Dask
Nim
Our great sponsors
Dask | Nim | |
---|---|---|
32 | 346 | |
11,982 | 16,060 | |
1.5% | 0.8% | |
9.7 | 9.9 | |
6 days ago | 3 days ago | |
Python | Nim | |
BSD 3-clause "New" or "Revised" License | GNU General Public License v3.0 or later |
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.
Dask
- The Distributed Tensor Algebra Compiler (2022)
-
A peek into Location Data Science at Ola
Data scientists work on phenomenally large datasets, and Dask is a handy tool for exploration within the confines of a single cloud VM or their local PCs. Location data visualization is an essential part of deciding further algorithm development and roadmap for projects. This lays the foundation for data engineering and science to work at scale, with petabytes of data.
- File format for large data with many columns
-
What is the best way to save a csv.file in number only ? PC hangs when my file is more than 2GB
Dask
-
Large Scale Hydrology: Geocomputational tools that you use
We're using a lot of Python. In addition to these, gridMET, Dask, HoloViz, and kerchunk.
-
msgspec - a fast & friendly JSON/MessagePack library
I wrote this for speeding up the RPC messaging in dask, but figured it might be useful for others as well. The source is available on github here: https://github.com/jcrist/msgspec.
-
What does it mean to scale your python powered pipeline?
Dask: Distributed data frames, machine learning and more
-
Data pipelines with Luigi
To do that, we are efficiently using Dask, simply creating on-demand local (or remote) clusters on task run() method:
-
Is Numpy always more efficient than Pandas? And how much should we rely on Python anyway?
Look into Dask, see: https://dask.org/
-
Ask HN: Is PySPark a Dead-End?
[1] https://dask.org/
Nim
-
Top Paying Programming Technologies 2024
22. Nim - $80,000
-
"14 Years of Go" by Rob Pike
I think the right answer to your question would be NimLang[0]. In reality, if you're seeking to use this in any enterprise context, you'd most likely want to select the subset of C++ that makes sense for you or just use C#.
[0]https://nim-lang.org/
- Odin Programming Language
-
Ask HN: Interest in a Rust-Inspired Language Compiling to JavaScript?
I don't think it's a rust-inspired language, but since it has strong typing and compiles to javascript, did you give a look at nim [0] ?
For what it takes, I find the language very expressive without the verbosity in rust that reminds me java. And it is also very flexible.
[0] : https://nim-lang.org/
-
The nim website and the downloads are insecure
I see a valid cert for https://nim-lang.org/
-
Nim
FYI, on the front page, https://nim-lang.org, in large type you have this:
> Nim is a statically typed compiled systems programming language. It combines successful concepts from mature languages like Python, Ada and Modula.
-
Things I've learned about building CLI tools in Python
You better off with using a compiled language.
If you interested in a language that's compiled, fast, but as easy and pleasant as Python - I'd recommend you take a look at [Nim](https://nim-lang.org).
And to prove what Nim's capable of - here's a cool repo with 100+ cli apps someone wrote in Nim: [c-blake/bu](https://github.com/c-blake/bu)
-
Mojo is now available on Mac
Chapel has at least several full-time developers at Cray/HPE and (I think) the US national labs, and has had some for almost two decades. That's much more than $100k.
Chapel is also just one of many other projects broadly interested in developing new programming languages for "high performance" programming. Out of that large field, Chapel is not especially related to the specific ideas or design goals of Mojo. Much more related are things like Codon (https://exaloop.io), and the metaprogramming models in Terra (https://terralang.org), Nim (https://nim-lang.org), and Zig (https://ziglang.org).
But Chapel is great! It has a lot of good ideas, especially for distributed-memory programming, which is its historical focus. It is more related to Legion (https://legion.stanford.edu, https://regent-lang.org), parallel & distributed Fortran, ZPL, etc.
- NIR: Nim Intermediate Representation
What are some alternatives?
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
zig - General-purpose programming language and toolchain for maintaining robust, optimal, and reusable software.
Numba - NumPy aware dynamic Python compiler using LLVM
go - The Go programming language
Kedro - Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.
Odin - Odin Programming Language
NetworkX - Network Analysis in Python
rust - Empowering everyone to build reliable and efficient software.
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
crystal - The Crystal Programming Language
Interactive Parallel Computing with IPython - IPython Parallel: Interactive Parallel Computing in Python
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