refactor: updated OpenMLEvaluation to use dataclass decarotor

[rohansen856]

I have Refactored the OpenMLEvaluation class from a traditional Python class to use the @dataclass decorator to reduce boilerplate code and improve code maintainability.

Metadata

• Reference Issue: [ENH] Refactor OpenMLEvaluation to Use Dataclass #1540
• New Tests Added: No
• Documentation Updated: No
• Change Log Entry: Refactored the OpenMLEvaluation class to use the @dataclass

Details

Edited the OpenMLEvaluation class in openml\evaluations\evaluation.py to use @dataclass decorator. This significantly reduces the boilerplate code in the following places:

• Instance Variable Definitions

Before:

def __init__(
    self,
    run_id: int,
    task_id: int,
    setup_id: int,
    flow_id: int,
    flow_name: str,
    data_id: int,
    data_name: str,
    function: str,
    upload_time: str,
    uploader: int,
    uploader_name: str,
    value: float | None,
    values: list[float] | None,
    array_data: str | None = None,
):
    self.run_id = run_id
    self.task_id = task_id
    self.setup_id = setup_id
    self.flow_id = flow_id
    self.flow_name = flow_name
    self.data_id = data_id
    self.data_name = data_name
    self.function = function
    self.upload_time = upload_time
    self.uploader = uploader
    self.uploader_name = uploader_name
    self.value = value
    self.values = values
    self.array_data = array_data

After:

run_id: int
task_id: int
setup_id: int
flow_id: int
flow_name: str
data_id: int
data_name: str
function: str
upload_time: str
uploader: int
uploader_name: str
value: float | None
values: list[float] | None
array_data: str | None = None

• _to_dict Method Simplification

Before:

def _to_dict(self) -> dict:
    return {
        "run_id": self.run_id,
        "task_id": self.task_id,
        "setup_id": self.setup_id,
        "flow_id": self.flow_id,
        "flow_name": self.flow_name,
        "data_id": self.data_id,
        "data_name": self.data_name,
        "function": self.function,
        "upload_time": self.upload_time,
        "uploader": self.uploader,
        "uploader_name": self.uploader_name,
        "value": self.value,
        "values": self.values,
        "array_data": self.array_data,
    }

After:

def _to_dict(self) -> dict:
    return asdict(self)

All tests are passing with accordnce to the changes:

PS C:\Users\ASUS\Documents\work\opensource\openml-python> pytest tests/test_evaluations/
======================================= test session starts =======================================
platform win32 -- Python 3.14.0, pytest-9.0.2, pluggy-1.6.0
rootdir: C:\Users\ASUS\Documents\work\opensource\openml-python
configfile: pyproject.toml
plugins: anyio-4.12.0, flaky-3.8.1, asyncio-1.3.0, cov-7.0.0, mock-3.15.1, rerunfailures-16.1, timeout-2.4.0, xdist-3.8.0, requests-mock-1.12.1
asyncio: mode=Mode.STRICT, debug=False, asyncio_default_fixture_loop_scope=None, asyncio_default_test_loop_scope=function
collected 13 items                                                                                 

tests\test_evaluations\test_evaluation_functions.py ............                             [ 92%]
tests\test_evaluations\test_evaluations_example.py .                                         [100%]

================================= 13 passed in 274.80s (0:04:34) ==================================