# hdf5storage **Repository Path**: mirrors_lepy/hdf5storage ## Basic Information - **Project Name**: hdf5storage - **Description**: Python package to read and write a wide range of Python types to/from HDF5 formatted files. Can read/write data to the HDF5 based Matlab v7.3 MAT files. - **Primary Language**: Unknown - **License**: BSD-2-Clause - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2021-01-14 - **Last Updated**: 2025-08-09 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README .. image:: https://travis-ci.org/frejanordsiek/hdf5storage.svg?branch=master :target: https://travis-ci.org/frejanordsiek/hdf5storage 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 http://pythonhosted.org/hdf5storage/ The package's source code is found at https://github.com/frejanordsiek/hdf5storage The package is licensed under a 2-clause BSD license (https://github.com/frejanordsiek/hdf5storage/blob/master/COPYING.txt). Installation ============ Dependencies ------------ This package only supports Python >= 3.5. Python < 3.5 support was dropped in version 0.2. This package requires the numpy and h5py (>= 2.3) packages to run. Note that support for h5py 2.1.x and 2.2.x has been dropped in version 0.2. An optional dependency is the scipy package. Installing by pip ----------------- This package is on `PyPI `_. To install hdf5storage using pip, run the command:: pip install hdf5storage Installing from Source ---------------------- To install hdf5storage from source, download the package and then install the dependencies :: pip install -r requirements.txt Then to install the package, run the command with Python :: python setup.py install Running Tests ------------- For testing, the package nose (>= 1.0) is additionally required. There are some tests that require Matlab and scipy to be installed and be in the executable path. In addition, there are some tests that require `Julia `_ with the `MAT `_ 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 requirements_tests.txt. To run the tests :: python setup.py nosetests Building Documentation ---------------------- The documentation additionally requires sphinx (>= 1.7) and `sphinx_rtd_theme `_. The documentation dependencies can be installed by :: pip install -r requirements_doc.txt To build the documentation :: python setup.py build_sphinx 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]_ | +--------------------+---------+-------------------------+-------------+---------+-------------------+ | 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]_ [12]_ | +--------------------+---------+-------------------------+-------------+---------+-------------------+ .. [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] 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 [13]_ | +-----------------+---------+-------------------------------------+ | double | 0.1 | np.float64 or np.complex128 [13]_ | +-----------------+---------+-------------------------------------+ | 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 [14]_ | +-----------------+---------+-------------------------------------+ | cell | 0.1 | np.object\_ | +-----------------+---------+-------------------------------------+ | canonical empty | 0.1 | ``np.float64([])`` | +-----------------+---------+-------------------------------------+ .. [13] Depends on whether there is a complex part or not. .. [14] Controlled by an option. Versions ======== 0.2. Feature release adding/changing the following, including some API breaking changes. * Issues #50 and #84. Python < 3.5 support dropped. * Issue #53. h5py 2.1.x and 2.2.x support dropped. * 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. * Added a file object class :py: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.py`` files. 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). ``utilities.write_data`` now returns this as well. * 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. * Issue #42. 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. * 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 #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. 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 #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. 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 `_ 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.