Julia 1.0: A new computing language
03
Sep
When the scenario of computing lijaguajes no longer seemed to present novelties, an audacious project of 
MIT arises that can change this logic, it is the language Julia, it is unnecessary to say that it is open source.
At a London event in 2018, the JuliaCon for developers: Professor Alan Edelman, Jeff Bezanson, Stefan Karpinski and Viral Shah released Julia 1.0, Edelman declaimed at the time: “Julia has been revolutionizing scientific and technical computing since 2009,” worked since this year in a new language that combined Ruby, MatLab, C, Python, R and others besides having parallel features, artificial intelligence and easy connection with semi-structured databases. The commands are similar to the already popular C, C ++ and Java, for example, the program of calculation of the roots of the equation of the 2º. Degree:
function quadratic2 (a :: Float64, b :: Float64, c :: Float64)
sqr_term = sqrt (b ^ 2-4a * c)
r1 = quadratic (a, sqr_term, b)
r2 = quadratic (a, -sqr -term, b)
# can return multiple values without using the return word ~
r1, r2
end
The version released on August 7, 2018, and its stable version the next day called Julia 1.0 puts it definitively in the universe of the programming languages of the present time.
The release candidate for Julia 1.0 (Julia 1.0.0-rc1) was released on August 7, 2018 and the final version one day later.
The team wrote that code that runs without warnings in Julia 0.7 will run identically on Julia 1.0. Julia uses JIT (MCJIT from LLVM) that generates native machine code directly, before a function is executed for the first time, are not bytecodes executed in a virtual machine (VM) or translated as the running bytecode, as copor example, Java, the JVM or Dalvik on Android, is even native code.
Julia is also used to drive standalone cars and 3-D printers as well as applications in precision medicine, augmented reality, genomic structures, machine learning and risk management.
As Professor Edelman said: “The release of Julia 1.0 indicates that Julia is ready to change the technical world by combining high-level productivity and ease of use of Python and R with the fast speed of C ++”, changes come there.
