Julia 0.5 Highlights
julialang.org
Julia 0.5 Highlights
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Re: Julia 0.5 Highlights
#2I'm curious to hear from people who are using Julia on a regular basis. What's the UX like? I only looked at it briefly and was turned off by some things (1-based indexing comes to mind). But I really liked other things (multiple dispatch).
Re: Julia 0.5 Highlights
#3TL;DR; This is a pretty big update. There are potentially breaking changes (e.g. errors when calling ambiguous methods). And there are significant performance improvements when dealing with functional-style programming (lambdas, closures, etc).
Re: Julia 0.5 Highlights
#4TL;DR; This is a pretty big update. There are potentially breaking changes (e.g. errors when calling ambiguous methods). And there are significant performance improvements when dealing with functional-style programming (lambdas, closures, etc).
Errors when calling ambiguous methods are unlikely to be a big hazard – at least we haven't found them to be. Most ambiguous calls are very unlikely to actually occur, which is why that change makes a lot of sense.
The big breaking change is the array indexing one – that will very much require adjusting multidimensional array code.
Re: Julia 0.5 Highlights
#5I'm curious to hear from people who are using Julia on a regular basis. What's the UX like? I only looked at it briefly and was turned off by some things (1-based indexing comes to mind). But I really liked other things (multiple dispatch).
1-based indexing is strange to a programmer, but it's commonly used in mathematical computing software like Matlab. It's actually more convenient in a lot of cases, since mathematics usually uses this form of indexing.
Re: Julia 0.5 Highlights
#6Exciting to hear -- I have used Julia for prototyping, and have found it to be excellent for that:
In my experience there are still some rough edges as compared to the Python ecosystem (of course!), which together with the 0.x status make it impractical for many production situations. However it is fantastic for prototyping numerical code, the type system is a pleasure, and the JuMP mathematical optimization library is a gem. Being able to have fast code be "first class," as opposed to the impedance mismatch of dealing with numba/Cython, feels great and is a real boon for trying new things. Then, it is fairly straightforward to port the final solution to whatever production language you use (e.g., Python with a sprinkle of numba).
Re: Julia 0.5 Highlights
#7I'm curious to hear from people who are using Julia on a regular basis. What's the UX like? I only looked at it briefly and was turned off by some things (1-based indexing comes to mind). But I really liked other things (multiple dispatch).
1-based for statistics is a STRONG reason to use it. 0 based is ridiculous for a statistics program and the reason why I left Python. I understand for looping and the arras to be internally 0 but when doing statistics I should have to use two different index.
Re: Julia 0.5 Highlights
#85 years ago I thought for sure I would be using Julia today. (I mostly use R) I have found that news tools have come into play that I haven't really felt the need for a faster language then R for my work.
I'm interested in people's everyday use of Julia and how it has impacted your workflow. I don't work with "Big Data" most of my data sets are bellow 100k in size. Anyone using Julia for medium and small data sets?
Re: Julia 0.5 Highlights
#9Exciting to hear -- I have used Julia for prototyping, and have found it to be excellent for that: In my experience there are still some rough edges as compared to the Python ecosystem (of course!), which together with the 0.x status make it impractical for many production situations. However it is fantastic for prototyping numerical code, the type system is a pleasure, and the JuMP mathematical optimization library…
Really interested in why you would use a "faster" language in julia then move to a "slower" language like Python or R?
Re: Julia 0.5 Highlights
#10I'm curious to hear from people who are using Julia on a regular basis. What's the UX like? I only looked at it briefly and was turned off by some things (1-based indexing comes to mind). But I really liked other things (multiple dispatch).
1-based indexing is strange to a programmer, but it's commonly used in mathematical computing software like Matlab. It's actually more convenient in a lot of cases, since mathematics usually uses this form of indexing.
As a primarily R and Python programmer, I've actually found that thinking in terms of 1-based indexing comes a lot more naturally to me than 0-based indexing, despite having worked exclusively in 0-based index languages for years before picking up R.
The only confusing edge case I've encountered is in biology, when manipulating a genomic region of zero length. Such a region is used, for example, when representing the location of an insertion of additional sequence. Before the insertion, the region has zero length. So, if the insertion occurs after the 500th element, then the zero-length range, in 1-based indexing, starts at 501 and ends at 500. However, it's rarely necessary to deal with this case directly, as such a range can be constructed as "starting at 501 with length 0".