Julia, oh Julia!

Hello, so far I have only been learning/programming with Julia in order to get a good understanding of how the language is compiled and how the data structures are implemented. Its been a whirl wind of a journey and I have learnt a bit. I have no background in any other language other than C++ but Julia has rather helped me learn on a bit about Python as well. The two languages are very similar in syntax and they’re both higher level scripting languages. But one of Julia’s main features is that it’s compiled at run time which allows for metaprogramming. It also boasts that its as fast as C despite being a traditionally scientific computing language like Matlab/R. Julia was originally created with scientific computing in mind but traditionally, languages that support those domains have lacked in performance. But Julia bridges that gap between convenience and performance and provides the ideal language for numerical crunching. It’s a fairly new project but it has a world wide appeal and there’s almost a thousand contributors on their main github page. As of now, thers’s about 2500 issues open on their github and more than 700 pull requests open. So it’s a very active community and the issues and PRs seem to get very quick responses from the reviewers. So they definitely need help over there and our team has managed to pin down some “good first issues” and started meeting up to work on them over the week. But at the same time it has been rather difficult because of exams and school work, we don’t really get all that much time to work on the project. But still we’re making some steady progress and hopefully by next week we’ll have something going. That’s all for this week, thanks for checking in!