| Name | hdf5storage JSON |
| Version |
0.2.1
JSON |
| download |
| home_page | None |
| Summary | Utilities to read/write Python types to/from HDF5 files, including MATLAB v7.3 MAT files. |
| upload_time | 2025-08-19 16:45:22 |
| maintainer | Jesse R Codling |
| docs_url | https://pythonhosted.org/hdf5storage/ |
| author | Freja Nordsiek |
| requires_python | <4.0,>=3.10 |
| license | BSD |
| keywords |
hdf5
matlab
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
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:alt: Unit tests and lint checks
Overview
========
This Python package provides high level utilities to read/write a
variety of Python types to/from HDF5 (Heirarchal Data Format) formatted
files. This package also provides support for MATLAB MAT v7.3 formatted
files, which are just HDF5 files with a different extension and some
extra meta-data.
All of this is done without pickling data. Pickling is bad for security
because it allows arbitrary code to be executed in the interpreter. One
wants to be able to read possibly HDF5 and MAT files from untrusted
sources, so pickling is avoided in this package.
The package's documetation is found at
https://hdf5storage.readthedocs.io
The package's source code is found at
https://github.com/jclds139/hdf5storage
The package is licensed under a 2-clause BSD license
(https://github.com/jclds139/hdf5storage/blob/master/COPYING.txt).
Installation
============
Dependencies
------------
This package only supports Python >= 3.10. Python < 3.10 support was dropped
in version 0.2.
This package requires the python packages to run
* `numpy <https://pypi.org/project/numpy>`_
* `h5py <https://pypi.org/project/h5py>`_ >= 3.9
* `poetry <https://python-poetry.org/>`_
Note that support for `h5py`_ 2.1 to 3.8.x
has been dropped in version 0.2.
This package also has the following optional dependencies
* `scipy <https://pypi.org/project/scipy>`_
Installing by pip
-----------------
This package is on `PyPI <https://pypi.org>`_ at
`hdf5storage <https://pypi.org/project/hdf5storage>`_. To install hdf5storage
using pip, run the command::
pip install hdf5storage
Installing from Source
----------------------
To install hdf5storage from source,
`poetry`_ is required.
Download this package and then run ::
pip install .
Running Tests
-------------
For testing, the package `pytest <https://pypi.org/project/pytest>`_
(>= 8.3) is additionally required. There are some tests that require
Matlab and `scipy`_ to be installed
and be in the executable path respectively. In addition, there are some
tests that require `Julia <http://julialang.org/>`_ with the
`MAT <https://github.com/simonster/MAT.jl>`_ package. Not having them
means that those tests cannot be run (they will be skipped) but all
the other tests will run. To install all testing dependencies, other
than `scipy`_, Julia, Matlab run ::
pip install -r <(poetry export -E tests)
To run the tests ::
pytest
Building Documentation
----------------------
The documentation additionally requires the following packages
* `sphinx <https://pypi.org/project/sphinx>`_ >= 8.0
* `sphinx_rtd_theme <https://pypi.org/project/sphinx-rtd-theme>`_ >= 3.0
* `sphinx_rtd_dark_mode <https://pypi.org/project/sphinx-rtd-dark-mode>`_ >= 1.3
The documentation dependencies can be installed by ::
pip install -r <(poetry export -E docs)
To build the HTML documentation, run either ::
sphinx-build doc/source doc/build/html
Development
===========
All Python code is formatted using `ruff format <https://docs.astral.sh/ruff/formatter/>`_.
Releases and Pull Requests should pass all unit tests, and ideally pass type
checking and have no warnings found by linting.
Type Checking
-------------
This package now has type annotations since version 0.2, which can be checked
with a type checker like `mypy <https://pypi.org/project/mypy>`_. To check with
`mypy`_, run ::
mypy -p hdf5storage
Linting
-------
This package has the configuration in ``pyproject.toml`` for linting with
* `ruff <https://pypi.org/project/ruff>`_
To lint with `ruff`_, run ::
ruff .
Python 2
========
This package no longer supports Python 2.6 and 2.7. This package was
designed and written for Python 3, then backported to Python 2.x, and
then support dropped. But it can still read files made by version 0.1.x
of this library with Python 2.x, and this package still tries to write
files compatible with 0.1.x when possible.
Hierarchal Data Format 5 (HDF5)
===============================
HDF5 files (see http://www.hdfgroup.org/HDF5/) are a commonly used file
format for exchange of numerical data. It has built in support for a
large variety of number formats (un/signed integers, floating point
numbers, strings, etc.) as scalars and arrays, enums and compound types.
It also handles differences in data representation on different hardware
platforms (endianness, different floating point formats, etc.). As can
be imagined from the name, data is represented in an HDF5 file in a
hierarchal form modelling a Unix filesystem (Datasets are equivalent to
files, Groups are equivalent to directories, and links are supported).
This package interfaces HDF5 files using the h5py package
(http://www.h5py.org/) as opposed to the PyTables package
(http://www.pytables.org/).
MATLAB MAT v7.3 file support
============================
MATLAB (http://www.mathworks.com/) MAT files version 7.3 and later are
HDF5 files with a different file extension (``.mat``) and a very
specific set of meta-data and storage conventions. This package provides
read and write support for a limited set of Python and MATLAB types.
SciPy (http://scipy.org/) has functions to read and write the older MAT
file formats. This package has functions modeled after the
``scipy.io.savemat`` and ``scipy.io.loadmat`` functions, that have the
same names and similar arguments. The dispatch to the SciPy versions if
the MAT file format is not an HDF5 based one.
Supported Types
===============
The supported Python and MATLAB types are given in the tables below.
The tables assume that one has imported collections and numpy as::
import collections as cl
import numpy as np
The table gives which Python types can be read and written, the first
version of this package to support it, the numpy type it gets
converted to for storage (if type information is not written, that
will be what it is read back as) the MATLAB class it becomes if
targetting a MAT file, and the first version of this package to
support writing it so MATlAB can read it.
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| Python | MATLAB | Notes |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| Type | Version | Converted to | Class | Version | |
+====================+=========+=========================+=============+=========+===================+
| bool | 0.1 | np.bool\_ or np.uint8 | logical | 0.1 | [1]_ |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| None | 0.1 | ``np.float64([])`` | ``[]`` | 0.1 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| Ellipsis | 0.2 | ``np.float64([])`` | ``[]`` | 0.2 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| NotImplemented | 0.2 | ``np.float64([])`` | ``[]`` | 0.2 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| int | 0.1 | np.int64 or np.bytes\_ | int64 | 0.1 | [2]_ [3]_ |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| long | 0.1 | np.int64 or np.bytes\_ | int64 | 0.1 | [3]_ [4]_ |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| float | 0.1 | np.float64 | double | 0.1 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| complex | 0.1 | np.complex128 | double | 0.1 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| str | 0.1 | np.uint32/16 | char | 0.1 | [5]_ |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| bytes | 0.1 | np.bytes\_ or np.uint16 | char | 0.1 | [6]_ |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| bytearray | 0.1 | np.bytes\_ or np.uint16 | char | 0.1 | [6]_ |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| list | 0.1 | np.object\_ | cell | 0.1 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| tuple | 0.1 | np.object\_ | cell | 0.1 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| set | 0.1 | np.object\_ | cell | 0.1 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| frozenset | 0.1 | np.object\_ | cell | 0.1 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| cl.deque | 0.1 | np.object\_ | cell | 0.1 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| cl.ChainMap | 0.2 | np.object\_ | cell | 0.2 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| dict | 0.1 | | struct | 0.1 | [7]_ |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| cl.OrderedDict | 0.2 | | struct | 0.2 | [7]_ |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| cl.Counter | 0.2 | | struct | 0.2 | [7]_ |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| slice | 0.2 | | struct | 0.2 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| range | 0.2 | | struct | 0.2 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| datetime.timedelta | 0.2 | | struct | 0.2 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| datetime.timezone | 0.2 | | struct | 0.2 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| datetime.date | 0.2 | | struct | 0.2 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| datetime.time | 0.2 | | struct | 0.2 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| datetime.datetime | 0.2 | | struct | 0.2 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| fractions.Fraction | 0.2 | | struct | 0.2 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| np.bool\_ | 0.1 | | logical | 0.1 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| np.void | 0.1 | | | | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| np.uint8 | 0.1 | | uint8 | 0.1 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| np.uint16 | 0.1 | | uint16 | 0.1 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| np.uint32 | 0.1 | | uint32 | 0.1 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| np.uint64 | 0.1 | | uint64 | 0.1 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| np.uint8 | 0.1 | | int8 | 0.1 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| np.int16 | 0.1 | | int16 | 0.1 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| np.int32 | 0.1 | | int32 | 0.1 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| np.int64 | 0.1 | | int64 | 0.1 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| np.float16 | 0.1 | | | | [8]_ |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| np.float32 | 0.1 | | single | 0.1 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| np.float64 | 0.1 | | double | 0.1 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| np.complex64 | 0.1 | | single | 0.1 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| np.complex128 | 0.1 | | double | 0.1 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| np.str\_ | 0.1 | np.uint32/16 | char/uint32 | 0.1 | [5]_ |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| np.bytes\_ | 0.1 | np.bytes\_ or np.uint16 | char | 0.1 | [6]_ |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| np.object\_ | 0.1 | | cell | 0.1 | |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| np.ndarray | 0.1 | *see notes* | *see notes* | 0.1 | [9]_ [10]_ [11]_ |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| np.matrix | 0.1 | *see notes* | *see notes* | 0.1 | [9]_ [12]_ |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| np.chararray | 0.1 | *see notes* | *see notes* | 0.1 | [9]_ |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| np.recarray | 0.1 | structured np.ndarray | *see notes* | 0.1 | [9]_ [10]_ |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
| np.dtype | 0.2 | np.bytes\_ or np.uint16 | char | 0.2 | [6]_ [13]_ |
+--------------------+---------+-------------------------+-------------+---------+-------------------+
.. [1] Depends on the selected options. Always ``np.uint8`` when doing
MATLAB compatiblity, or if the option is explicitly set.
