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Update README for v0.7
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brenhinkeller committed Jul 28, 2022
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[![CI (Integration nightly)](https://github.com/brenhinkeller/StaticTools.jl/workflows/CI%20(Integration%20nightly)/badge.svg)](https://github.com/brenhinkeller/StaticTools.jl/actions/workflows/CI-integration-nightly.yml)
[![Coverage](https://codecov.io/gh/brenhinkeller/StaticTools.jl/branch/main/graph/badge.svg)](https://codecov.io/gh/brenhinkeller/StaticTools.jl)

Tools to enable [StaticCompiler.jl](https://github.com/tshort/StaticCompiler.jl)-based static compilation of Julia code (or more accurately, a subset of Julia which we might call "unsafe Julia") to standalone native binaries by avoiding GC allocations and `llvmcall`-ing all the things. Warning: experimental! 🐛
Tools to enable [StaticCompiler.jl](https://github.com/tshort/StaticCompiler.jl)-based static compilation of Julia code (or more accurately, a subset of Julia which we might call "unsafe Julia") to standalone native binaries by avoiding GC allocations and `llvmcall`-ing all the things! (Experimental! 🐛)

This package currently requires Julia 1.8 for best results (in particular, 1.8.0-beta3 is known to work). Integration tests against StaticCompiler.jl and LoopVectorization.jl are currently run with Julia 1.8 on x86-64 linux and mac; other platforms and versions may or may not work but will depend on StaticCompiler.jl support.
This package currently requires Julia 1.8 or greater for best results (if in doubt, check [which versions are passing CI](https://github.com/brenhinkeller/StaticTools.jl/actions?query=workflow%3ACI++)). Integration tests against StaticCompiler.jl and LoopVectorization.jl are currently run with Julia 1.8 and 1.9 on x86-64 linux and mac; other platforms and versions may or may not work but will depend on StaticCompiler.jl support.

While we'll do our best to keep things working, this package should still be considered experimental at present, and necessarily involves a lot of juggling of pointers and such (i.e., "unsafe Julia"). If I've made errors in any of the `llvmcall`s (which we have to use instead of simpler `ccall`s for things to statically compile smoothly), there could be serious bugs or even undefined behavior. PRs welcome!
While we'll do our best to keep things working, this package should still be considered experimental at present, and necessarily involves a lot of juggling of pointers and such (i.e., "unsafe Julia"). If there are errors in any of the `llvmcall`s (which we have to use instead of simpler `ccall`s for things to statically compile smoothly), there could be serious bugs or even undefined behavior. Please report any unexpected bugs you find, and PRs are welcome!

The stack-allocated statically-sized `StaticString`s in this package are heavily inspired by the techniques used in [JuliaSIMD/ManualMemory.jl](https://github.com/JuliaSIMD/ManualMemory.jl); you can use that package via [StrideArraysCore.jl](https://github.com/JuliaSIMD/StrideArraysCore.jl) or [StrideArrays.jl](https://github.com/chriselrod/StrideArrays.jl) to obtain fast stack-allocated statically-sized arrays which should also be StaticCompiler-friendly.

In addition to the exported names, Julia `Base` functions extended for StaticTools types (i.e., `StaticString`/ `MallocString` and `StackArray`/`MallocArray`) include:
* `print`, `println`, `error`,
* `parse`,
* `rand` (when using an `rng` initialied with `static_rng`, `SplitMix64`, or `Xoshiro256✴︎✴︎` )
* `randn` (when using an `rng` initialied with `BoxMuller`, or `MarsagliaPolar` )
* `parse`, `read`, `write`
* `rand`/`rand!` (when using an `rng` initialied with `static_rng`, `SplitMix64`, or `Xoshiro256✴︎✴︎` )
* `randn`/`randn!` (when using an `rng` initialied with `MarsagliaPolar`, `BoxMuller`, or `Ziggurat` )
* and much or all of the `AbstractArray` and `AbstractString` interfaces where relevant.

[![Mandelbrot Set in the terminal with compiled Julia](docs/mandelcompilemov.jpg)](http://www.youtube.com/watch?v=YsNC4oO0rLA)
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Release notes:

  • Switch to Base rand's syntax where the rng always comes before the type (breaking!)
  • Add rand(::StaticRNG, ...) methods for more native types, efficiency improvments
  • Add new Ziggurat StaticRNG for Gaussian random numbers (expensive to initialize, but subsequently fast)
  • Add dependency on Random stdlib so we can extend rand! and randn! for StaticRNGs
  • Add, test, and export methods for rand! and randn!
  • Refactor rng dispatch

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Registration pull request created: JuliaRegistries/General/65344

After the above pull request is merged, it is recommended that a tag is created on this repository for the registered package version.

This will be done automatically if the Julia TagBot GitHub Action is installed, or can be done manually through the github interface, or via:

git tag -a v0.7.0 -m "<description of version>" 202812af2cb214767a1320638d3b8fb79e0c667f
git push origin v0.7.0

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