Explain the concept of Python generators.

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What is a Python Generator? A generator is a special kind of iterator in Python that yields items one at a time, on demand, rather than storing them all in memory at once. Generators let you produce a sequence of values lazily, which is efficient when working with large data or infinite sequences. How Generators Work You create a generator using either: A generator function, which uses the yield keyword.A generator expression, similar to list comprehensions but with parentheses. When a generator function is called, it returns a generator object but doesn’t execute the function body immediately.Each call to next() on the generator runs the function until it hits yield, then it pauses and returns that value.The next call resumes execution right after the last yield. Why use generators? Memory efficient: No need to store entire sequences in memory.Lazy evaluation: Values are produced only when requested.Represent infinite sequences: You can generate values forever without using infinite memory. Example: Generator Function Output: Example: Generator Expression Output: Key points about generators: They maintain their internal state between yields.They can only be iterated once.You can convert their output into a list using list(generator) if needed.Useful for streaming data, processing large files, or pipelines.

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Explain the concept of Python generators.

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What is a Python Generator?

How Generators Work

Why use generators?

Example: Generator Function

Example: Generator Expression

Key points about generators: