Git’s stash and pop commands provide a convenient way to temporarily store uncommitted changes and reapply them later. This allows for easy context switching without losing work or creating unnecessary commits.

Consider this common scenario in a data science project:

# Working on improving a linear regression model
git checkout -b improved-model

# Editing model.py with new improvements

# Urgent: Critical bug discovered in data loading function
git stash save "WIP: Improving linear regression model"

# Switch to main branch to fix the bug
git checkout main

# Fix the bug in data_loader.py
git add data_loader.py
git commit -m "Fix critical bug in data loading"

# Return to model improvement
git checkout improved-model
git stash pop

# Continue enhancing the model
git add model.py
git commit -m "Complete improved model with scaling"

In this workflow:

1. git stash save temporarily stores your uncommitted model improvements with a descriptive message.
2. You switch to the main branch with a clean working directory to address the critical bug.
3. After fixing the bug, git checkout improved-model returns you to your feature branch.
4. git stash pop retrieves your saved changes, allowing you to resume work on the model.

This approach helps maintain a clean, organized development process while providing the flexibility to address urgent issues without losing progress on ongoing tasks.