[Python] How do I resolve version conflicts between installed Python libraries in a virtual...

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:

1. 
   What is the recommended way to resolve conflicting library versions in Python?
   
   
2. 
   Should I use tools like pip-tools, poetry, or conda to handle dependency conflicts?
   
   
3. 
   Is there a way to auto-generate compatible versions for all my installed libraries?
   

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