Marcos Díez García

Thank you for resolving GitHub Issue #190. Kind regards, Marcos Diez García, PhD Senior Researcher Quantum Application Research (QAR) Email: ***@***.******@***.***> Find me: ORCID, Google Scholar, LinkedIn Fujitsu Research of...

Tried your first suggestion but got the same error: ```bash (test) mdg@vm-mdg20241122:~/qar$ python3.12 --version Python 3.12.9 (test) mdg@vm-mdg20241122:~/qar$ cat example.py import numpy (test) mdg@vm-mdg20241122:~/qar$ python3.12 -m scalene --no-browser --cli --html...

I found a simple fix to `JlWrap/array.jl` ([line 370](https://github.com/JuliaPy/PythonCall.jl/blob/71666ca0a30eafee2456a191fa2490cdd0b0ed22/src/JlWrap/array.jl#L370)) in PythonCall 0.9.28, which resolves the conversion issue I described above: ```diff try: import numpy - arr = numpy.array(arr, dtype=dtype) +...

> You said that you absolutely cannot use Matrix{Int64} in your application. Can you explain why? I am interacting with another Julia package functionality, entirely outside my control, whose output...

I just thought first of the `list()` call. But yes, actually converting to `Matrix` does also work. ```julia julia> m = reduce(hcat, [[1,2,3], [4,5,6]]) 3×2 Matrix{Int64}: 1 4 2 5...

Using the `list()` call as I suggested handles also the case of `Vector{Vector{Vector{Int}}}`, but the conversion to `Matrix` using reduce and hcat still leads to `dtype('O')`: ```julia julia> m =...