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Feat/improve yaml extraction (#2428)
* Support wildcard handling in `emit()` Change `emit()` to call handlers registered for parent classes using `isinstance()`. Ensures that base event handlers receive derived events. * Fix failing test * Remove unused variable * update interpolation to work with example response types in yaml docs * make tests * fix circular deps * Fixing interpolation imports * Improve test --------- Co-authored-by: Vinicius Brasil <vini@hey.com> Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com>
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@@ -15,6 +15,7 @@ from crewai import Agent, Crew, Process, Task
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from crewai.tasks.conditional_task import ConditionalTask
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from crewai.tasks.task_output import TaskOutput
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from crewai.utilities.converter import Converter
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from crewai.utilities.string_utils import interpolate_only
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def test_task_tool_reflect_agent_tools():
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@@ -822,7 +823,7 @@ def test_interpolate_only():
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# Test JSON structure preservation
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json_string = '{"info": "Look at {placeholder}", "nested": {"val": "{nestedVal}"}}'
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result = task.interpolate_only(
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result = interpolate_only(
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input_string=json_string,
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inputs={"placeholder": "the data", "nestedVal": "something else"},
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)
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@@ -833,20 +834,18 @@ def test_interpolate_only():
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# Test normal string interpolation
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normal_string = "Hello {name}, welcome to {place}!"
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result = task.interpolate_only(
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result = interpolate_only(
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input_string=normal_string, inputs={"name": "John", "place": "CrewAI"}
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)
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assert result == "Hello John, welcome to CrewAI!"
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# Test empty string
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result = task.interpolate_only(input_string="", inputs={"unused": "value"})
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result = interpolate_only(input_string="", inputs={"unused": "value"})
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assert result == ""
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# Test string with no placeholders
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no_placeholders = "Hello, this is a test"
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result = task.interpolate_only(
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input_string=no_placeholders, inputs={"unused": "value"}
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)
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result = interpolate_only(input_string=no_placeholders, inputs={"unused": "value"})
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assert result == no_placeholders
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@@ -858,7 +857,7 @@ def test_interpolate_only_with_dict_inside_expected_output():
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)
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json_string = '{"questions": {"main_question": "What is the user\'s name?", "secondary_question": "What is the user\'s age?"}}'
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result = task.interpolate_only(
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result = interpolate_only(
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input_string=json_string,
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inputs={
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"questions": {
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@@ -872,18 +871,16 @@ def test_interpolate_only_with_dict_inside_expected_output():
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assert result == json_string
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normal_string = "Hello {name}, welcome to {place}!"
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result = task.interpolate_only(
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result = interpolate_only(
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input_string=normal_string, inputs={"name": "John", "place": "CrewAI"}
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)
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assert result == "Hello John, welcome to CrewAI!"
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result = task.interpolate_only(input_string="", inputs={"unused": "value"})
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result = interpolate_only(input_string="", inputs={"unused": "value"})
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assert result == ""
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no_placeholders = "Hello, this is a test"
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result = task.interpolate_only(
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input_string=no_placeholders, inputs={"unused": "value"}
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)
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result = interpolate_only(input_string=no_placeholders, inputs={"unused": "value"})
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assert result == no_placeholders
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@@ -1085,12 +1082,12 @@ def test_interpolate_with_list_of_strings():
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# Test simple list of strings
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input_str = "Available items: {items}"
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inputs = {"items": ["apple", "banana", "cherry"]}
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result = task.interpolate_only(input_str, inputs)
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result = interpolate_only(input_str, inputs)
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assert result == f"Available items: {inputs['items']}"
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# Test empty list
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empty_list_input = {"items": []}
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result = task.interpolate_only(input_str, empty_list_input)
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result = interpolate_only(input_str, empty_list_input)
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assert result == "Available items: []"
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@@ -1106,7 +1103,7 @@ def test_interpolate_with_list_of_dicts():
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{"name": "Bob", "age": 25, "skills": ["Java", "Cloud"]},
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]
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}
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result = task.interpolate_only("{people}", input_data)
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result = interpolate_only("{people}", input_data)
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parsed_result = eval(result)
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assert isinstance(parsed_result, list)
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@@ -1138,7 +1135,7 @@ def test_interpolate_with_nested_structures():
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],
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}
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}
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result = task.interpolate_only("{company}", input_data)
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result = interpolate_only("{company}", input_data)
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parsed = eval(result)
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assert parsed["name"] == "TechCorp"
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@@ -1161,7 +1158,7 @@ def test_interpolate_with_special_characters():
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"empty": "",
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}
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}
