How do I resolve version conflicts between installed Python libraries in a virtual environment?

I’m working on a Python project where I’m using multiple libraries like numpy, pandas, and matplotlib. After installing a new library (scikit-learn), I started getting version conflict warnings like:

ERROR: Cannot install -r requirements.txt because these package versions have conflicting dependencies: pandas 2.2.1 requires numpy>=1.26.0 scikit-learn 1.1.3 requires numpy<1.25.0 and >=1.17.3

I’m using a virtual environment and installing packages with:

pip install -r requirements.txt

I tried upgrading and downgrading libraries manually, but it keeps breaking something else.

My questions:

What is the recommended way to resolve conflicting library versions in Python?

Should I use tools like pip-tools, poetry, or conda to handle dependency conflicts?

Is there a way to auto-generate compatible versions for all my installed libraries?