Some of you may have seen one of my recent tweets that left a big question hanging in the air: Dude, what are you doing next?? I'm excited to announce today is my first official day working at RelationalAI! I've walked through a lot of the story here...
Ok, first post in a while. Sorry. Some of you know me; I come and go on the blogging front. Here's my latest attempt to restart blogging efforts, and insider tip: the more requests for blogposts, the more motivated I am to write! Oh man I'm excited t...
It's been a while, but I wanted to put up a quick post around some new functionality in the Tables.jl package; as of the v1.1 release, a new function [Tables.partitions](https://juliadata.github.io/Tables.jl/stable/#Tables.partitions) has been introd...
I'm currently working through a refactor of CSV.jl internals and once again am faced with some tricky questions surrounding which data structures to use. In csv reading, like many things, there are trade-offs between performance/efficiency and conven...
Since its inception on a couple of whiteboards at JuliaCon 2018 in London, the Tables.jl package has grown to become a foundational set of interfaces for data packages in Julia, even accumulating 74 direct dependencies in the General registry as of t...
Some may be familiar with the idea of closures), which, in short, are local functions that capture state from enclosing context. Closures are obviously supported in Julia, which often just look like anonymous functions; in those docs, it mentions tha...
We all know 'em, we all hate 'em, let's get a good benchmarking blogpost up in here. Most people who groggily glance at their phone at 5:30 AM just roll over and go back to sleep. For some of us, you also open up the email just to see if there's anyt...
Julia 1.0 was released at JuliaCon 2018 and it's been a quick year for the package ecosystem to build upon the first long-term stable release. In a lot of ways, pre-1.0 for packages involved a lot of experimentation; a lot of trying out various ideas...
In a recent JuliaLang Discourse post, OP was looking for a simple way to convert their Vector{CustomType} to a DataFrame, treating each CustomType element as a "row", with the fields of CustomType as fields in the row. The post piqued my interest, gi...