Require real openai dependency in dataset preparation tests

Author: benjibc

tests/pytest/test_dataset_preparation.py

@@ -1,166 +1,8 @@
-import sys
-import types
-from pathlib import Path
 from typing import cast
 
 import pytest
 
-# The evaluation modules depend on optional third-party packages that aren't
-# available in the execution environment for these unit tests. To exercise the
-# real implementation of ``load_and_prepare_rows`` without installing those
-# packages, we register lightweight stubs in ``sys.modules`` that provide the
-# minimal interfaces required during import.
-
-PACKAGE_ROOT = Path(__file__).resolve().parents[2] / "eval_protocol"
-sys.modules.pop("eval_protocol", None)
-sys.modules.pop("eval_protocol.pytest", None)
-
-eval_protocol_pkg = types.ModuleType("eval_protocol")
-eval_protocol_pkg.__path__ = [str(PACKAGE_ROOT)]  # type: ignore[attr-defined]
-sys.modules["eval_protocol"] = eval_protocol_pkg
-
-pytest_pkg = types.ModuleType("eval_protocol.pytest")
-pytest_pkg.__path__ = [str(PACKAGE_ROOT / "pytest")]  # type: ignore[attr-defined]
-sys.modules["eval_protocol.pytest"] = pytest_pkg
-setattr(eval_protocol_pkg, "pytest", pytest_pkg)
-
-if "loguru" not in sys.modules:
-    loguru_module = types.ModuleType("loguru")
-
-    class _DummyLogger:
-        def __getattr__(self, _name):  # pragma: no cover - dynamic fallback
-            def _noop(*_args, **_kwargs):
-                return None
-
-            return _noop
-
-    loguru_module.logger = _DummyLogger()  # type: ignore[attr-defined]
-    sys.modules["loguru"] = loguru_module
-
-if "toml" not in sys.modules:
-    toml_module = types.ModuleType("toml")
-
-    def _noop_load(*_args, **_kwargs):  # pragma: no cover - helper for stubbing
-        return {}
-
-    def _noop_dump(*_args, **_kwargs):  # pragma: no cover - helper for stubbing
-        return None
-
-    toml_module.load = _noop_load  # type: ignore[attr-defined]
-    toml_module.dump = _noop_dump  # type: ignore[attr-defined]
-    sys.modules["toml"] = toml_module
-
-if "addict" not in sys.modules:
-    addict_module = types.ModuleType("addict")
-
-    class _AddictDict(dict):  # pragma: no cover - simple stub
-        def __getattr__(self, item):
-            try:
-                return self[item]
-            except KeyError as exc:
-                raise AttributeError(item) from exc
-
-        def __setattr__(self, key, value):
-            self[key] = value
-
-    addict_module.Dict = _AddictDict  # type: ignore[attr-defined]
-    sys.modules["addict"] = addict_module
-
-if "eval_protocol.mcp_env" not in sys.modules:
-    mcp_env_module = types.ModuleType("eval_protocol.mcp_env")
-
-    class _DummyPolicy:  # pragma: no cover - stub placeholder
-        pass
-
-    def _noop(*_args, **_kwargs):
-        return None
-
-    mcp_env_module.AnthropicPolicy = _DummyPolicy  # type: ignore[attr-defined]
-    mcp_env_module.FireworksPolicy = _DummyPolicy  # type: ignore[attr-defined]
-    mcp_env_module.LiteLLMPolicy = _DummyPolicy  # type: ignore[attr-defined]
-    mcp_env_module.OpenAIPolicy = _DummyPolicy  # type: ignore[attr-defined]
-    mcp_env_module.make = _noop  # type: ignore[attr-defined]
-    mcp_env_module.rollout = _noop  # type: ignore[attr-defined]
-    mcp_env_module.test_mcp = _noop  # type: ignore[attr-defined]
-    sys.modules["eval_protocol.mcp_env"] = mcp_env_module
-
-if "eval_protocol.mcp" not in sys.modules:
-    sys.modules["eval_protocol.mcp"] = types.ModuleType("eval_protocol.mcp")
-
-if "eval_protocol.rewards" not in sys.modules:
-    sys.modules["eval_protocol.rewards"] = types.ModuleType("eval_protocol.rewards")
-
