Installation

For Python beginners

It can be a pain to install NumPy, HDF5, h5py, Cython and other dependencies. If you’re just starting out, by far the easiest approach is to install h5py via your package manager (apt-get or similar), or by using one of the major science-oriented Python distributions:

Installing on Windows

You will need:

  • Python 2.6, 2.7, 3.2, 3.3 or 3.4 (from Python.org)
  • NumPy 1.6.1 or newer
  • The “six” Python 2/3 compatibility package

Download the installer from http://www.h5py.org and run it. HDF5 is included.

Note

If you are using Anaconda, PythonXY or another non-Python.org distribution, you should instead install h5py via your distribution’s own pacakge manager.

Installing on Linux and Mac OS X

System dependencies

You will need:

  • Python 2.6, 2.7, 3.2, 3.3, or 3.4 with development headers (python-dev or similar)
  • HDF5 1.8.4 or newer, shared library version with development headers (libhdf5-dev or similar)

On Mac OS X, homebrew is a reliable way of getting Python, HDF5 and other dependencies set up. It is also safe to use h5py with the OS X system Python.

Install with pip

Simply run:

$ pip install h5py

All dependencies are installed automatically.

Via setup.py

You will need:

$ tar xzf h5py-X.Y.Z.tar.gz
$ cd h5py
$ python setup.py install

Running the test suite

With the tarball version of h5py:

$ python setup.py build
$ python setup.py test

After installing h5py:

>>> import h5py
>>> h5py.run_tests()

Custom installation

You can specify build options for h5py with the configure option to setup.py. Options may be given together or separately:

$ python setup.py configure --hdf5=/path/to/hdf5
$ python setup.py configure --hdf5-version=X.Y.Z
$ python setup.py configure --mpi

Note the --hdf5-version option is generally not needed, as h5py auto-detects the installed version of HDF5 (even for custom locations).

Once set, build options apply to all future builds in the source directory. You can reset to the defaults with the --reset option:

$ python setup.py configure --reset

You can also configure h5py using environment variables. This is handy when installing via pip, as you don’t have direct access to setup.py:

$ HDF5_DIR=/path/to/hdf5 pip install h5py
$ HDF5_VERSION=X.Y.Z pip install h5py

Here’s a list of all the configure options currently supported:

Option Via setup.py Via environment variable
Custom path to HDF5 --hdf5=/path/to/hdf5 HDF5_DIR=/path/to/hdf5
Force HDF5 version --hdf5-version=X.Y.Z HDF5_VERSION=X.Y.Z
Enable MPI mode --mpi (none)

Building against Parallel HDF5

If you just want to build with mpicc, and don’t care about using Parallel HDF5 features in h5py itself:

$ export CC=mpicc
$ python setup.py install

If you want access to the full Parallel HDF5 feature set in h5py (Parallel HDF5), you will have to build in MPI mode. Right now this must be done with command-line options from the h5py tarball.

You will need a shared-library build of Parallel HDF5 (i.e. built with ./configure –enable-shared –enable-parallel).

To build in MPI mode, use the --mpi option to setup.py configure:

$ export CC=mpicc
$ python setup.py configure --mpi
$ python setup.py build

See also Parallel HDF5.

Help! It didn’t work!

You may wish to check the FAQ first for common installation problems.

Then, feel free to ask the discussion group at Google Groups. There’s only one discussion group for h5py, so you’re likely to get help directly from the maintainers.