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julia
ringpop-go | julia | |
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86 | 351 | |
816 | 44,622 | |
0.4% | 0.7% | |
0.0 | 10.0 | |
9 months ago | 6 days ago | |
Go | Julia | |
MIT License | MIT 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.
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Level Up Your Web App with Stunning React Charts: Introducing the Top 10 React Charts Libraries
React-vis is a user-friendly React visualization library that adheres to the core principles of React development. It seamlessly integrates with other React components, allowing you to work with it effortlessly. With properties, children, and callbacks, React-vis components can be easily composed, making it accessible even to React beginners. It was created by Uber and built with React and D3.
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Reliable Microservices Data Exchange With Streaming Database
Ride-hailing services are where a customer orders the ride from a ride-hailing platform. The best-known such services are Uber, Lyft, and Bolt.
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Waymo, Uber team up for large-scale self-driving tech
Two of the world’s leading mobility service providers, Waymo and Uber, have announced a strategic partnership to integrate Waymo’s state-of-the-art autonomous driving technology into Uber’s vast ridesharing and delivery networks. This ambitious venture is set to launch later this year, beginning in Phoenix, and is likely to significantly shift how we perceive and utilize ridesharing services.
- Taxie Rides in Fresno
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Node.js use cases: When is it worthy to use node.js for developing apps??
Successful organizations leveraging Node.js include PayPal, Netflix, Trello, LinkedIn, Uber, NASA, Walmart, Twitter, eBay, and GoDaddy. Let us explore the different industries where Node.js use cases work for offering effective results.
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What happens if you don't have a car or any transportation to get to drills?
www.uber.com
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I need somebody to help take me to UPMC East for an outpatient procedure tomorrow
They can definitely help.
- MPD officer's squad car hit by drunk driver while responding to OWI
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Vercel vs Netlify: Battle of the Jamstack Giants
The platform’s prominent clients include Meta, McDonald’s and Uber.
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Data Engineering and DataOps: A Beginner's Guide to Building Data Solutions and Solving Real-World Challenges
Whereas, Real-time processing involves persistently storing data as it comes in through events in real-time. For example, Companies like Uber and In-Drive use GPS trackers in their fleets of vehicles. Every vehicle’s location, speed, and other data are constantly being sent to a centralized server by the GPS units installed in them. So, the real-time processing system set up by these companies analyzes the data from the GPS units in near real-time. This information is used to give passengers up-to-date updates on things like vehicle locations and expected arrival times.
julia
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Top Paying Programming Technologies 2024
34. Julia - $74,963
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Optimize sgemm on RISC-V platform
I don't believe there is any official documentation on this, but https://github.com/JuliaLang/julia/pull/49430 for example added prefetching to the marking phase of a GC which saw speedups on x86, but not on M1.
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Dart 3.3
3. dispatch on all the arguments
the first solution is clean, but people really like dispatch.
the second makes calling functions in the function call syntax weird, because the first argument is privileged semantically but not syntactically.
the third makes calling functions in the method call syntax weird because the first argument is privileged syntactically but not semantically.
the closest things to this i can think of off the top of my head in remotely popular programming languages are: nim, lisp dialects, and julia.
nim navigates the dispatch conundrum by providing different ways to define free functions for different dispatch-ness. the tutorial gives a good overview: https://nim-lang.org/docs/tut2.html
lisps of course lack UFCS.
see here for a discussion on the lack of UFCS in julia: https://github.com/JuliaLang/julia/issues/31779
so to sum up the answer to the original question: because it's only obvious how to make it nice and tidy like you're wanting if you sacrifice function dispatch, which is ubiquitous for good reason!
