Access SQL Server from Nebari

[empollon9]

All,

It might be a dumb question, but I have not seen it anywhere. If you need to import your data from a DB (I use Microsoft SQL Server), you need to install the drivers. I am using pyodbc. example below:

import pyodbc
import pandas as pd

server = 'servername'
database = 'yourDB'
username = 'myuser'
password = 'mysecret'

conn = pyodbc.connect(
                'DRIVER={ODBC Driver 17 for SQL Server};SERVER=' + server + '.colchester.local' +
                ';DATABASE=' + database + ';UID=' + username + ';PWD=' + password)


sql = 'SELECT * FROM MyTable'
params = None
result = pd.read_sql_query(sql, conn, params=p)

print(result.head(3)) # Display top three rows

This fails as

Traceback (most recent call last):
  File "/home/yournebariuser/testconnection.py", line 10, in <module>
    conn = pyodbc.connect(
           ^^^^^^^^^^^^^^^
pyodbc.Error: ('01000', "[01000] [unixODBC][Driver Manager]Can't open lib 'ODBC Driver 17 for SQL Server' : file not found (0) (SQLDriverConnect)")

I tried to install the driver in Nebari following Microsoft guide

But I found that you cannot sudo from a bash terminal either on VS Code or JupyterHub

sudo apt-get update
bash: sudo: command not found

[viniciusdc]

Hi @empollon9, Based on what I understood about your issue, you installed a package from Conda that requires a few drivers. It might be more straightforward for you to build on top of our jupytelab docker image and install the appropriate drivers for the Ubuntu platform as outlined here

[viniciusdc]

Then you can reference your image in the nebari-config:

default_images:
  jupyterhub: "quay.io/nebari/nebari-jupyterhub:2024.12.1"
  jupyterlab: "quay.io/nebari/nebari-jupyterlab:2024.12.1"

changing the image repository to your own

[empollon9]

Hi @viniciusdc, it is not really a conda package, but the DataBase Driver for Microsoft SQL Server. This will be used accross the data platform to grab data from our own database. I wopuld have spected this to be an standard thing to do an a data platform.

What you propose seems like a work around, but I am not sure I want to do that, as I will have to do this accross all environments we can ever configure in conda. Is there a more straightforward way to install the database drivers?