Library for flexible HDF5 saving/loading. It was forked from the deepdish library from the University of Chicago to maintain its convenient i/o module.
pip install flammkuchen
The primary feature of flammkuchen (ex deepdish) is its ability to save and load all kinds of data as HDF5. It can save any Python data structure, offering the same ease of use as pickling or numpy.save. However, it improves by also offering:
- Interoperability between languages (HDF5 is a popular standard)
- Easy to inspect the content from the command line (using
h5ls
or our specialized toolddls
) - Highly compressed storage (thanks to a PyTables backend)
- Native support for scipy sparse matrices and pandas
DataFrame
andSeries
- Ability to partially read files, even slices of arrays
An example:
import flammkuchen as fl
d = {
'foo': np.ones((10, 20)),
'sub': {
'bar': 'a string',
'baz': 1.23,
},
}
fl.save('test.h5', d)
This can be reconstructed using fl.load('test.h5')
, or inspected through
the command line using either a standard tool:
$ h5ls test.h5 foo Dataset {10, 20} sub Group
Or, better yet, our custom tool ddls
(or python -m fl.ls
):
$ ddls test.h5 /foo array (10, 20) [float64] /sub dict /sub/bar 'a string' (8) [unicode] /sub/baz 1.23 [float64]
Read more at `Saving and loading data <https://github.com/portugueslab/flammkuchen/blob/master/io.rst`__.