Numpy structured array unintuitive handling

[MaxandreJ]

Hi,

Thank you for the great work on this package.

I have to deal with a numpy structured array variable that I've imported into Julia. I've called this variable my_simulations.

To see the different fields inside this variable, I can call my_simulations[:dtype] and I get
PyObject dtype([('drugs', 'O'), ('Vms', 'O'), ('I_tots', 'O'), ('Ycs', 'O'), ('Cais', 'O'), ('Nais', 'O'), ('caSRs', 'O'), ('ts', 'O')]).
The first element of each tuple in the list corresponds to the names of the keys (numpy calls them fields) in this variable.

In Python, you can access each key using my_simulations['keyname'], e.g. my_simulations['Vms']. I expected that in Julia you could access each key using my_simulations["keyname"], e.g. my_simulations["Vms"]. But this doesn't work and I get the following error message
ERROR: KeyError: key "Vms" not found

The workaround I've found is to call get(my_sims,"keyname") e.g. get(my_sims,"Vms") which works. But the method my_simulations["keyname"] would be more intuitive and closer to the Python syntax.

Thank you!

My version of PyCall is v"1.18.5+".

Best,
Max

[tkf]

With #517, I think we can solve this after some deprecation period of the current behavior.

[tkf]

I guess it's also possible to convert numpy's structured array to an Array of NamedTuples in a zero-copy manner (if the fields only contain "primitive" types).

[MaxandreJ]

Thanks, I'll try this later!

[tkf]

What I mean by that is it's possible to add this in PyCall as an additional feature. But if you want to hack PyCall to do this, I think it's better to wait for #487 to be merged.

[MaxandreJ]

Ah okay, I hadn't understood. Thank you for clarifying!

[tkf]

convert numpy's structured array to an Array of NamedTuples

Here is a way to do this with unsafe_wrap https://discourse.julialang.org/t/structured-array-in-pycall/21118/2