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In August, I set out to improve the machine learning ecosystem for Ruby. I wasn’t sure where it would go. Over the next 5 months, I ended up releasing .
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Sometimes we need to generate really large file exports or run reports that are just slow. It’s not enough to optimize a few queries, we need to move t.
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This is the second in an indefinite series of posts about things that I think went well in the Sorbet project. The previous one covered our testing app.
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This post is based on Jeremy Evans‘s Optimization Techniques Used by the Benchmark Winners presentation. Slides | YouTube at Ruby Kaigi 2019. It‘s bett.
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If you are building a REST API on Ruby/Rails and decide to implement it as a JSON:API to avoid bike-shedding, chances are you are using fast_jsonapi or.
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