go-linq
root
go-linq | root | |
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4 | 31 | |
3,443 | 2,425 | |
- | 1.3% | |
0.0 | 10.0 | |
almost 2 years ago | 3 days ago | |
Go | C++ | |
Apache License 2.0 | GNU General Public License v3.0 or later |
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go-linq
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Fourteen Years of Go
This is a lot more possible now that Go has generics (as of 1.18).
I would probably never use these, as I find such libraries are a whole new domain-specific language to learn, and often don't make things much simpler anyway, but here are some libraries where people have done something like this:
* https://github.com/ahmetb/go-linq: modelled after LINQ, but created pre-generics so only recently added some generics features
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Querying and transforming object graphs in Go
So awhile back, there was a port of Linq https://github.com/ahmetb/go-linq that ended up giving up, since then it has been continued with https://github.com/szmcdull/glinq
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Juniper is an extended Go standard library using generics, including containers, iterators, and streams
I am aware of this that predates generics: https://github.com/ahmetb/go-linq/blob/master/groupby.go
- What libraries from other languages do you wish were ported over into go?
root
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If you can't reproduce the model then it's not open-source
I think the process of data acquisition isn't so clear-cut. Take CERN as an example: they release loads of data from various experiments under the CC0 license [1]. This isn't just a few small datasets for classroom use; we're talking big-league data, like the entire first run data from LHCb [2].
On their portal, they don't just dump the data and leave you to it. They've got guides on analysis and the necessary tools (mostly open source stuff like ROOT [3] and even VMs). This means anyone can dive in. You could potentially discover something new or build on existing experiment analyses. This setup, with open data and tools, ticks the boxes for reproducibility. But does it mean people need to recreate the data themselves?
Ideally, yeah, but realistically, while you could theoretically rebuild the LHC (since most technical details are public), it would take an army of skilled people, billions of dollars, and years to do it.
This contrasts with open source models, where you can retrain models using data to get the weights. But getting hold of the data and the cost to reproduce the weights is usually prohibitive. I get that CERN's approach might seem to counter this, but remember, they're not releasing raw data (which is mostly noise), but a more refined version. Try downloading several petabytes of raw data if not; good luck with that. But for training something like a LLM, you might need the whole dataset, which in many cases have its own problems with copyrights…etc.
[1] https://opendata.cern.ch/docs/terms-of-use
[2] https://opendata.cern.ch/docs/lhcb-releases-entire-run1-data...
[3] https://root.cern/
- What software is used to generate plots/graphs like this seen in many particle physics papers?
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Interactive GCC (igcc) is a read-eval-print loop (REPL) for C/C++
The odd part is that this is not just for fun. For many physicists when I was at CERN, a C++ REPL was a commonly used tool to interactively debug analyses to such a degree that many never compiled their code. Back then, I believe, it was some custom implementation included in ROOT (https://root.cern/). I even went out of my way to write C++ code compatible to it just so it could run with this implementation, otherwise some colleagues weren't interested in collaborating at all.
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Stable Diffusion in pure C/C++
That Python ML code is calling C++ code running in the GPU, one more reason to use C++ across the whole stack.
CERN already used prototyping in C++, with ROOT and CINT, 20 years ago.
https://root.cern/
Nowadays it is even usable from Netbooks via Xeus.
It is more a matter of lack of exposure to C++ interpreters than anything else.
- Root: Analyzing Petabytes of Data, Scientifically
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Aliens might be waiting for humans to solve a puzzle
Quantum computing is a pretty interesting science too. https://home.cern/news/press-release/knowledge-sharing/cern-quantum-technology-initiative-unveils-strategic-roadmap they have to deal with lots of data streaming too https://root.cern/
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cppyy Generated Wrappers and Type Annotations
I'm a user of CERN's ROOT (https://root.cern/) and while I'd usually write in C++, I've been trying to write as much Python as I can recently to get a bit better in the language.
- Root: Analyzing Petabytes of Scientific Data
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Span: how to cast pointer of pointer to other types?
I'm dealing with a C++ software called ROOT made by CERN, which is, if I'm not wrong, the only C++ API that we could use for data analysis such as plotting histograms, fitting multi-parameter functions and storing data in the size of TB to the disk and many more. That's the only reason why physicists still stick to this software. you can check here .
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How exactly would you go about writing a program to simplify algebraic expressions?
Hey, I found something which could be useful: https://root.cern
What are some alternatives?
Anakin - Codegeneration tool for isomorphic server and mobile Go apps with gRPC & Protobuf. Share code between your backend, Android & iOS app! :sun_with_face:
PyMesh - Geometry Processing Library for Python
pkgreflect - A Go preprocessor for package scoped reflection
xeus - Implementation of the Jupyter kernel protocol in C++
efaceconv
tfgo - Tensorflow + Go, the gopher way
gen - Type-driven code generation for Go
windows-telemetry-blocklist - Blocks outgoing Windows telemetry, compatible with Pi-Hole.
interfaces - Code generation tools for Go.
decimal - Arbitrary-precision fixed-point decimal numbers in Go
jennifer - Jennifer is a code generator for Go
apd - Arbitrary-precision decimals for Go