Refactor Version Constraints

Refactor Version Constraints in `setup.py` to Ensure Flexibility and Stability

Currently, the version constraints in the setup.py file use a mix of minimum version specifiers (e.g., >=) for the dependencies. While this provides flexibility in allowing newer versions of libraries, it may also introduce compatibility issues if future versions of dependencies introduce breaking changes.

The setup.py file contains version constraints using the >= specifier, which allows the installation of newer versions without any upper bounds.

Proposed Refactor (Example)

install_requires=[
    "joblib>=1.3.2,<2.0.0",
    "numpy>=1.21.6,<2.0.0",
    "pandas>=1.3.5,<2.0.0",
    "scikit-learn>=1.0.2,<2.0.0",
    "scipy>=1.7.3,<2.0.0",
    "tqdm>=4.66.4,<5.0.0",
],

Currently tested on:

python 3.7 ---> catboosttest.py

This ensures that the project remains compatible with future releases of these libraries but avoids breaking changes that may come with major version upgrades (i.e., 2.0.0 or later).

Benefits of Refactoring:

Improves stability by preventing breaking changes from major version releases.
Ensures that the project maintains compatibility with a tested range of dependency versions.
Offers a balance between flexibility (using newer minor/patch updates) and stability (avoiding potentially breaking major versions).

This refactor will help prevent unexpected behavior in production and improve the long-term maintainability of the project.

uclamii / model_tuner