|
| 1 | +import unittest |
| 2 | +import numpy as np |
| 3 | +import types |
| 4 | +import dcp |
| 5 | + |
| 6 | +dcp.init() |
| 7 | +from dcp.api import job_serializers as js |
| 8 | + |
| 9 | +def helper_shallow_cmp(self, left, right): |
| 10 | + """Best effort to compare two values shallowly.""" |
| 11 | + self.assertIsInstance(left, type(right)) |
| 12 | + |
| 13 | + if isinstance(left, (list, tuple)): |
| 14 | + self.assertEqual(list(left), list(right)) |
| 15 | + |
| 16 | + elif isinstance(left, set): |
| 17 | + self.assertEqual(left, right) |
| 18 | + |
| 19 | + elif isinstance(left, dict): |
| 20 | + self.assertEqual(set(left.keys()), set(right.keys())) |
| 21 | + self.assertEqual(set(left.values()), set(right.values())) |
| 22 | + |
| 23 | + elif isinstance(left, (bytes, bytearray)): |
| 24 | + self.assertEqual(bytes(left), bytes(right)) |
| 25 | + |
| 26 | + elif isinstance(left, types.LambdaType): |
| 27 | + self.assertEqual(left.__code__.co_code, right.__code__.co_code) |
| 28 | + |
| 29 | + elif isinstance(left, np.ndarray): |
| 30 | + # Compare numpy arrays: check shape, dtype, and content |
| 31 | + self.assertEqual(left.shape, right.shape) |
| 32 | + self.assertEqual(left.dtype, right.dtype) |
| 33 | + self.assertTrue(np.array_equal(left, right), "Numpy arrays are not equal") |
| 34 | + |
| 35 | + else: |
| 36 | + self.assertEqual(left, right) |
| 37 | + |
| 38 | + |
| 39 | +class TestJobSerializers(unittest.TestCase): |
| 40 | + def test_default_serialize_and_deserialize_basic(self): |
| 41 | + job = dcp.compute_for([], '') |
| 42 | + |
| 43 | + values = [ |
| 44 | + 123, |
| 45 | + 3.14, |
| 46 | + 'some string', |
| 47 | + True, |
| 48 | + False, |
| 49 | + 1 + 2j, |
| 50 | + [1,2,3], |
| 51 | + (1,2,3), |
| 52 | + {1,2,3 }, |
| 53 | + { 'key': 'value' }, |
| 54 | + b'some bytes', |
| 55 | + bytearray('some bytes in a bytearray', 'utf-8'), |
| 56 | + lambda x: x, |
| 57 | + None, |
| 58 | + ] |
| 59 | + |
| 60 | + serialized_vals = [] |
| 61 | + for val in values: |
| 62 | + serialized_vals.append(js.serialize(val, job.serializers)) |
| 63 | + |
| 64 | + des_vals = [] |
| 65 | + for val in serialized_vals: |
| 66 | + des_vals.append(js.deserialize(val, job.serializers)) |
| 67 | + |
| 68 | + for i in range(len(values)): |
| 69 | + helper_shallow_cmp(self, values[i], des_vals[i]) |
| 70 | + |
| 71 | + def test_default_serialize_and_deserialize_numpy_array(self): |
| 72 | + job = dcp.compute_for([], '') |
| 73 | + |
| 74 | + values = [ |
| 75 | + np.array([]), |
| 76 | + np.array([1, 2, 3, 4]), |
| 77 | + np.array([[1, 2], [3, 4]]), |
| 78 | + np.array([[[1], [2]], [[3], [4]]]), |
| 79 | + np.array([1.1, 2.2, 3.3], dtype=np.float64), |
| 80 | + np.array([True, False, True], dtype=np.bool_), |
| 81 | + np.array([(1, 2), (3, 4)], dtype=[('x', 'i4'), ('y', 'i4')]), |
| 82 | + np.ma.array([1, 2, 3], mask=[False, True, False]), |
| 83 | + np.array([1, 2, 3, 4])[1:3], |
| 84 | + np.random.rand(2, 3, 4), |
| 85 | + np.array([1 + 1j, 2 + 2j], dtype=np.complex128), |
| 86 | + |
| 87 | + np.arange(10), |
| 88 | + np.linspace(0, 1, 5), |
| 89 | + np.random.randint(0, 10, (2, 2)), |
| 90 | + np.random.normal(size=(2, 2)), |
| 91 | + np.zeros((2, 2)), |
| 92 | + np.ones((3, 3)), |
| 93 | + np.eye(3), |
| 94 | + np.recarray((2,), dtype=[('col1', 'int32'), ('col2', 'float32')]), |
| 95 | + ] |
| 96 | + |
| 97 | + serialized_vals = [] |
| 98 | + for val in values: |
| 99 | + serialized_vals.append(js.serialize(val, job.serializers)) |
| 100 | + |
| 101 | + des_vals = [] |
| 102 | + for val in serialized_vals: |
| 103 | + des_vals.append(js.deserialize(val, job.serializers)) |
| 104 | + |
| 105 | + |
| 106 | + for i in range(len(values)): |
| 107 | + helper_shallow_cmp(self, values[i], des_vals[i]) |
| 108 | + |
| 109 | +if __name__ == '__main__': |
| 110 | + unittest.main() |
| 111 | + |
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