🧠 What is a Generator in Python?
A generator is a special type of iterator that produces values lazily—one at a time, and only when needed—without storing them all in memory.

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❓ How do you create a generator?
✅ Correct answer:
Option 1: Use the yield keyword inside a function.

🔥 Simple example:

def countdown(n):
    while n > 0:
        yield n
        n -= 1

When you call this function:

gen = countdown(3)
print(next(gen))  # 3
print(next(gen))  # 2
print(next(gen))  # 1

Each time you call next(), the function resumes from where it left off, runs until it hits yield, returns a value, and pauses again.

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⛔ Why are the other options incorrect?

- Option 2 (class with __iter__ and __next__):
It works, but it’s more complex. Using yield is simpler and more Pythonic.

- Options 3 & 4 (for or while loops):
Loops are not generators themselves. They just iterate over iterables.

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💡 Pro Tip:
Generators are perfect when working with large or infinite datasets. They’re memory-efficient, fast, and clean to write.

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📌 #Python #Generator #yield #AdvancedPython #PythonTips #Coding


🔍By: https://t.iss.one/DataScienceQ

❓ Interview question

What is a generator in Python?

Answer: A generator is a special type of function that returns an iterator using the `yield` keyword instead of `return`. It allows you to generate a sequence of values lazily, meaning values are produced on-demand rather than all at once. This saves memory and improves performance when dealing with large datasets.

tags: #python #interview #generator #iterator #programming

By: t.iss.one/DataScienceQ 🚀