Choice of complex buffer protocol format intentional break with PEP?

[vstinner (Victor Stinner)]

Hi Sebastian,

Thanks for raising this issue here.

@seberg

It was reported to NumPy that the newly added buffer protocol support for complex array.array and ctypes uses the character codes D and F rather than Zd and Zf.

D (double complex) and F (float complex) format were introduced in Python 3.14 which was released on October 2025, so IMO it’s too late to change the chosen format strings.

• Python 3.14 added D and F support to the ctypes and struct module
• Python 3.15 adds D and F support to the array module and to memoryview

Before the 3.14 final release, ctypes and struct used C (double complex) and E (float complex) formats. These formats were replaced with D and F for compatibility with numpy:

$ python3.14
>>> import numpy as np
>>> np.__version__
'2.3.5'

>>> np.typename("F")
'complex single precision'
>>> np.typename("D")
'complex double precision'

>>> np.dtype(np.complex64).char
'F'
>>> np.dtype(np.complex128).char
'D'

>>> np.array([1, 2, 3], dtype='F')
array([1.+0.j, 2.+0.j, 3.+0.j], dtype=complex64)
>>> np.array([1, 2, 3], dtype='D')
array([1.+0.j, 2.+0.j, 3.+0.j])

>>> memoryview(np.array([1, 2, 3], dtype='F')).format
'Zf'
>>> memoryview(np.array([1, 2, 3], dtype='D')).format
'Zd'

@seberg

NumPy (and that means all meaningful users of the buffer protocol) would have to keep exporting Zd (and Python doesn’t understand this!).

As Sergey wrote above, in the bfloat16 format discussion, Serhiy proposed adding an API to register custom types:

@storchaka

For perfomance, we need the C API for registering custom types, but for convenience, we need also the Python API.

It may be a solution to D vs Zd formats, maybe both can be accepted transparently.

@seberg

Now, it’s a fair choice to accept the friction that this introduces, but for now it is still unclear that this was considered much and I think it is a violation of the PEP.

PEP 3118 was written in 2006. It now has the header: “This PEP is a historical document”. I don’t think that using this old PEP is still relevant nowadays. Maybe numpy should reconsider its error message on unknown format.

Yeah, it’s unfortunate that numpy and Python stdlib (array, ctypes, struct and memoryview) are using different formats. But it’s maybe the opportunity to provide a generic solution to this kind of problem (API to register formats).

It’s also unfortunate that this issue wasn’t raised before, but as I wrote above, IMO it’s too late to change Python stdlib. By the way, currently the stdlib only use single letter formats which make some parts of the code simpler.