def test_map():
fk = Map(int32, Record([('a', int32)]))
assert fk.key == int32
assert fk.value == Record([('a', int32)])
assert fk.value.dict == {'a': int32}
assert fk.value.fields == (('a', int32), )
assert fk.to_numpy_dtype() == np.dtype('int32')
def test_unite_records():
assert (discover([{
'name': 'Alice',
'balance': 100
}, {
'name': 'Bob',
'balance': ''
}]) == 2 * Record([['balance', Option(int64)], ['name', string]]))
assert (discover([{
'name': 'Alice',
's': 'foo'
}, {
'name': 'Bob',
's': None
}]) == 2 * Record([['name', string], ['s', Option(string)]]))
assert (discover([{
'name': 'Alice',
's': 'foo',
'f': 1.0
}, {
'name': 'Bob',
's': None,
'f': None
}]) == 2 * Record([['f', Option(float64)], ['name', string],
['s', Option(string)]]))
def test_record():
assert_dshape_equal(
Record((('a', int32), ('b', float32))),
Record((('a', int32), ('b', float32))),
)
with pytest.raises(AssertionError) as e:
assert_dshape_equal(
Record((('a', int32), ('b', float32))),
Record((('a', int32), ('b', int32))),
)
assert "'float32' != 'int32'" in str(e)
assert "_['b'].name" in str(e.value)
with pytest.raises(AssertionError) as e:
assert_dshape_equal(
Record((('a', int32), ('b', float32))),
Record((('a', int32), ('c', float32))),
)
assert "'b' != 'c'" in str(e.value)
assert_dshape_equal(
Record((('b', float32), ('a', int32))),
Record((('a', int32), ('b', float32))),
check_record_order=False,
)
with pytest.raises(AssertionError) as e:
assert_dshape_equal(
Record((('b', float32), ('a', float32))),
Record((('a', int32), ('b', float32))),
check_record_order=False,
)
assert "'float32' != 'int32'" in str(e.value)
assert "_['a']" in str(e.value)
def test_map():
fk = Map(int32, Record([('a', int32)]))
assert fk.key == int32
assert fk.value == Record([('a', int32)])
assert fk.value.dict == {'a': int32}
assert fk.value.fields == (('a', int32), )
with pytest.raises(TypeError):
fk.to_numpy_dtype()
def test_unicode_record_names(names, typ):
types = [int64, float64]
record = Record(list(zip(names, types)))
string_type, = set(map(type, record.names))
assert record.names == names
assert record.types == types
assert all(isinstance(s, string_type) for s in record.names)
def test_launder_raises():
with pytest.raises(TypeError) as exc:
Record([('y', int)])
returned_err = str(exc)
# Py 2/3 differences mean that 2 will error with <type 'int'> and 3 will
# error with <class 'int'>
assert "Received unsupported type" in returned_err
assert "int" in returned_err
def build_datashape(sample_data):
""" Build a datashape from sample_data
In case of multiple dimensions, the firt is replace by 'var' to
handle varing time samples in models
"""
if isinstance(sample_data, collections.Mapping):
return Record((k,build_datashape(v)) for k,v in sample_data.items() )
else:
ds = discover(sample_data)
if len(ds) > 1:
ds = var * ds.subarray(1)
else:
ds = Option( ds )
return ds
def c():
return Record([('y', '?int'), ('x', '?int')])
def test_record_with_unicode_name_as_numpy_dtype():
r = Record([(unicode('a'), 'int32')])
assert r.to_numpy_dtype() == np.dtype([('a', 'i4')])
def test_strings(self):
self.assertEqual(Record([('x', 'real')]), Record([('x', real)]))
def test_map_parse():
result = dshape("var * {b: map[int32, {a: int64}]}")
recmeasure = Map(dshape(int32), DataShape(Record([('a', int64)])))
assert result == DataShape(var, Record([('b', recmeasure)]))
def test_strings():
assert Record([('x', 'real')]) == Record([('x', real)])
def test_record_from_OrderedDict():
r = Record(OrderedDict([("a", "int32"), ("b", "float64")]))
assert r.to_numpy_dtype() == np.dtype([("a", "i4"), ("b", "f8")])
def test_record_with_unicode_name_as_numpy_dtype():
r = Record([(unicode("a"), "int32")])
assert r.to_numpy_dtype() == np.dtype([("a", "i4")])
def test_slice_subshape_negative_start():
ds = var * Record([('a', 'int32')])
assert ds.subshape[-1:] == var * Record([('a', 'int32')])
def test_slice_subshape_bad_types():
ds = var * Record([('a', 'int32')])
with pytest.raises(TypeError):
assert ds.subshape[1.0]
with pytest.raises(TypeError):
assert ds.subshape[1.0]
@pytest.mark.parametrize(
['base', 'expected'],
zip([timedelta_, date_, datetime_],
['timedelta64[us]', 'datetime64[D]', 'datetime64[us]']))
def test_option_to_numpy_dtype(base, expected):
assert Option(base).to_numpy_dtype() == np.dtype(expected)
@pytest.mark.xfail(raises=TypeError,
reason=('NumPy has no notion of missing for types other '
'than timedelta, datetime, and date'))
@pytest.mark.parametrize('base', [int32, float64, Record([('a', uint32)])])
def test_option_to_numpy_dtype_fails(base):
Option(base).to_numpy_dtype()
@pytest.mark.xfail(raises=NotImplementedError,
reason='DataShape does not know about void types (yet?)')
def test_from_numpy_dtype_fails():
x = np.zeros(2, np.dtype([('a', 'int32')]))
CType.from_numpy_dtype(x[0].dtype)
def test_ctype_alignment():
assert int32.alignment == 4
def test_funcproto_attrs():
f = dshape('(int32, ?float64) -> {a: ?string}').measure
assert f.restype == DataShape(Record([('a', Option(String()))]))
assert f.argtypes == (DataShape(int32), DataShape(Option(float64)))
def test_record_with_unicode_name_as_numpy_dtype():
r = Record([(unicode('a'), 'int32')])
assert r.to_numpy_dtype() == np.dtype([('a', 'i4')])
def test_integers():
assert Record([(0, 'real')]) == Record([('0', real)])
def test_record_from_OrderedDict():
r = Record(OrderedDict([('a', 'int32'), ('b', 'float64')]))
assert r.to_numpy_dtype() == np.dtype([('a', 'i4'), ('b', 'f8')])
def test_duplicate_field_names_fails():
fields = [('a', 'int32'), ('b', 'string'), ('a', 'float32')]
with pytest.raises(ValueError):
Record(fields)
def b():
return Record([('y', int), ('x', int)])
def setUp(self):
self.a = Record([('x', int), ('y', int)])
self.b = Record([('y', int), ('x', int)])
def test_record_subshape_integer_index():
ds = DataShape(Record([('a', 'int32')]))
assert ds.subshape[0] == int32
def test_record():
assert (discover({'name': 'Alice', 'amount': 100}) ==
Record([['amount', discover(100)],
['name', discover('Alice')]]))
def test_slice_subshape_negative_step():
ds = 30 * Record([('a', 'int32')])
assert ds.subshape[:-1] == 29 * Record([('a', 'int32')])
def test_record_from_OrderedDict():
r = Record(OrderedDict([('a', 'int32'), ('b', 'float64')]))
assert r.to_numpy_dtype() == np.dtype([('a', 'i4'), ('b', 'f8')])
def b():
return Record([('y', 'int'), ('x', 'int')])
