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https://github.com/Taaitaaiger/jlrs

Julia bindings for Rust
https://github.com/Taaitaaiger/jlrs

ffi julia rust

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Julia bindings for Rust

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README 

        
# jlrs



[![Rust Docs](https://docs.rs/jlrs/badge.svg)](https://docs.rs/jlrs)

[![License:MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)



jlrs is a crate that provides access to the Julia C API. It can be used to embed Julia in Rust

applications and to write interop libraries to Rust crates that can be used by Julia.



Julia versions 1.6 up to and including 1.11 are supported, but only the LTS and stable versions

are actively tested. Using the current stable version of Julia is highly recommended. The minimum

supported Rust version is currently 1.77.



This readme only contains information about what features are supported by jlrs, what

prerequisites must be met, and how to meet them. For information and examples about how to use

jlrs, please read the [docs](https://docs.rs/jlrs). The documentation assumes you are already

familiar with the Julia and Rust programming languages.



## Overview



An incomplete list of features that are currently supported by jlrs:



 - Access arbitrary Julia modules and their content.

 - Call Julia functions, including functions that take keyword arguments.

 - Handle exceptions or convert them to an error message, optionally with color.

 - Include and call your own Julia code.

 - Use custom system images.

 - Create values that Julia can use, and convert them back to Rust, from Rust.

 - Access the type information and fields of such values. Inline and bits-union fields can be

   accessed directly.

 - Create and use n-dimensional arrays. The `jlrs-ndarray` feature can be enabled for

   integration with ndarray.

 - Map Julia structs to Rust structs, the Rust implementation can be generated with the

   JlrsCore package.

 - Structs that can be mapped to Rust include those with type parameters and bits unions.

 - Use Julia from multiple threads either directly or via Julia-aware thread pools.

 - Export Rust types, methods and functions to Julia with the `julia_module` macro.

 - Libraries that use `julia_module` can be compiled with BinaryBuilder and distributed as JLLs.



## Prerequisites



Julia must be installed before jlrs can be used, jlrs is compatible with Julia 1.6 up to and

including Julia 1.11. If the JlrsCore package has not been installed, it will automatically be

installed when jlrs is initialized by default. jlrs has not been tested with juliaup yet on Linux

and macOS.



### Linux



The recommended way to install Julia is to download the binaries from the official website,

which is distributed as an archive containing a directory called `julia-x.y.z`. This directory

contains several other directories, including a `bin` directory containing the `julia`

executable.



During compilation, the paths to the header and library are normally detected automatically by

executing the command `which julia`. The path to `julia.h` must be

`$(which julia)/../include/julia/julia.h` and the path to the library

`$(which julia)/../lib/libjulia.so`. If you want to override this default behaviour the

`JULIA_DIR` environment variable must be set to the path to the appropriate `julia.x-y-z`

directory, in this case `$JULIA_DIR/include/julia/julia.h` and

`$JULIA_DIR/lib/libjulia.so` are used instead.



In order to be able to load `libjulia.so` this file must be on the library search path. If

this is not the case you must add `/path/to/julia-x.y.z/lib` to the `LD_LIBRARY_PATH`

environment variable.



### macOS



Follow the instructions for Linux, but replace `LD_LIBRARY_PATH` with `DYLD_LIBRARY_PATH`.



### Windows



Julia can be installed using juliaup, or with the installer or portable installation

downloaded from the official website. In the first case, Julia has been likely installed in

`%USERPROFILE%\.julia\juliaup\julia-x.y.z+0~x64`, while using the installer or extracting

allows you to pick the destination. After installation or extraction a folder called

`Julia-x.y.z` exists, which contains several folders including a `bin` folder containing

`julia.exe`. The path to the `bin` folder must be added to the `Path` environment variable.



Julia is automatically detected by executing the command `where julia`. If this returns

multiple locations the first one is used. The default can be overridden by setting the

`JULIA_DIR` environment variable. This doesn't work correctly with juliaup, in this case

the environment variable must be set.



## Features



Most functionality of jlrs is only available if the proper features are enabled. These

features generally belong to one of three categories: versions, runtimes and utilities.



### Versions



The Julia C API is unstable and there are minor incompatibilities between different versions of

Julia. To ensure the correct bindings are used for a particular version of Julia you must enable a

version feature. The following version features currently exist:



 - `julia-1-6`

 - `julia-1-7`

 - `julia-1-8`

 - `julia-1-9`

 - `julia-1-10`

 - `julia-1-11`



Exactly one version feature must be enabled. Otherwise, jlrs will fail to compile.