.. [2] In Python 2.x with the 0.1.x version of this package, it may be
read back as a ``long`` if it can't fit in the size of an
``int``.
.. [3] Stored as a ``np.int64`` if it is small enough to fit. Otherwise
its decimal string representation is stored as an ``np.bytes_``
for hdf5storage >= 0.2 (error in earlier versions).
.. [4] Type found only in Python 2.x. Python 2.x's ``long`` and ``int``
are unified into a single ``int`` type in Python 3.x. Read as an
``int`` in Python 3.x.
.. [5] Depends on the selected options and whether it can be converted
to UTF-16 without using doublets. If the option is explicity set
(or implicitly when doing MATLAB compatibility) and it can be
converted to UTF-16 without losing any characters that can't be
represented in UTF-16 or using UTF-16 doublets (MATLAB doesn't
support them), then it is written as ``np.uint16`` in UTF-16
encoding. Otherwise, it is stored at ``np.uint32`` in UTF-32
encoding.
.. [6] Depends on the selected options. If the option is explicitly set
(or implicitly when doing MATLAB compatibility), it will be
stored as ``np.uint16`` in UTF-16 encoding unless it has
non-ASCII characters in which case a ``NotImplementedError`` is
thrown). Otherwise, it is just written as ``np.bytes_``.
.. [7] Stored either as each key-value as their own Dataset or as two
Datasets, one for keys and one for values. The former is used if
all keys can be converted to ``str`` and they don't have null
characters (``'\x00'``) or forward slashes (``'/'``) in them.
Otherwise, the latter format is used.
.. [8] ``np.float16`` are not supported for h5py versions before
``2.2``. Version ``2.3`` or higher is required for this package
since version ``0.2``.
.. [9] Container types are only supported if their underlying dtype is
supported. Data conversions are done based on its dtype.
.. [10] Structured ``np.ndarray`` s (have fields in their dtypes) can be
written as an HDF5 COMPOUND type or as an HDF5 Group with
Datasets holding its fields (either the values directly, or as
an HDF5 Reference array to the values for the different elements
of the data). Can only be written as an HDF5 COMPOUND type if
none of its field are of dtype ``'object'``. Field names cannot
have null characters (``'\x00'``) and, when writing as an HDF5
GROUP, forward slashes (``'/'``) in them.
.. [11] Structured ``np.ndarray`` s with no elements, when written like a
structure, will not be read back with the right dtypes for their
fields (will all become 'object').
.. [12] Will be read back as a ``np.ndarray`` if the ``np.matrix`` class
is removed.
.. [13] Stored in their string representation.
This table gives the MATLAB classes that can be read from a MAT file,
the first version of this package that can read them, and the Python
type they are read as.
+-----------------+---------+-------------------------------------+
| MATLAB Class | Version | Python Type |
+=================+=========+=====================================+
| logical | 0.1 | np.bool\_ |
+-----------------+---------+-------------------------------------+
| single | 0.1 | np.float32 or np.complex64 [14]_ |
+-----------------+---------+-------------------------------------+
| double | 0.1 | np.float64 or np.complex128 [14]_ |
+-----------------+---------+-------------------------------------+
| uint8 | 0.1 | np.uint8 |
+-----------------+---------+-------------------------------------+
| uint16 | 0.1 | np.uint16 |
+-----------------+---------+-------------------------------------+
| uint32 | 0.1 | np.uint32 |
+-----------------+---------+-------------------------------------+
| uint64 | 0.1 | np.uint64 |
+-----------------+---------+-------------------------------------+
| int8 | 0.1 | np.int8 |
+-----------------+---------+-------------------------------------+
| int16 | 0.1 | np.int16 |
+-----------------+---------+-------------------------------------+
| int32 | 0.1 | np.int32 |
+-----------------+---------+-------------------------------------+
| int64 | 0.1 | np.int64 |
+-----------------+---------+-------------------------------------+
| char | 0.1 | np.str\_ |
+-----------------+---------+-------------------------------------+
| struct | 0.1 | structured np.ndarray or dict [15]_ |
+-----------------+---------+-------------------------------------+
| cell | 0.1 | np.object\_ |
+-----------------+---------+-------------------------------------+
| canonical empty | 0.1 | ``np.float64([])`` |
+-----------------+---------+-------------------------------------+
.. [14] Depends on whether there is a complex part or not.
.. [15] Controlled by an option.
File Incompatibilities
======================
The storage of empty ``numpy.ndarray`` (or objects that would be stored like
one) when the ``Options.store_shape_for_empty`` (implicitly set when Matlab
compatibility is enabled) is incompatible with the main branch of this package
before 2021-07-11 as well as all 0.1.x versions of this package since they
have a bug (Issue #114). The incompatibility is caused by those versions
storing the array shape in the Dataset after reversing the dimension order
instead of before, meaning that the array is read with its dimensions reversed
from what is expected if read after the bug fix or by Matlab.
Versions
========
0.2. Feature release adding/changing the following, including some API breaking changes.
* Issues #50 and #84 and #117 and #126. Python < 3.7 support dropped.
* Issue #53 and #126. h5py < 3.3 support dropped.
* Issue #114. Fixed bug where the shape was stored in the opposite order as
Matlab for empty ndarrays when ``Options.store_shape_for_empty`` is set.
This causes a file compatibility change.
* Issue #85. Changed to using the PEP 518 method of specifying
build dependencies from using the older ``ez_setup.py`` to ensure
``setuptools`` was available for building.
* The entire configuration is now put in the ``pyproject.toml`` files
(PEP 621) and the ``setup.py`` file has been removed.
* Changed all ``IOError`` to ``OSError``.
* Added a file object class ``hdf5storage.File`` for
opening a file and doing multiple read and/or write calls on the
same file.
* ``reads``, ``read``, and ``loadmat`` now raise a ``KeyError`` if
an object can't be found as opposed to a
``hdf5storage.exceptions.CantReadError``.
* Issue #88. Made it so that objects inside the Group specified by
``Options.group_for_references`` cannot be read from or written
to directly by the external API.
* Issue #64 and PR #87. Added ``structs_as_dicts`` that will cause MATLAB structs
to be read as ``dict`` instead of structured ``np.dnarray``.
* Issue #60. Platform label in the MAT file header changed to
``hdf5storage VERSION`` from ``CPython VERSION``.
* Issue #61. User provided marshallers must inherit from
``Marshallers.TypeMarshaller``. Before, they just had to provide
the same interface.
* Issue #78. Added the ability to pass object paths as
``pathlib.PurePath`` (and descendants) objects.
