Log Message:
py-h5py: updated to 3.2.1

What's new in h5py 3.2
======================

New features
------------

* Added support to use the HDF5 ROS3 driver to access HDF5 files on S3
  (:pr:`1755`). This is not enabled in the pre-built packages on PyPI. To use
  it, ensure HDF5 is built with read-only S3 support enabled, and then
  :ref:`build h5py from source <source_install>` using that HDF5 library.

Breaking changes & deprecations
-------------------------------

* Python 3.7 is now the minimum supported version. It may still be possible to
  use this release with Python 3.6, but it isn't tested and wheels are not
  provided for Python 3.6.
* Setting the config option ``default_file_mode`` to values other than ``'r'``
  is deprecated. Pass the desired mode when opening a :class:`~.File` instead.

Exposing HDF5 functions
-----------------------

* ``H5Pset_fapl_ros3`` & ``H5Pget_fapl_ros3`` (where HDF5 is built with
  read-only S3 support).

Bug fixes
---------

* :exc:`OSError` exceptions raised by h5py should now have a useful ``.errno``
  attribute, where HDF5 provides this information. Subclasses such as
  :exc:`FileNotFoundError` should also be raised where appropriate (:pr:`1815`).
* Fix reading data with a datatype of variable-length arrays of fixed length
  strings (:issue:`1817`).
* Fix :meth:`.Dataset.read_direct` and :meth:`.Dataset.write_direct` when the
  source and destination have different shapes (:pr:`1796`).
* Fix selecting data using integer indices in :meth:`.Dataset.read_direct`
  and :meth:`.Dataset.write_direct` (:pr:`1818`).
* Fix exception handling in :meth:`.Group.visititems` (:issue:`1740`).
* Issue a warning when ``File(..., swmr=True)`` is specified with any mode other
  than ``'r'``, as the SWMR option is ignored in these cases (:pr:`1812`).
* Fix NumPy 1.20 deprecation warnings concerning the use of None as shape, and
  the deprecated aliases np.float, np.int and np.bool (:pr:`1780`).

3.2.1 bug fix release
---------------------

* Fix :attr:`.File.driver` when the read-only S3 driver is available (:pr:`1844`).

What's new in h5py 3.1
======================

Bug fixes
---------

* Fix reading numeric data which is not in the native endianness,
  e.g. big-endian data on a little-endian system (:issue:`1729`).
* Fix using bytes as names for :meth:`.Group.create_dataset` and
  :meth:`.Group.create_virtual_dataset` (:issue:`1732`).
* Fix writing data as a list to a dataset with a sub-array data type
  (:issue:`1735`).

Building h5py
-------------

* Allow building against system lzf library by setting ``H5PY_SYSTEM_LZF=1``.
  See :ref:`custom_install`.

Development
-----------

* If pytest is missing `pytest-mpi \ 
<https://pytest-mpi.readthedocs.io/en/latest/>`_
  it will now fail with a clear error.
* Fix a test which was failing on big-endian systems.

What's new in h5py 3.0
======================

New features
------------

* The interface for storing & reading strings has changed - see :doc:`/strings`.
  The new rules are hopefully more consistent, but may well require some changes
  in coding using h5py.
* Reading & writing data now releases the GIL, so another Python thread can
  continue while HDF5 accesses data. Where HDF5 can call back into Python, such
  as for data conversion, h5py re-acquires the GIL. However, HDF5 has its own
  global lock, so this won't speed up parallel data access using multithreading.
* Numpy datetime and timedelta arrays can now be stored and read as HDF5
  opaque data (:issue:`1339`), though other tools will not understand them.
  See :ref:`opaque_dtypes` for more information.
* New :meth:`.Dataset.iter_chunks` method, to iterate over chunks within the
  given selection.
* Compatibility with HDF5 1.12.
* Methods which accept a shape tuple, e.g. to create a dataset, now also allow
  an integer for a 1D shape (:pr:`1340`).
* Casting data to a specified type on reading (:meth:`.Dataset.astype`) can now
  be done without a with statement, like this::

      data = dset.astype(np.int32)[:]