If you want your crate to be compatible with multiple versions of Julia, you should "reexport"

these version features as follows:



```toml

[features]

julia-1-6 = ["jlrs/julia-1-6"]

julia-1-7 = ["jlrs/julia-1-7"]

julia-1-8 = ["jlrs/julia-1-8"]

julia-1-9 = ["jlrs/julia-1-9"]

julia-1-10 = ["jlrs/julia-1-10"]

julia-1-11 = ["jlrs/julia-1-11"]

```



### Runtimes



A runtime lets initialize Julia from Rust application, the following features enable a runtime:



- `local-rt`



  Enables the local runtime. The local runtime provides single-threaded, blocking access to Julia.



- `async-rt`



  Enables the async runtime. The async runtime runs on a separate thread and can be used from

  multiple threads.



- `tokio-rt`



  The async runtime requires an executor. This feature provides a tokio-based executor.



- `multi-rt`



  Enables the multithreaded runtime. The multithreaded runtime lets you call Julia from arbitrary

  threads. It can be combined with the `async-rt` feature to create Julia-aware thread pools. This

  feature requires Julia 1.9 or higher.



**WARNING**: Runtime features must only be enabled by applications that embed Julia. Libraries

must never enable a runtime feature.



**WARNING**: When a runtime feature is enabled on Linux, set `RUSTFLAGS="-Clink-args=-rdynamic"`

if you want fast code.



### Utilities



All other features are called utility features. The following are available:



- `async`



  Enable the features of the async runtime which don't depend on the executor. This

  can be used in libraries which provide implementations of tasks that the async runtime can

  handle.



- `jlrs-derive`



  This feature should be used in combination with the code generation provided by the Reflect

  module in the JlrsCore package. This module lets you generate Rust implementations of Julia

  structs, this generated code uses custom derive macros made available with this feature to

  enable the safe conversion of data from Julia to Rust, and from Rust to Julia in some cases.



- `jlrs-ndarray`



  Access the content of a Julia array as an `ArrayView` or `ArrayViewMut` from ndarray.



- `f16`



  Adds support for working with Julia's `Float16` type from Rust using half's `f16` type.



- `complex`

  Adds support for working with Julia's `Complex` type from Rust using num's `Complex` type.



- `ccall`



  Julia's `ccall` interface can be used to call functions written in Rust from Julia. No

  runtime can be used in this case because Julia has already been initialized, when this

  feature is enabled the `CCall` struct is available which offers the same functionality as

  the local runtime without initializing Julia. The `julia_module` macro is provided to

  easily export functions, types, and data in combination with the macros from the Wrap

  module in the JlrsCore package.



- `lto`



  jlrs depends on a support library written in C, if this feature is enabled this support library

  is built with support for cross-language LTO which can provide a significant performance boost.



  This feature has only been tested on Linux and requires building the support library using a

  version of `clang` with the same major version as `rustc`'s LLVM version; e.g. rust 1.78.0 uses

  LLVM 18.1.2, so it requires `clang-18`. You can check what version you need by executing

  `rustc -vV`.



  You must set the `RUSTFLAGS` environment variable if this feature is enabled, and possibly the

  `CC` environment variable. Setting `RUSTFLAGS` overrides the default flags that jlrs sets, so

  you must set at least the following flags:

  `RUSTFLAGS="-Clinker-plugin-lto -Clinker=clang-XX -Clink-arg=-fuse-ld=lld -Clink-args=-rdynamic"`.

  The last one is particularly important for embedders, forgetting it is guaranteed to kill

  performance.



- `diagnostics`



  Enable custom diagnostics for several traits because the default lint is unhelpful. This feature

  requires Rust 1.78.



- `i686`



  Link with a 32-bit build of Julia on Linux, only used for cross-compilation.



- `windows`



  Flag that must be enabled when cross-compiling for Windows from Linux.



- `debug`



  Link with a debug build of Julia on Linux.



- `no-link`



  Don't link Julia.



- `yggdrasil`



  Flag that must be enabled when compiling with BinaryBuilder.



You can enable all features except `debug`, `i686`, `windows`, `no-link` and `yggdrasil` by

enabling the `full` feature. If you don't want to enable any runtimes either, you can use

`full-no-rt`.