from datetime import date, datetime from typing import List from unittest.mock import Mock import pytest from pydantic import BaseModel from crewai.flow import Flow from crewai.flow.state_utils import export_state, to_string class Address(BaseModel): street: str city: str country: str class Person(BaseModel): name: str age: int address: Address birthday: date skills: List[str] @pytest.fixture def mock_flow(): def create_flow(state): flow = Mock(spec=Flow) flow._state = state return flow return create_flow @pytest.mark.parametrize( "test_input,expected", [ ({"text": "hello world"}, {"text": "hello world"}), ({"number": 42}, {"number": 42}), ({"decimal": 3.14}, {"decimal": 3.14}), ({"flag": True}, {"flag": True}), ({"empty": None}, {"empty": None}), ({"list": [1, 2, 3]}, {"list": [1, 2, 3]}), ({"tuple": (1, 2, 3)}, {"tuple": [1, 2, 3]}), ({"set": {1, 2, 3}}, {"set": [1, 2, 3]}), ({"nested": [1, [2, 3], {4, 5}]}, {"nested": [1, [2, 3], [4, 5]]}), ], ) def test_basic_serialization(mock_flow, test_input, expected): flow = mock_flow(test_input) result = export_state(flow) assert result == expected @pytest.mark.parametrize( "input_date,expected", [ (date(2024, 1, 1), "2024-01-01"), (datetime(2024, 1, 1, 12, 30), "2024-01-01T12:30:00"), ], ) def test_temporal_serialization(mock_flow, input_date, expected): flow = mock_flow({"date": input_date}) result = export_state(flow) assert result["date"] == expected @pytest.mark.parametrize( "key,value,expected_key_type", [ (("tuple", "key"), "value", str), (None, "value", str), (123, "value", str), ("normal", "value", str), ], ) def test_dictionary_key_serialization(mock_flow, key, value, expected_key_type): flow = mock_flow({key: value}) result = export_state(flow) assert len(result) == 1 result_key = next(iter(result.keys())) assert isinstance(result_key, expected_key_type) assert result[result_key] == value @pytest.mark.parametrize( "callable_obj,expected_in_result", [ (lambda x: x * 2, "lambda"), (str.upper, "upper"), ], ) def test_callable_serialization(mock_flow, callable_obj, expected_in_result): flow = mock_flow({"func": callable_obj}) result = export_state(flow) assert isinstance(result["func"], str) assert expected_in_result in result["func"].lower() def test_pydantic_model_serialization(mock_flow): address = Address(street="123 Main St", city="Tech City", country="Pythonia") person = Person( name="John Doe", age=30, address=address, birthday=date(1994, 1, 1), skills=["Python", "Testing"], ) flow = mock_flow( { "single_model": address, "nested_model": person, "model_list": [address, address], "model_dict": {"home": address}, } ) result = export_state(flow) assert ( to_string(result) == '{"single_model": {"street": "123 Main St", "city": "Tech City", "country": "Pythonia"}, "nested_model": {"name": "John Doe", "age": 30, "address": {"street": "123 Main St", "city": "Tech City", "country": "Pythonia"}, "birthday": "1994-01-01", "skills": ["Python", "Testing"]}, "model_list": [{"street": "123 Main St", "city": "Tech City", "country": "Pythonia"}, {"street": "123 Main St", "city": "Tech City", "country": "Pythonia"}], "model_dict": {"home": {"street": "123 Main St", "city": "Tech City", "country": "Pythonia"}}}' ) def test_depth_limit(mock_flow): """Test max depth handling with a deeply nested structure""" def create_nested(depth): if depth == 0: return "value" return {"next": create_nested(depth - 1)} deep_structure = create_nested(10) flow = mock_flow(deep_structure) result = export_state(flow) assert result == { "next": { "next": { "next": { "next": { "next": "{'next': {'next': {'next': {'next': {'next': 'value'}}}}}" } } } } }