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121 lines
3.3 KiB
Python
121 lines
3.3 KiB
Python
import json
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from typing import Dict, List, Mapping, Union
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import pytest
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from pydantic import BaseModel, ValidationError
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from pydantic.dataclasses import dataclass
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from pydantic.tools import parse_file_as, parse_obj_as, parse_raw_as, schema_json_of, schema_of
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@pytest.mark.parametrize('obj,type_,parsed', [('1', int, 1), (['1'], List[int], [1])])
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def test_parse_obj(obj, type_, parsed):
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assert parse_obj_as(type_, obj) == parsed
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def test_parse_obj_as_model():
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class Model(BaseModel):
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x: int
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y: bool
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z: str
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model_inputs = {'x': '1', 'y': 'true', 'z': 'abc'}
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assert parse_obj_as(Model, model_inputs) == Model(**model_inputs)
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def test_parse_obj_preserves_subclasses():
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class ModelA(BaseModel):
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a: Mapping[int, str]
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class ModelB(ModelA):
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b: int
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model_b = ModelB(a={1: 'f'}, b=2)
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parsed = parse_obj_as(List[ModelA], [model_b])
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assert parsed == [model_b]
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def test_parse_obj_fails():
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with pytest.raises(ValidationError) as exc_info:
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parse_obj_as(int, 'a')
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assert exc_info.value.errors() == [
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{'loc': ('__root__',), 'msg': 'value is not a valid integer', 'type': 'type_error.integer'}
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]
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assert exc_info.value.model.__name__ == 'ParsingModel[int]'
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def test_parsing_model_naming():
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with pytest.raises(ValidationError) as exc_info:
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parse_obj_as(int, 'a')
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assert str(exc_info.value).split('\n')[0] == '1 validation error for ParsingModel[int]'
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with pytest.raises(ValidationError) as exc_info:
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parse_obj_as(int, 'a', type_name='ParsingModel')
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assert str(exc_info.value).split('\n')[0] == '1 validation error for ParsingModel'
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with pytest.raises(ValidationError) as exc_info:
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parse_obj_as(int, 'a', type_name=lambda type_: type_.__name__)
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assert str(exc_info.value).split('\n')[0] == '1 validation error for int'
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def test_parse_as_dataclass():
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@dataclass
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class PydanticDataclass:
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x: int
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inputs = {'x': '1'}
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assert parse_obj_as(PydanticDataclass, inputs) == PydanticDataclass(1)
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def test_parse_mapping_as():
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inputs = {'1': '2'}
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assert parse_obj_as(Dict[int, int], inputs) == {1: 2}
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def test_parse_file_as(tmp_path):
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p = tmp_path / 'test.json'
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p.write_text('{"1": "2"}')
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assert parse_file_as(Dict[int, int], p) == {1: 2}
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def test_parse_file_as_json_loads(tmp_path):
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def custom_json_loads(*args, **kwargs):
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data = json.loads(*args, **kwargs)
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data[1] = 99
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return data
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p = tmp_path / 'test_json_loads.json'
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p.write_text('{"1": "2"}')
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assert parse_file_as(Dict[int, int], p, json_loads=custom_json_loads) == {1: 99}
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def test_raw_as():
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class Item(BaseModel):
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id: int
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name: str
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item_data = '[{"id": 1, "name": "My Item"}]'
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items = parse_raw_as(List[Item], item_data)
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assert items == [Item(id=1, name='My Item')]
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def test_schema():
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assert schema_of(Union[int, str], title='IntOrStr') == {
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'title': 'IntOrStr',
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'anyOf': [{'type': 'integer'}, {'type': 'string'}],
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}
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assert schema_json_of(Union[int, str], title='IntOrStr', indent=2) == (
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'{\n'
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' "title": "IntOrStr",\n'
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' "anyOf": [\n'
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' {\n'
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' "type": "integer"\n'
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' },\n'
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' {\n'
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' "type": "string"\n'
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' }\n'
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' ]\n'
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'}'
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)
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