#100DaysOfCode in Python Transcripts
Chapter: Days 16-18: List comprehensions and generators
Lecture: Generators - the basics
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Next up are generators,
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sometimes building up a big list
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hits your performance right?
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It doesn't fit into memory and you can write
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a generator that yields values one by one.
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Its like a function that pauses itself.
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You call it you get one value, it pauses,
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you call it again, it gets you another value
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and it keeps your memory footprint small.
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Its best to write the simplest of generators next,
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lets do a number generator, so def num_10
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for e in range 5,
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and then we use the yield keyword
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and that's it, that's like the
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smallest easiest generator is,
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that's stored in a variable,
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and that's it.
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Now you can get the next value from the generator
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using the next keyword and that's zero
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and you can loop through them, like this
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and notice that the for loop took of at one
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because zero was already used or returned,
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and another important thing to know about generators
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is that they consume their sequence once
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and once you get to the end and try to go beyond
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that limit you get a StopIteration.
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If I now do next gen, boom
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it doesn't work, it says StopIteration
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because we've exhausted the sequence right?
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And again, for handles this for us,
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so if I initiate this again,
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and do again the for loop,
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we don't get this exception
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because for is smart enough to catch this for us.
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So, that's the simplest generator example
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I could come up with.
