What’s new in h5py 3.9
This version of h5py requires Python 3.8 or above.
New features
New
out
argument toread_direct_chunk()
to allow passing the output buffer (PR 2232).The objects from
Dataset.asstr()
andDataset.astype()
now implement the__array__()
method (PR 2269). This speeds up access for functions that support it, such asnp.asarray()
.Validate key types when creating groups and attributes, giving better error messages when invalid types are used (PR 2266).
Deprecations & removals
Using
Dataset.astype()
as a context manager has been removed, after being deprecated in h5py 3.6. Read data by slicing the returned object instead:dset.astype('f4')[:]
.
Exposing HDF5 functions
H5Pget_elink_acc_flags
&H5Pset_elink_acc_flags
ash5py.h5p.PropLAID.get_elink_acc_flags()
&h5py.h5p.PropLAID.set_elink_acc_flags()
: access the external link file access traversal flags in a link access property list (PR 2244).H5Zregister
ash5py.h5z.register_filter()
: register an HDF5 filter (PR 2229).
Bug fixes
Group.__contains__
andGroup.get
now use the default link access property list systematically (PR 2244).Removed various calls to the deprecated
numpy.product
function (PR 2242 & PR 2273).Fix the IPython tab-completion integration in IPython 8.12 (:pr:2256`).
Replacing attributes with
AttributeManager.create()
now deletes the old attributes before creating the new one, rather than using a temporary name and renaming the new attribute (PR 2274). This should avoid some confusing bugs affecting attributes. However, failures creating an attribute are less likely to leave an existing attribute of the same name in place. To change an attribute value without changing its shape or dtype, usemodify()
instead.
Building h5py
When building with Parallel HDF5 support, the version of mpi4py used on various Python versions is increased to 3.1.1, fixing building with a newer setuptools (PR 2225).
Some fixes towards compatibility with the upcoming Cython 3 (PR 2247).