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Julia 1.10 Highlights
https://github.com/JuliaLang/julia/blob/release-1.10/NEWS.md
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Best Programming languages for Data Analysis📊
Visit official site: https://julialang.org/
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Potential of the Julia programming language for high energy physics computing
No. It runs natively on ARM.
julia> versioninfo() Julia Version 1.9.3 Commit bed2cd540a1 (2023-08-24 14:43 UTC) Build Info: Official https://julialang.org/ release
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Rust std:fs slower than Python
https://github.com/JuliaLang/julia/issues/51086#issuecomment...
So while this "fixes" the issue, it'll introduce a confusing time delay between you freeing the memory and you observing that in `htop`.
But according to https://jemalloc.net/jemalloc.3.html you can set `opt.muzzy_decay_ms = 0` to remove the delay.
Still, the musl author has some reservations against making `jemalloc` the default:
https://www.openwall.com/lists/musl/2018/04/23/2
> It's got serious bloat problems, problems with undermining ASLR, and is optimized pretty much only for being as fast as possible without caring how much memory you use.
With the above-mentioned tunables, this should be mitigated to some extent, but the general "theme" (focusing on e.g. performance vs memory usage) will likely still mean "it's a tradeoff" or "it's no tradeoff, but only if you set tunables to what you need".
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Eleven strategies for making reproducible research the norm
I have asked about Julia's reproducibility story on the Guix mailing list in the past, and at the time Simon Tournier didn't think it was promising. I seem to recall Julia itself didnt have a reproducible build. All I know now is that github issue is still not closed.
https://github.com/JuliaLang/julia/issues/34753
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Julia as a unifying end-to-end workflow language on the Frontier exascale system
I don't really know what kind of rebuttal you're looking for, but I will link my HN comments from when this was first posted for some thoughts: https://news.ycombinator.com/item?id=31396861#31398796. As I said, in the linked post, I'm quite skeptical of the business of trying to assess relative buginess of programming in different systems, because that has strong dependencies on what you consider core vs packages and what exactly you're trying to do.
However, bugs in general suck and we've been thinking a fair bit about what additional tooling the language could provide to help people avoid the classes of bugs that Yuri encountered in the post.
The biggest class of problems in the blog post, is that it's pretty clear that `@inbounds` (and I will extend this to `@assume_effects`, even though that wasn't around when Yuri wrote his post) is problematic, because it's too hard to write. My proposal for what to do instead is at https://github.com/JuliaLang/julia/pull/50641.
Another common theme is that while Julia is great at composition, it's not clear what's expected to work and what isn't, because the interfaces are informal and not checked. This is a hard design problem, because it's quite close to the reasons why Julia works well. My current thoughts on that are here: https://github.com/Keno/InterfaceSpecs.jl but there's other proposals also.
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Getaddrinfo() on glibc calls getenv(), oh boy
Doesn't musl have the same issue? https://github.com/JuliaLang/julia/issues/34726#issuecomment...
I also wonder about OSX's libc. Newer versions seem to have some sort of locking https://github.com/apple-open-source-mirror/Libc/blob/master...
but older versions (from 10.9) don't have any lockign: https://github.com/apple-oss-distributions/Libc/blob/Libc-99...
What are some alternatives?
raft - Golang implementation of the Raft consensus protocol
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
serf - Service orchestration and management tool.
NetworkX - Network Analysis in Python
Olric - Distributed in-memory object store. It can be used as an embedded Go library and a language-independent service.
Lua - Lua is a powerful, efficient, lightweight, embeddable scripting language. It supports procedural programming, object-oriented programming, functional programming, data-driven programming, and data description.
redis-lock - Simplified distributed locking implementation using Redis
rust-numpy - PyO3-based Rust bindings of the NumPy C-API
DHT - BitTorrent DHT Protocol && DHT Spider.
Numba - NumPy aware dynamic Python compiler using LLVM
go-doudou - go-doudou(doudou pronounce /dəudəu/)is OpenAPI 3.0 (for REST) spec and Protobuf v3 (for grpc) based lightweight microservice framework. It supports monolith service application as well.
F# - Please file issues or pull requests here: https://github.com/dotnet/fsharp