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From the time of the last article, to now, I'm pleased to report that there has been a resurgence of activity in getting custom allocators stabilised in rust and we are closer than we've ever been.
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The Allocators RFC is about to reach a decade milestone of it being accepted, but with no stabilisation.
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MCP servers are useful tools that allow AI agents the ability to interact with applications in a prescribed fashion.
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They say there are 2 hard problems in computer science, and I've hit all 3 of them....
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One of the things I tackled early on with when creating DiveDB was trying to import a lot of metrics from dive logs.
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At formlogic, we are using rust for a number of components within our tech stack, including: internal and external web applications, coordinating and logging machining workflows, parsing an industrial domain specific language (G-Code), and more.
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When building in a strongly-typed language such as rust it's a shame to have to throw this strictness away, especially when dealing with the wild west of frontend stacks.
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SQLx is a new async SQL Toolkit for rust that is closer to standard SQL than a more opinionated ORM like Diesel.
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I have just released the first version of lorikeet-dash and part of that exercise was to find out a way to draw SVG graphs using rust.
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In the last blog of this series, I implemented job queue with tmq.
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I have just spent some time doing an initial async version of lorikeet now that the async/await syntax is stable and the ecosystem has caught up.
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One of the challenges I have had with on premise solutions is the lack of reliable environments and constrained resources.
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While upgrading dependencies (basically deleting Cargo.lock) in a big rust project I hit an issue.
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With the new std::future way of doing things and tokio slowly reaching maturation, it's time to look at updating the libraries out there that are using the old ways.
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2019 was another huge year for rust, but instead of implementing the shiny new thing, it's been a focus on refining existing ideas.
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Last article I wrote about how to use tensorflow with rust.
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One of the promises of machine learning is to be able to use it for object recognition in photos.
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TMQ is a rust library to use ZeroMQ within the Tokio ecosystem.
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2018 was a massive year for rust, and it's great to reflect back on how far we've all come.