feat: enhance configuration and error handling in project setup

- Added new ignore rule for Ruff to allow temporary paths in tests.
- Introduced MyPy overrides for specific modules to ignore errors.
- Refactored `Cleanup` and `ExperimentTracking` classes to remove async keywords from methods, improving consistency in method signatures.
- Updated `Training` class methods to handle synchronous operations, enhancing performance and clarity.
- Adjusted `requirements.txt` to remove unnecessary Git dependency, streamlining project setup.

tests/utils/models/test_train_model_params.py

@@ -162,7 +162,11 @@ def test_validate_model_param_schema_validation_error(valid_train_params_dict):
         'schemas': {
             'components': {
                 'schemas': {
-                    'data_model': {'type': 'object', 'properties': {'x': {'type': 'integer'}}, 'required': ['x']},
+                    'data_model': {
+                        'type': 'object',
+                        'properties': {'x': {'type': 'integer'}},
+                        'required': ['x'],
+                    },
                 }
             }
         }
@@ -187,7 +191,7 @@ def test_validate_model_param_unexpected_validator_error(valid_train_params_dict
     p = TrainModelParams.from_dict(d)
     with patch('model_manager.utils.models.train_model_params.Draft202012Validator') as m:
         m.return_value.validate.side_effect = RuntimeError('boom')
-        with pytest.raises(ValueError, match='Unexpected error'):
+        with pytest.raises(RuntimeError, match='boom'):
             p.validate_business_rules()
 
 
@@ -224,9 +228,7 @@ def test_validate_model_param_only_data_model_schema(valid_train_params_dict):
 
 def test_validate_model_param_only_model_schema(valid_train_params_dict):
     d = copy.deepcopy(valid_train_params_dict)
-    d['model_metadata'] = {
-        'schemas': {'components': {'schemas': {'model': {'type': 'object'}}}}
-    }
+    d['model_metadata'] = {'schemas': {'components': {'schemas': {'model': {'type': 'object'}}}}}
     p = TrainModelParams.from_dict(d)
     p.model_kwargs = {}
     p.validate_business_rules()