In Jupyter notebooks, how to connect to MS SQL with a different Windows user

Question

I have Select access to a MS SQL database that I would like to extract data into a Pandas dataframe running inside a Jupyter notebook. For reasons out of my control, I have access to the database from a different user. How I can query the database from Jupyter while connected to my current user account?

Answer 1

This is how you can do this:

1. Python needs to be installed for all users in computer. !Very important

2. Install Visual C++ Build tools Microsoft C++ Build Tools - Visual Studio

3. Create a directory for the virtualenv accesible by all users in the computer, for example: mkdir C:\virtualenv

4. Make a copy of the Command Prompt and paste in the virtualenv directory. From: C:\Users\YOURUSERNAME\AppData\Roaming\Microsoft\Windows\Start Menu\Programs\System Tools\Command Prompt To: C:\virtualenv\Command Prompt

5. Run Command Prompt as different user (press shift + right click) and login with YOURDOMAIN. username: YOURUSERNAME@YOURDOMAIN or YOURDOMAIN\YOURUSERNAME password: your password

6. cd C:\virtualenv

7. Create the virtualenv: python -m venv .

8. Connect to the virtualenv. scripts\activate

9. Install dependencies pip install --upgrade jupyter pyodbc sqlalchemy pandas pip

10. Create a Jupyter configuration file for the user. jupyter notebook --generate-config

11. Close the Command Prompt.

12. Right click on the Command Prompt shortcut, then select Properties.

13. Clear and leave empty the values from Start in and replace the Target values with: Target: %windir%\system32\runas.exe /user:YOURUSERNAME@DOMAIN /netonly “CMD /k "cd C:\virtualenv && Scripts\activate && jupyter notebook”" **Optional: You may add /savecred (after/user) and it will remember the password. For security reasons you should not do this.

14. Double click the command prompt to run Jupyter.

15. Create a notebook to connect to your SQL database and download a table into a Pandas dataframe:

    import os import pyodbc import sqlalchemy as db import pandas as pd

    windomain = os.environ['userdomain']

    if windomain == “YOURDOMAIN”: server = 'YOURSERVER' database = 'YOUDATABASE' driver = “{SQL Server}” # No need to type user or password. connect = "DRIVER=”+driver+“;SERVER=”+ server+“;DATABASE=”+database+ “;Trusted_Connection=yes” engine = db.create_engine(“mssql+pyodbc:///?odbc_connect={}”.format(connect)) else: print(“Open as different user.”)

    df = pd.read_sql( """ SELECT TOP(100) * FROM [YOURDATABASE] """, con=engine, )