* Issue #62. The priority ordering between builtin, plugin, and
user provided marshallers can be selected. The default is now
builtin, plugin, user; as opposed to user, builtin in the 0.1.x
branch.
* Issue #65. Added the ability to load marshallers from other python
packages via plugin using the
``'hdf5storage.marshallers.plugins'`` entry point in their setup.
Third party marshallers are not loaded into
the default initial ``MarshallerCollection``. Users who want
to use them must call ``make_new_default_MarshallerCollection``
with the ``load_plugins`` option set to ``True``.
* Issue #66. A version Marshaller API has been added to make it
easier for developers to write plugin marshallers without having
to do extensive checking of the ``hdf5storage`` package version.
The Marshaller API version will advance separately from the
package version. The initial version is ``'1.0'``.
* Fixed bugs in ``savemat`` and ``loadmat`` with appening the file
extension to filenames that are ``bytes``.
* Issue #27. Added support for paths with null characters, slashes,
and leading periods. It is used for the field names of structured
numpy ndarrays as well as the keys of ``dict`` like objects when
writing their values to individual Datasets.
* Issue #89. ``Marshallers.PythonNoneMarshaller`` was renamed to
``Marshallers.PythonNoneEllipsisNotImplementedMarshaller`` and
support added for the ``Ellipsis`` and ``NotImplemented`` types.
* The ``write`` method of all marshallers now must return the written
HDF5 Group or Dataset (or ``None`` if unsuccessful).
* Issue #49. Changed marshaller types and their handling code to
support marshallers that handle types in modules that may not be
available or should not be imported until needed. If the the
required modules are not available, an approximate version of
the data is read using the ``read_approximate`` method of the
marshaller instead of the ``read`` method. The required modules,
if available, can either be imported immediately upon the
creation of the ``MarshallerCollection`` or they can be imported
only when the marshaller is needed for actual use (lazy loading).
* Changed the type of the ``types``, ``python_type_strings``, and
``matlab_classes`` attributes of ``TypeMarshaller`` to ``tuple``
from ``list``.
* Issue #52. Added the usage of a default ``MarshallerCollection``
which is used whenever creating a new ``Options`` without
a ``MarshallerCollection`` specified. The default can be
obtained using ``get_default_MarshallerCollection`` and a new
default can be generated using
``make_new_default_MarshallerCollection``. This is useful if
one wants to override the default lazy loading behavior.
* Issues #42 and #106. read and write functions moved from the ``lowlevel``
and ``Marshallers`` modules to the ``utilities`` module and
the ``lowlevel`` module renamed to ``exceptions`` since that is
all that remains in it. The functions to read/write Datasets and Groups
were replaced with a wrapper class ``LowLevelFile`` with methods
that are similar.
* Issue #106. Marshallers are passed a ``utilities.LowLevelFile`` object
as the first argument (``f``) instead of the file handle (``h5py.File``)
with the ``Options`` as the keyword argument ``options``.
* Ability to write Python 3.x ``int`` and Python 2.x ``long`` that
are too large to fit into ``np.int64``. Doing so no longer
raises an exception.
* Ability to write ``np.bytes_`` with non-ASCII characters in them.
Doing so no longer raises an exception.
* Issue #24 and #25. Added support for writing ``dict`` like
objects with keys that are not all ``str`` without null and ``'/'``
characters. Two new options, ``'dict_like_keys_name'`` and
``'dict_like_values_name'`` control how they are stored if the
keys are not string like, can't be converted to Python 3.x
``str`` or Python 2.x ``unicode``, or have null or ``'/'``
characters.
* Issues #38 and #91. Added support for ``cl.OrderedDict`` and
``cl.Counter``. The were added added to
``Marshallers.PythonDictMarshaller`` and the new
``Marshallers.PythonCounterMarshaller`` respectively.
* Issue #80. Added a support for ``slice`` and ``range`` with the new
marshaller ``Marshallers.PythonSliceRangeMarshaller``.
* Issue #92. Added support for ``collections.ChainMap`` with the new
marshaller ``Marshallers.PythonChainMap``.
* Issue #93. Added support for ``fractions.Fraction`` with the new
marshaller ``Marshallers.PythonFractionMarshaller``.
* Issue #99. Added support for ``np.dtype`` with the new marshaller
``Marshallers.NumpyDtypeMarshaller``.
* Issue #95. Added support for objects in the ``datetime`` module
(only ``datetime.tzinfo`` class implemented is
``datetime.timezone``) in the new marshaller
``Marshallers.PythonDatetimeObjsMarshaller``.
* Issue #107. Added handling of the eventual removal of the
``numpy.matrix`` class since it is pending deprecation. If the class
is not available, objects that were written as one are read back as
``numpy.ndarray``.
* Added the utility function ``utilities.convert_dtype_to_str`` to convet
``numpy.dtype`` to ``str`` in a way they can be converted back by
passing through ``ast.literal_eval`` and then ``numpy.dtype``.
* Issue #40. Made it so that tests use tempfiles instead of
using hardcoded filenames in the local directory.
* Issue #41. Added tests using the Julia MAT package to check
interop with Matlab v7.3 MAT files.
* Issue #39. Documentation now uses the napoleon extension in
Sphinx >= 1.3 as a replacement for numpydoc package.
* Changed documentation theme to ``sphinx_rtd_theme``.
* Issue #55. Major performance increases by reducing the overhead
involved with reading and writing each Dataset and Group.
* Issue #96. Changed unit testing to use
`pytest`_ instead of
`nose <https://pypi.org/project/nose>`_.
* Issue #113. Removed the ``get_attribute``, ``get_attribute_string``,
``get_attribute_string_array``, ``set_attribute``,
``set_attribute_string``, ``set_attribute_string_array``, and
``del_attribute`` functions in the ``utilities`` module.
* Issue #115. Added an ``options`` argument to ``loadmat`` to explicitly
pass an ``Options`` instance.
* The string converters ``convert_to_str``, ``convert_to_numpy_str``, and
``convert_to_numpy_bytes`` in the ``utilities`` module have been changed
to raise ``TypeError`` when given types that cannot be converted.
* Issue #118. Added type hints and configuration for
`mypy`_
0.1.19. Bugfix release.
* Issue #122 and #124. Replaced use of deprecated ``numpy.asscalar``
functions with the ``numpy.ndarray.item`` method.
* Issue #123. Forced the use of English month and day of the week names
in the HDF5 header for MATLAB compatibility.
* Issue #125. Fixed accidental collection of
``pkg_resources.parse_version`` from setuptools as a Marshaller now
that it is a class.
0.1.18. Performance improving release.
* Pull Request #111 from Daniel Hrisca. Many repeated calls to the
``__getitem__`` methods of objects were turned into single calls.
* Further reducionts in ``__getitem__`` calls in the spirit of PR #111.
0.1.17. Bugfix and deprecation workaround release that fixed the following.
* Issue #109. Fixed the fix Issue #102 for 32-bit platforms (previous
fix was segfaulting).
* Moved to using ``pkg_resources.parse_version`` from ``setuptools``
with ``distutils.version`` classes as a fallback instead of just the
later to prepare for the removal of ``distutils`` (PEP 632) and
prevent warnings on Python versions where it is marked as deprecated.
* Issue #110. Changed all uses of the ``tostring`` method on numpy types
to using ``tobytes`` if available, with ``tostring`` as the fallback
for old versions of numpy where it is not.
0.1.16. Bugfix release that fixed the following bugs.
* Issue #81 and #82. ``h5py.File`` will require the mode to be
passed explicitly in the future. All calls without passing it were
fixed to pass it.
* Issue #102. Added support for h5py 3.0 and 3.1.
* Issue #73. Fixed bug where a missing variable in ``loadmat`` would
cause the function to think that the file is a pre v7.3 format MAT
file fall back to ``scipy.io.loadmat`` which won't work since the file
is a v7.3 format MAT file.
* Fixed formatting issues in the docstrings and the documentation that
prevented the documentation from building.
0.1.15. Bugfix release that fixed the following bugs.
* Issue #68. Fixed bug where ``str`` and ``numpy.unicode_``
strings (but not ndarrays of them) were saved in
``uint32`` format regardless of the value of
``Options.convert_numpy_bytes_to_utf16``.
