The summary of this diff is that it:
* adds a `_ctypes_alloc_format_padding` function to append strings like `37x` to a format string to indicate 37 padding bytes
* removes the branches that amount to "give up on producing a valid format string if the struct is packed"
* combines the resulting adjacent `if (isStruct) {`s now that neither is `if (isStruct && !isPacked) {`
* invokes `_ctypes_alloc_format_padding` to add padding between structure fields, and after the last structure field. The computation used for the total size is unchanged from ctypes already used.
This patch does not affect any existing aligment computation; all it does is use subtraction to deduce the amount of paddnig introduced by the existing code.
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Without this fix, it would never include padding bytes - an assumption that was only
valid in the case when `_pack_` was set - and this case was explicitly not implemented.
This should allow conversion from ctypes structs to numpy structs
Fixes https://github.com/numpy/numpy/issues/10528
On some platforms, and in particular macOS/arm64, the calling
convention for variadic arguments is different from the regular
calling convention. Add a section to the documentation to document
this.
Adds `ctypes.c_time_t` to represent the C `time_t` type accurately as its size varies.
Primarily-authored-by: Adam Turner <9087854+AA-Turner@users.noreply.github.com>
Co-authored-by: Gregory P. Smith <greg@krypto.org> [Google]
This gains 10% or more in startup time for `python -c pass` on UNIX-ish systems.
The Makefile.pre.in generating code builds on Eric's work for bpo-45020, but the .c file generator is new.
Windows version TBD.
Currently custom modules (the array set on PyImport_FrozenModules) replace all the frozen stdlib modules. That can be problematic and is unlikely to be what the user wants. This change treats the custom frozen modules as additions instead. They take precedence over all other frozen modules except for those needed to bootstrap the import system. If the "code" field of an entry in the custom array is NULL then that frozen module is treated as disabled, which allows a custom entry to disable a frozen stdlib module.
This change allows us to get rid of is_essential_frozen_module() and simplifies the logic for which frozen modules should be ignored.
https://bugs.python.org/issue45395
Replace old names when they refer to actual versions of macOS.
Keep historical names in references to older versions.
Co-authored-by: Patrick Reader <_@pxeger.com>
* Remove commented deprecation of ctypes.c_buffer.
* Remove references to ctypes.c_string which doesn't exist.
* Remove StringTestCase: it only had skipped test methods.
The issue being resolved is shown in the 3.10 docs (if you select docs for older versions you won't see a visual glitch).
The newer sphinx version that produces the 3.10 docs doesn't treat the backslash to escape things in some situations it previously did.
Add documentation to help diagnose CDLL dependent DLL loading errors
on windows for OSError with message:
"[WinError 126] The specified module could not be found"
This error is otherwise difficult to diagnose.
