When I do commit, I write up the title of what I did, and describe it, and then use periods for related commits. Just easier.

I’m just glad I have other options than just Python. Am not afraid of writing my solutions either. I rarely use Python these day.

For small projects, rewriting is often superb. It allows us to reorganize a mess, apply new knowledge, add neat features and doodads, etc.

This. I’m coding to contribute to a open-source software with very small amount of coders, and with a non-mainstream Domain-Specific Language. A lot of the code I did before has been proven to work from times to time, but they all could benefit from better outputs and better GUI. So, I end up reengineering the entire and that’ll take a really long time, however, I do a lot of tests to ensure it works.

I been meaning to learn Ruby to get around using Python. I like Ruby syntax better.

I kind of like it. I can understand where it start and end.

Chances are there’s probably something similar to dictionary in Python in your languages or at least it’s a import/#include away. Although I don’t use general programming languages at all, in my used language (G’MIC), I do something like dict$var=input where $var is a defined variable, and this way I can access input by doing ${dict$var} and that’s similar to Python dictionary. In C++, there’s hash table implementation out there via github. That being said, there are sometimes when you don’t need a hashtable dependent on the hashmap, and sometimes, it’s just as simple as basic mathematics to access data.

Seems like a good idea, I’m hoping that the syntax is sane. As far as languages goes, I think you’re missing out on G’MIC to compare as it does have things like FFT and other tools all for image processing which is just part of digital signal processing. And then, there’s Python with libraries and so on.

This is what I prefer too! I also some times prefer to use bitshift when it comes to division or multiplication of power of 2.

I only stick with these:

• pull
• add
• commit
• push

Easy.

For raster graphics image processing, I’d highly recommend G’MIC. Otherwise, Python and especially for string using regex library. I wish there was a vector graphics version of G’MIC.

I only do raster graphics image processing, so G’MIC it is. A entire coding language and it’s a library in of by itself for that.

On non-DSL, don’t have a fave. I’ll choose one of these: Python, C++, C#.

Here’s my opinion, a well-developed DSL could even be arguably more flexible than say Python even with existing libraries on their specific domains. So, if one is just limited to domains, they may be very well be preferable to general languages.

I have coded in C#, Python, C++, and currently nearly everyday, G’MIC. Which one of those are a DSL? The last one. What it is? It’s a Domain-Specific Language that has been geared toward raster graphics image processing. Why do I use it? Looking at the stack-based processing, commands, built-in mathematical functions. It seems that it has a lot more things that are built-in than say Pillow library for Python and other things. And I only do create images with code, so I am happy with this, and I even did things like Python itertools combinatorics with more things like rank2list/list2rank variation of those combinatorics which aren’t image processing by themselves, but can aid to it.

If I feel that it is way too limited for that Domain, then I wouldn’t use it. DSLs are only good if the other options are much more difficult to build with and their flexibility are often enough to entice their audience which is one with limited use cases. Of course, generic languages are usually better even than most DSL even within their domains because of wider support, and wider audience. More DSLs would be better than generics given enough time and support for their domains in my opinion.