def _dump(py_obj, h_group, call_id=None, **kwargs):
""" Dump a python object to a group within an HDF5 file.
This function is called recursively by the main dump() function.
Args:
py_obj: python object to dump.
h_group (h5.File.group): group to dump data into.
call_id (int): index to identify object's relative location in the
iterable.
"""
# Check if we have a unloaded loader for the provided py_obj
load_loader(py_obj)
# Firstly, check if item is a numpy array. If so, just dump it.
if check_is_ndarray_like(py_obj):
create_hkl_dataset(py_obj, h_group, call_id, **kwargs)
# Next, check if item is a dict
elif isinstance(py_obj, dict):
create_hkl_dataset(py_obj, h_group, call_id, **kwargs)
# If not, check if item is iterable
elif check_is_iterable(py_obj):
item_type = check_iterable_item_type(py_obj)
# item_type == False implies multiple types. Create a dataset
if not item_type:
h_subgroup = create_hkl_group(py_obj, h_group, call_id)
for ii, py_subobj in enumerate(py_obj):
_dump(py_subobj, h_subgroup, call_id=ii, **kwargs)
# otherwise, subitems have same type. Check if subtype is an iterable
# (e.g. list of lists), or not (e.g. list of ints, which should be
# treated as a single dataset).
else:
if item_type in dumpable_dtypes:
create_hkl_dataset(py_obj, h_group, call_id, **kwargs)
else:
h_subgroup = create_hkl_group(py_obj, h_group, call_id)
for ii, py_subobj in enumerate(py_obj):
_dump(py_subobj, h_subgroup, call_id=ii, **kwargs)
# item is not iterable, so create a dataset for it
else:
create_hkl_dataset(py_obj, h_group, call_id, **kwargs)
def test_check_is_iterable():
assert check_is_iterable([1, 2, 3]) is True
assert check_is_iterable(1) is False
def test_check_is_iterable():
assert check_is_iterable([1, 2, 3])
assert not check_is_iterable(1)
def test_check_is_iterable():
assert check_is_iterable([1,2,3]) is True
assert check_is_iterable(1) is False
def test_is_iterable():
a = [1, 2, 3]
b = 1
assert helpers.check_is_iterable(a)
assert not helpers.check_is_iterable(b)