Julia 1.9 Highlights
The difference in TTL arises because the system image can safely skip all the code-validation checks that are necessary when loading packages. At the time of Julia 1.9's release, only a small fraction of the package ecosystem has adopted PrecompileTools. As these new tools become leveraged more widely, users can probably expect ongoing improvements in TTFX. Methodology A demonstration workload was
Julia 1.8 Highlights
18 August 2022 | Jeff Bezanson, Jameson Nash, Ian Butterworth, Kristoffer Carlsson, Shuhei Kadowaki, Elliot Saba, Mosè Giordano, Simeon Schaub, Tim Holy, Keno Fischer After 3 betas and 4 release candidates, Julia version 1.8 has finally been released. We would like to thank all the contributors to this release and all the testers that helped with finding regressions and issues in the pre-releases.
Why We Use Julia, 10 Years Later
Exactly ten years ago today, we published "Why We Created Julia", introducing the Julia project to the world. At this point, we have moved well past the ambitious goals set out in the original blog post. Julia is now used by hundreds of thousands of people. It is taught at hundreds of universities and entire companies are being formed that build their software stacks on Julia. From personalized me
Julia 1.6 Highlights
24 March 2021 | Jeff Bezanson, Ian Butterworth, Nathan Daly, Keno Fischer, Jameson Nash, Tim Holy, Elliot Saba, Mosè Giordano, Stefan Karpinski, Kristoffer Carlsson Julia version 1.6 has been released. Most Julia releases are timed and hence not planned around specific features, but this release was an exception since it is likely to become the next long-term support (LTS) release of Julia. Becaus
A Julia interpreter and debugger
The authors are pleased to announce the release of a fully-featured debugger for Julia. You can now easily debug and introspect Julia code in a variety of ways: Step into functions and manually walk through your code while inspecting its state Set breakpoints and trap errors, allowing you to discover what went wrong at the point of trouble Interactively update and replace existing code to rapidly
Announcing the release of Julia 1.0
Translations: Simplified Chinese, Traditional Chinese, Spanish The much anticipated 1.0 release of Julia is the culmination of nearly a decade of work to build a language for greedy programmers. JuliaCon 2018 celebrated the event with a reception where the community officially set the version to 1.0.0 together. The release was accompanied by a talk: A brief history and wild speculation about the f
Some fun with Π in Julia
14 March 2017 | Simon Byrne, Luis Benet and David Sanders Image courtesy of Cormullion, code here. This post is available as a Jupyter notebook here. π in Julia by Simon Byrne Like most technical languages, Julia provides a variable constant for π. However Julia's handling is a bit special. pi π = 3.1415926535897... It can also be accessed via the unicode symbol (you can get it at the REPL or in a
Julia 0.5 Highlights
To follow along with the examples in this blog post and run them live, you can go to JuliaBox, create a free login, and open the "Julia 0.5 Highlights" notebook under "What's New in 0.5". The notebook can also be downloaded from here. Julia 0.5 is a pivotal release. It introduces more transformative features than any release since the first official version. Moreover, several of these features set
StructuredQueries.jl - A generic data manipulation framework
This post describes my work conducted this summer at the Julia Lab to develop StructuredQueries.jl, a generic data manipulation framework for Julia. Our initial vision for this work was much inspired by Hadley Wickham's dplyr R package, which provides data manipulation verbs that are generic over in-memory R tabular data structures and SQL databases, and DataFramesMeta (begun by Tom Short), which
Multidimensional algorithms and iteration
Note: updated December 2018 for Julia 1.1 Note: updated April 2020 for clarity Julia makes it easy to write elegant and efficient multidimensional algorithms. The new capabilities rest on two foundations: an iterator called CartesianIndices, and sophisticated array indexing mechanisms. Before I explain, let me emphasize that developing these capabilities was a collaborative effort, with the bulk o
JSoC 2015 project: Efficient data structures and algorithms for sequence analysis in BioJulia
JSoC 2015 project: Efficient data structures and algorithms for sequence analysis in BioJulia Participant: Kenta Sato (@bicycle1885) Mentor: Daniel C. Jones (@dcjones) Thanks to a grant from the Gordon and Betty Moore Foundation, I've enjoyed the Julia Summer of Code 2015 program administered by the NumFOCUS and a travel to the JuliaCon 2015 at Boston. During this program, I have created several p
Julia 0.4 Release Announcement
We are pleased to announce the release of Julia 0.4.0. This release contains major language refinements and numerous standard library improvements. A summary of changes is available in the NEWS log found in our main repository. We will be making regular 0.4.x bugfix releases from the release-0.4 branch of the codebase, and we recommend the 0.4.x line for users requiring a more stable Julia environ
The Julia Programming Language
Fast Julia was designed for high performance. Julia programs automatically compile to efficient native code via LLVM, and support multiple platforms. Dynamic Julia is dynamically typed, feels like a scripting language, and has good support for interactive use, but can also optionally be separately compiled. Reproducible Reproducible environments make it possible to recreate the same Julia environm
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Julia 1.10 Highlights
DiffEqFlux.jl – A Julia Library for Neural Differential Equations
Knowing where you are: custom array indices in Julia
JuliaCon 2015 Preview - Deep Learning, 3D Printing, Parallel Computing, and so much more
Videos from the Julia tutorial at MIT