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thautwarm
MLStyle.jl
Julia2019–2021
thautwarm / MLStyle.jl

MLStyle.jl

Julia functional programming infrastructures and metaprogramming facilities

Libraries & SDKs
Explore on GitHubRead Hacker News discussions
4Distinct people
4Mentions
0Explicit recommenders
422GitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

Julia functional programming infrastructures and metaprogramming facilities

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 3:56:07 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by month4 dated mentions

Observed mentions: 2019-05-05 11:35:30 UTC to 2021-02-10 22:22:31 UTC.

0122019-05-01 00:00:00 UTC to 2019-06-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 commentsMay 20192019-06-01 00:00:00 UTC to 2019-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-07-01 00:00:00 UTC to 2019-08-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2019-08-01 00:00:00 UTC to 2019-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-09-01 00:00:00 UTC to 2019-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-10-01 00:00:00 UTC to 2019-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-11-01 00:00:00 UTC to 2019-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-12-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-01-01 00:00:00 UTC to 2020-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-02-01 00:00:00 UTC to 2020-03-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-03-01 00:00:00 UTC to 2020-04-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 commentsMar 20202020-04-01 00:00:00 UTC to 2020-05-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-05-01 00:00:00 UTC to 2020-06-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-06-01 00:00:00 UTC to 2020-07-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-07-01 00:00:00 UTC to 2020-08-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-08-01 00:00:00 UTC to 2020-09-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-09-01 00:00:00 UTC to 2020-10-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-10-01 00:00:00 UTC to 2020-11-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-11-01 00:00:00 UTC to 2020-12-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-12-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-01-01 00:00:00 UTC to 2021-02-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2021-02-01 00:00:00 UTC to 2021-03-01 00:00:00 UTC (exclusive): 2 mentions; 0 submissions, 2 commentsFeb 2021

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
May 20192019-05-01 00:00:00 UTC2019-06-01 00:00:00 UTC101
Jun 20192019-06-01 00:00:00 UTC2019-07-01 00:00:00 UTC000
Jul 20192019-07-01 00:00:00 UTC2019-08-01 00:00:00 UTC101
Aug 20192019-08-01 00:00:00 UTC2019-09-01 00:00:00 UTC000
Sep 20192019-09-01 00:00:00 UTC2019-10-01 00:00:00 UTC000
Oct 20192019-10-01 00:00:00 UTC2019-11-01 00:00:00 UTC000
Nov 20192019-11-01 00:00:00 UTC2019-12-01 00:00:00 UTC000
Dec 20192019-12-01 00:00:00 UTC2020-01-01 00:00:00 UTC000
Jan 20202020-01-01 00:00:00 UTC2020-02-01 00:00:00 UTC000
Feb 20202020-02-01 00:00:00 UTC2020-03-01 00:00:00 UTC000
Mar 20202020-03-01 00:00:00 UTC2020-04-01 00:00:00 UTC000
Apr 20202020-04-01 00:00:00 UTC2020-05-01 00:00:00 UTC000
May 20202020-05-01 00:00:00 UTC2020-06-01 00:00:00 UTC000
Jun 20202020-06-01 00:00:00 UTC2020-07-01 00:00:00 UTC000
Jul 20202020-07-01 00:00:00 UTC2020-08-01 00:00:00 UTC000
Aug 20202020-08-01 00:00:00 UTC2020-09-01 00:00:00 UTC000
Sep 20202020-09-01 00:00:00 UTC2020-10-01 00:00:00 UTC000
Oct 20202020-10-01 00:00:00 UTC2020-11-01 00:00:00 UTC000
Nov 20202020-11-01 00:00:00 UTC2020-12-01 00:00:00 UTC000
Dec 20202020-12-01 00:00:00 UTC2021-01-01 00:00:00 UTC000
Jan 20212021-01-01 00:00:00 UTC2021-02-01 00:00:00 UTC000
Feb 20212021-02-01 00:00:00 UTC2021-03-01 00:00:00 UTC202

