Backend Development 4 min read

Python Tutorial: Connecting to SQL Server with pymssql and Building a Tkinter UI

This guide walks through setting up a Python 3.8 environment, configuring SQL Server authentication, installing pymssql and ttkbootstrap, and running a Tkinter‑based application via command line or Visual Studio, complete with screenshots and a QR code for additional Python learning resources.

Python Programming Learning Circle
Python Programming Learning Circle
Python Programming Learning Circle
Python Tutorial: Connecting to SQL Server with pymssql and Building a Tkinter UI

Introduction: This project uses Python's pymssql library to connect to a SQL Server database and Tkinter with ttkbootstrap for a UI.

Environment: Python 3.8 and SQL Server 2019.

Database preparation: Import the database file using MSSQL Manager Studio, enable the SA login, set the password to 123456 , ensure the TCP/IP protocol is enabled, and restart the SQL service.

Python environment setup: Create a conda environment named python38 and run pip install -r requirements to install required packages.

Running the project (Method 1 – Command Line): Open the EIMSystem folder (see image below), open a command prompt in that directory, activate the environment with conda activate python38 , then execute python main.py . Use username admin and password 123456 to log in.

Running the project (Method 2 – Visual Studio): Open the folder in Visual Studio, select main.py , choose the Python 3.8 interpreter, and run the file.

Images illustrate the folder view, command‑prompt steps, and the application UI, including login screen and case‑record screenshots.

At the end of the article, a QR code is provided for readers to scan and obtain a free Python course and additional learning materials.

BackendTutorialTkintersqlserverpymssql
Python Programming Learning Circle
Written by

Python Programming Learning Circle

A global community of Chinese Python developers offering technical articles, columns, original video tutorials, and problem sets. Topics include web full‑stack development, web scraping, data analysis, natural language processing, image processing, machine learning, automated testing, DevOps automation, and big data.

0 followers
Reader feedback

How this landed with the community

login Sign in to like

Rate this article

Was this worth your time?

Sign in to rate
Discussion

0 Comments

Thoughtful readers leave field notes, pushback, and hard-won operational detail here.