-if "eval_protocol.dataset_logger" not in sys.modules:
-    dataset_logger_module = types.ModuleType("eval_protocol.dataset_logger")
-
-    class _StubDatasetLogger:  # pragma: no cover - stub placeholder
-        def log(self, *_args, **_kwargs):
-            return None
-
-    dataset_logger_module.default_logger = _StubDatasetLogger()  # type: ignore[attr-defined]
-    sys.modules["eval_protocol.dataset_logger"] = dataset_logger_module
-
-if "eval_protocol.dataset_logger.dataset_logger" not in sys.modules:
-    dataset_logger_pkg = types.ModuleType("eval_protocol.dataset_logger.dataset_logger")
-    dataset_logger_pkg.DatasetLogger = _StubDatasetLogger  # type: ignore[attr-defined]
-    sys.modules["eval_protocol.dataset_logger.dataset_logger"] = dataset_logger_pkg
-
-if "backoff" not in sys.modules:
-    backoff_module = types.ModuleType("backoff")
-
-    def _noop_decorator(*_args, **_kwargs):
-        def _decorator(func):
-            return func
-
-        return _decorator
-
-    backoff_module.on_exception = _noop_decorator  # type: ignore[attr-defined]
-    backoff_module.expo = lambda *args, **kwargs: None  # type: ignore[attr-defined]
-    sys.modules["backoff"] = backoff_module
-
-if "litellm" not in sys.modules:
-    litellm_module = types.ModuleType("litellm")
-    cost_calculator_module = types.ModuleType("litellm.cost_calculator")
-    cost_calculator_module.cost_per_token = lambda *args, **kwargs: 0.0  # type: ignore[attr-defined]
-    sys.modules["litellm"] = litellm_module
-    sys.modules["litellm.cost_calculator"] = cost_calculator_module
-
-if "tqdm" not in sys.modules:
-    tqdm_module = types.ModuleType("tqdm")
-
-    def _noop_tqdm(iterable=None, **_kwargs):
-        return iterable if iterable is not None else []
-
-    tqdm_module.tqdm = _noop_tqdm  # type: ignore[attr-defined]
-    sys.modules["tqdm"] = tqdm_module
-
-if "openai" not in sys.modules:
-    openai_module = types.ModuleType("openai")
-    openai_types_module = types.ModuleType("openai.types")
-    openai_chat_module = types.ModuleType("openai.types.chat")
-    openai_chat_completion_module = types.ModuleType("openai.types.chat.chat_completion_message")
-    openai_chat_tool_module = types.ModuleType("openai.types.chat.chat_completion_message_tool_call")
-
-    class _NotGiven:  # pragma: no cover - stub placeholder
-        pass
-
-    openai_module.NOT_GIVEN = _NotGiven()  # type: ignore[attr-defined]
-    openai_module.NotGiven = _NotGiven  # type: ignore[attr-defined]
-
-    openai_types_module.CompletionUsage = object  # type: ignore[attr-defined]
-    openai_chat_completion_module.FunctionCall = object  # type: ignore[attr-defined]
-    openai_chat_tool_module.ChatCompletionMessageToolCall = object  # type: ignore[attr-defined]
-
-    openai_types_module.chat = openai_chat_module  # type: ignore[attr-defined]
-    openai_chat_module.chat_completion_message = openai_chat_completion_module  # type: ignore[attr-defined]
-    openai_chat_module.chat_completion_message_tool_call = openai_chat_tool_module  # type: ignore[attr-defined]
-    openai_module.types = openai_types_module  # type: ignore[attr-defined]
-
-    sys.modules["openai"] = openai_module
-    sys.modules["openai.types"] = openai_types_module
-    sys.modules["openai.types.chat"] = openai_chat_module
-    sys.modules["openai.types.chat.chat_completion_message"] = openai_chat_completion_module
-    sys.modules["openai.types.chat.chat_completion_message_tool_call"] = openai_chat_tool_module
+pytest.importorskip("openai")
 
 from eval_protocol.models import EvaluationRow, Message
 from eval_protocol.pytest.dataset_preparation import load_and_prepare_rows