JuliaPy / JuliaPy/PythonCall.jl
Support more of abstract array interface
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描述
Currently `similar` will return an array of a different type:
```python
from juliacall import Main as jl
import numpy as np
x = np.random.randn(5)
y = jl.similar(x)
print(jl.typeof(x))
# PyArray{Float64, 1, true, true, Float64}
print(jl.typeof(y))
# Vector{Float64}
```
This can introduce some type instabilities in libraries due to the assumption that container type is preserved by `similar`.
I guess we just need the "optional methods" from here: https://docs.julialang.org/en/v1/manual/interfaces/#man-interface-array
贡献指南
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调研方向
No implementation file or test is named. Reproduce the Python/Julia `similar` example from the issue, then read the linked Julia array-interface documentation and trace the existing `similar` handling in PythonCall.jl. Done means the relevant optional array-interface methods are supported and the example preserves the expected container type.
由索引模型根据 Issue 内容生成。
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- julia, python
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- api, backend
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