I received the following email a few days ago: Jeff, It seems that you know about iterators. Maybe you can explain some weird behavior. If you run the code below you will find that the function is treated differently just because it has a ‘yield’ in it somewhere, even if it’s completely unreachable. def func():print("> Why doesn't this line print?")exit() # Within this function, nothing should matter after this point. The program should exityield "> The exit line above will exit ONLY if you comment out this line." x = func()print(x) When I run the code, I get the following output from the print() call: <generator object func at 0x10e968a50>. So what’s going on here? Why doesn’t that line in func() print? Even if yield is completely unreachable, it seems to affect the way the function executes. How yield affects a function To shed some light on why this behavior is occurring, let’s review yield. Any function that includes the yield keyword is automatically converted to a generator. What it returns (the generator) is a generator iterator. Our print output is actually hinting at this: $ python yield.py <generator object func at 0x10e968a50> When x = func() is executed, we are not actually executing any of the code within _func()_. Rather, since func() is a generator, a generator iterator is returned. So while that may look like a function call, it's actually giving us the generator iterator we would use to generate values yielded by the generator. So how do we actually “call” a generator? By calling _next()_ on a generator iterator. In the code above, this would execute the "next" call to the generator iterator returned by func() and bound to x. If we want to see that cryptic message actually printed out, simply change the last line of the code to print(next(x)). Of course, calling next() over and over on something that's meant to be treated as an iterator is a bit cumbersome. Luckily, for loops support iteration over generator iterators. Imagine a toy generator implemented as follows: def one_to_ten():"""Return the integers between one and ten, inclusive."""value = 1while value <= 10:yield value value += 1 We can call this in a for loop in the following way: for element in one_to_ten():print(element) Of course, we could have more verbosely written: iterator = one_to_ten()for element in iterator:print(element) This is similar to what the original code did. It just never used x to actually execute the code in the generator. Summary I hope that clears up some common questions about yield and generators in Python. For a more in-depth tutorial on the topic, check out Improve Your Python: 'yield' and Generators Explained. Posted on Jun 04, 2018 by Jeff Knupp Originally published at jeffknupp.com on June 4, 2018. I received the following email a few days ago: Jeff, Jeff, Jeff, It seems that you know about iterators. Maybe you can explain some weird behavior. If you run the code below you will find that the function is treated differently just because it has a ‘yield’ in it somewhere, even if it’s completely unreachable. It seems that you know about iterators. Maybe you can explain some weird behavior. If you run the code below you will find that the function is treated differently just because it has a ‘yield’ in it somewhere, even if it’s completely unreachable. It seems that you know about iterators. Maybe you can explain some weird behavior. If you run the code below you will find that the function is treated differently just because it has a ‘yield’ in it somewhere, even if it’s completely unreachable. def func():print("> Why doesn't this line print?")exit() # Within this function, nothing should matter after this point. The program should exityield "> The exit line above will exit ONLY if you comment out this line." x = func()print(x) When I run the code, I get the following output from the print() call: <generator object func at 0x10e968a50> . print() <generator object func at 0x10e968a50> So what’s going on here? Why doesn’t that line in func() print? Even if yield is completely unreachable, it seems to affect the way the function executes. doesn’t func() yield seems How yield affects a function yield To shed some light on why this behavior is occurring, let’s review yield . Any function that includes the yield keyword is automatically converted to a generator . What it returns (the generator ) is a generator iterator . Our print output is actually hinting at this: yield yield generator generator generator generator iterator $ python yield.py <generator object func at 0x10e968a50> $ python yield.py <generator object func at 0x10e968a50> When x = func() is executed, we are not actually executing any of the code within _func()_ . Rather, since func() is a generator , a generator iterator is returned. So while that may look like a function call, it's actually giving us the generator iterator we would use to generate values yielded by the generator . x = func() we are not actually executing any of the code within _func()_ func() generator generator iterator generator iterator generator So how do we actually “call” a generator ? By calling _next()_ on a generator iterator . In the code above, this would execute the "next" call to the generator iterator returned by func() and bound to x . generator By calling _next()_ on a generator iterator generator iterator func() x If we want to see that cryptic message actually printed out, simply change the last line of the code to print(next(x)) . print(next(x)) Of course, calling next() over and over on something that's meant to be treated as an iterator is a bit cumbersome. Luckily, for loops support iteration over generator iterators . Imagine a toy generator implemented as follows: next() for generator iterators def one_to_ten():"""Return the integers between one and ten, inclusive."""value = 1while value <= 10:yield value value += 1 We can call this in a for loop in the following way: for element in one_to_ten():print(element) Of course, we could have more verbosely written: iterator = one_to_ten()for element in iterator:print(element) This is similar to what the original code did. It just never used x to actually execute the code in the generator . x generator Summary I hope that clears up some common questions about yield and generators in Python . For a more in-depth tutorial on the topic, check out Improve Your Python: 'yield' and Generators Explained . yield generators Python Improve Your Python: 'yield' and Generators Explained Posted on Jun 04, 2018 by Jeff Knupp Originally published at jeffknupp.com on June 4, 2018. Originally published at jeffknupp.com jeffknupp.com on June 4, 2018.
