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Memoize instances typcasters in typecaster map #152

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@film42 film42 commented Feb 8, 2016

All of the default typecasters are stateless, so allocating a new instance for each field becomes extremely costly, especially for larger models. To reduce this, we can memoize the TYPECASTER_MAP.

This should be a backwards compatible change with a speed boost. The only people who might have trouble are those who modified the typecaster map. This is a frozen constant, though, so nobody should be touching this.

This is currently about 10% quicker on a model with 93 fields. The benchmark creates a model and then calls to_json. I also ran the benchmark on a smaller model with only 12 String fields and saw a 1-2% improvement.

#
# @since 0.6.0
def typecaster_for(type)
typecaster = TYPECASTER_MAP[type]
typecaster.new if typecaster
typecaster if typecaster
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This final line is no longer necessary since you're not calling anything. The method simply becomes:

def typecaster_for(type)
    TYPECASTER_MAP[type]
end

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💥 Thanks for catching that!

All of the default typecasters are stateless by default, so allocating
a new instance for each field becomes extremely costly, especially for
larger models. To reduce this, we memoize instances by default, but
still allow users to provide a custom stateful type.
@film42 film42 force-pushed the gt/optimize_typing branch from f4ccaa1 to bbf20e7 Compare February 9, 2016 04:30
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fxfilmxf commented Jul 7, 2016

+1 I was just about to open a PR with the exact same change!

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film42 commented May 15, 2017

🤖 Beep boop! Just sending a ping ❤️😄

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3 participants