Source installation on Linux and OS X

You need, via apt-get, yum or Homebrew:

  • Python 2.6, 2.7, 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)
  • NumPy 1.6.1 or later
$ pip install h5py

or, from a tarball:

$ python install

Source installation on Windows

Installing from source on Windows is effectively impossible because of the C library dependencies involved.

If you don’t want to use Anaconda, Canopy, or PythonXY, download a third-party wheel from Chris Gohlke’s excellent collection.

Custom installation

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

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

$ 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 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 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 configure:

$ export CC=mpicc
$ python configure --mpi
$ python build

See also Parallel HDF5.