* Issue #70. Updated ``setup.py`` and ``requirements.txt`` to specify
the maximum versions of numpy and h5py that can be used for specific
python versions (avoid version with dropped support).
* Issue #71. Fixed bug where the ``'python_fields'`` attribute wouldn't
always be written when doing python metadata for data written in
a struct-like fashion. The bug caused the field order to not be
preserved when writing and reading.
* Fixed an assertion in the tests to handle field re-ordering when
no metadata is used for structured dtypes that only worked on
older versions of numpy.
* Issue #72. Fixed bug where python collections filled with ndarrays
that all have the same shape were converted to multi-dimensional
object ndarrays instead of a 1D object ndarray of the elements.
0.1.14. Bugfix release that also added a couple features.
* Issue #45. Fixed syntax errors in unicode strings for Python
3.0 to 3.2.
* Issues #44 and #47. Fixed bugs in testing of conversion and
storage of string types.
* Issue #46. Fixed raising of ``RuntimeWarnings`` in tests due
to signalling NaNs.
* Added requirements files for building documentation and
running tests.
* Made it so that Matlab compatability tests are skipped if
Matlab is not found, instead of raising errors.
0.1.13. Bugfix release fixing the following bug.
* Issue #36. Fixed bugs in writing ``int`` and ``long`` to HDF5
and their tests on 32 bit systems.
0.1.12. Bugfix release fixing the following bugs. In addition, copyright years were also updated and notices put in the Matlab files used for testing.
* Issue #32. Fixed transposing before reshaping ``np.ndarray``
when reading from HDF5 files where python metadata was stored
but not Matlab metadata.
* Issue #33. Fixed the loss of the number of characters when
reading empty numpy string arrays.
* Issue #34. Fixed a conversion error when ``np.chararray`` are
written with Matlab metadata.
0.1.11. Bugfix release fixing the following.
* Issue #30. Fixed ``loadmat`` not opening files in read mode.
0.1.10. Minor feature/performance fix release doing the following.
* Issue #29. Added ``writes`` and ``reads`` functions to write
and read more than one piece of data at a time and made
``savemat`` and ``loadmat`` use them to increase performance.
Previously, the HDF5 file was being opened and closed for
each piece of data, which impacted performance, especially
for large files.
0.1.9. Bugfix and minor feature release doing the following.
* Issue #23. Fixed bug where a structured ``np.ndarray`` with
a field name of ``'O'`` could never be written as an
HDF5 COMPOUND Dataset (falsely thought a field's dtype was
object).
* Issue #6. Added optional data compression and the storage of
data checksums. Controlled by several new options.
0.1.8. Bugfix release fixing the following two bugs.
* Issue #21. Fixed bug where the ``'MATLAB_class'`` Attribute is
not set when writing ``dict`` types when writing MATLAB
metadata.
* Issue #22. Fixed bug where null characters (``'\x00'``) and
forward slashes (``'/'``) were allowed in ``dict`` keys and the
field names of structured ``np.ndarray`` (except that forward
slashes are allowed when the
``structured_numpy_ndarray_as_struct`` is not set as is the
case when the ``matlab_compatible`` option is set). These
cause problems for the ``h5py`` package and the HDF5 library.
``NotImplementedError`` is now thrown in these cases.
0.1.7. Bugfix release with an added compatibility option and some added test code. Did the following.
* Fixed an issue reading variables larger than 2 GB in MATLAB
MAT v7.3 files when no explicit variable names to read are
given to ``hdf5storage.loadmat``. Fix also reduces memory
consumption and processing time a little bit by removing an
unneeded memory copy.
* ``Options`` now will accept any additional keyword arguments it
doesn't support, ignoring them, to be API compatible with future
package versions with added options.
* Added tests for reading data that has been compressed or had
other HDF5 filters applied.
0.1.6. Bugfix release fixing a bug with determining the maximum size of a Python 2.x ``int`` on a 32-bit system.
0.1.5. Bugfix release fixing the following bug.
* Fixed bug where an ``int`` could be stored that is too big to
fit into an ``int`` when read back in Python 2.x. When it is
too big, it is converted to a ``long``.
* Fixed a bug where an ``int`` or ``long`` that is too big to
big to fit into an ``np.int64`` raised the wrong exception.
* Fixed bug where fields names for structured ``np.ndarray`` with
non-ASCII characters (assumed to be UTF-8 encoded in
Python 2.x) can't be read or written properly.
* Fixed bug where ``np.bytes_`` with non-ASCII characters can
were converted incorrectly to UTF-16 when that option is set
(set implicitly when doing MATLAB compatibility). Now, it throws
a ``NotImplementedError``.
0.1.4. Bugfix release fixing the following bugs. Thanks goes to `mrdomino <https://github.com/mrdomino>`_ for writing the bug fixes.
* Fixed bug where ``dtype`` is used as a keyword parameter of
``np.ndarray.astype`` when it is a positional argument.
* Fixed error caused by ``h5py.__version__`` being absent on
Ubuntu 12.04.
0.1.3. Bugfix release fixing the following bug.
* Fixed broken ability to correctly read and write empty
structured ``np.ndarray`` (has fields).
0.1.2. Bugfix release fixing the following bugs.
* Removed mistaken support for ``np.float16`` for h5py versions
before ``2.2`` since that was when support for it was
introduced.
* Structured ``np.ndarray`` where one or more fields is of the
``'object'`` dtype can now be written without an error when
the ``structured_numpy_ndarray_as_struct`` option is not set.
They are written as an HDF5 Group, as if the option was set.
* Support for the ``'MATLAB_fields'`` Attribute for data types
that are structures in MATLAB has been added for when the
version of the h5py package being used is ``2.3`` or greater.
Support is still missing for earlier versions (this package
requires a minimum version of ``2.1``).
* The check for non-unicode string keys (``str`` in Python 3 and
``unicode`` in Python 2) in the type ``dict`` is done right
before any changes are made to the HDF5 file instead of in the
middle so that no changes are applied if an invalid key is
present.
* HDF5 userblock set with the proper metadata for MATLAB support
right at the beginning of when data is being written to an HDF5
file instead of at the end, meaning the writing can crash and
the file will still be a valid MATLAB file.
0.1.1. Bugfix release fixing the following bugs.
* ``str`` is now written like ``numpy.str_`` instead of
``numpy.bytes_``.
* Complex numbers where the real or imaginary part are ``nan``
but the other part are not are now read correctly as opposed
to setting both parts to ``nan``.
* Fixed bugs in string conversions on Python 2 resulting from
``str.decode()`` and ``unicode.encode()`` not taking the same
keyword arguments as in Python 3.
* MATLAB structure arrays can now be read without producing an
error on Python 2.
* ``numpy.str_`` now written as ``numpy.uint16`` on Python 2 if
the ``convert_numpy_str_to_utf16`` option is set and the
conversion can be done without using UTF-16 doublets, instead
of always writing them as ``numpy.uint32``.
