rename DataManager -> FileSystemManager

ITMO-NSS-team · Jun 1, 2023 · 404a5a5 · 404a5a5
1 parent b89fd9a
commit 404a5a5
Show file tree

Hide file tree

Showing 8 changed files with 14 additions and 14 deletions.
diff --git a/experiments/fedot_warm_start/run.py b/experiments/fedot_warm_start/run.py
@@ -22,7 +22,7 @@
 from sklearn.model_selection import StratifiedKFold
 from tqdm import tqdm
 
-from meta_automl.data_preparation.data_manager import DataManager
+from meta_automl.data_preparation.file_system_manager import FileSystemManager
 from meta_automl.data_preparation.dataset import OpenMLDataset, DatasetData
 from meta_automl.data_preparation.datasets_loaders import OpenMLDatasetsLoader
 from meta_automl.data_preparation.datasets_train_test_split import openml_datasets_train_test_split
@@ -61,7 +61,7 @@
 time_now = datetime.now()
 time_now_iso = time_now.isoformat(timespec="minutes")
 time_now_for_path = time_now_iso.replace(":", ".")
-save_dir = DataManager.get_data_dir(). \
+save_dir = FileSystemManager.get_data_dir(). \
     joinpath('experiments').joinpath('fedot_warm_start').joinpath(f'run_{time_now_for_path}')
 save_dir.mkdir(parents=True)
 log_file = save_dir.joinpath('log.txt')

diff --git a/meta_automl/data_preparation/dataset/file_dataset.py b/meta_automl/data_preparation/dataset/file_dataset.py
@@ -3,7 +3,7 @@
 import pickle
 from pathlib import Path
 
-from meta_automl.data_preparation.data_manager import DataManager
+from meta_automl.data_preparation.file_system_manager import FileSystemManager
 from meta_automl.data_preparation.dataset import DatasetBase
 from meta_automl.data_preparation.dataset.dataset_base import DatasetData
 
@@ -17,7 +17,7 @@ class FileDataset(DatasetBase):
 
     @property
     def cache_path(self) -> Path:
-        return DataManager.get_dataset_cache_path(self.id_, self.source_name)
+        return FileSystemManager.get_dataset_cache_path(self.id_, self.source_name)
 
     def get_data(self) -> DatasetData:
         if not self.cache_path.exists():

diff --git a/meta_automl/data_preparation/dataset/openml_dataset.py b/meta_automl/data_preparation/dataset/openml_dataset.py
@@ -2,12 +2,12 @@
 
 import openml
 
-from meta_automl.data_preparation.data_manager import DataManager
+from meta_automl.data_preparation.file_system_manager import FileSystemManager
 from meta_automl.data_preparation.dataset import DatasetBase
 from meta_automl.data_preparation.dataset.dataset_base import DatasetData
 
 OpenMLDatasetIDType = int
-openml_cache_path = str(DataManager.get_data_dir().joinpath('openml_cache'))
+openml_cache_path = str(FileSystemManager.get_data_dir().joinpath('openml_cache'))
 openml.config.set_cache_directory(openml_cache_path)
 
 

diff --git a/meta_automl/data_preparation/datasets_loaders/datasets_loader.py b/meta_automl/data_preparation/datasets_loaders/datasets_loader.py
@@ -3,12 +3,12 @@
 from abc import abstractmethod
 from typing import List, Type
 
-from meta_automl.data_preparation.data_manager import DataManager
+from meta_automl.data_preparation.file_system_manager import FileSystemManager
 from meta_automl.data_preparation.dataset import DatasetBase
 
 
 class DatasetsLoader:
-    data_manager: Type[DataManager] = DataManager
+    data_manager: Type[FileSystemManager] = FileSystemManager
 
     @abstractmethod
     def load(self, *args, **kwargs) -> List[DatasetBase]:

diff --git a/meta_automl/data_preparation/data_manager.py → ...l/data_preparation/file_system_manager.py b/meta_automl/data_preparation/data_manager.py → ...l/data_preparation/file_system_manager.py
@@ -8,7 +8,7 @@
 PathType = Union[PathLike, str]
 
 
-class DataManager:
+class FileSystemManager:
     default_cache_extension = '.pkl'
 
     @classmethod

diff --git a/meta_automl/data_preparation/meta_features_extractors/meta_features_extractor.py b/meta_automl/data_preparation/meta_features_extractors/meta_features_extractor.py
@@ -5,14 +5,14 @@
 
 import pandas as pd
 
-from meta_automl.data_preparation.data_manager import DataManager
+from meta_automl.data_preparation.file_system_manager import FileSystemManager
 from meta_automl.data_preparation.dataset import DatasetIDType
 
 
 class MetaFeaturesExtractor:
     default_params: Optional[Dict[str, Any]] = None
     source_name: Optional[str] = None
-    data_manager: Type[DataManager] = DataManager
+    data_manager: Type[FileSystemManager] = FileSystemManager
 
     @abstractmethod
     def extract(self, datasets) -> pd.DataFrame:

diff --git a/meta_automl/data_preparation/models_loaders/fedot_pipelines_loader.py b/meta_automl/data_preparation/models_loaders/fedot_pipelines_loader.py
@@ -14,7 +14,7 @@
 from golem.core.log import default_log
 from tqdm import tqdm
 
-from meta_automl.data_preparation.data_manager import PathType
+from meta_automl.data_preparation.file_system_manager import PathType
 from meta_automl.data_preparation.dataset import DatasetCache
 from meta_automl.data_preparation.datasets_loaders import DatasetsLoader, OpenMLDatasetsLoader
 from meta_automl.data_preparation.model import Model

diff --git a/meta_automl/data_preparation/models_loaders/knowledge_base_models_loader.py b/meta_automl/data_preparation/models_loaders/knowledge_base_models_loader.py
@@ -7,12 +7,12 @@
 from fedot.core.pipelines.pipeline import Pipeline
 from golem.core.optimisers.fitness import SingleObjFitness
 
-from meta_automl.data_preparation.data_manager import DataManager
+from meta_automl.data_preparation.file_system_manager import FileSystemManager
 from meta_automl.data_preparation.dataset import DatasetCache
 from meta_automl.data_preparation.model import Model
 from meta_automl.data_preparation.models_loaders import ModelsLoader
 
-DEFAULT_KNOWLEDGE_BASE_PATH = DataManager.get_data_dir().joinpath('knowledge_base_0')
+DEFAULT_KNOWLEDGE_BASE_PATH = FileSystemManager.get_data_dir().joinpath('knowledge_base_0')
 
 
 class KnowledgeBaseModelsLoader(ModelsLoader):