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result = task.interpolate_only("{special_data}", input_data)
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result = interpolate_only("{special_data}", input_data)
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parsed = eval(result)
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assert parsed["quotes"] == """This has "double" and 'single' quotes"""
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@@ -1188,7 +1185,7 @@ def test_interpolate_mixed_types():
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},
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}
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}
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result = task.interpolate_only("{data}", input_data)
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result = interpolate_only("{data}", input_data)
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parsed = eval(result)
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assert parsed["name"] == "Test Dataset"
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@@ -1216,7 +1213,7 @@ def test_interpolate_complex_combination():
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},
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]
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}
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result = task.interpolate_only("{report}", input_data)
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result = interpolate_only("{report}", input_data)
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parsed = eval(result)
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assert len(parsed) == 2
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@@ -1233,7 +1230,7 @@ def test_interpolate_invalid_type_validation():
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# Test with invalid top-level type
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with pytest.raises(ValueError) as excinfo:
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task.interpolate_only("{data}", {"data": set()}) # type: ignore we are purposely testing this failure
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interpolate_only("{data}", {"data": set()}) # type: ignore we are purposely testing this failure
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assert "Unsupported type set" in str(excinfo.value)
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@@ -1246,7 +1243,7 @@ def test_interpolate_invalid_type_validation():
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}
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}
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with pytest.raises(ValueError) as excinfo:
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task.interpolate_only("{data}", {"data": invalid_nested})
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interpolate_only("{data}", {"data": invalid_nested})
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assert "Unsupported type set" in str(excinfo.value)
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@@ -1265,24 +1262,22 @@ def test_interpolate_custom_object_validation():
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# Test with custom object at top level
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with pytest.raises(ValueError) as excinfo:
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task.interpolate_only("{obj}", {"obj": CustomObject(5)}) # type: ignore we are purposely testing this failure
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interpolate_only("{obj}", {"obj": CustomObject(5)}) # type: ignore we are purposely testing this failure
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assert "Unsupported type CustomObject" in str(excinfo.value)
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# Test with nested custom object in dictionary
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with pytest.raises(ValueError) as excinfo:
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task.interpolate_only(
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"{data}", {"data": {"valid": 1, "invalid": CustomObject(5)}}
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)
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interpolate_only("{data}", {"data": {"valid": 1, "invalid": CustomObject(5)}})
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assert "Unsupported type CustomObject" in str(excinfo.value)
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# Test with nested custom object in list
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with pytest.raises(ValueError) as excinfo:
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task.interpolate_only("{data}", {"data": [1, "valid", CustomObject(5)]})
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interpolate_only("{data}", {"data": [1, "valid", CustomObject(5)]})
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assert "Unsupported type CustomObject" in str(excinfo.value)
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# Test with deeply nested custom object
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with pytest.raises(ValueError) as excinfo:
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task.interpolate_only(
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interpolate_only(
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"{data}", {"data": {"level1": {"level2": [{"level3": CustomObject(5)}]}}}
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)
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assert "Unsupported type CustomObject" in str(excinfo.value)
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@@ -1306,7 +1301,7 @@ def test_interpolate_valid_complex_types():
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}
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# Should not raise any errors
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result = task.interpolate_only("{data}", {"data": valid_data})
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result = interpolate_only("{data}", {"data": valid_data})
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parsed = eval(result)
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assert parsed["name"] == "Valid Dataset"
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assert parsed["stats"]["nested"]["deeper"]["b"] == 2.5
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@@ -1319,16 +1314,16 @@ def test_interpolate_edge_cases():
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)
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# Test empty dict and list
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assert task.interpolate_only("{}", {"data": {}}) == "{}"
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assert task.interpolate_only("[]", {"data": []}) == "[]"
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assert interpolate_only("{}", {"data": {}}) == "{}"
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assert interpolate_only("[]", {"data": []}) == "[]"
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# Test numeric types
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assert task.interpolate_only("{num}", {"num": 42}) == "42"
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assert task.interpolate_only("{num}", {"num": 3.14}) == "3.14"
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assert interpolate_only("{num}", {"num": 42}) == "42"
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assert interpolate_only("{num}", {"num": 3.14}) == "3.14"
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# Test boolean values (valid JSON types)
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assert task.interpolate_only("{flag}", {"flag": True}) == "True"
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assert task.interpolate_only("{flag}", {"flag": False}) == "False"
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assert interpolate_only("{flag}", {"flag": True}) == "True"
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assert interpolate_only("{flag}", {"flag": False}) == "False"
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def test_interpolate_valid_types():
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@@ -1346,7 +1341,7 @@ def test_interpolate_valid_types():
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"nested": {"flag": True, "empty": None},
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}
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result = task.interpolate_only("{data}", {"data": valid_data})
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result = interpolate_only("{data}", {"data": valid_data})
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parsed = eval(result)
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assert parsed["active"] is True
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