Update unit test workflow to include Python 3.11 and refactor ApiMana…

…ger initialization

.github/workflows/poetry_unit_test.yml

@@ -13,7 +13,7 @@ jobs:
     timeout-minutes: 60
     strategy:
       matrix:
-        python-version: [3.9, '3.10']
+        python-version: [3.9, '3.10', '3.11']
 
     steps:
       - uses: actions/checkout@v2

fedot_ind/api/utils/api_init.py

@@ -16,30 +16,31 @@
 
 class ApiManager:
     def __init__(self, **kwargs):
-        self.null_state_object()
-        self.user_config_object(kwargs)
-        self.path_object(kwargs)
-        self.industrial_config_object(kwargs)
-        self.industrial_api_object()
+        self.industrial_strategy_params = kwargs.get('industrial_strategy_params', {})
+        self.logger = logging.getLogger('FedotIndustrialAPI')
+        self.backend_method = kwargs.get('backend', 'cpu')
+        self.task_params = kwargs.get('task_params', {})
+
+        self.industrial_strategy = kwargs.get('industrial_strategy', None)
+        self.path_to_composition_results = kwargs.get('history_dir', None)
+        self.output_folder = kwargs.get('output_folder', None)
 
-    def null_state_object(self):
-        self.solver = None
+        self.is_default_fedot_context = None
         self.predicted_labels = None
         self.predicted_probs = None
-        self.predict_data = None
         self.target_encoder = None
         self.is_finetuned = False
+        self.predict_data = None
+        self.solver = None
 
-    def user_config_object(self, kwargs):
-        self.output_folder = kwargs.get('output_folder', None)
-        self.industrial_strategy_params = kwargs.get(
-            'industrial_strategy_params', {})
-        self.industrial_strategy = kwargs.get('industrial_strategy', None)
-        self.path_to_composition_results = kwargs.get('history_dir', None)
-        self.backend_method = kwargs.get('backend', 'cpu')
-        self.task_params = kwargs.get('task_params', {})
+        self.create_path(kwargs)
+        self.industrial_config_object(kwargs)
+        self.industrial_api_object()
+
+    def get(self, key):
+        return self.config_dict(key)
 
-    def path_object(self, kwargs):
+    def create_path(self, kwargs):
         # create dirs with results
         if self.path_to_composition_results is None:
             prefix = './composition_results'
@@ -51,30 +52,27 @@ def path_object(self, kwargs):
         # create dirs with results
         if self.output_folder is None:
             self.output_folder = default_path_to_save_results
-            Path(self.output_folder).mkdir(parents=True, exist_ok=True)
-        else:
-            Path(self.output_folder).mkdir(parents=True, exist_ok=True)
-            del kwargs['output_folder']
+        Path(self.output_folder).mkdir(parents=True, exist_ok=True)
 
         # init logger
         logging.basicConfig(
             level=logging.INFO,
             format='%(asctime)s %(levelname)s: %(name)s - %(message)s',
             handlers=[
-                logging.FileHandler(
-                    Path(
-                        self.output_folder) /
-                    'log.log'),
-                logging.StreamHandler()])
-        self.logger = logging.getLogger('FedotIndustrialAPI')
+                logging.FileHandler(Path(self.output_folder) / 'log.log'),
+                logging.StreamHandler()
+            ]
+        )
 
     def industrial_config_object(self, kwargs):
         # map Fedot params to Industrial params
         self.config_dict = kwargs
         # self.config_dict['history_dir'] = prefix
         self.preset = kwargs.get('preset', self.config_dict['problem'])
-        self.config_dict['available_operations'] = kwargs.get('available_operations',
-                                                              default_industrial_availiable_operation(self.preset))
+        self.config_dict['available_operations'] = kwargs.get(
+            'available_operations',
+            default_industrial_availiable_operation(self.preset)
+        )
         self.is_default_fedot_context = self.preset.__contains__('tabular')
         self.is_regression_task_context = self.config_dict['problem'] in ['ts_forecasting', 'regression']
         self.config_dict['cv_folds'] = kwargs.get('cv_folds', 3)
@@ -87,12 +85,10 @@ def industrial_config_object(self, kwargs):
                 either(left_function=fedot_init_assumptions,
                        right_function=fedot_init_assumptions)
 
-        self.config_dict['use_input_preprocessing'] = kwargs.get(
-            'use_input_preprocessing', False)
+        self.config_dict['use_input_preprocessing'] = kwargs.get('use_input_preprocessing', False)
 
         if self.task_params is not None and self.config_dict['problem'] == 'ts_forecasting':
-            self.config_dict['task_params'] = TsForecastingParams(
-                forecast_length=self.task_params['forecast_length'])
+            self.config_dict['task_params'] = TsForecastingParams(forecast_length=self.task_params['forecast_length'])
         self.__init_experiment_setup()
 
     def industrial_api_object(self):
@@ -115,8 +111,7 @@ def industrial_api_object(self):
     def __init_experiment_setup(self):
         self.logger.info('Initialising experiment setup')
 
-        industrial_params = set(self.config_dict.keys()) - \
-            set(FEDOT_API_PARAMS.keys())
+        industrial_params = set(self.config_dict.keys()) - set(FEDOT_API_PARAMS.keys())
         for param in industrial_params:
             self.config_dict.pop(param, None)