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import json
from enum import IntEnum
import pytest
from pydantic_core import CoreConfig, SchemaSerializer, core_schema
try:
import numpy
except ImportError:
numpy = None
class IntSubClass(int):
pass
class MyIntEnum(IntEnum):
one = 1
two = 2
class FloatSubClass(float):
pass
# A number well outside of i64 range
_BIG_NUMBER_BYTES = b'1' + (b'0' * 40)
@pytest.mark.parametrize('custom_type_schema', [None, 'any'])
@pytest.mark.parametrize(
'schema_type,value,expected_python,expected_json',
[
('int', 1, 1, b'1'),
('int', int(_BIG_NUMBER_BYTES), int(_BIG_NUMBER_BYTES), _BIG_NUMBER_BYTES),
('bool', True, True, b'true'),
('bool', False, False, b'false'),
('float', 1.0, 1.0, b'1.0'),
('float', 42.31415, 42.31415, b'42.31415'),
('none', None, None, b'null'),
('int', IntSubClass(42), IntSubClass(42), b'42'),
('int', MyIntEnum.one, MyIntEnum.one, b'1'),
('float', FloatSubClass(42), FloatSubClass(42), b'42.0'),
],
)
def test_simple_serializers(schema_type, value, expected_python, expected_json, custom_type_schema):
if custom_type_schema is None:
schema = {'type': schema_type}
else:
schema = {'type': custom_type_schema}
s = SchemaSerializer(schema)
v = s.to_python(value)
assert v == expected_python
assert type(v) == type(expected_python)
assert s.to_json(value) == expected_json
v_json = s.to_python(value, mode='json')
v_json_expected = json.loads(expected_json)
assert v_json == v_json_expected
assert type(v_json) == type(v_json_expected)
def test_int_to_float():
"""
See https://github.com/pydantic/pydantic-core/pull/866
"""
s = SchemaSerializer(core_schema.float_schema())
v_plain = s.to_python(1)
assert v_plain == 1
assert type(v_plain) == int
v_plain_subclass = s.to_python(IntSubClass(1))
assert v_plain_subclass == IntSubClass(1)
assert type(v_plain_subclass) == IntSubClass
v_json = s.to_python(1, mode='json')
assert v_json == 1.0
assert type(v_json) == float
v_json_subclass = s.to_python(IntSubClass(1), mode='json')
assert v_json_subclass == 1
assert type(v_json_subclass) == float
assert s.to_json(1) == b'1.0'
assert s.to_json(IntSubClass(1)) == b'1.0'
def test_int_to_float_key():
"""
See https://github.com/pydantic/pydantic-core/pull/866
"""
s = SchemaSerializer(core_schema.dict_schema(core_schema.float_schema(), core_schema.float_schema()))
v_plain = s.to_python({1: 1})
assert v_plain == {1: 1}
assert type(list(v_plain.keys())[0]) == int
assert type(v_plain[1]) == int
v_json = s.to_python({1: 1}, mode='json')
assert v_json == {'1': 1.0}
assert type(v_json['1']) == float
assert s.to_json({1: 1}) == b'{"1":1.0}'
@pytest.mark.parametrize('schema_type', ['int', 'bool', 'float', 'none'])
def test_simple_serializers_fallback(schema_type):
s = SchemaSerializer({'type': schema_type})
with pytest.warns(
UserWarning,
match=rf'Expected `{schema_type}` - serialized value may not be as expected \[input_value=\[1, 2, 3\], input_type=list\]',
):
assert s.to_python([1, 2, 3]) == [1, 2, 3]
with pytest.warns(
UserWarning,
match=rf"Expected `{schema_type}` - serialized value may not be as expected \[input_value=\[1, 2, b'bytes'\], input_type=list\]",
):
assert s.to_python([1, 2, b'bytes'], mode='json') == [1, 2, 'bytes']
with pytest.warns(
UserWarning,
match=rf'Expected `{schema_type}` - serialized value may not be as expected \[input_value=\[1, 2, 3\], input_type=list\]',
):
assert s.to_json([1, 2, 3]) == b'[1,2,3]'
@pytest.mark.skipif(numpy is None, reason='numpy is not installed')
def test_numpy():
s = SchemaSerializer(core_schema.float_schema())
v = s.to_python(numpy.float64(1.0))
assert v == 1.0
assert type(v) == numpy.float64
v = s.to_python(numpy.float64(1.0), mode='json')
assert v == 1.0
assert type(v) == float
assert s.to_json(numpy.float64(1.0)) == b'1.0'
@pytest.mark.parametrize(
'value,expected_json,config',
[
# default values of ser_json_inf_nan
(float('inf'), 'null', {}),
(float('-inf'), 'null', {}),
(float('nan'), 'null', {}),
# explicit values of ser_json_inf_nan
(float('inf'), 'null', CoreConfig(ser_json_inf_nan='null')),
(float('-inf'), 'null', CoreConfig(ser_json_inf_nan='null')),
(float('nan'), 'null', CoreConfig(ser_json_inf_nan='null')),
(float('inf'), 'Infinity', CoreConfig(ser_json_inf_nan='constants')),
(float('-inf'), '-Infinity', CoreConfig(ser_json_inf_nan='constants')),
(float('nan'), 'NaN', CoreConfig(ser_json_inf_nan='constants')),
(float('inf'), '"Infinity"', CoreConfig(ser_json_inf_nan='strings')),
(float('-inf'), '"-Infinity"', CoreConfig(ser_json_inf_nan='strings')),
(float('nan'), '"NaN"', CoreConfig(ser_json_inf_nan='strings')),
],
)
def test_float_inf_and_nan_serializers(value, expected_json, config):
s = SchemaSerializer(core_schema.float_schema(), config)
# Python can represent these values without needing any changes
assert s.to_python(value) is value
assert s.to_python(value, mode='json') is value
# Serialized JSON value respects the ser_json_inf_nan setting
assert s.to_json(value).decode() == expected_json
|
