Have you used data prefetching strategies in your projects?

Data prefetching strategy is often used to optimize working with databases or APIs by loading necessary data in advance and reducing delays during their use. In Python projects, especially when working with ORM (such as Django ORM or SQLAlchemy), prefetch helps avoid the N+1 query problem.

Example with Django ORM:

# Without prefetch_related
books = Book.objects.all()
for book in books:
    print(book.author.name)  # Each book will trigger a separate query to the author

# With prefetch_related
books = Book.objects.prefetch_related('author').all()
for book in books:
    print(book.author.name)  # All authors are loaded with one additional query

Thus, data preloading improves performance by reducing the number of database queries.