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Loops represent fundamental building blocks in Python programming, empowering developers to process data efficiently and elegantly. When dealing with mutable sequences like lists or dictionaries, looping over copies instead of original objects becomes vital for preserving integrity and avoiding surprises. Delve deeper into nuances distinguishing safe looping approaches from riskier alternatives alongside actionable advice and enlightening examples.
Why Copy Matters
Mutable sequences contain modifiable contents subject to change anytime during runtime. Altering these collections mid-loop introduces inconsistencies affecting subsequent iterations adversely. Imagine updating a shopping cart while calculating total costs simultaneously:
cart = ["apple", "banana", "cherries"]
total_cost = 0
# Dangerous approach: Modify the list directly!
for item in cart:
cost = calculate_price(item)
total_cost += cost
cart.append("extra discount") # Oh no! We modified the list!
print(f"Total Cost: ${total_cost:.2f}")
