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https://github.com/7effrey89/streamlit_azuresqldb_fabric

Demo of a Custom Data Entry App you can build for your Azure SQL Database and Microsoft Fabric Warehouse and Lakehouse using python framework called Streamlit.
https://github.com/7effrey89/streamlit_azuresqldb_fabric

azure db fabric microsoft sql streamlit-webapp

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Demo of a Custom Data Entry App you can build for your Azure SQL Database and Microsoft Fabric Warehouse and Lakehouse using python framework called Streamlit.

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# Custom Data Entry UI for Azure SQL Database and Microsoft Fabric Warehouse and Lakehouse:

![image](https://github.com/user-attachments/assets/7d768b49-1483-4056-ab3e-924366af3f9c)



This demo uses a python framework called streamlit to accelerate the development of browser based solutions.

In this demo you will find pages that enables you:



Azure SQL DB:

- Embed table from Azure SQL DB as native text on a website

- Custom made form that can be dyncamilly controlled to submit one or multiple inputs to a table in Azure SQL DB

- Spreadsheet alike Data Editor to Insert, Update, Delete rows in an Azure SQL DB table

  

Microsoft Fabric:

- Show table data from any SQL Endpoint in Microsoft Fabric (e.g. Warehouse, Lakehouse)

- Spreadsheet alike Data Editor to Insert, Update, Delete rows in an Microsoft Fabric Warehouse

- Spreadsheet alike Data Editor to Insert, Update, Delete rows in an Microsoft Fabric Lakehouse 



# Video demonstration of the solution 

https://youtu.be/bSH6AZi9C8k



## Getting Started:

Open a Terminal in VS Code



Download the code to your machine:



``` git clone https://github.com/7effrey89/streamlit_azuresqldb_fabric.git```



Configure your Azure SQL Database connection

Modify .streamlit/secrets.toml with your details:

``` server = ".database.windows.net"

 database = ""

 username = ""

 password = ""

```

Modify each of the .py files to target the table you want to interact with:



```

Example: DataEditorAzureSQTable.py:



DATABASE = ''

TABLE_SCHEMA = ''

TABLE_NAME = ''

```



Run the streamlit app:



``` python -m streamlit run main.py```



## Structure - designed for adoption:

- Each of the .py files represent a webpage in streamlit.

- I've decided to write each page as if it was a standalone python script; making it easy for you to paste into your own solutions. The only dependencies each page has is to the .streamlit/secrets.toml file that contains the global variable of your azure sql db connection details.

- If you are here for only the python logic, you can remove all streamlit related code (typically all with st.xxxxx like replacing st.session_state['xx'] with a variable, st.write/st.table with print('xxx') etc.

- main.py serve as the place to configure the left navigation menu for the streamlit app. Here you can easily remove and add more webpages.

  

## Troubleshooiting

I've included a troubleshooting.txt with all the packages and their listed versions that was installed on my machine - just in case that becomes relevant for you one day...



## Docker

I've also made the solution ready for you to run it on a container. You can modify the solutions to your liking - if you add more packages to the solution, remember to include them in the requirement.txt file so they will be included in the docker image when you build it.



1. : Open terminal in VS Code, and make sure you are located in the root folder of the project e.g.:



``` cd c:\streamlit_azuresqldb_fabric ``` 



2. start docker desktop on your local machine



3. Building Docker Image using the details from the file Dockerfile, and call it streamlit_azuresqldb_fabric



```docker build -f Dockerfile -t streamlit_azuresqldb_fabric . ```



4. Run the docker Image, and redicts traffic from 8501 to 80



```docker run -p 80:8501 streamlit_azuresqldb_fabric```