julia
CPython
julia | CPython | |
---|---|---|
350 | 1,319 | |
44,569 | 59,856 | |
0.6% | 1.4% | |
10.0 | 10.0 | |
2 days ago | 4 days ago | |
Julia | Python | |
MIT License | GNU General Public License v3.0 or later |
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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...
CPython
- A library to assist writing memory-unsafe code in "pure" Python
- OpenBSD 7.3 を 7.4 へ アップグレード
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Bitcoin Sentiment Analysis using Python and X (Formerly Twitter)
Thankfully, Python, the go-to coding language for loads of developers, is here to save the day. It's got some awesome features for diving into text sentiment analysis. With cool libraries like Tweepy, we can sift through X(Twitter) data and snag those interesting tweets about Bitcoin. And then there's TextBlob, a clever tool for understanding the sentiment in text. When it's time to clean up and organize all that data, libraries like pandas and numpy are there to help out. And let's not forget about matplotlib, the master of visualisations that can help us see the trends in sentiment crystal clear. Armed with these tools, developers can really dig deep into social media data and figure out what the general public thinks about Bitcoin.
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scrape-yahoo-finance
Web Scraping Tool Development: Develop a Python based web scraping tool capable of extracting data from targeted web pages on Yahoo Finance and presenting the data extracted in a readable format. Our target site relies on AJAX to load and update the data dynamically so we will need a tool that is capable of processing JavaScript.
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Employee Management System using Python.
Dealing with piles of papers or scattered Excel sheets for employee information can be a real headache, right? Well, what if I told you there's a smoother way to handle all that? A system that lets you easily store, update, and find details about your employees in just a few clicks. Sounds neat, doesn't it? In this article, we're going to explore creating an employee management system using Python, Tkinter, and SQLite3.
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Build a Product Receipt Generator using Python.
Python is a versatile tool, and today we're delving into a practical use case that can simplify your daily routines. With the datetime module at your disposal, handling dates and times becomes a breeze, making it perfect for crafting accurate and dynamic product receipts. Whether you're a seasoned Python pro or just starting your coding journey, this article will guide you through each step with ease.
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Build a Music Player with Python
When working in Visual Studio Code (VS Code), create a new Python file for our music player project. It's helpful to have separate files for different parts of your project.
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PEP 744 – JIT Compilation
> It provides a meaningful performance improvement for at least one popular platform (realistically, on the order of 5%).
At first it will not provide a large boost, but it will set the foundations for larger gains in subsequent releases. They link a list of some proposed improvements already underway, with improvement estimates, at https://github.com/python/cpython/issues/115802
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Featured Mod of the Month: Phil Ashby
After that, with the basics of software engineering understood, I would move on to a wider use language, with a bigger ecosystem to employ, most likely Python. This would expose me to large system design / distributed systems and architectural challenges...
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Convert Images Into Pencil Sketch
Have you ever felt like your photos needed a little extra touch to stand out? Well, get ready because we're about to learn a cool Python trick! We're going to take ordinary photos and turn them into awesome pencil sketches using Python and OpenCV. This will make your pictures look like they were drawn by hand!
What are some alternatives?
jax - Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more
RustPython - A Python Interpreter written in Rust
NetworkX - Network Analysis in Python
ipython - Official repository for IPython itself. Other repos in the IPython organization contain things like the website, documentation builds, etc.
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.
Vulpix - Fast, unopinionated, minimalist web framework for .NET core inspired by express.js
rust-numpy - PyO3-based Rust bindings of the NumPy C-API
Visual Studio Code - Visual Studio Code
Numba - NumPy aware dynamic Python compiler using LLVM
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F# - Please file issues or pull requests here: https://github.com/dotnet/fsharp
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more