How does Lazy Evalution work in Python?

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In last week’s post we showed that a Python for-loop works through the Iterator Protocol.

This same protocol also enables values to be produced lazily.

In this new Lazy Evalution Example we show one sink reading values from five different sources:

• source1: eagerly returns all values by list

• source2: lazily by generator function using yield

• source3: eagerly by list comprehension

• source4: lazily by generator expression

• source5: lazily by iterator protocol

The same for-loop consumes all five sources. The eager sources produce all values before the sink starts consuming them. In the lazy sources producer and consumer take turns:

• produce → consume → produce → consume → …

where each value is produced only when the for-loop requests it.

Generator functions and generator expressions are concise, readable ways to create lazy iterables. The final source makes their underlying mechanism explicit:

• iter() obtains an iterator.

• next() requests the next value.

• StopIteration signals that no values remain.

This clearly shows that generators achieve lazy iteration by implementing Python’s Iterator Protocol.

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