semantic-link-labs Library is not supported for version >= 3.12

Semantic-Link-Labs Library Incompatibility with Python 3.12+

You might encounter an issue where the semantic-link-labs library, as used in the ms-fabric-mcp project, appears to be incompatible with Python versions 3.12 and above. The project's Readme.md might suggest using Python 3.12 or later, while the semantic-link-labs library, according to its dependencies and setup, might only support Python versions below 3.12. This creates a conflict and can lead to installation errors or runtime issues.

Understanding the Root Cause

The core of the problem lies in the dependencies of the semantic-link-labs library. Certain packages that semantic-link-labs relies on may not have been updated to support the changes introduced in Python 3.12. Python releases often include modifications to the language's internal workings, and libraries need to be updated to be compatible. If a dependency has not been updated, it can cause installation failures or unexpected behavior when running code that uses the library.

Looking at the provided requirements.txt file (linked in the original issue), we can infer the specific dependencies involved. However, without the exact content of that file, we can only speculate. Common culprits in such situations are libraries that perform low-level operations or rely on C extensions, as these often require more significant updates to maintain compatibility across Python versions.

Solution: Addressing the Incompatibility

Here's a step-by-step approach to resolve this incompatibility:

Verify Your Python Version: First, confirm the Python version you're using:
```
python --version
  
```
If it's 3.12 or higher, proceed to the next steps.
Try Creating a Python 3.11 Environment: The simplest solution is to use a Python version that is known to be compatible with semantic-link-labs. You can use venv or conda to create a virtual environment with Python 3.11:
```
# Using venv
  python3.11 -m venv .venv
  source .venv/bin/activate

  # Using conda (if you have Anaconda or Miniconda installed)
  conda create -n myenv python=3.11
  conda activate myenv
  
```
Replace myenv with a name of your choice for the environment.
Install Dependencies in the Compatible Environment: After activating the environment, install the dependencies from your requirements.txt file:
```
pip install -r requirements.txt
  
```
Consider Downgrading Python: If creating a virtual environment isn't feasible, you might need to downgrade your system's default Python version. However, this is generally not recommended, as it can affect other applications.
Investigate Alternatives: If downgrading or using a virtual environment isn't possible, explore alternative libraries that provide similar functionality and are compatible with Python 3.12+. This might involve refactoring your code to use the new library's API.

Practical Tips and Considerations

Pin Dependencies: In your requirements.txt, consider pinning the versions of your dependencies to avoid unexpected breakages in the future. For example, instead of semantic-link-labs, specify semantic-link-labs==1.0.0 (replace 1.0.0 with the actual version).
Regularly Update Dependencies: Keep your dependencies up-to-date, but test thoroughly after each update to ensure compatibility.
Check Library Documentation: Always refer to the official documentation of the semantic-link-labs library for the most accurate information on supported Python versions.
Report the Issue: If you've confirmed that the library is indeed incompatible with Python 3.12+, consider reporting the issue to the library's maintainers on their GitHub repository or other issue tracker. This helps them prioritize updates and address compatibility problems.