crumsort
go
crumsort | go | |
---|---|---|
7 | 2,075 | |
314 | 119,718 | |
- | 0.7% | |
3.6 | 10.0 | |
2 months ago | 5 days ago | |
C | Go | |
The Unlicense | BSD 3-clause "New" or "Revised" License |
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.
crumsort
-
Blitsort: An ultra-fast in-place stable hybrid merge/quick sort
Blitsort is a hybrid quicksort, see title.
It is slower than it's unstable brother, aptly named crumsort. https://github.com/scandum/crumsort
- Crumsort: Introduction to a new unstable sorting algorithm faster than pdqsort
- 380 points in 6 hours
- Crumsort: Introduction to a new sorting algorithm faster than pdqsort
-
Go will use pdqsort in the next release
https://github.com/scandum/crumsort claims better performance than pdqsort
-
Changing std:sort at Google’s Scale and Beyond
Any chance you could comment on fluxsort[0], another fast quicksort? It's stable and uses a buffer about the size of the original array, which sounds like it puts it in a similar category as glidesort. Benchmarks against pdqsort at the end of that README; I can verify that it's faster on random data by 30% or so, and the stable partitioning should mean it's at least as adaptive (but the current implementation uses an initial analysis pass followed by adaptive mergesort rather than optimistic insertion sort to deal with nearly-sorted data, which IMO is fragile). There's an in-place effort called crumsort along similar lines, but it's not stable.
I've been doing a lot of work on sorting[2], in particular working to hybridize various approaches better. Very much looking forward to seeing how glidesort works.
[0] https://github.com/scandum/fluxsort
[1] https://github.com/scandum/crumsort
[2] https://mlochbaum.github.io/BQN/implementation/primitive/sor...
go
-
Go: the future encoding/json/v2 module
A Discussion about including this package in Go as encoding/json/v2 has been started on the Go Github project on 2023-10-05. Please provide your feedback there.
-
Evolving the Go Standard Library with math/rand/v2
I like the Principles section. Very measured and practical approach to releasing new stdlib packages. https://go.dev/blog/randv2#principles
The end of the post they mention that an encoding/json/v2 package is in the works: https://github.com/golang/go/discussions/63397
-
Microsoft Maintains Go Fork for FIPS 140-2 Support
There used to be the GO FIPS branch :
https://github.com/golang/go/tree/dev.boringcrypto/misc/bori...
But it looks dead.
And it looks like https://github.com/golang-fips/go as well.
-
Borgo is a statically typed language that compiles to Go
I'm not sure what exactly you mean by acknowledgement, but here are some counterexamples:
- A proposal for sum types by a Go team member: https://github.com/golang/go/issues/57644
- The community proposal with some comments from the Go team: https://github.com/golang/go/issues/19412
Here are some excerpts from the latest Go survey [1]:
- "The top responses in the closed-form were learning how to write Go effectively (15%) and the verbosity of error handling (13%)."
- "The most common response mentioned Go’s type system, and often asked specifically for enums, option types, or sum types in Go."
I think the problem is not the lack of will on the part of the Go team, but rather that these issues are not easy to fix in a way that fits the language and doesn't cause too many issues with backwards compatibility.
[1]: https://go.dev/blog/survey2024-h1-results
-
AWS Serverless Diversity: Multi-Language Strategies for Optimal Solutions
Now, I’m not going to use C++ again; I left that chapter years ago, and it’s not going to happen. C++ isn’t memory safe and easy to use and would require extended time for developers to adapt. Rust is the new kid on the block, but I’ve heard mixed opinions about its developer experience, and there aren’t many libraries around it yet. LLRD is too new for my taste, but **Go** caught my attention.
-
How to use Retrieval Augmented Generation (RAG) for Go applications
Generative AI development has been democratised, thanks to powerful Machine Learning models (specifically Large Language Models such as Claude, Meta's LLama 2, etc.) being exposed by managed platforms/services as API calls. This frees developers from the infrastructure concerns and lets them focus on the core business problems. This also means that developers are free to use the programming language best suited for their solution. Python has typically been the go-to language when it comes to AI/ML solutions, but there is more flexibility in this area. In this post you will see how to leverage the Go programming language to use Vector Databases and techniques such as Retrieval Augmented Generation (RAG) with langchaingo. If you are a Go developer who wants to how to build learn generative AI applications, you are in the right place!
-
From Homemade HTTP Router to New ServeMux
net/http: add methods and path variables to ServeMux patterns Discussion about ServeMux enhancements
-
Building a Playful File Locker with GoFr
Make sure you have Go installed https://go.dev/.
- Fastest way to get IPv4 address from string
- We now have crypto/rand back ends that ~never fail
What are some alternatives?
fluxsort - A fast branchless stable quicksort / mergesort hybrid that is highly adaptive.
v - Simple, fast, safe, compiled language for developing maintainable software. Compiles itself in <1s with zero library dependencies. Supports automatic C => V translation. https://vlang.io
awesome-algorithms - A curated list of awesome places to learn and/or practice algorithms.
TinyGo - Go compiler for small places. Microcontrollers, WebAssembly (WASM/WASI), and command-line tools. Based on LLVM.
SHOGUN - Shōgun
zig - General-purpose programming language and toolchain for maintaining robust, optimal, and reusable software.
awesome-theoretical-computer
Nim - Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula. Its design focuses on efficiency, expressiveness, and elegance (in that order of priority).
awesome-theoretical-computer-science - The interdicplinary of Mathematics and Computer Science, Distinguisehed by its emphasis on mathemtical technique and rigour.
Angular - Deliver web apps with confidence 🚀
combsort.h - optimized combsort macro
golang-developer-roadmap - Roadmap to becoming a Go developer in 2020