One question.. On Thu., 29 Mar. 2018, 07:42 Antoine Pitrou, <solip...@pitrou.net> wrote:
> ... > ======= > > Mutability > ---------- > > PEP 3118 buffers [#pep-3118]_ can be readonly or writable. Some objects, > such as Numpy arrays, need to be backed by a mutable buffer for full > operation. Pickle consumers that use the ``buffer_callback`` and > ``buffers`` > arguments will have to be careful to recreate mutable buffers. When doing > I/O, this implies using buffer-passing API variants such as ``readinto`` > (which are also often preferrable for performance). > > Data sharing > ------------ > > If you pickle and then unpickle an object in the same process, passing > out-of-band buffer views, then the unpickled object may be backed by the > same buffer as the original pickled object. > > For example, it might be reasonable to implement reduction of a Numpy array > as follows (crucial metadata such as shapes is omitted for simplicity):: > > class ndarray: > > def __reduce_ex__(self, protocol): > if protocol == 5: > return numpy.frombuffer, (PickleBuffer(self), self.dtype) > # Legacy code for earlier protocols omitted > > Then simply passing the PickleBuffer around from ``dumps`` to ``loads`` > will produce a new Numpy array sharing the same underlying memory as the > original Numpy object (and, incidentally, keeping it alive):: This seems incompatible with v4 semantics. There, a loads plus dumps combination is approximately a deep copy. This isn't. Sometimes. Sometimes it is. Other than that way, I like it. Rob > >
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