return self._handle_protocol_error(e, attempt + 1)
time.sleep(5) # Longer wait for connection issues
def _handle_timeout_error(self, error, attempts):
return {
"success": False,
"error": "timeout",
"message": f"Request timed out after {attempts} attempts. Try increasing timeout or checking server load.",
"url": getattr(error, 'url', 'unknown'),
"timeout": getattr(error, 'timeout', 'unknown')
}
def _handle_protocol_error(self, error, attempts):
return {
"success": False,
"error": "connection",
"message": f"Connection closed by server after {attempts} attempts. This may indicate server-side issues.",
"details": str(error)
}
# Usage
handler = NylasErrorHandler(client)
result = handler.execute_with_retry(
client.messages.list,
"grant-id",
limit=100
)
Best Practices
-
Start with timeout configuration before implementing retries
-
Use fresh connections for retry attempts when possible
-
Implement exponential backoff with jitter to avoid thundering herd
-
Set maximum backoff limits to prevent excessive delays
-
Log detailed error information for debugging
-
Consider the specific API operation - some operations naturally take longer
-
Monitor retry patterns to identify systematic issues
The ProtocolError typically indicates server-side connection management issues rather than client problems, so focus on robust error handling rather than trying to “fix” the underlying connection behavior.
Potential Issue in Retry Logic: