def coerce_type(cls,
obj,
typedef=None,
key_order=None,
dont_wrap_single=False,
**kwargs):
r"""Coerce objects of specific types to match the data type.
Args:
obj (object): Object to be coerced.
typedef (dict, optional): Type defintion that object should be
coerced to. Defaults to None.
key_order (list, optional): Order that keys from a dictionary should
be used to compose an array. Defaults to None.
dont_wrap_single (bool, optional): If True, single element
data types will not attempt to wrap input object in
additional list. Defaults to False.
**kwargs: Additional keyword arguments are metadata entries that may
aid in coercing the type.
Returns:
object: Coerced object.
Raises:
RuntimeError: If obj is a dictionary, but key_order is not provided.
"""
from yggdrasil.serialize import pandas2list, numpy2list, dict2list
if isinstance(obj, pd.DataFrame):
obj = pandas2list(obj)
elif isinstance(obj, np.ndarray) and (len(obj.dtype) == 0):
obj = [obj]
elif isinstance(obj, np.ndarray) and (len(obj.dtype) > 0):
obj = numpy2list(obj)
elif isinstance(obj, dict):
if (key_order is not None) or (len(obj) == 1):
obj = dict2list(obj, order=key_order)
elif (isinstance(typedef, dict)
and isinstance(typedef.get('items', None), list)
and all([('title' in x) for x in typedef['items']])):
key_order = [x['title'] for x in typedef['items']]
obj = dict2list(obj, order=key_order)
else:
obj = [obj]
elif ((isinstance(typedef, dict) and (not dont_wrap_single)
and (len(typedef.get('items', [])) == 1))):
typedef_validated = kwargs.get('typedef_validated', False)
try_obj = cls.coerce_type([obj],
typedef=typedef,
key_order=key_order,
dont_wrap_single=True,
**kwargs)
if cls.check_decoded(try_obj,
typedef,
typedef_validated=typedef_validated):
obj = try_obj
return super(JSONArrayMetaschemaType, cls).coerce_type(obj,
typedef=typedef,
**kwargs)
def test_dict2list():
r"""Test conversion of a dictionary to a list and back."""
with pytest.raises(TypeError):
serialize.dict2list(None)
with pytest.raises(TypeError):
serialize.list2dict(None)
x = {'c': 0, 'b': 1, 'a': 2}
y = [2, 1, 0]
assert (serialize.dict2list(x) == y)
def test_coerce():
r"""Test serialization of coerced types."""
typedef = {
'type': 'object',
'properties': {
'a': {
'type': '1darray',
'subtype': 'float',
'title': 'a',
'precision': 64
}
}
}
x = JSONObjectMetaschemaType(**typedef)
key_order = ['a']
msg_recv = {'a': np.zeros(3, 'float64')}
msg_send_list = [
serialize.dict2numpy(msg_recv, order=key_order),
serialize.dict2pandas(msg_recv, order=key_order),
serialize.dict2list(msg_recv, order=key_order)
]
def do_send_recv(msg_send):
msg_seri = x.serialize(msg_send, tyepdef=typedef, key_order=key_order)
assert_equal(x.deserialize(msg_seri)[0], msg_recv)
for y in msg_send_list:
do_send_recv(y)
def test_coerce(nested_approx):
r"""Test serialization of coerced types."""
from yggdrasil.metaschema.datatypes.JSONObjectMetaschemaType import (
JSONObjectMetaschemaType)
from yggdrasil import serialize
typedef = {
'type': 'object',
'properties': {
'a': {
'type': '1darray',
'subtype': 'float',
'title': 'a',
'precision': 64
}
}
}
x = JSONObjectMetaschemaType(**typedef)
key_order = ['a']
msg_recv = {'a': np.zeros(3, 'float64')}
msg_send_list = [{
'a': np.zeros(3, 'float32')
},
serialize.dict2numpy(msg_recv, order=key_order),
serialize.dict2pandas(msg_recv, order=key_order),
serialize.dict2list(msg_recv, order=key_order)]
def do_send_recv(msg_send):
msg_seri = x.serialize(msg_send, tyepdef=typedef, key_order=key_order)
assert (x.deserialize(msg_seri)[0] == nested_approx(msg_recv))
for y in msg_send_list:
do_send_recv(y)
def coerce_type(cls, obj, typedef=None, key_order=None, **kwargs):
r"""Coerce objects of specific types to match the data type.
Args:
obj (object): Object to be coerced.
typedef (dict, optional): Type defintion that object should be
coerced to. Defaults to None.
key_order (list, optional): Order that keys from a dictionary should
be used to compose an array. Defaults to None.
**kwargs: Additional keyword arguments are metadata entries that may
aid in coercing the type.
Returns:
object: Coerced object.
Raises:
RuntimeError: If obj is a dictionary, but key_order is not provided.
"""
from yggdrasil.serialize import pandas2list, numpy2list, dict2list
if isinstance(obj, pd.DataFrame):
obj = pandas2list(obj)
elif isinstance(obj, np.ndarray) and (len(obj.dtype) > 0):
obj = numpy2list(obj)
elif isinstance(obj, dict):
if (key_order is not None) or (len(obj) == 1):
obj = dict2list(obj, order=key_order)
else:
obj = [obj]
elif isinstance(typedef, dict) and (len(typedef.get('items', [])) == 1):
typedef_validated = kwargs.get('typedef_validated', False)
if cls.check_decoded([obj], typedef,
typedef_validated=typedef_validated):
obj = [obj]
return obj
def evaluate_transform(self, x, no_copy=False):
r"""Call transform on the provided message.
Args:
x (object): Message object to transform.
no_copy (bool, optional): If True, the transformation occurs in
place. Otherwise a copy is created and transformed. Defaults
to False.
Returns:
object: The transformed message.
"""
out = x
np_dtype = type2numpy(self.transformed_datatype)
if isinstance(x, pandas.DataFrame):
out = pandas2numpy(x).astype(np_dtype, copy=True)
elif isinstance(x, np.ndarray):
out = x.astype(np_dtype, copy=True)
elif np_dtype and isinstance(x, (list, tuple, dict, np.ndarray)):
if len(x) == 0:
out = np.zeros(0, np_dtype)
else:
if isinstance(x, dict):
x = dict2list(x, order=np_dtype.names)
out = consolidate_array(x, dtype=np_dtype)
else:
# warning?
raise TypeError(("Cannot consolidate object of type %s "
"into a structured numpy array.") % type(x))
if not no_copy:
out = copy.deepcopy(out)
return out
def test_dict2list():
r"""Test conversion of a dictionary to a list and back."""
assert_raises(TypeError, serialize.dict2list, None)
assert_raises(TypeError, serialize.list2dict, None)
x = {'c': 0, 'b': 1, 'a': 2}
y = [2, 1, 0]
assert_equal(serialize.dict2list(x), y)