0.1. Initial version.
Raw data
{
"_id": null,
"home_page": null,
"name": "hdf5storage",
"maintainer": "Jesse R Codling",
"docs_url": "https://pythonhosted.org/hdf5storage/",
"requires_python": "<4.0,>=3.10",
"maintainer_email": "codling@umich.edu",
"keywords": "hdf5, matlab",
"author": "Freja Nordsiek",
"author_email": "fnordsie@posteo.net",
"download_url": "https://files.pythonhosted.org/packages/23/9f/ce456d3d9ec4c979eec7cb26bda6baf60fc6f61af8bab50d3701ac3b6ae8/hdf5storage-0.2.1.tar.gz",
"platform": null,
"description": "|lint-badge| |pre-commit-badge|\n\n.. |pre-commit-badge| image:: https://results.pre-commit.ci/badge/github/jclds139/hdf5storage/main.svg\n :target: https://results.pre-commit.ci/latest/github/jclds139/hdf5storage/main\n :alt: pre-commit.ci status\n\n.. |lint-badge| image:: https://github.com/jclds139/hdf5storage/actions/workflows/unit_tests.yml/badge.svg\n :target: https://github.com/jclds139/hdf5storage/actions/workflows/unit_tests.yml\n :alt: Unit tests and lint checks\n\nOverview\n========\n\nThis Python package provides high level utilities to read/write a\nvariety of Python types to/from HDF5 (Heirarchal Data Format) formatted\nfiles. This package also provides support for MATLAB MAT v7.3 formatted\nfiles, which are just HDF5 files with a different extension and some\nextra meta-data.\n\nAll of this is done without pickling data. Pickling is bad for security\nbecause it allows arbitrary code to be executed in the interpreter. One\nwants to be able to read possibly HDF5 and MAT files from untrusted\nsources, so pickling is avoided in this package.\n\nThe package's documetation is found at\nhttps://hdf5storage.readthedocs.io\n\nThe package's source code is found at\nhttps://github.com/jclds139/hdf5storage\n\nThe package is licensed under a 2-clause BSD license\n(https://github.com/jclds139/hdf5storage/blob/master/COPYING.txt).\n\nInstallation\n============\n\nDependencies\n------------\n\nThis package only supports Python >= 3.10. Python < 3.10 support was dropped\nin version 0.2.\n\nThis package requires the python packages to run\n\n* `numpy <https://pypi.org/project/numpy>`_\n* `h5py <https://pypi.org/project/h5py>`_ >= 3.9\n* `poetry <https://python-poetry.org/>`_\n\nNote that support for `h5py`_ 2.1 to 3.8.x\nhas been dropped in version 0.2.\nThis package also has the following optional dependencies\n\n* `scipy <https://pypi.org/project/scipy>`_\n\nInstalling by pip\n-----------------\n\nThis package is on `PyPI <https://pypi.org>`_ at\n`hdf5storage <https://pypi.org/project/hdf5storage>`_. To install hdf5storage\nusing pip, run the command::\n\n pip install hdf5storage\n\nInstalling from Source\n----------------------\n\nTo install hdf5storage from source,\n`poetry`_ is required.\nDownload this package and then run ::\n\n pip install .\n\nRunning Tests\n-------------\n\nFor testing, the package `pytest <https://pypi.org/project/pytest>`_\n(>= 8.3) is additionally required. There are some tests that require\nMatlab and `scipy`_ to be installed\nand be in the executable path respectively. In addition, there are some\ntests that require `Julia <http://julialang.org/>`_ with the\n`MAT <https://github.com/simonster/MAT.jl>`_ package. Not having them\nmeans that those tests cannot be run (they will be skipped) but all\nthe other tests will run. To install all testing dependencies, other\nthan `scipy`_, Julia, Matlab run ::\n\n pip install -r <(poetry export -E tests)\n\nTo run the tests ::\n\n pytest\n\n\nBuilding Documentation\n----------------------\n\nThe documentation additionally requires the following packages\n\n* `sphinx <https://pypi.org/project/sphinx>`_ >= 8.0\n* `sphinx_rtd_theme <https://pypi.org/project/sphinx-rtd-theme>`_ >= 3.0\n* `sphinx_rtd_dark_mode <https://pypi.org/project/sphinx-rtd-dark-mode>`_ >= 1.3\n\nThe documentation dependencies can be installed by ::\n\n pip install -r <(poetry export -E docs)\n\nTo build the HTML documentation, run either ::\n\n sphinx-build doc/source doc/build/html\n\n\nDevelopment\n===========\n\nAll Python code is formatted using `ruff format <https://docs.astral.sh/ruff/formatter/>`_.\nReleases and Pull Requests should pass all unit tests, and ideally pass type\nchecking and have no warnings found by linting.\n\n\nType Checking\n-------------\n\nThis package now has type annotations since version 0.2, which can be checked\nwith a type checker like `mypy <https://pypi.org/project/mypy>`_. To check with\n`mypy`_, run ::\n\n mypy -p hdf5storage\n\n\nLinting\n-------\n\nThis package has the configuration in ``pyproject.toml`` for linting with\n\n* `ruff <https://pypi.org/project/ruff>`_\n\nTo lint with `ruff`_, run ::\n\n ruff .\n\n\nPython 2\n========\n\nThis package no longer supports Python 2.6 and 2.7. This package was\ndesigned and written for Python 3, then backported to Python 2.x, and\nthen support dropped. But it can still read files made by version 0.1.x\nof this library with Python 2.x, and this package still tries to write\nfiles compatible with 0.1.x when possible.\n\nHierarchal Data Format 5 (HDF5)\n===============================\n\nHDF5 files (see http://www.hdfgroup.org/HDF5/) are a commonly used file\nformat for exchange of numerical data. It has built in support for a\nlarge variety of number formats (un/signed integers, floating point\nnumbers, strings, etc.) as scalars and arrays, enums and compound types.\nIt also handles differences in data representation on different hardware\nplatforms (endianness, different floating point formats, etc.). As can\nbe imagined from the name, data is represented in an HDF5 file in a\nhierarchal form modelling a Unix filesystem (Datasets are equivalent to\nfiles, Groups are equivalent to directories, and links are supported).\n\nThis package interfaces HDF5 files using the h5py package\n(http://www.h5py.org/) as opposed to the PyTables package\n(http://www.pytables.org/).\n\nMATLAB MAT v7.3 file support\n============================\n\nMATLAB (http://www.mathworks.com/) MAT files version 7.3 and later are\nHDF5 files with a different file extension (``.mat``) and a very\nspecific set of meta-data and storage conventions. This package provides\nread and write support for a limited set of Python and MATLAB types.\n\nSciPy (http://scipy.org/) has functions to read and write the older MAT\nfile formats. This package has functions modeled after the\n``scipy.io.savemat`` and ``scipy.io.loadmat`` functions, that have the\nsame names and similar arguments. The dispatch to the SciPy versions if\nthe MAT file format is not an HDF5 based one.\n\nSupported Types\n===============\n\nThe supported Python and MATLAB types are given in the tables below.\nThe tables assume that one has imported collections and numpy as::\n\n import collections as cl\n import numpy as np\n\nThe table gives which Python types can be read and written, the first\nversion of this package to support it, the numpy type it gets\nconverted to for storage (if type information is not written, that\nwill be what it is read back as) the MATLAB class it becomes if\ntargetting a MAT file, and the first version of this package to\nsupport writing it so MATlAB can read it.\n\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| Python | MATLAB | Notes |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| Type | Version | Converted to | Class | Version | |\n+====================+=========+=========================+=============+=========+===================+\n| bool | 0.1 | np.bool\\_ or np.uint8 | logical | 0.1 | [1]_ |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| None | 0.1 | ``np.float64([])`` | ``[]`` | 0.1 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| Ellipsis | 0.2 | ``np.float64([])`` | ``[]`` | 0.2 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| NotImplemented | 0.2 | ``np.float64([])`` | ``[]`` | 0.2 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| int | 0.1 | np.int64 or np.bytes\\_ | int64 | 0.1 | [2]_ [3]_ |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| long | 0.1 | np.int64 or np.bytes\\_ | int64 | 0.1 | [3]_ [4]_ |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| float | 0.1 | np.float64 | double | 0.1 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| complex | 0.1 | np.complex128 | double | 0.1 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| str | 0.1 | np.uint32/16 | char | 0.1 | [5]_ |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| bytes | 0.1 | np.bytes\\_ or np.uint16 | char | 0.1 | [6]_ |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| bytearray | 0.1 | np.bytes\\_ or np.uint16 | char | 0.1 | [6]_ |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| list | 0.1 | np.object\\_ | cell | 0.1 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| tuple | 0.1 | np.object\\_ | cell | 0.1 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| set | 0.1 | np.object\\_ | cell | 0.1 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| frozenset | 0.1 | np.object\\_ | cell | 0.1 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| cl.deque | 0.1 | np.object\\_ | cell | 0.1 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| cl.ChainMap | 0.2 | np.object\\_ | cell | 0.2 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| dict | 0.1 | | struct | 0.1 | [7]_ |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| cl.OrderedDict | 0.2 | | struct | 0.2 | [7]_ |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| cl.Counter | 0.2 | | struct | 0.2 | [7]_ |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| slice | 0.2 | | struct | 0.2 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| range | 0.2 | | struct | 0.2 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| datetime.timedelta | 0.2 | | struct | 0.2 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| datetime.timezone | 0.2 | | struct | 0.2 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| datetime.date | 0.2 | | struct | 0.2 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| datetime.time | 0.2 | | struct | 0.2 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| datetime.datetime | 0.2 | | struct | 0.2 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| fractions.Fraction | 0.2 | | struct | 0.2 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| np.bool\\_ | 0.1 | | logical | 0.1 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| np.void | 0.1 | | | | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| np.uint8 | 0.1 | | uint8 | 0.1 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| np.uint16 | 0.1 | | uint16 | 0.1 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| np.uint32 | 0.1 | | uint32 | 0.1 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| np.uint64 | 0.1 | | uint64 | 0.1 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| np.uint8 | 0.1 | | int8 | 0.1 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| np.int16 | 0.1 | | int16 | 0.1 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| np.int32 | 0.1 | | int32 | 0.1 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| np.int64 | 0.1 | | int64 | 0.1 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| np.float16 | 0.1 | | | | [8]_ |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| np.float32 | 0.1 | | single | 0.1 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| np.float64 | 0.1 | | double | 0.1 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| np.complex64 | 0.1 | | single | 0.1 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| np.complex128 | 0.1 | | double | 0.1 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| np.str\\_ | 0.1 | np.uint32/16 | char/uint32 | 0.1 | [5]_ |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| np.bytes\\_ | 0.1 | np.bytes\\_ or np.uint16 | char | 0.1 | [6]_ |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| np.object\\_ | 0.1 | | cell | 0.1 | |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| np.ndarray | 0.1 | *see notes* | *see notes* | 0.1 | [9]_ [10]_ [11]_ |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| np.matrix | 0.1 | *see notes* | *see notes* | 0.1 | [9]_ [12]_ |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| np.chararray | 0.1 | *see notes* | *see notes* | 0.1 | [9]_ |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| np.recarray | 0.1 | structured np.ndarray | *see notes* | 0.1 | [9]_ [10]_ |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n| np.dtype | 0.2 | np.bytes\\_ or np.uint16 | char | 0.2 | [6]_ [13]_ |\n+--------------------+---------+-------------------------+-------------+---------+-------------------+\n\n.. [1] Depends on the selected options. Always ``np.uint8`` when doing\n MATLAB compatiblity, or if the option is explicitly set.\n.. [2] In Python 2.x with the 0.1.x version of this package, it may be\n read back as a ``long`` if it can't fit in the size of an\n ``int``.\n.. [3] Stored as a ``np.int64`` if it is small enough to fit. Otherwise\n its decimal string representation is stored as an ``np.bytes_``\n for hdf5storage >= 0.2 (error in earlier versions).\n.. [4] Type found only in Python 2.x. Python 2.x's ``long`` and ``int``\n are unified into a single ``int`` type in Python 3.x. Read as an\n ``int`` in Python 3.x.\n.. [5] Depends on the selected options and whether it can be converted\n to UTF-16 without using doublets. If the option is explicity set\n (or implicitly when doing MATLAB compatibility) and it can be\n converted to UTF-16 without losing any characters that can't be\n represented in UTF-16 or using UTF-16 doublets (MATLAB doesn't\n support them), then it is written as ``np.uint16`` in UTF-16\n encoding. Otherwise, it is stored at ``np.uint32`` in UTF-32\n encoding.\n.. [6] Depends on the selected options. If the option is explicitly set\n (or implicitly when doing MATLAB compatibility), it will be\n stored as ``np.uint16`` in UTF-16 encoding unless it has\n non-ASCII characters in which case a ``NotImplementedError`` is\n thrown). Otherwise, it is just written as ``np.bytes_``.\n.. [7] Stored either as each key-value as their own Dataset or as two\n Datasets, one for keys and one for values. The former is used if\n all keys can be converted to ``str`` and they don't have null\n characters (``'\\x00'``) or forward slashes (``'/'``) in them.\n Otherwise, the latter format is used.\n.. [8] ``np.float16`` are not supported for h5py versions before\n ``2.2``. Version ``2.3`` or higher is required for this package\n since version ``0.2``.\n.. [9] Container types are only supported if their underlying dtype is\n supported. Data conversions are done based on its dtype.\n.. [10] Structured ``np.ndarray`` s (have fields in their dtypes) can be\n written as an HDF5 COMPOUND type or as an HDF5 Group with\n Datasets holding its fields (either the values directly, or as\n an HDF5 Reference array to the values for the different elements\n of the data). Can only be written as an HDF5 COMPOUND type if\n none of its field are of dtype ``'object'``. Field names cannot\n have null characters (``'\\x00'``) and, when writing as an HDF5\n GROUP, forward slashes (``'/'``) in them.\n.. [11] Structured ``np.ndarray`` s with no elements, when written like a\n structure, will not be read back with the right dtypes for their\n fields (will all become 'object').\n.. [12] Will be read back as a ``np.ndarray`` if the ``np.matrix`` class\n is removed.\n.. [13] Stored in their string representation.\n\nThis table gives the MATLAB classes that can be read from a MAT file,\nthe first version of this package that can read them, and the Python\ntype they are read as.\n\n+-----------------+---------+-------------------------------------+\n| MATLAB Class | Version | Python Type |\n+=================+=========+=====================================+\n| logical | 0.1 | np.bool\\_ |\n+-----------------+---------+-------------------------------------+\n| single | 0.1 | np.float32 or np.complex64 [14]_ |\n+-----------------+---------+-------------------------------------+\n| double | 0.1 | np.float64 or np.complex128 [14]_ |\n+-----------------+---------+-------------------------------------+\n| uint8 | 0.1 | np.uint8 |\n+-----------------+---------+-------------------------------------+\n| uint16 | 0.1 | np.uint16 |\n+-----------------+---------+-------------------------------------+\n| uint32 | 0.1 | np.uint32 |\n+-----------------+---------+-------------------------------------+\n| uint64 | 0.1 | np.uint64 |\n+-----------------+---------+-------------------------------------+\n| int8 | 0.1 | np.int8 |\n+-----------------+---------+-------------------------------------+\n| int16 | 0.1 | np.int16 |\n+-----------------+---------+-------------------------------------+\n| int32 | 0.1 | np.int32 |\n+-----------------+---------+-------------------------------------+\n| int64 | 0.1 | np.int64 |\n+-----------------+---------+-------------------------------------+\n| char | 0.1 | np.str\\_ |\n+-----------------+---------+-------------------------------------+\n| struct | 0.1 | structured np.ndarray or dict [15]_ |\n+-----------------+---------+-------------------------------------+\n| cell | 0.1 | np.object\\_ |\n+-----------------+---------+-------------------------------------+\n| canonical empty | 0.1 | ``np.float64([])`` |\n+-----------------+---------+-------------------------------------+\n\n.. [14] Depends on whether there is a complex part or not.\n.. [15] Controlled by an option.\n\n\nFile Incompatibilities\n======================\n\nThe storage of empty ``numpy.ndarray`` (or objects that would be stored like\none) when the ``Options.store_shape_for_empty`` (implicitly set when Matlab\ncompatibility is enabled) is incompatible with the main branch of this package\nbefore 2021-07-11 as well as all 0.1.x versions of this package since they\nhave a bug (Issue #114). The incompatibility is caused by those versions\nstoring the array shape in the Dataset after reversing the dimension order\ninstead of before, meaning that the array is read with its dimensions reversed\nfrom what is expected if read after the bug fix or by Matlab.