Pre-configured installation (recommended)¶
It’s strongly recommended that you use a Python distribution or package manager to install h5py along with its compiled dependencies. Here are some which are popular in the Python community:
- Anaconda or Miniconda (Mac, Windows, Linux)
- Enthought Canopy (Mac, Windows, Linux)
- PythonXY (Windows)
conda install h5py # Anaconda/Miniconda enpkg h5py # Canopy
Or, use your package manager:
- apt-get (Linux/Debian, including Ubuntu)
- yum (Linux/Red Hat, including Fedora and CentOS)
- Homebrew (OS X)
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 (
- HDF5 1.8.4 or newer, shared library version with development headers (
- NumPy 1.6.1 or later
$ pip install h5py
or, from a tarball:
$ python setup.py 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.
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
--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
$ 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||
|Force HDF5 version||
|Enable MPI mode||
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
$ export CC=mpicc $ python setup.py configure --mpi $ python setup.py build
See also Parallel HDF5.