Challenge 1: Cache an Expensive Computation — Possible Solution
====================================================================

# catalog/utils.py

from django.db.models import Avg, Count
from .models import Book

def get_catalog_stats():
    return Book.objects.aggregate(
        avg_price=Avg("price"),
        total_books=Count("id"),
    )

# catalog/views.py

from django.core.cache import cache
from django.shortcuts import render
from .utils import get_catalog_stats

def catalog_overview(request):
    stats = cache.get_or_set("book_stats", get_catalog_stats, timeout=600)
    return render(request, "catalog/overview.html", {"stats": stats})

WHY THIS WORKS
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- get_catalog_stats() is a plain function with no arguments — this is
  required for cache.get_or_set() to be able to call it as a "compute
  the value" callback if the cache doesn't already have a fresh entry.
- cache.get_or_set("book_stats", get_catalog_stats, timeout=600) checks
  for an existing "book_stats" key first; if it's missing or expired, it
  calls get_catalog_stats() ONCE, stores the result under that key for
  600 seconds (10 minutes), and returns it — all in a single call, rather
  than writing a separate get()-then-if-None-then-set() sequence by hand.
- Within that 10-minute window, every subsequent call to
  cache.get_or_set("book_stats", ...) returns the cached dict instantly
  without running the aggregate() query again — the expensive database
  aggregation only actually executes roughly once every 10 minutes,
  regardless of how many requests hit catalog_overview in between.
- Because get_catalog_stats is passed as a reference (not called as
  get_catalog_stats()), get_or_set() only invokes it when actually needed
  — it isn't run eagerly on every request just to check if its result
  should be discarded.