Numpy structured array unintuitive handling

Hi,

Thank you for the great work on this package.

I have to deal with a [numpy structured array](https://docs.scipy.org/doc/numpy-1.15.0/user/basics.rec.html) 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

Reproduce the reported behavior with a NumPy structured array imported through PyCall, comparing my_simulations["Vms"] with get(my_simulations,"Vms"). Inspect PyCall's object-indexing behavior and existing tests around Python objects. Done means string indexing accesses structured-array fields as requested without regressing the working get form.

Scritto dal modello di indicizzazione a partire dal testo della issue.