FsLibLog VS equinox

Compare FsLibLog vs equinox and see what are their differences.


FsLibLog is a single file you can copy paste or add through Paket Github dependencies to provide your F# library with a logging abstraction. This is a port of the C# LibLog. (by TheAngryByrd)


Callable PyTrees and filtered JIT/grad transformations => neural networks in JAX. (by patrick-kidger)
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FsLibLog equinox
1 12
44 540
- -
5.9 9.4
26 days ago 9 days ago
F# Python
MIT License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.


Posts with mentions or reviews of FsLibLog. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-11-10.


Posts with mentions or reviews of equinox. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-04-14.

What are some alternatives?

When comparing FsLibLog and equinox you can also consider the following projects:

treex - A Pytree Module system for Deep Learning in JAX

flax - Flax is a neural network library for JAX that is designed for flexibility.

fsharp - Native support for destructuring F# types when logging to Serilog.

TF_JAX_tutorials - All about the fundamental blocks of TF and JAX!

Roslyn - The Roslyn .NET compiler provides C# and Visual Basic languages with rich code analysis APIs.

Giraffe - A native functional ASP.NET Core web framework for F# developers.

the-ray-tracer-challenge-fsharp - F# implementations of the ray tracer found in The Ray Tracer Challenge book by Jamis Buck.

torchtyping - Type annotations and dynamic checking for a tensor's shape, dtype, names, etc.