What Hacker News says

4 sources
O_H_E·Feb 10, 2021
> and we're stuck with an inferior Lisp/ML, especially in the scientific sector. You will love Julia. Here are some links: https://julialang.org/blog/2012/02/why-we-created-julia/ Julia: Dynamism and Performance Reconciled by Design (https://dl.acm.org/doi/pdf/10.1145/3276490) <= This is great and surprisingly approachable. https://opensourc.es/blog/basics-multiple-dispatch/ And when you start finding things that you miss, Julia and the community got you with excellent Metaprogramming support. https://github.com/thautwarm/MLStyle.jl https://github.com/MikeInnes/Lazy.jl https://github.com/jkrumbiegel/Chain.jl
In Pattern matching accepted for Python
ddragon·Jul 24, 2019
You can use the search tools to find libraries for the categories you're interested at: https://juliaobserver.com/packages https://pkg.julialang.org/docs/ As a personal answer, I really like unitful for keeping track of physical units and libraries like MLStyle.jl or Match.jl which add stuff like pattern matching to the language (though they are more general helper libraries compared to stuff like Turing.jl and DifferentialEquations.jl): https://painterqubits.github.io/Unitful.jl/stable/highlights... https://github.com/thautwarm/MLStyle.jl
In Composable multi-threaded parallelism in Julia
KenoFischer·May 5, 2019
ML Style constructors are not particularly idiomatic, but you can write basically the same thing in Julia: struct Cons{T, S}; head::T; tail::S end pairwiseReduction(f, a::Cons{T, Cons{S, Tail}}) where {T,S,Tail} = Cons(f(a.head, a.tail.head), a.tail.tail) pairwiseReduction(f, a) = a (https://github.com/thautwarm/MLStyle.jl if you want the syntax) but that's somewhat beside the point. I think the primary problem here is one of terminology. Take Stefan's quote from the post you're responding to: > The primary difference between static and dynamic languages, in my view, is this: in static languages, expressions have types; in dynamic languages, values have types. There is a clash in terminology here. People coming from a static languages background would use the term "tag" for what dynamic languages people call a type. There isn
Read the rest
't really a super good word in the dynamic languages world for what static languages people call a type, and the word type is generally re-used, since the distinction isn't as important (generally there is an embedding of the tags into the type system, so using "type" for both can be sensible). I'm gonna adopt (my best interpretation of) the static languages terminology here for this comment. Some languages have both types and tags. The biggest difference then between static and dynamic languages are which of the two is primarily dispositive (in the sense of determining the semantics of the language). In dynamic languages, the tags are, in static languages the types are. This choice has deep seated implication for the kind of programs that can be written and the behavior of the program. In fact, you sometimes end up in situations where static languages have multiple tag systems (but generally only one type system) and dynamic languages have multiple type systems (but generally only one tag system). In julia, the tag system is primary, but we have a very rich type system that is embedded in the tag system by parametricity and is used for dispatch. This type system is constructed in such a way that the subtyping relationship is induced by tag system (for types T, S, (T <: S iff for all values v s.t. tagof(v) <: T, tagof(v) <: S)) [1]. You basically want to choose a decidable type system that satisfies this constraint, but is at the same time sufficiently expressive to be useful for what people want to do. We also have another, larger type system that is used for inference judgements, but that is generally transparent to the user. It is in principle possible to type check over any of these type static system, but type checking is not part of the semantics of the language. The problem with statements like "Julia's type system does not allow for X", is that it presumes that the type system having some feature is a pre-requisite for having the corresponding functionality. So while Julia's type system does happen have support for unions (and universally qualified unions), the significance of that is for dispatch, not for whether the language can have expressions that can take on values of different tags. In any case, I can assure you that many people working on Julia are well familiar with Haskell's type system. Hopefully I was able to convince you that there is at least something interesting about the way Julia's type system works. [1] I should credit the Northeastern PL group for the term "tag-based semantic subtyping" here to describe this notion (https://github.com/julbinb/ftfjp-2019/blob/master/paper/mini...).
In What to Know Before Debating Type Systems (2008)

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