The programming language Julia 1.9 has been released, featuring high performance, support for dynamic typification, and built-in means for parallel programming. Comparable to Matlab, Julia also borrows from Ruby and Lisp and manipulates lines in a way similar to Perl. The code for the project is distributed under the mit license, and the key features of the language include:
- High performance, with the goal of achieving near-SI program performance through a compiler based on LLVM project development and generating effective native machine code for multiple target platforms.
- Support for various programming paradigms with elements of object-oriented and functional programming, as well as a standard library that provides functions for asynchronous I/O, process management, logging, profiling, and packet management.
- Dynamic typification without a clear definition of types for variables, with the support of an interactive mode.
- Optional possibility of a clear indication of types, and syntax suitable for numerical, scientific, and machine learning calculations, and data visualization.
- Direct call of functions from libraries in the language without additional layers.
The principal changes in Julia 1.9 include:
- New language opportunities, including assignments in another module using “Setproperty! (:: Module, :: symbol, x)”, support for nested combinations of morphisms and named troughs of characters as type parameters, and new built-in functions “Getglobal (:: Module, :: Symbol [ Order])” and “Setglobal! (:: Module, :: Symbol, X [ Order])” for reading and writing exclusively in global variables.
- Changes in the language, such as macro “@invoke” now being exported and available for use, and the exporting of the function “Invokelatest” and the macro “@invokelatest” from the previous version.
/Reports, release notes, official announcements.