Python Jumpstart by Building 10 Apps Transcripts
Chapter: App 9: Real Estate Analysis App
Lecture: Concept: generator expressions
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Let's quickly talk about this cool concept of generator expressions.
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Generator expressions are sort of the next evolution from list comprehensions,
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and list comprehensions of course take the idea
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of writing procedural code, declaring a list,
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and writing some kind of loop within that loop doing a filter
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maybe somehow transforming the data and putting into the list.
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Generator expressions do the exact same thing
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but instead of computing the entire thing into a list in memory
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it works just like the coroutines that you get when you use the yield keyword,
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you don't actually do the computation,
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you don't pull the item back from the get active customers in this example,
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you don't do the test until you start to pull items out of it,
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so if you say for n in paying usernames,
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and you only pull three of those out,
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maybe within the first five of a million active customers
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there are three ones who are active today
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well you are only going to process five customers instead of a million.
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That can have a lot of really powerful
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positive effects for your application performance.
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Now to be fair, there are certain situations where this doesn't work as well,
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you can't index into generators for example,
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or you can for a list comprehension,
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every time you loop over paying usernames,
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you recompute this information,
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so if you are going to use the item over and over and over,
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maybe it makes sense to use a list comprehension,
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often though with these little expressions you create them,
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you blast over them and you are done, in that case,
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generator expressions probably are the way to go.
