narimiran

> learning rust for a python programmer

You might give Nim[1] a try.

Coming from Python, you might find Nim's syntax (and significant whitespace) familiar. It took me (also a Python programmer) a week or so before I was able to write small programs in Nim.

(Don't let "not yet v1.0" to turn you off)

[1] https://nim-lang.org/

Captain Disillusion - https://www.youtube.com/user/CaptainDisillusion

> TD Gammon, one of the very first algorithms to reach superhuman levels in a nontrivial game, learned by self play.

Thank you for mentioning this! Neural-nets self-trained bots have been a thing for quite a while in backgammon. Chronologically, from my memory: TD Gammon, Jellyfish, Snowie, GnuBG [1], XG (eXtreme Gammon) [2]

[1] http://gnubg.org/

[2] http://extremegammon.com/

> Check out 'Fluent Python' for juicier python concepts.

One of the best Python books I've read!

But I would never recommend it to a (Python) beginner. There are more 'lightweight' books/solutions for beginner.

If GP is somewhat experienced in Python and would like to broaden his knowledge - Fluent Python all the way!

This would be my reply too. The whole site is great! I've recently went through hex grid tutorial - very informative, interactive and nicely presented.

> Anything interesting?

Couple months ago I discovered Nim [1], which I find as an interesting language, and I just finished 2015's tasks as a practice [2].

Now I'm considering using it for this year too. I'll use Python as a fallback, if/when I fail to complete some task in Nim.

[1] https://nim-lang.org/

[2] https://github.com/narimiran/advent_of_code_2015

> This year I need to make sure I do the graph search problems properly

I'm guessing this year it might be some other 'common theme' for the tasks, and we might not see as many graph-problems as in 2016.

But learning graph searches cannot hurt you either way :)

> is there a specific language used for these?

There isn't. Some previous tasks could be solved by pen-and-paper, or by using your browser's search on the input, etc.

Also, there were some users who solved each day in a different programming language.

Well, I've used previous challenges to learn/improve my Nim. And I can tell you, after solving whole 2015 challenge - my Nim skills have noticeably improved.

Would recommend AoC as a learning tool.

> Is the adventofcode.com fun/educational/worthwhile?

For me, the answer to all three questions is - yes.

It depends on your previous knowledge, so some problems might seem too easy and/or some other problems might be too hard.

If you are an experienced programmer, maybe use AoC to learn/practice some language you didn't use before?

When I started reading the feature list above, Nim was the first thing that came to my mind, until I saw the thing you mention:

> except the ecosystem/commercial backing

If this is not the most important feature on that list, here is one more vote for Nim. Give it a try, it might (pleasantly) surprise you!

> I will not consider using it for anything more than toy projects until it hits 1.0. Hopefully soon.

It should happen soon (TM), but from what I understand it will be just another version, just this time renamed to 1.0 - this basically means you could start using it more seriously even now.

> Thank you, this looks very useful to me.

I'm glad to hear that! :)

> someone who has spent several hours converting csv data to latex tables in the past

Hopefully, tably will save you some hours in the future. If you find anything that could be improved, contact me and I'll see what I can do about it.

> If you have pandas installed, ...

I'll just copy my Reddit comment when somebody notified me about `to_latex()`:

> To be honest, I didn't know this exists (and I use pandas for lots of things). If I did, I probably wouldn't even start making tably.

> Thanks for letting me know about it, I might use it as an inspiration to maybe add some more functionality in the future....

> Why? Is CSV easier to write than LaTeX?

1. When it comes to tables, yes - CSV is easier to write than LaTeX. Everything is easier than LaTeX tables :)

2. More serious reason - I have some lab equipment which outputs its results as CSV files, so this tool is used to convert those 'automatically' created .csv files.

I know this is very basic and not comparable with most of the stuff posted here, but anyway...

If you have some feature suggestion, bug report, or some general (coding) advice, please let me know. Thank you in advance!

> Sadly now I'm moving into the data science/data engineering field and everything is Python and I don't know. I don't want to go back to this nightmare.

Now there are (optional) type annotations and mypy [0]. I've been using them in my latest projects and I found them useful/helpful.

[0] http://mypy-lang.org/

> I want something that works first time, every time.

My experience with Mint is exactly like that.

Coming from Windows, I was quite surprised to see that everything works from the start - I thought the transition would be much more painful.

> I really doubt you'd prefer matplotlib's bland standard style (MBSS)

To be fair, MBSS got much better in the recent version 2.x

Before (version 1.x), I always had to use seaborn and/or modify parameters, but now the default style is good enough for most of my use cases.

> He is using all standard libraries now - once he needs more, we will figure it out as we go!

Maybe you could install Anaconda (or some similar distribution), which has lots (almost 500) of popular libraries preinstalled.

Are you sure you want to publicly share `api_key` and `api_id`?

I know this is not as impressive as some other projects here, but I would very much appreciate your feedback.

Is it easy to use? If not, what should be changed/improved? Some feature to add (or remove)?

Is the code ok? Should I refactor some parts (and why)?

Thank you in advance.

> GitHub supports rendering ipynb files so nicely (...) without cloning and firing up a Jupyter notebook.

There is a better way, with (even) nicer rendering, without any cloning: https://nbviewer.jupyter.org/

Here is a direct link for this repo: https://nbviewer.jupyter.org/github/coells/100days/tree/mast...

> you'll be blown away by the tools and functionality that proper VS offers

I've used PyCharm before, but currently VS Code seems like the right balance for my needs.

> I've done plenty of freelance projects in F# over the past few years and enjoy it

Could you give some examples of what did you do in F#? Did you choose F# just because you wanted to see if you can do it in it, or did F# have some advantages over other (functional) languages?

> It takes a while to figure out your style however. (...) Some people end up with "C# in F#" (...) And until you figure that out, it's hard to be as productive as in a language you already know.

My plan is to avoid as much as possible "writing Python in F#", because I choose F# as an opportunity to learn something new/different (which might transfer to writing better Python later). Any tips for this?

> One is lagging support in Visual Studio

I use VS Code, both for Python and now for F#, and so far my experience has been positive. But that might be because I've used F# only for very basic stuff, and I don't know how better it could be in some other language and/or IDE.

> scripts

I think I'll stick with Python for that :) But I'm thinking about maybe transferring some machine learning stuff from Python to F# in (some distant) future.

> it's hard to hire people

Many other commentators said something like this, so it seems to me that:

Not many people are using F#, because it's hard to find employer who needs F#. And employers don't seek for F# programmers, because there are too few of them.

> I would encourage you to stick with F# as you will be further along in not only understanding FP, but other modern programming languages

Thank you for your kind words!

As I mentioned elsewhere, I have also tried Haskell, but I never managed to move past some basic examples. With F#, at least for now, it seems like I can more easily read/understand even more complex stuff (and one day maybe even write it by myself).

> At some point, if your language(s) of choice are decently powerful and you are decently good at them, you don't feel yourself shackled by a lack of agility, expressivity, or capacity for producing something of quality. Rather, you feel fluent.

I consider myself fluent in Python.

But in my case, that was the extra reason to try to learn something new and different, and after searching for a suitable second language, I kinda settled for F#. (I have also tried Haskell, but never managed to move past some basic examples)

Thanks for both links! It'll be interesting to see if something has changed in public opinion in last 9 months.