"""
This example shows how to read and write string datatypes to a dataset.  The
program first writes strings to a dataset with a dataspace of DIM0, then
closes the file.  Next, it reopens the file, reads back the data, and outputs
it to the screen.
"""
import sys

import numpy as np
import h5py

FILE = "h5ex_t_vlstringatt.h5"
DATASET = "DS1"
ATTRIBUTE = "A1"

# Strings are handled very differently between python2 and python3.
if sys.hexversion >= 0x03000000:
    FILE = FILE.encode()
    DATASET = DATASET.encode()
    ATTRIBUTE = ATTRIBUTE.encode()

DIM0 = 4
SDIM = 8

def run():
    # The "write" data must be a numpy array for variable length strings,
    # not a list.  
    #
    # Does this mean that we can use "|O"?
    wdata = np.empty((DIM0,), "|O")
    wdata[0] = "Parting"
    wdata[1] = "is such"
    wdata[2] = "sweet"
    wdata[3] = "sorrow"

    # Create a new file using the default properties.
    fid = h5py.h5f.create(FILE)

    # Create the file and memory datatypes.  For this example we will save the
    # strings as FORTRAN strings, therefore they do not need space for the null
    # terminator in the file.
    filetype = h5py.h5t.FORTRAN_S1.copy()
    filetype.set_size(h5py.h5t.VARIABLE)
    memtype = h5py.h5t.C_S1.copy()
    memtype.set_size(h5py.h5t.VARIABLE)


    # Create a dataset with a scalar dataspace.
    # The origin C example uses a NULL dataspace, but this does not seem to
    # yet be possible in H5PY.
    space = h5py.h5s.create(h5py.h5s.SCALAR)
    dset = h5py.h5d.create(fid, DATASET, h5py.h5t.STD_I32LE, space)

    # Create the attribute dataspace.
    space = h5py.h5s.create_simple((DIM0,))

    # Create the attribute and write the string data to it.
    attr = h5py.h5a.create(dset, ATTRIBUTE, filetype, space)
    attr.write(wdata)

    # Explicitly close and release resources.
    del attr
    del space
    del dset
    del fid

    # Open file and dataset using the default properties.
    fid = h5py.h5f.open(FILE)
    dset = h5py.h5d.open(fid, DATASET)
    attr = h5py.h5a.open(dset, ATTRIBUTE)

    # Get the dataspace and allocate an array big enough to accomodate it.
    space = attr.get_space()
    dims = space.get_simple_extent_dims()

    rdata = np.empty(dims, dtype="|O")
    attr.read(rdata)

    # Output the data to the screen.
    print("%s:" % ATTRIBUTE)
    print(rdata)


if __name__ == "__main__":
    run()