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jlrs

jlrs provides bindings to the Julia C API that enable Julia code to be called from Rust and more

38 releases (20 breaking)

0.21.1 Nov 10, 2024
0.21.0 Jul 11, 2024
0.20.0 Jun 16, 2024
0.19.2 Nov 11, 2023
0.1.3 Feb 25, 2020

#48 in Math

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160 downloads per month
Used in jlrs-ndarray

MIT license

1.5MB
29K SLoC

jlrs

Rust Docs License: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. A complete tutorial is available here. For more information and examples about how to use jlrs, please read the docs. All 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:

[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.

Dependencies

~1–10MB
~114K SLoC