topic Re: pyodbc login timeout expired when connecting to Lakehouse SQL endpoint using Service Principal in Data Warehouse

pyodbc login timeout expired when connecting to Lakehouse SQL endpoint using Service Principal

ThucLe — Wed, 28 May 2025 08:03:11 GMT

I'm running into an issue trying to connect to a Lakehouse SQL endpoint using pyodbc and a service principal in Python. Despite verifying that the service principal works (I successfully authenticated using SSMS with the same credentials), I get the following error in my script:

pyodbc.OperationalError: ('HYT00', '[HYT00] [Microsoft][ODBC Driver 18 for SQL Server]Login timeout expired (0) (SQLDriverConnect)')

Environment & What I've Tried:

Using Python with pyodbc
Target: Lakehouse SQL endpoint
Authentication: Service Principal (Client ID + Secret)
Verified network/firewall is not an issue (connection via SSMS using the same service principal works fine)
Using ODBC Driver 18
Tried setting ConnectRetryCount to handle retries

Here's a redacted version of my code:

import pyodbc TENANT_ID = "<tenant-id>" CLIENT_ID = "<client-id>" CLIENT_SECRET = "<client-secret>" server = "<sql-endpoint>.datawarehouse.fabric.microsoft.com" database = "<database-name>" username = CLIENT_ID password = CLIENT_SECRET connection_string = f"Driver={{ODBC Driver 18 for SQL Server}};Server={server};Database={database};Authentication=ActiveDirectoryServicePrincipal;UID={username};PWD={password};ConnectRetryCount=4" print("Attempting connection...") conn = pyodbc.connect(connection_string) # Fails here with login timeout # Sample query cursor = conn.cursor() cursor.execute("SELECT * FROM sys.tables") rows = cursor.fetchall() for row in rows: print(row) conn.close()

Re: pyodbc login timeout expired when connecting to Lakehouse SQL endpoint using Service Principal

BhavinVyas3003 — Thu, 29 May 2025 07:16:29 GMT

Try to include Authority with your Tenant ID

Authority=https://login.microsoftonline.com/<tenant-id> is required for service principal auth to work.

Re: pyodbc login timeout expired when connecting to Lakehouse SQL endpoint using Service Principal

v-lgarikapat — Fri, 30 May 2025 09:49:07 GMT

Hi ThucLe ,
Thanks for reaching out to the Microsoft fabric community forum.
BhavinVyas3003

Thanks for your prompt response
ThucLe

You must include Encrypt=yes;TrustServerCertificate=no; in your connection string. Without those, the ODBC driver silently fails during the Azure AD auth handshake, resulting in a timeout.

import pyodbc

TENANT_ID = "<tenant-id>"
CLIENT_ID = "<client-id>"
CLIENT_SECRET = "<client-secret>"

server = "<lakehouse-name>.datawarehouse.fabric.microsoft.com"
database = "<your-database-name>"
username = CLIENT_ID
password = CLIENT_SECRET

connection_string = (
"Driver={ODBC Driver 18 for SQL Server};"
f"Server={server};"
f"Database={database};"
"Authentication=ActiveDirectoryServicePrincipal;"
f"UID={username};"
f"PWD={password};"
"Encrypt=yes;"
"TrustServerCertificate=no;"
"ConnectRetryCount=4;"
)

print("Attempting connection...")
conn = pyodbc.connect(connection_string, timeout=30)

cursor = conn.cursor()
cursor.execute("SELECT * FROM sys.tables")
rows = cursor.fetchall()
for row in rows:
print(row)

conn.close()

Additional Notes:
Make sure ODBC Driver 18 is installed.

Double-check that the Lakehouse SQL endpoint is correct.

You don't need to explicitly specify the TenantId in the connection string — Authentication=ActiveDirectoryServicePrincipal handles that based on the domain.

Using Microsoft Entra ID with the ODBC Driver - ODBC Driver for SQL Server | Microsoft Learn

Python SQL Driver - pyodbc - Python driver for SQL Server | Microsoft Learn

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We appreciate your engagement and thank you for being an active part of the community.

Best regards,
LakshmiNarayana.

Re: pyodbc login timeout expired when connecting to Lakehouse SQL endpoint using Service Principal

v-lgarikapat — Mon, 02 Jun 2025 07:22:42 GMT

Hi ThucLe ,

If your issue has been resolved, please consider marking the most helpful reply as the accepted solution. This helps other community members who may encounter the same issue to find answers more efficiently.

If you're still facing challenges, feel free to let us know we’ll be glad to assist you further.

Looking forward to your response.

Best regards,
LakshmiNarayana.

Re: pyodbc login timeout expired when connecting to Lakehouse SQL endpoint using Service Principal

v-lgarikapat — Thu, 05 Jun 2025 04:48:39 GMT

Hi ThucLe ,

If your question has been answered, kindly mark the appropriate response as the Accepted Solution. This small step goes a long way in helping others with similar issues.

We appreciate your collaboration and support!

Best regards,
LakshmiNarayana

Re: pyodbc login timeout expired when connecting to Lakehouse SQL endpoint using Service Principal

dbeavon3 — Thu, 09 Apr 2026 00:48:11 GMT

Hi v-lgarikapat

You said:

You must include Encrypt=yes;TrustServerCertificate=no; in your connection string. Without those, the ODBC driver silently fails during the Azure AD auth handshake, resulting in a timeout.

Is this still true now (about a year later)?

I'm also having timeout messages when trying to connect, and it seems possible that your suggestion is the reason for the problems.

Your explanation sounds so crazy, that I am starting to think it might be true. Can you share any documentation about this silent suppression of auth failures? How did you learn about it? Can you please share a source? I will probably open a support ticket with CSS-pro at Mindtree. Do you have a prior SR# or ICM# that can be used as a reference? The MT engineers will probably have a hard time believing your explanation without some sort of corroboration.

Re: pyodbc login timeout expired when connecting to Lakehouse SQL endpoint using Service Principal

v-lgarikapat — Thu, 09 Apr 2026 15:40:04 GMT

Hi dbeavon3 ,

Thanks for reaching out to the Fabric forum. Since this thread has already been marked as solved, could you please create a new thread that covers your specific use cases along with sample details? This will help us address your follow‑up questions more effectively

Thanks,

Lakshmi.