What is a Python generator?
Asked by iligimul13527 days ago
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How do generators work and when should I use them?
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1 Answer
A **Python generator** is a special type of iterable that allows you to iterate over a sequence of values lazily, meaning it generates each value on-the-fly as you loop through it, rather than computing and storing the entire sequence in memory upfront. Generators are defined using functions and the `yield` keyword instead of `return`. When a generator function is called, it returns a generator object without actually running the function’s code immediately. The function’s code runs each time you request the next value, pausing at each `yield` and resuming from there on subsequent calls.
Here’s a simple example of a generator function:
```python
def count_up_to(n):
count = 1
while count <= n:
yield count
count += 1
```
When you iterate over `count_up_to(5)`, it yields numbers from 1 to 5 one at a time, without creating a list of all those numbers in memory.
### How generators work
- When you call a generator function, it returns a generator object.
- Each call to `next()` on the generator runs the function until it hits `yield`, which produces a value and pauses the function’s state.
- The function’s local variables and execution state are saved between yields.
- When the function runs out of values to yield or finishes, it raises `StopIteration`, signaling the end of iteration.
### When to use generators
- **Memory efficiency:** Use generators when working with large datasets or streams of data where holding the entire dataset in memory would be impractical or impossible.
- **Lazy evaluation:** When you want to compute values only as needed, which can improve performance and responsiveness, especially in pipelines or when processing data from files or network streams.
- **Infinite sequences:** Generators can represent infinite sequences because they generate each value on demand instead of precomputing the whole sequence.
In summary, generators provide a powerful and memory-efficient way to work with sequences and streams of data, making your programs more scalable and often easier to write.
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by Michael Rodriguez15 days ago