\n\n\nVersions\n========\n\n0.2. Feature release adding/changing the following, including some API breaking changes.\n * Issues #50 and #84 and #117 and #126. Python < 3.7 support dropped.\n * Issue #53 and #126. h5py < 3.3 support dropped.\n * Issue #114. Fixed bug where the shape was stored in the opposite order as\n Matlab for empty ndarrays when ``Options.store_shape_for_empty`` is set.\n This causes a file compatibility change.\n * Issue #85. Changed to using the PEP 518 method of specifying\n build dependencies from using the older ``ez_setup.py`` to ensure\n ``setuptools`` was available for building.\n * The entire configuration is now put in the ``pyproject.toml`` files\n (PEP 621) and the ``setup.py`` file has been removed.\n * Changed all ``IOError`` to ``OSError``.\n * Added a file object class ``hdf5storage.File`` for\n opening a file and doing multiple read and/or write calls on the\n same file.\n * ``reads``, ``read``, and ``loadmat`` now raise a ``KeyError`` if\n an object can't be found as opposed to a\n ``hdf5storage.exceptions.CantReadError``.\n * Issue #88. Made it so that objects inside the Group specified by\n ``Options.group_for_references`` cannot be read from or written\n to directly by the external API.\n * Issue #64 and PR #87. Added ``structs_as_dicts`` that will cause MATLAB structs\n to be read as ``dict`` instead of structured ``np.dnarray``.\n * Issue #60. Platform label in the MAT file header changed to\n ``hdf5storage VERSION`` from ``CPython VERSION``.\n * Issue #61. User provided marshallers must inherit from\n ``Marshallers.TypeMarshaller``. Before, they just had to provide\n the same interface.\n * Issue #78. Added the ability to pass object paths as\n ``pathlib.PurePath`` (and descendants) objects.\n * Issue #62. The priority ordering between builtin, plugin, and\n user provided marshallers can be selected. The default is now\n builtin, plugin, user; as opposed to user, builtin in the 0.1.x\n branch.\n * Issue #65. Added the ability to load marshallers from other python\n packages via plugin using the\n ``'hdf5storage.marshallers.plugins'`` entry point in their setup.\n Third party marshallers are not loaded into\n the default initial ``MarshallerCollection``. Users who want\n to use them must call ``make_new_default_MarshallerCollection``\n with the ``load_plugins`` option set to ``True``.\n * Issue #66. A version Marshaller API has been added to make it\n easier for developers to write plugin marshallers without having\n to do extensive checking of the ``hdf5storage`` package version.\n The Marshaller API version will advance separately from the\n package version. The initial version is ``'1.0'``.\n * Fixed bugs in ``savemat`` and ``loadmat`` with appening the file\n extension to filenames that are ``bytes``.\n * Issue #27. Added support for paths with null characters, slashes,\n and leading periods. It is used for the field names of structured\n numpy ndarrays as well as the keys of ``dict`` like objects when\n writing their values to individual Datasets.\n * Issue #89. ``Marshallers.PythonNoneMarshaller`` was renamed to\n ``Marshallers.PythonNoneEllipsisNotImplementedMarshaller`` and\n support added for the ``Ellipsis`` and ``NotImplemented`` types.\n * The ``write`` method of all marshallers now must return the written\n HDF5 Group or Dataset (or ``None`` if unsuccessful).\n * Issue #49. Changed marshaller types and their handling code to\n support marshallers that handle types in modules that may not be\n available or should not be imported until needed. If the the\n required modules are not available, an approximate version of\n the data is read using the ``read_approximate`` method of the\n marshaller instead of the ``read`` method. The required modules,\n if available, can either be imported immediately upon the\n creation of the ``MarshallerCollection`` or they can be imported\n only when the marshaller is needed for actual use (lazy loading).\n * Changed the type of the ``types``, ``python_type_strings``, and\n ``matlab_classes`` attributes of ``TypeMarshaller`` to ``tuple``\n from ``list``.\n * Issue #52. Added the usage of a default ``MarshallerCollection``\n which is used whenever creating a new ``Options`` without\n a ``MarshallerCollection`` specified. The default can be\n obtained using ``get_default_MarshallerCollection`` and a new\n default can be generated using\n ``make_new_default_MarshallerCollection``. This is useful if\n one wants to override the default lazy loading behavior.\n * Issues #42 and #106. read and write functions moved from the ``lowlevel``\n and ``Marshallers`` modules to the ``utilities`` module and\n the ``lowlevel`` module renamed to ``exceptions`` since that is\n all that remains in it. The functions to read/write Datasets and Groups\n were replaced with a wrapper class ``LowLevelFile`` with methods\n that are similar.\n * Issue #106. Marshallers are passed a ``utilities.LowLevelFile`` object\n as the first argument (``f``) instead of the file handle (``h5py.File``)\n with the ``Options`` as the keyword argument ``options``.\n * Ability to write Python 3.x ``int`` and Python 2.x ``long`` that\n are too large to fit into ``np.int64``. Doing so no longer\n raises an exception.\n * Ability to write ``np.bytes_`` with non-ASCII characters in them.\n Doing so no longer raises an exception.\n * Issue #24 and #25. Added support for writing ``dict`` like\n objects with keys that are not all ``str`` without null and ``'/'``\n characters. Two new options, ``'dict_like_keys_name'`` and\n ``'dict_like_values_name'`` control how they are stored if the\n keys are not string like, can't be converted to Python 3.x\n ``str`` or Python 2.x ``unicode``, or have null or ``'/'``\n characters.\n * Issues #38 and #91. Added support for ``cl.OrderedDict`` and\n ``cl.Counter``. The were added added to\n ``Marshallers.PythonDictMarshaller`` and the new\n ``Marshallers.PythonCounterMarshaller`` respectively.\n * Issue #80. Added a support for ``slice`` and ``range`` with the new\n marshaller ``Marshallers.PythonSliceRangeMarshaller``.\n * Issue #92. Added support for ``collections.ChainMap`` with the new\n marshaller ``Marshallers.PythonChainMap``.\n * Issue #93. Added support for ``fractions.Fraction`` with the new\n marshaller ``Marshallers.PythonFractionMarshaller``.\n * Issue #99. Added support for ``np.dtype`` with the new marshaller\n ``Marshallers.NumpyDtypeMarshaller``.\n * Issue #95. Added support for objects in the ``datetime`` module\n (only ``datetime.tzinfo`` class implemented is\n ``datetime.timezone``) in the new marshaller\n ``Marshallers.PythonDatetimeObjsMarshaller``.\n * Issue #107. Added handling of the eventual removal of the\n ``numpy.matrix`` class since it is pending deprecation. If the class\n is not available, objects that were written as one are read back as\n ``numpy.ndarray``.\n * Added the utility function ``utilities.convert_dtype_to_str`` to convet\n ``numpy.dtype`` to ``str`` in a way they can be converted back by\n passing through ``ast.literal_eval`` and then ``numpy.dtype``.\n * Issue #40. Made it so that tests use tempfiles instead of\n using hardcoded filenames in the local directory.\n * Issue #41. Added tests using the Julia MAT package to check\n interop with Matlab v7.3 MAT files.\n * Issue #39. Documentation now uses the napoleon extension in\n Sphinx >= 1.3 as a replacement for numpydoc package.\n * Changed documentation theme to ``sphinx_rtd_theme``.\n * Issue #55. Major performance increases by reducing the overhead\n involved with reading and writing each Dataset and Group.\n * Issue #96. Changed unit testing to use\n `pytest`_ instead of\n `nose <https://pypi.org/project/nose>`_.\n * Issue #113. Removed the ``get_attribute``, ``get_attribute_string``,\n ``get_attribute_string_array``, ``set_attribute``,\n ``set_attribute_string``, ``set_attribute_string_array``, and\n ``del_attribute`` functions in the ``utilities`` module.\n * Issue #115. Added an ``options`` argument to ``loadmat`` to explicitly\n pass an ``Options`` instance.\n * The string converters ``convert_to_str``, ``convert_to_numpy_str``, and\n ``convert_to_numpy_bytes`` in the ``utilities`` module have been changed\n to raise ``TypeError`` when given types that cannot be converted.\n * Issue #118. Added type hints and configuration for\n `mypy`_\n\n0.1.19. Bugfix release.\n * Issue #122 and #124. Replaced use of deprecated ``numpy.asscalar``\n functions with the ``numpy.ndarray.item`` method.\n * Issue #123. Forced the use of English month and day of the week names\n in the HDF5 header for MATLAB compatibility.\n * Issue #125. Fixed accidental collection of\n ``pkg_resources.parse_version`` from setuptools as a Marshaller now\n that it is a class.\n\n0.1.18. Performance improving release.\n * Pull Request #111 from Daniel Hrisca. Many repeated calls to the\n ``__getitem__`` methods of objects were turned into single calls.\n * Further reducionts in ``__getitem__`` calls in the spirit of PR #111.\n\n0.1.17. Bugfix and deprecation workaround release that fixed the following.