Another open source Fortran code that would be ideal for Julia to replace is esp-r. It does a really good job of hourly simulation for building energy use.
If Julia were the glue code, would new development in Code Aster be done in Julia?
Agree here – I love all the work that’s been put into the dataframes ecosystem, but I still tilt more towards R and tidyverse to do general data manipulation. I suspect this is more because I just know how do tidyverse and less that Julia’s dataframe stuff is insufficient. Perhaps I just need to finally get over myself and lean in fully to the Julia stack when it comes to lots of dataframe manipulation.
Maybe GitHub - TidierOrg/Tidier.jl: 100% Julia implementation of the R tidyverse mini-language can help the transition.
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I wonder if there are some comparisons like “that’s how easy it is in Stata” vs “that’s how difficult it is in Python/Julia”. Speaking as someone who never used nor seen Stata, understanding the nice tools already existing in those ecosystems would potentially be useful, including for creation of relevant tools in Julia. Pretty sure there are a lot of people with Python+Julia background, but without any knowledge of specialized software like stata.
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That would be the idea. I am pretty convinced that the source code is much less important than the mechanical knowledge accumulated in the tests. The glue code, i.e the command language (dsl),could be nicely redesigned with Julia.
My thoughts are that Julia will gain popularity as the market demands focus more on things that Julia is so good at.
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List item Julia is FAST. In our current - and future economy - this is extremely important… quoting NVidia CEO Jensen Huang “The idea that a chip is going to go down in cost over time, unfortunately, is a story of the past” PC Mag article link. So, if the question is upgrade CPU’s and GPU’s to support the future computational load… or switch to more efficient programming languages, companies will probably take a close look at both.
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List item Julia is EASY to learn
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Julia has already adopted many major packages that Python leverages or created packages with similar capabilities.
So, I have been using Julia for less than 1 month today. During that time, I have joined the Genie Discord and received some wonderful help and advice. Since the day that I joined, around 25 persons have also joined the discord server… so approximately 1 per day.
I have noticed, in my short time, my biggest obstacle was setting up a working system. Secondly, that several examples and online resources were outdated, and I spend a lot of my time trying to find the correct syntax to execute the code that I want to execute. Although, I have probably started learning Julia the wrong way… just brute force “I’m going to try this…” 
and finding out how different the syntax is compared to Python.
There are some really great resources:
Youtube - Doggo dot jl
JuliaAcademy (but admittedly I just browsed content, and I have yet to register for a class 
)
I think Julia has a bright future. I believe the tech and business industries had a tough time adopting Python from the research industry… but now that has been done once, it may be easier for the those industries (and others) to adopt Julia, because this type change has already been done once.
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What did you think of Julia, Its community and its ecosystem before you started learning it? Have those thoughts changed?
I first learned of Julia several years ago when I was learning Python. I heard that Julia was very fast and an excellent choice for data analysis. I continued to learn Python though, because of its utility, and I am happy to see it adopted in so many applications.
Recently, and out of curiousity, I decided to look at Julia. At the time, I did not know anything about the language or about the community. I started looking at Julia on YouTube and watched many of the JuliaCon videos.
I was really attracted to the demos using interactive dashboards and web applications to work with data. I think it’s the kind of thing that you can take to a small or medium-sized business and fulfill the roles of several off-the-shelf and custom off-the-shelf software packages. I have a lot to say of this topic and it would be best for another thread.
I am very happy with the community because there are a lot of very knowledgeable people willing to answer questions. I am grateful for all of the assistance that I have received, and I try to help other new users and answer questions where I can.
So far, in my Julia journey, I have made a lot of mistakes, and I make more each day… but I learn from each of them. I spend a lot of time reading about Julia, watching videos, and trying to find the right way to write code in Julia, and I am not afraid to ask embarrassing or stupid questions (seriously, clueless is in my name 
). As a result from hard work, a bit of vulnerability, and a gracious and helpful community, I am learning quickly.
Everyone should thank a Julia DEV! Thank you all!! 
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It seems that Julia is easily marketable, but little known outside the Julia community.
Would blog posts like the one comparing Rust vs Julia for scientific computing help promote Julia outside the Julia community? This week’s Rust newsletter promotes that blog post.
What do you think of the didactic material? Did you find it adequate for a beginner or a bit difficult to understand with too much jargon?
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Step 0: Make admission to online JuliaCon free.
Watching juliacon videos is free, as it has always been. The JuliaLang channel on YouTube doesn’t even have ads, as far as I can tell.
If you’re referring to the ticket for online admission, that’s only to support cost of audio/video setup for the conference and remain in the loop of communication sent to participants. But videos will be publicly available anyway.
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Of course, the videos are free.
Making online admission free is the least one can do, given a big chunk of the target audience at this point are students and academics.
I’m missing what you expect from having a free online ticket. The online admission is basically a voluntary donation. Do you want to make a free donation?
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- Virtual JuliaCon (due to the pandemic) has been entirely free.
- Online “admission” is free this year as well. As @giordano said, the online “ticket” is merely a free donation.
Note, however, that this years JuliaCon is in-person and not really hybrid. That is, while talks will be recorded and even live-streamed as much as possible, there won’t be many ways to participate, i.e. no discord as we had it the last couple of years. Running a (good!) hybrid event is much(!) more work and currently impossible to realise with the funds and manpower we have. After all, someone has to pay and work for these extra services.
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Thanks.
So, it appears Julia is in need of some serious (corporate) backing, if we need to bring it to the “next level of popularity”. At what stage does this become critical with the kind of money pouring into other languages & frameworks?
It seems like a chicken or the egg problem. Without corporate backing, Julia can’t move to the next level of popularity, and if Julia isn’t more popular, companies won’t back it.
By the way, could the Julia-lang website show which companies and scientific institutions use Julia as the Go website does?
Not sure if popularity is a criterion for corporate backing. Return on investment is.
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Echoing @GenerallyClueless, I had heard of Julia a while back (8 years?) and it sounded cool, but the version number was 0.x, and what I had been working with seemed to be working okay (Python wrappers around C/C++). Now I am doing something different, and we at the office agreed that there had to be a more efficient way of doing things (which was, prototype in Python, then replace the slow parts in C/C++ - but we actually rarely did that, we just suffered with slow).
My great idea was “use Rust,” because it was my hobby language. My boss said “try Julia,” and I didn’t know enough about Julia to tell him that I knew better. All I could come up with is that I couldn’t figure out how to compile to an executable - but the more I worked with Julia, the less I cared about that.
I’m far from expert yet, but I find for science/engineering work, Julia is just great, and for a group of people that are moving from Python/NumPy/Jupyter … the transition is pretty easy. Sure, I miss some things like OpenCV and VTK, but sooner or later I’ll figure out how to integrate them.
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The JuliaHub website shows users and customers.
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