These are a lot lighter than AsyncFuture and safer to use in C++ due to the reliance on RAII. An async method can now take a CompletionToken, which will implicitly accept an arbitrary callable or an AsyncFuture pointer.
This change enables persistent Python wrapper objects for Python subclasses of typed, reference counted C++ objects. That means that these objects will store a reference to `self` on the C++ object, and interrogate will always return that instead of making a new Python wrapper every time it is returned from C++.
Practically, this means that you could subclass eg. PandaNode, Event, Fog, what have you, and store these in the scene graph - the Python data in the subclass will be retained and Panda will return your subclass when you ask for the object back rather than creating a new wrapper object without your original data.
To do this, Interrogate generates a proxy class inheriting from the C++ type with additional room to store a `self` pointer and a TypeHandle (which is returned by an overridden `get_type()`). This TypeHandle is automatically created by registering the Python subclass with the typing system. The proxy class is only used when the constructor detects that it's constructing for a subtype, so that regular uses of the C++ type are not affected by this mechanism.
(The registration with the typing system could use some improvement. There's no regard for namespacing right now, in particular. Furthermore, we could move the registration to an `__init_subclass__()` method, with parameters to specify an existing TypeHandle or to customize the type name.)
This creates a reference cycle, which must be cleared somehow. One way this happens is by overriding `unref()` in the proxy, which checks that if the Python and C++ reference counts are both 1, this must be the circular reference, and then it breaks the cycle. Note that this will _only_ work if all other Python references have been cleared before the last C++ reference goes away. For the other case, we need to rely on Python's garbage collector, so these classes also implement tp_traverse and tp_clear.
This commit also therefore re-enables Python garbage collector support (ie. defining `__traverse__()`), which was previously disabled due to the problems caused by multiple Python wrappers referring to the same C++ object. To avoid these problems, Panda will only cooperate with Python's GC if the C++ reference count is 1, in which case we can trivially prove that the last reference must be from the Python wrapper. Note that this explains why we need persistent wrappers for traversal to work--if there are multiple Python wrappers pointing to the C++ object, and they are all participating in a reference cycle, the reference count cannot be 1, and cycle detection does not work. By default, the GC is only enabled for Python subclasses, but a class may define `__traverse__()` in order to opt-in, keeping the previous limitation in mind.
There is a second mechanism introduced by this commit: classes may define a public `__self__` member of type `PyObject *` if they want to use persistent objects even if they aren't being subclassed. This allows these classes to participate in Python's GC and avoid the situation above.
The cycle detection is implemented for PandaNode's Python tags, but this is very incomplete, since the traversal doesn't recurse into children and it won't work if there is more than one wrapper object that is part of a cycle, since PandaNode by default doesn't use persistent wrappers. This problem may need more attention later.
Fixes#1410
This is more idiomatic, simplifies the code, makes it easier to port to eg. HPy later on, and makes it easier to use the limited ABI (where it can be optimized to a tail call) later on
A polyfill is provided for compatibility with Python versions 3.8 and 3.9
Starting with Python 3.12, passing a PyLong into Py_SIZE() triggers an
assertion. PyLong (and the whole C API) is transitioning to be more
opaque and expose fewer implementation details.
This vector implementation does is optimized for the case of having only a small number of elements, which are stored directly on the vector object rather than being allocated from the heap. If the capacity exceeds this small number, then a heap allocation is done.
This should improve performance in a couple of cases where vectors typically store 1 element and rarely more than that.
These hashes are used in various places in the Panda codebase (for integrity checks, not for crypto), so using an internal implementation allows retaining this functionality when building Panda without OpenSSL.
Based on the following public domain implementation:
https://github.com/B-Con/crypto-algorithms
init_memory_hook() is no longer required, eliminating static initialization order issues
This required moving the DeletedBufferChain map elsewhere, which now also has a const-initialized array for relatively small allocations.
Also, deletedChain.T has been renamed to deletedChain.I
Fixes#539
rdb
Wizzerinus
Maxwell Dreytser
jb
Mitchell Stokes
Disyer
Max Rodriguez
Timothy Paustian
Frang
Cary Sandvig