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"""
Tests for L{eliot.json}.
"""
from unittest import TestCase, skipUnless, skipIf
from json import loads
try:
import numpy as np
except ImportError:
np = None
from eliot.json import (
EliotJSONEncoder,
json_default,
_encoder_to_default_function,
_dumps_unicode as dumps,
)
class EliotJSONEncoderTests(TestCase):
"""Tests for L{EliotJSONEncoder} and L{json_default}."""
@skipUnless(np, "NumPy not installed.")
def test_numpy(self):
"""NumPy objects get serialized to readable JSON."""
encoder_default = _encoder_to_default_function(EliotJSONEncoder())
l = [
np.float32(12.5),
np.float64(2.0),
np.float16(0.5),
np.bool_(True),
np.str_("hello"),
np.byte(12),
np.short(12),
np.intc(-13),
np.int_(0),
np.longlong(100),
np.intp(7),
np.ubyte(12),
np.ushort(12),
np.uintc(13),
np.ulonglong(100),
np.uintp(7),
np.int8(1),
np.int16(3),
np.int32(4),
np.int64(5),
np.uint8(1),
np.uint16(3),
np.uint32(4),
np.uint64(5),
]
l2 = [l, np.array([1, 2, 3])]
roundtripped = loads(dumps(l2, default=encoder_default))
self.assertEqual([l, [1, 2, 3]], roundtripped)
roundtripped2 = loads(dumps(l2, default=json_default))
self.assertEqual([l, [1, 2, 3]], roundtripped2)
@skipIf(np, "NumPy is installed.")
def test_numpy_not_imported(self):
"""If NumPy is not available, C{json_default} continues to work.
This ensures NumPy isn't a hard dependency.
"""
with self.assertRaises(TypeError):
dumps([object()], default=json_default)
self.assertEqual(dumps(12, default=json_default), "12")
@skipUnless(np, "NumPy is not installed.")
def test_large_numpy_array(self):
"""
Large NumPy arrays are not serialized completely, since this is (A) a
performance hit (B) probably a mistake on the user's part.
"""
a1000 = np.array([0] * 10000)
self.assertEqual(loads(dumps(a1000, default=json_default)), a1000.tolist())
a1002 = np.zeros((2, 5001))
a1002[0][0] = 12
a1002[0][1] = 13
a1002[1][1] = 500
self.assertEqual(
loads(dumps(a1002, default=json_default)),
{"array_start": a1002.flat[:10000].tolist(), "original_shape": [2, 5001]},
)
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