File size: 1,409 Bytes
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import json
from dataclasses import dataclass
import pytest
from pydantic import BaseModel
from aws_lambda_powertools.shared.json_encoder import Encoder
def test_jsonencode_decimal():
result = json.dumps({"val": decimal.Decimal("8.5")}, cls=Encoder)
assert result == '{"val": "8.5"}'
def test_jsonencode_decimal_nan():
result = json.dumps({"val": decimal.Decimal("NaN")}, cls=Encoder)
assert result == '{"val": NaN}'
def test_jsonencode_calls_default():
class CustomClass:
pass
with pytest.raises(TypeError):
json.dumps({"val": CustomClass()}, cls=Encoder)
def test_json_encode_pydantic():
# GIVEN a Pydantic model
class Model(BaseModel):
data: dict
data = {"msg": "hello"}
model = Model(data=data)
# WHEN json.dumps use our custom Encoder
result = json.dumps(model, cls=Encoder)
# THEN we should serialize successfully; not raise a TypeError
assert result == json.dumps({"data": data}, cls=Encoder)
def test_json_encode_dataclasses():
# GIVEN a standard dataclass
@dataclass
class Model:
data: dict
data = {"msg": "hello"}
model = Model(data=data)
# WHEN json.dumps use our custom Encoder
result = json.dumps(model, cls=Encoder)
# THEN we should serialize successfully; not raise a TypeError
assert result == json.dumps({"data": data}, cls=Encoder)
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