\n * Issue #109. Fixed the fix Issue #102 for 32-bit platforms (previous\n fix was segfaulting).\n * Moved to using ``pkg_resources.parse_version`` from ``setuptools``\n with ``distutils.version`` classes as a fallback instead of just the\n later to prepare for the removal of ``distutils`` (PEP 632) and\n prevent warnings on Python versions where it is marked as deprecated.\n * Issue #110. Changed all uses of the ``tostring`` method on numpy types\n to using ``tobytes`` if available, with ``tostring`` as the fallback\n for old versions of numpy where it is not.\n\n0.1.16. Bugfix release that fixed the following bugs.\n * Issue #81 and #82. ``h5py.File`` will require the mode to be\n passed explicitly in the future. All calls without passing it were\n fixed to pass it.\n * Issue #102. Added support for h5py 3.0 and 3.1.\n * Issue #73. Fixed bug where a missing variable in ``loadmat`` would\n cause the function to think that the file is a pre v7.3 format MAT\n file fall back to ``scipy.io.loadmat`` which won't work since the file\n is a v7.3 format MAT file.\n * Fixed formatting issues in the docstrings and the documentation that\n prevented the documentation from building.\n\n0.1.15. Bugfix release that fixed the following bugs.\n * Issue #68. Fixed bug where ``str`` and ``numpy.unicode_``\n strings (but not ndarrays of them) were saved in\n ``uint32`` format regardless of the value of\n ``Options.convert_numpy_bytes_to_utf16``.\n * Issue #70. Updated ``setup.py`` and ``requirements.txt`` to specify\n the maximum versions of numpy and h5py that can be used for specific\n python versions (avoid version with dropped support).\n * Issue #71. Fixed bug where the ``'python_fields'`` attribute wouldn't\n always be written when doing python metadata for data written in\n a struct-like fashion. The bug caused the field order to not be\n preserved when writing and reading.\n * Fixed an assertion in the tests to handle field re-ordering when\n no metadata is used for structured dtypes that only worked on\n older versions of numpy.\n * Issue #72. Fixed bug where python collections filled with ndarrays\n that all have the same shape were converted to multi-dimensional\n object ndarrays instead of a 1D object ndarray of the elements.\n\n0.1.14. Bugfix release that also added a couple features.\n * Issue #45. Fixed syntax errors in unicode strings for Python\n 3.0 to 3.2.\n * Issues #44 and #47. Fixed bugs in testing of conversion and\n storage of string types.\n * Issue #46. Fixed raising of ``RuntimeWarnings`` in tests due\n to signalling NaNs.\n * Added requirements files for building documentation and\n running tests.\n * Made it so that Matlab compatability tests are skipped if\n Matlab is not found, instead of raising errors.\n\n0.1.13. Bugfix release fixing the following bug.\n * Issue #36. Fixed bugs in writing ``int`` and ``long`` to HDF5\n and their tests on 32 bit systems.\n\n0.1.12. Bugfix release fixing the following bugs. In addition, copyright years were also updated and notices put in the Matlab files used for testing.\n * Issue #32. Fixed transposing before reshaping ``np.ndarray``\n when reading from HDF5 files where python metadata was stored\n but not Matlab metadata.\n * Issue #33. Fixed the loss of the number of characters when\n reading empty numpy string arrays.\n * Issue #34. Fixed a conversion error when ``np.chararray`` are\n written with Matlab metadata.\n\n0.1.11. Bugfix release fixing the following.\n * Issue #30. Fixed ``loadmat`` not opening files in read mode.\n\n0.1.10. Minor feature/performance fix release doing the following.\n * Issue #29. Added ``writes`` and ``reads`` functions to write\n and read more than one piece of data at a time and made\n ``savemat`` and ``loadmat`` use them to increase performance.\n Previously, the HDF5 file was being opened and closed for\n each piece of data, which impacted performance, especially\n\t for large files.\n\n0.1.9. Bugfix and minor feature release doing the following.\n * Issue #23. Fixed bug where a structured ``np.ndarray`` with\n a field name of ``'O'`` could never be written as an\n HDF5 COMPOUND Dataset (falsely thought a field's dtype was\n object).\n * Issue #6. Added optional data compression and the storage of\n data checksums. Controlled by several new options.\n\n0.1.8. Bugfix release fixing the following two bugs.\n * Issue #21. Fixed bug where the ``'MATLAB_class'`` Attribute is\n not set when writing ``dict`` types when writing MATLAB\n metadata.\n * Issue #22. Fixed bug where null characters (``'\\x00'``) and\n forward slashes (``'/'``) were allowed in ``dict`` keys and the\n field names of structured ``np.ndarray`` (except that forward\n slashes are allowed when the\n ``structured_numpy_ndarray_as_struct`` is not set as is the\n case when the ``matlab_compatible`` option is set). These\n cause problems for the ``h5py`` package and the HDF5 library.\n ``NotImplementedError`` is now thrown in these cases.\n\n0.1.7. Bugfix release with an added compatibility option and some added test code. Did the following.\n * Fixed an issue reading variables larger than 2 GB in MATLAB\n MAT v7.3 files when no explicit variable names to read are\n given to ``hdf5storage.loadmat``. Fix also reduces memory\n consumption and processing time a little bit by removing an\n unneeded memory copy.\n * ``Options`` now will accept any additional keyword arguments it\n doesn't support, ignoring them, to be API compatible with future\n package versions with added options.\n * Added tests for reading data that has been compressed or had\n other HDF5 filters applied.\n\n0.1.6. Bugfix release fixing a bug with determining the maximum size of a Python 2.x ``int`` on a 32-bit system.\n\n0.1.5. Bugfix release fixing the following bug.\n * Fixed bug where an ``int`` could be stored that is too big to\n fit into an ``int`` when read back in Python 2.x. When it is\n too big, it is converted to a ``long``.\n * Fixed a bug where an ``int`` or ``long`` that is too big to\n\t big to fit into an ``np.int64`` raised the wrong exception.\n * Fixed bug where fields names for structured ``np.ndarray`` with\n non-ASCII characters (assumed to be UTF-8 encoded in\n Python 2.x) can't be read or written properly.\n * Fixed bug where ``np.bytes_`` with non-ASCII characters can\n were converted incorrectly to UTF-16 when that option is set\n (set implicitly when doing MATLAB compatibility). Now, it throws\n a ``NotImplementedError``.\n\n0.1.4. Bugfix release fixing the following bugs. Thanks goes to `mrdomino <https://github.com/mrdomino>`_ for writing the bug fixes.\n * Fixed bug where ``dtype`` is used as a keyword parameter of\n ``np.ndarray.astype`` when it is a positional argument.\n * Fixed error caused by ``h5py.__version__`` being absent on\n Ubuntu 12.04.\n\n0.1.3. Bugfix release fixing the following bug.\n * Fixed broken ability to correctly read and write empty\n structured ``np.ndarray`` (has fields).\n\n0.1.2. Bugfix release fixing the following bugs.\n * Removed mistaken support for ``np.float16`` for h5py versions\n before ``2.2`` since that was when support for it was\n introduced.\n * Structured ``np.ndarray`` where one or more fields is of the\n ``'object'`` dtype can now be written without an error when\n the ``structured_numpy_ndarray_as_struct`` option is not set.\n They are written as an HDF5 Group, as if the option was set.\n * Support for the ``'MATLAB_fields'`` Attribute for data types\n that are structures in MATLAB has been added for when the\n version of the h5py package being used is ``2.3`` or greater.\n Support is still missing for earlier versions (this package\n requires a minimum version of ``2.1``).\n * The check for non-unicode string keys (``str`` in Python 3 and\n ``unicode`` in Python 2) in the type ``dict`` is done right\n before any changes are made to the HDF5 file instead of in the\n middle so that no changes are applied if an invalid key is\n present.\n * HDF5 userblock set with the proper metadata for MATLAB support\n right at the beginning of when data is being written to an HDF5\n file instead of at the end, meaning the writing can crash and\n the file will still be a valid MATLAB file.\n\n0.1.1. Bugfix release fixing the following bugs.\n * ``str`` is now written like ``numpy.str_`` instead of\n ``numpy.bytes_``.\n * Complex numbers where the real or imaginary part are ``nan``\n but the other part are not are now read correctly as opposed\n to setting both parts to ``nan``.\n * Fixed bugs in string conversions on Python 2 resulting from\n ``str.decode()`` and ``unicode.encode()`` not taking the same\n keyword arguments as in Python 3.\n * MATLAB structure arrays can now be read without producing an\n error on Python 2.\n * ``numpy.str_`` now written as ``numpy.uint16`` on Python 2 if\n the ``convert_numpy_str_to_utf16`` option is set and the\n conversion can be done without using UTF-16 doublets, instead\n of always writing them as ``numpy.uint32``.\n\n0.1. Initial version.\n",
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