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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def ascii2h5(dirname, output_fname):
 """ Converts from a directory of tarballed ASCII ".samp" files to a single HDF5 file. Essentially, converts from the original release format to a single HDF5 file. """


    import tarfile
    import sys
    from glob import glob
    from contextlib import closing

    # The datatype that will be used to store extinction, A0
    A0_dtype = 'float16'

    def load_samp_file(f, fname):
        # Parse filename
        fname_chunks = os.path.split(fname)[1].split('_')
        l = float(fname_chunks[0])
        b = float(fname_chunks[1])

        # Load ASCII data
        data_raw = np.loadtxt(f, dtype='float64')

        n_samples = data_raw.shape[1] - 1
        n_dists = data_raw.shape[0]

        # Construct output
        dtype = [
            ('dist', 'int32'),
            ('A0', A0_dtype, (n_samples,))]

        data = np.empty(n_dists, dtype=dtype)
        data['dist'][:] = data_raw[:,0]
        data['A0'][:,:] = data_raw[:,1:]

        return (l,b), data

    def process_tarball(tarball_fname):
        # Write to the progress bar
        print('.', end='')
        sys.stdout.flush()

        with closing(tarfile.open(tarball_fname, mode='r:gz')) as f_tar:
            fnames = f_tar.getnames()

            f = f_tar.extractfile(fnames[0])
            (l,b), data = load_samp_file(f, fnames[0])
            n_dists, n_samples = data['A0'].shape
            n_coords = len(fnames)

            dtype = [
                ('l', 'float32'),
                ('b', 'float32'),
                ('dist', 'int32', (n_dists,)),
                ('A0', A0_dtype, (n_dists, n_samples))]
            data_combined = np.empty(n_coords, dtype=dtype)

            for k,fn in enumerate(fnames):
                # print('File {: >4d} of {:d}'.format(k+1, n_coords))
                f = f_tar.extractfile(fn)
                (l,b), data = load_samp_file(f, fn)
                data_combined['l'][k] = l
                data_combined['b'][k] = b
                data_combined['dist'][k] = data['dist']
                data_combined['A0'][k] = data['A0']

        return data_combined

    def save_data(data, fname):
        with closing(h5py.File(fname, 'w')) as f:
            f.create_dataset(
                'samples',
                data=data,
                chunks=True,
                compression='gzip',
                compression_opts=3)

    print('Progress: ', end='')
    sys.stdout.flush()

    tar_fname_list = glob(os.path.join(dirname, 'A_samp_*.tar.gz'))
    d = np.hstack([process_tarball(fn) for fn in tar_fname_list])

    print('+', end='')
    sys.stdout.flush()

    save_data(d, output_fname)

    print('')