* A new :meth:`.Dataset.fields` method lets you read only selected fields from
  a dataset with a compound datatype.
* Reading data has less overhead, as selection has been implemented in Cython.
  Making many small reads from the same dataset can be as much as 10 times
  faster, but there are many factors that can affect performance.
* A new NumPy-style :attr:`.Dataset.nbytes` attribute to get the size of the
  dataset's data in bytes.  This differs from the :attr:`~.Dataset.size`
  attribute, which gives the number of elements.
* The ``external`` argument of :meth:`.Group.create_dataset`, which
  specifies any external storage for the dataset, accepts more types
  (:issue:`1260`), as follows:

  * The top-level container may be any iterable, not only a list.
  * The names of external files may be not only ``str`` but also ``bytes`` or
    ``os.PathLike`` objects.
  * The offsets and sizes may be NumPy integers as well as Python integers.

  See also the deprecation related to the ``external`` argument.
* Support for setting file space strategy at file creation. Includes option to
  persist empty space tracking between sessions. See :class:`.File` for details.
* More efficient writing when assiging a scalar to a chunked dataset, when the
  number of elements to write is no more than the size of one chunk.
* Introduced support for the split :ref:`file driver <file_driver>`
  (:pr:`1468`).
* Allow making virtual datasets which can grow as the source data is resized
  - see :doc:`/vds`.
* New `allow_unknown_filter` option to :meth:`.Group.create_dataset`. This should
  only be used if you will compress the data before writing it with the
  low-level :meth:`~h5py.h5d.DatasetID.write_direct_chunk` method.
* The low-level chunk query API provides information about dataset chunks in an
  HDF5 file: :meth:`~h5py.h5d.DatasetID.get_num_chunks`,
  :meth:`~h5py.h5d.DatasetID.get_chunk_info` and
  :meth:`~h5py.h5d.DatasetID.get_chunk_info_by_coord`.
* The low-level :meth:`h5py.h5f.FileID.get_vfd_handle` method now works for any
  file driver that supports it, not only the sec2 driver.

Breaking changes & deprecations
-------------------------------

* h5py now requires Python 3.6 or above; it is no longer compatible with Python
  2.7.
* The default mode for opening files is now 'r' (read-only).
  See :ref:`file_open` for other possible modes if you need to write to a file.
* In previous versions, creating a dataset from a list of bytes objects would
  choose a fixed length string datatype to fit the biggest item. It will now
  use a variable length string datatype. To store fixed length strings, use a
  suitable dtype from :func:`h5py.string_dtype`.
* Variable-length UTF-8 strings in datasets are now read as ``bytes`` objects
  instead of ``str`` by default, for consistency with other kinds of strings.
  See :doc:`/strings` for more details.
* When making a virtual dataset, a dtype must be specified in
  :class:`.VirtualLayout`. There is no longer a default dtype, as this was
  surprising in some cases.
* The ``external`` argument of :meth:`Group.create_dataset` no longer accepts
  the following forms (:issue:`1260`):

  * a list containing *name*, [*offset*, [*size*]];
  * a list containing *name1*, *name2*, …; and
  * a list containing tuples such as ``(name,)`` and ``(name, offset)`` that
    lack the offset or size.

  Furthermore, each *name*–*offset*–*size* triplet now must be a tuple rather
  than an arbitrary iterable.  See also the new feature related to the
  ``external`` argument.
* The MPI mode no longer supports mpi4py 1.x.
* The deprecated ``h5py.h5t.available_ftypes`` dictionary was removed.
* The deprecated ``Dataset.value`` property was removed.
  Use ``ds[()]`` to read all data from any dataset.
* The deprecated functions ``new_vlen``, ``new_enum``, ``get_vlen`` and
  ``get_enum`` have been removed. See :doc:`/special` for the newer APIs.
* Removed deprecated File.fid attribute. Use :attr:`.File.id` instead.
* Remove the deprecated ``h5py.highlevel`` module.
  The high-level API is available directly in the ``h5py`` module.
* The third argument of ``h5py._hl.selections.select()`` is now an optional
  high-level :class:`.Dataset` object, rather than a ``DatasetID``.
  This is not really a public API - it has to be imported through the private
  ``_hl`` module - but probably some people are using it anyway.

