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How do you add a filtering condition to a list comprehension using 'if'? What is a generator function, and how does 'yield' make it different from a regular function? How do dict comprehensions and set comprehensions differ in syntax from list comprehensions? What is a generator expression, and how does it differ syntactically and behaviorally from a list comprehension? How do you write a nested comprehension, like flattening a list of lists into a single flat list? How do you send a value INTO a generator using the .send() method, and how does this differ from just calling next()? How does 'yield from' delegate iteration to a sub-generator, and what does it return as its own expression value? How does generator.throw() let you inject an exception into a paused generator, and how would the generator handle it? How does lazy evaluation in a chained sequence of generator expressions actually process elements, one at a time end-to-end, without intermediate lists? How would you implement a memory-efficient sliding window or batching generator over a large iterable?
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How do you write a basic list comprehension, and how does it compare to an equivalent for loop?

Beginner

Answer

A list comprehension `[expr for item in iterable]` builds a new list in one concise expression, evaluating 'expr' for each item — functionally equivalent to a for loop that appends to a list, but generally more readable and slightly faster since it avoids repeated append() method calls.
squares = [n * n for n in range(5)]
print(squares)  # [0, 1, 4, 9, 16]

# Equivalent for loop:
squares2 = []
for n in range(5):
    squares2.append(n * n)
Real-world example Quickly transforming a list of raw values (like strings) into a list of processed values (like their uppercase forms).

Common follow-ups: How do you add a conditional filter to a list comprehension?

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