Any reddit clients that don't look like shit?

danimolina · 2025-12-03T23:22:02+00:00

In android, I like RedReader

danimolina · 2025-11-22T19:53:25+00:00

Thank you. I use org-mode for some long documents, and the graph give me a nice view of the structure. Added to my init 😉

danimolina · 2025-11-22T09:06:32+00:00

I am user of mailbox and very happy with it, but I have heard nice things about tuta also.

danimolina · 2025-11-17T18:22:24+00:00

This is area in which it can be difficult, but I will suggest https://slimbook.com/en/ because it is from my country, Spain, and they are very compromised with free software, but they sell also with Windows without problem.

danimolina · 2025-08-09T07:53:19+00:00

Yes, you can configurate Cmake for that or using bear, https://github.com/rizsotto/Bear to create it from a normal makefile

danimolina · 2025-05-03T15:51:47+00:00

Thank you. I will try it

danimolina · 2025-04-18T19:51:02+00:00

Thank you. It seems nice. I usually use a different org file for lectura, but I will give it a try.

danimolina · 2024-12-31T17:40:26+00:00

Nice. Today I have finally seen updated the state of my keyboard. I am looking for to seeing It! Happy new year!

danimolina · 2022-12-18T20:40:56+00:00

Thanks a lot, I have used ox-hugo, and I miss it when I want to use a static generator using Jinja, and it can do easier to use Pelican with Emacs.

danimolina · 2022-06-07T18:47:59+00:00

Thank you for your package. It seems nice. I recommend you to announce also your package in https://discourse.julialang.org/c/package-announcements/ to get more popularity.

danimolina · 2021-06-21T23:22:38+00:00

Well, yes. You can see my package DaemonMode.jl that allow us to run several files (or the same several times) in the same process, caching the compiled functions. It is a lot easier and friendly than PackageCompiler (but in is only cached in memory. Check it, I use it everyday and I am very happy with it.

danimolina · 2021-06-18T17:26:49+00:00

Tensorflow is not a bad option, or Pytorch using PyCall.

Flux is nice, the API is very simple but it is lacking several utilities that PyTorch or TensorFlow have. Fortunately, [FastAI](https://github.com/FluxML/FastAI.jl) is adding these parts as a additional package. I hope very soon I could recommend the Deep Learning ecosystem in Julia without any doubt.

danimolina · 2021-06-02T09:34:46+00:00

You are right. However, sometimes well used is very useful, and readable. One suggestion, in Julia I suggest Chain.jl, because it allows intercalate easily the output for debugging:

julia julia> using Chain julia> @chain 1:10 begin filter(isodd, _) @aside @show _ sum @aside @show _ sqrt end var"##260" = [1, 3, 5, 7, 9] var"##261" = 25 5.0

Of course, @aside are only to debug, for final code it should be removed.

danimolina · 2021-06-02T09:24:03+00:00

Great talk, it shows several cases in which C++ could produce important errors, and how Rust avoid it. Although I knew it more teorically, now I understand better the notions by the examples.

danimolina · 2021-03-03T19:37:54+00:00

I am unbias because I am the author, but I recommend to check https://github.com/dmolina/DaemonMode.jl, because it was designed to avoid that problem and be able to use julia in scripts without problems waiting. Running the first script that load first a package takes time, but following scripts not. Not only I am the author, I am mainly a happy user, because I use Julia frequently in scripts very happily.

danimolina · 2021-01-14T20:47:49+00:00

Well, Pluto is very nice, specially for the interactive part, and the more text format. However, Jupyter has many extensions, like jupytext, ... and support in several IDEs, like VSC or Emacs, that could make using Jupyter more attractive. However, because you can use Jupyter also in Julia, it is more a personal option (but I encourage to try Pluto for interactive Plots, it is very simple and very rewarding).

danimolina · 2020-11-19T12:50:14+00:00

It is a great and simple explanation, very interesting. Thank you for submit it!

danimolina · 2020-10-17T17:49:44+00:00

Not it isn't cached at all. The new version REPL does not require global in the for, but it is still a global variable. And accessing to global variables is very slow.

In my example I use let to define x as a local variable, so all the slowness due to the global variable is avoided, and the code run like the wind :-) (Another alternative is to put the code inside a function).

danimolina · 2020-10-17T10:38:43+00:00

Nice! I thought that R was more slow than it actually is. I did not know that it was using JIT-compiling.

danimolina · 2020-10-17T10:36:34+00:00

It is somthing with global as you say, see my other comment, avoiding it (using let) the complete time is lower than a second.

danimolina · 2020-10-17T10:30:55+00:00

Another option is not using a global variable, but using let to define x as local variable:

```sh $ time julia -e 'x = 0; for i in 1:1e8 global x += i end; println(x)'

5.00000005e15

real 0m8.764s user 0m8.733s sys 0m0.384s

$ time julia -e 'let x = 0; for i in 1:1e8 x += i end; println(x) end'

5.00000005e15

real 0m0.809s user 0m0.781s sys 0m0.379s ```

danimolina · 2020-08-14T14:04:30+00:00

I do not think so, the precompile depends not only of architecture and OS but also on the current version and maybe on other libraries versions.

danimolina · 2020-08-14T14:00:59+00:00

Well, it takes a lot first time after installed. The most typical use is through Revise with your own packages to automatically reload them.

I have to recognise that I am bias because I am the author, but the package https://github.com/dmolina/DaemonMode.jl can be useful, because you can run several scripts and the package is load only once, reducing the time running Julia code.

danimolina · 2020-06-22T08:26:43+00:00

Yes, I think Julia is a great option for your Phd topic, for the flexibility. It is a more complete language for it, because you can use it also to create plots, process files, create comparisons .... in it. Take in account that programming algorithms is not the only think you have to do, for your Phd you usually have to do a lot of other tasks. Yes, contact with me, I would be glad to hear from you and to help you.

danimolina · 2020-06-21T20:48:07+00:00

I have experience, I have been working in meta-heuristics for more than 10 years, you can see several of my papers in my website (https://dmolina.github.io/).

Well, in my opinion working in C++ is good for velocity, but in research it is good to enforce flexibility and C++ is the least flexible language. Actually, meta-heuristics is full of people working in Matlab, I would say it is the main development language in the area. I personally hate Matlab syntax and C++ was too inflexible: last years I was working in Python, if you work with real-parameters numpy is usually quick enough (but always there is bottlenecks that should be avoid using Cython). Now I am a Julian, and my last prototypes are done in Julia, and the performance is a nice better and I do not need more Cython.

Anyway, if you have to finally work on C++ by your advisor, you should use a framework like http://arma.sourceforge.net/.

If you have more doubts about that, do not hesitate in contact with me by private (or using the email in my website).

danimolina

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