H5Attr: Quick access to hdf5 data via attributes, allowing group.dataset (equivalent to group['dataset']) and IPython/Jupyter tab completion.
pip install git+https://github.com/syrte/h5attr# create example HDF5 file for this guide
import h5py, io
file = io.BytesIO()
with h5py.File(file, 'w') as fp:
fp['0'] = [1, 2]
fp['a'] = [3, 4]
fp['b/c'] = 5
fp.attrs['d'] = 's'
# import package
from h5attr import H5Attr
# open file
f = H5Attr(file)
# easy access to members, with tab completion in IPython/Jupyter
f.a, f['a']
# also work for subgroups, but note that f['b/c'] is more efficient
# because it does not create f['b']
f.b.c, f['b'].c, f['b/c']
# convert integer keys to strings automatically (cannot use f.0)
f[0], f['0']
# allow dict-like operations
list(f), [key for key in f], 'a' in f
# access to HDF5 attrs via a H5Attr wrapper
f._attrs.d, f._attrs['d']
# show summary of the data
f._show()
# 0 int64 (2,)
# a int64 (2,)
# b/ 1 members
# close the hdf5 file
f._close()
# lazy (default) and non-lazy mode
f = H5Attr(file)
f.a # <HDF5 dataset "a": shape (2,), type "<i8">
f = H5Attr(file, lazy=False)
f.a # array([3, 4])
H5Attr(path, lazy=True, **args)
- Parameters
path: h5py group, file path, or file-like object.lazy: bool, if true, dataset[()] will be returned.args: additional arguments used for opening h5py file.
- Properties
_attrs: access to the h5py attrs dict.
- Methods
_close(): close the h5py file if applicable._show(): show a summary of the h5py group.