Fix lint issues, remove unittest class, add proper type annotations

Author: mousberg

src/openai/lib/_parsing/_completions.py

@@ -262,7 +262,7 @@ def type_to_response_format_param(
     else:
         raise TypeError(f"Unsupported response_format type - {response_format}")
 
-    schema_param = {
+    schema_param: ResponseFormatParam = {
         "type": "json_schema",
         "json_schema": {
             "schema": to_strict_json_schema(json_schema_type),

tests/lib/_parsing/test_memory_leak.py

@@ -1,56 +1,12 @@
-import unittest
 import gc
-import sys
-from unittest.mock import AsyncMock, patch, MagicMock
 from typing import List
 
 import pytest
 from pydantic import Field, create_model
 
-from openai.resources.beta.chat.completions import AsyncCompletions
 from openai.lib._parsing import type_to_response_format_param
 from openai.lib._parsing._completions import _schema_cache
 
-class TestMemoryLeak(unittest.TestCase):
-    def setUp(self):
-        # Clear the schema cache before each test
-        _schema_cache.clear()
-        
-    def test_schema_cache_with_models(self):
-        """Test if schema cache properly handles dynamic models and prevents memory leak"""
-        
-        StepModel = create_model(
-            "Step",
-            explanation=(str, Field()),
-            output=(str, Field()),
-        )
-        
-        # Create several models and ensure they're cached properly
-        models = []
-        for i in range(5):
-            model = create_model(
-                f"MathResponse{i}",
-                steps=(List[StepModel], Field()),
-                final_answer=(str, Field()),
-            )
-            models.append(model)
-            
-            # Convert model to response format param
-            param = type_to_response_format_param(model)
-            
-            # Check if the model is in the cache
-            self.assertIn(model, _schema_cache)
-        
-        # Test that all models are in the cache
-        self.assertEqual(len(_schema_cache), 5)
-        
-        # Let the models go out of scope and trigger garbage collection
-        models = None
-        gc.collect()
-        
-        # After garbage collection, the cache should be empty or reduced
-        # since we're using weakref.WeakKeyDictionary
-        self.assertLess(len(_schema_cache), 5)
 
 @pytest.mark.asyncio
 async def test_async_completions_parse_memory():
@@ -65,13 +21,6 @@ async def test_async_completions_parse_memory():
     _schema_cache.clear()
     initial_cache_size = len(_schema_cache)
 
-    # Create a mock client 
-    mock_client = MagicMock()
-    mock_client.chat.completions.create = AsyncMock()
-    
-    # Create the AsyncCompletions instance with our mock client
-    completions = AsyncCompletions(mock_client)
-    
     # Simulate the issue by creating multiple models and making calls
     models = []
     for i in range(10):