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Julia package for creating composable invariants with helpful error messages

Home Page: https://lorenzoh.github.io/Invariants.jl/dev/documents/README.md

License: MIT License

Julia 100.00%
julia

invariants.jl's Introduction

Hi, I'm Lorenz ๐Ÿ‘‹

I am passionate about computer vision, deep learning and software design.

Without a particular order, things I am interested in: computer vision, software, martial arts, API design, Neapolitan pizza, procedural generation, pen & paper, developer experience, technical writing, reading, pose estimation and more that I might find the time to add later ๐Ÿ˜….

If you want to reach out, feel free to message me on my Twitter, @holylorenzo!

Here on GitHub, I mainly work on better tooling for deep learning in Julia. To do this, I've authored several Julia libraries, including:

  • FastAI.jl, a high-level interface for complete deep learning projects (approved by fastai creators) (see the announcement post),
  • FluxTraining.jl, an extensible training loop with best practices,
  • DataLoaders.jl, an efficient, parallel data loader for larger-than-memory datasets
  • DataAugmentation.jl: high-performance, composable data augmentations for 2D and 3D spatial data like images, segmentation masks, and keypoints
  • Pollen.jl, a documentation system to build beautiful documentation pages for your libraries (see this example page)

I'm also a member of the FluxML organization. If you're interested in contributing, come say hi on the Zulip channel or on the biweekly ML ecosystem call (find the link here).

invariants.jl's People

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invariants.jl's Issues

Dependencies

These dependencies are a little concerning:

ANSIColoredPrinters = "a4c015fc-c6ff-483c-b24f-f7ea428134e9"
AbstractTrees = "1520ce14-60c1-5f80-bbc7-55ef81b5835c"
InlineTest = "bd334432-b1e7-49c7-a2dc-dd9149e4ebd6"
Markdown = "d6f4376e-aef5-505a-96c1-9c027394607a"
TextWrap = "b718987f-49a8-5099-9789-dcd902bef87d"

I'm wondering if it's possible to separate out the testing workflow from the invariant declarations (e.g. as a subpackage InvariantTests.jl). Invariant interfaces will be most very useful in extremely light weight base packages, and these deps will be a major source of friction for package devs.

API for interface tests

Continuing the discussion from https://discourse.julialang.org/t/discussion-on-why-i-no-longer-recommend-julia-by-yuri-vishnevsky/81151/219?u=holylorenzo @rafaqz.

Yeah lets try and get as much as possible out of defining this list! Maybe to make it available for other uses, instead of calling check like that, you could call it on the object then call the implements trait:

implements(::Type{<:MyObject}) = my_interface(optional_thing_1=true, optional_thing_2=false)

then in tests do:

check(obj)

and in docs like this would generate the markdown list of implemented traits and sub-traits:

@implements MyObject

and then in Invariants.jl define check like:

check(obj) = check(implements(obj), obj))
etc.

One problem I see with implements returning a list of invariants is that now other packages cannot extend the list of supported interfaces for a type. I think that specifically dispatching on an interface that should be checked would resolve that.

TagBot trigger issue

This issue is used to trigger TagBot; feel free to unsubscribe.

If you haven't already, you should update your TagBot.yml to include issue comment triggers.
Please see this post on Discourse for instructions and more details.

If you'd like for me to do this for you, comment TagBot fix on this issue.
I'll open a PR within a few hours, please be patient!

Issue with printing

For nested invariants, the wrapping to a fixed width and indentation does not always work correctly. This is not critical right now but should be fixed.

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