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Python-Julia interops.

Project description

TyJuliaCall

CI codecov versions pypi License

Calling Julia from Python for the real world.

Features:

  1. Cross-platform support for both dynamically linked Python and statically linked Python.

  2. Support Julia system images.

Installation

Prerequisites: Python (>=3.7), Julia (>=1.6)

Then install the tyjuliacall Python package and TyPython Julia package.

pip install -U tyjuliacall
julia -e "import Pkg; Pkg.add(\"TyPython\")"

Using System Images

from tyjuliasetup import use_sysimage  # CAUTIOUS: not 'tyjuliacall'!
use_sysimage(r"/path/to/sysimg")
# if your sysimage contains TyPython,
# you could call use_system_typython() to reduce the time cost of setting up julia.
from tyjuliacall import Base
print(
    "current sysimage in use",
    Base.unsafe_string(Base.JLOptions().image_file))
# out: /path/to/sysimg

受信赖的Python-Julia数据类型转换

虽然tyjuliacall允许在Python和Julia之间传递任意数据,但由于是两门不同的语言,数据转换的类型对应关系是复杂的。

为了保证代码的后向兼容性,使得规范的代码在不同版本的Syslab/tyjuliacall上都可以运行,建议只使用如下的数据类型转换。

Python数据传递到Julia

Python向Julia函数传参时,推荐只使用下表左边的数据类型,以保证代码的后向兼容。

Python Type Julia Type
基本类型
int Int64
float Float64
bool Bool
complex ComplexF64
None nothing
str String
组合类型
numpy.ndarray (dtype为数字或字符串或bool) 原生Array
tuple,且元素均为表中数据类型 Tuple

对于Python传递给Julia的tuple,其各个元素按照以上规则依次转换。

TIPS: 如何传递bytearray或者bytes到Julia?

  1. 向Julia函数传递bytes时,可以改为传递一个uint8的数组。

    无拷贝传参: np.array(memoryview(b'mybytes'), dtype=np.uint8) 拷贝传参: np.array(list(b'mybytes'), dtype=np.uint8)

  2. 向Julia函数传递bytearray时,可以改为传递一个uint8的数组。

    无拷贝传参: np.asarray(bytearray(b'mybytes')))

Julia数据传递到Python

当获取Julia函数返回值,或导入Julia模块的非函数对象时,将发生Julia到Python的数据传递。

保证后向兼容的Julia到Python数据转换关系如下表所示:

Julia Python
基本类型
Integer子类型 int
AbstractFloat子类型 float
Bool bool
Complex子类型 complex
nothing对象 None
AbstractString子类型 str
Vector{UInt8} bytearray
组合类型
AbstrctArray{T} (T见下方说明) numpy.ndarray
Tuple{T1, ..., Tn}, 且Ti为该表中的类型 tuple
其余Julia类型 tyjuliacall.JV

一个Julia AbstrctArray能转换为numpy数组,当且仅当其元素类型T是以下类型之一

  • Int8, Int16, Int32, Int64, UInt8, UInt16, UInt32, UInt64
  • Float16, Float32, Float64
  • ComplexF16, ComplexF32, ComplexF64
  • Bool

注意,当类型为Vector{String}或者Array{String, 2}的Julia对象被返回给Python时,它被封装为一个tyjuliacall.JV类型。

其他说明

  1. 不要对Julia包/模块使用from ... import *
  2. Vector{String}传到Python是一个tyjuliacall.JV,这是一个纯Julia对象的包装,因此下标索引是从1开始的。

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