Integration tests fix

examples/advanced/time_series_forecasting/exogenous.py

@@ -10,7 +10,7 @@
 from fedot.core.data.multi_modal import MultiModalData
 from fedot.core.pipelines.pipeline_builder import PipelineBuilder
 from fedot.core.repository.dataset_types import DataTypesEnum
-from fedot.core.repository.tasks import Task, TsForecastingParams, TaskTypesEnum
+from fedot.core.repository.tasks import Task, TaskTypesEnum, TsForecastingParams
 from fedot.core.utils import fedot_project_root
 
 warnings.filterwarnings('ignore')
@@ -33,23 +33,23 @@ def run_exogenous_experiment(path_to_file, len_forecast=250, with_exog=True, vis
     exog_variable = np.array(df['Neighboring level'])
 
     task = Task(TaskTypesEnum.ts_forecasting, TsForecastingParams(forecast_length=len_forecast))
-    valiadion_blocks = 2
+    validation_blocks = 2
 
     # Target time series for lagged transformation
     train_lagged, predict_lagged = train_test_data_setup(InputData(idx=np.arange(len(time_series)),
                                                                    features=time_series,
                                                                    target=time_series,
                                                                    task=task,
                                                                    data_type=DataTypesEnum.ts),
-                                                         validation_blocks=valiadion_blocks)
+                                                         validation_blocks=validation_blocks)
 
     # Exogenous time series
     train_exog, predict_exog = train_test_data_setup(InputData(idx=np.arange(len(exog_variable)),
                                                                features=exog_variable,
                                                                target=time_series,
                                                                task=task,
                                                                data_type=DataTypesEnum.ts),
-                                                     validation_blocks=valiadion_blocks)
+                                                     validation_blocks=validation_blocks)
 
     if with_exog:
         train_dataset = MultiModalData({
@@ -76,13 +76,14 @@ def run_exogenous_experiment(path_to_file, len_forecast=250, with_exog=True, vis
                   task_params=task.task_params,
                   timeout=10,
                   initial_assumption=pipeline,
-                  max_pipeline_fit_time=1,
+                  available_operations=['lagged', 'ridge', 'exog_ts'],
+                  max_pipeline_fit_time=2,
                   n_jobs=-1)
     fedot.fit(train_dataset)
 
     # Predict
-    predicted = fedot.predict(predict_dataset, validation_blocks=valiadion_blocks)
-    print(fedot.get_metrics(metric_names='mae', validation_blocks=valiadion_blocks))
+    predicted = fedot.predict(predict_dataset, validation_blocks=validation_blocks)
+    print(fedot.get_metrics(metric_names='mae', validation_blocks=validation_blocks))
 
     if visualization:
         fedot.current_pipeline.show()

test/integration/cache/test_cache_parallel.py

@@ -63,4 +63,4 @@ def test_parallel_cache_files():
             Parallel(n_jobs=cpus)(tasks)
         except sqlite3.OperationalError:
             assert False, 'DBs collides'
-        assert len(list(data_dir.glob('cache_*.*'))) == 6  # (operations_cache, preprocessing_cache) x 3
+        assert len(list(data_dir.glob('cache_*.*_db'))) >= 6  # (operations_cache, preprocessing_cache) x 3

test/integration/real_applications/test_model_result_reproducing.py

@@ -1,11 +1,12 @@
 from typing import List
 
 import numpy as np
-from fedot.core.repository.tasks import Task, TaskTypesEnum, TsForecastingParams
+
 from fedot.api.main import Fedot
 from fedot.core.data.data import InputData
-from fedot.core.repository.dataset_types import DataTypesEnum
 from fedot.core.data.data_split import train_test_data_setup
+from fedot.core.repository.dataset_types import DataTypesEnum
+from fedot.core.repository.tasks import Task, TaskTypesEnum, TsForecastingParams
 
 
 def get_data(data_length=500, test_length=100):

test/integration/remote/test_remote_composer.py

@@ -4,6 +4,7 @@
 import pytest
 
 from fedot.api.main import Fedot
+from fedot.core.pipelines.pipeline import Pipeline, PipelineNode
 from fedot.core.repository.tasks import TsForecastingParams
 from fedot.core.utils import fedot_project_root
 from fedot.remote.infrastructure.clients.test_client import TestClient
@@ -94,13 +95,15 @@ def test_pseudo_remote_composer_ts_forecasting():
         'show_progress': False
     }
 
-    preset = 'best_quality'
-    automl = Fedot(problem='ts_forecasting', timeout=0.2, task_params=TsForecastingParams(forecast_length=1),
-                   preset=preset, **composer_params)
+    automl = Fedot(problem='ts_forecasting', task_params=TsForecastingParams(forecast_length=1),
+                   **composer_params)
 
     path = os.path.join(fedot_project_root(), 'test', 'data', 'short_time_series.csv')
 
-    automl.fit(path, target='sea_height')
+    predefined_model = Pipeline(PipelineNode('ridge', nodes_from=[PipelineNode('lagged')]))
+
+    automl.fit(path, target='sea_height', predefined_model=predefined_model)
     predict = automl.predict(path)
-    shutil.rmtree(os.path.join(fedot_project_root(), 'test', 'data', 'remote', 'fitted_pipeline'))  # recursive deleting
+    shutil.rmtree(os.path.join(fedot_project_root(), 'test', 'data', 'remote', 'fitted_pipeline'),  # recursive deleting
+                  ignore_errors=True)
     assert predict is not None