Exposing HDF5 functions
-----------------------

* H5Dget_num_chunks
* H5Dget_chunk_info
* H5Dget_chunk_info_by_coord
* H5Oget_info1
* H5Oget_info_by_name1
* H5Oget_info_by_idx1
* H5Ovisit1
* H5Ovisit_by_name1
* H5Pset_attr_phase_change
* H5Pset_fapl_split
* H5Pget_file_space_strategy
* H5Pset_file_space_strategy
* H5Sencode1
* H5Tget_create_plist

Bug fixes
---------

* Fix segmentation fault when accessing vlen of strings (:issue:`1336`).
* Fix the storage of non-contiguous arrays, such as numpy slices, as HDF5 vlen
  data (:issue:`1649`).
* Fix pathologically slow reading/writing in certain conditions with integer
  indexing (:issue:`492`).
* Fix bug when :meth:`.Group.copy` source is a high-level object and destination
  is a Group (:issue:`1005`).
* Fix reading data for region references pointing to an empty selection.
* Unregister converter functions at exit, preventing segfaults on exit in some
  situations with threads (:pr:`1440`).
* As HDF5 1.10.6 and later support UTF-8 paths on Windows, h5py built against
  HDF5 1.10.6 will use UTF-8 for file names, allowing all filenames.
* Fixed :meth:`h5py.h5d.DatasetID.get_storage_size` to report storage size of
  zero bytes without raising an exception (:issue:`1475`).
* Attribute Managers (``obj.attrs``) can now work on HDF5 stored
  datatypes (:issue:`1476`).
* Remove broken inherited ``ds.dims.values()`` and ``ds.dims.items()`` methods.
  The dimensions interface behaves as a sequence, not a mapping (:issue:`744`).
* Fix creating attribute with :class:`.Empty` by converting its dtype to a numpy
  dtype object.
* Fix getting :attr:`~.Dataset.maxshape` on empty/null datasets.
* The :attr:`.File.swmr_mode` property is always available (:issue:`1580`).
* The :attr:`.File.mode` property handles SWMR access modes in addition to plain
  RDONLY/RDWR modes
* Importing an MPI build of h5py no longer initialises MPI immediately,
  which will hopefully avoid various strange behaviours.
* Avoid launching a subprocess by using ``platform.machine()`` at import time.
  This could trigger a warning in MPI.
* Removed an equality comparison with an empty array, which will cause problems
  with future versions of numpy.
* Better error message if you try to use the mpio driver and h5py was not built
  with MPI support.
* Improved error messages when requesting chunked storage for an empty dataset.
* Data conversion functions should fail more gracefully if no memory is
  available.
* Fix some errors for internal functions that were raising "TypeError:
  expected bytes, str found" instead of the correct error.
* Use relative path for virtual data sources if the source dataset is in the
  same file as the virtual dataset.
* Generic exception types used in tests' assertRaise (exception types changed in
  new HDF5 version)
* Use ``dtype=object`` in tests with ragged arrays

Building h5py
-------------

* The ``setup.py configure`` command was removed. Configuration for the build
  can be specified with environment variables instead. See :ref:`custom_install`
  for details.
* It is now possible to specify separate include and library directories for
  HDF5 via environment variables. See :ref:`custom_install` for more details.
* The pkg-config name to use when looking up the HDF5 library can now be
  configured, this can assist with selecting the correct HDF5 library when using
  MPI. See :ref:`custom_install` for more details.
* Using bare ``char*`` instead of ``array.array`` in h5d.read_direct_chunk since
  ``array.array`` is a private CPython C-API interface
* Define ``NPY_NO_DEPRECATED_API`` to silence a warning.
* Make the lzf filter build with HDF5 1.10 (:issue:`1219`).
* If HDF5 is not loaded, an additional message is displayed to check HDF5
  installation
* Rely much more on the C-interface provided by Cython to call Python and NumPy.
* Removed an old workaround which tried to run Cython in a subprocess if
  cythonize() didn't work. This shouldn't be necessary for any recent version
  of setuptools.
* Migrate all Cython code base to Cython3 syntax

    * The only noticeable change is in exception raising from cython which use bytes
    * Massively use local imports everywhere as expected from Python3
    * Explicitly mark several Cython functions as non-binding

Development
-----------

* Unregistering converter functions on exit (:pr:`1440`) should allow profiling
  and code coverage tools to work on Cython code.