Add plain dataset

backend/data_import/datasets.py

@@ -4,7 +4,7 @@ from typing import List, Type
 from django.contrib.auth.models import User
 
 from .models import DummyLabelType
-from .pipeline.catalog import RELATION_EXTRACTION
+from .pipeline.catalog import RELATION_EXTRACTION, TextFile, TextLine
 from .pipeline.data import BaseData, BinaryData, TextData
 from .pipeline.exceptions import FileParseException
 from .pipeline.factories import create_parser
@@ -45,6 +45,21 @@ class Dataset(abc.ABC):
         raise NotImplementedError()
 
 
+class PlainDataset(Dataset):
+    def __init__(self, reader: Reader, project: Project, **kwargs):
+        super().__init__(reader, project, **kwargs)
+        self.example_maker = ExampleMaker(project=project, data_class=TextData)
+
+    def save(self, user: User, batch_size: int = 1000):
+        for records in self.reader.batch(batch_size):
+            examples = self.example_maker.make(records)
+            Example.objects.bulk_create(examples)
+
+    @property
+    def errors(self) -> List[FileParseException]:
+        return self.reader.errors + self.example_maker.errors
+
+
 class DatasetWithSingleLabelType(Dataset):
     data_class: Type[BaseData]
     label_class: Type[Label]
@@ -195,7 +210,7 @@ class CategoryAndSpanDataset(Dataset):
         return self.reader.errors + self.example_maker.errors + self.category_maker.errors + self.span_maker.errors
 
 
-def select_dataset(task: str, project: Project) -> Type[Dataset]:
+def select_dataset(project: Project, task: str, file_format: str) -> Type[Dataset]:
     mapping = {
         DOCUMENT_CLASSIFICATION: TextClassificationDataset,
         SEQUENCE_LABELING: SequenceLabelingDataset,
@@ -207,11 +222,13 @@ def select_dataset(task: str, project: Project) -> Type[Dataset]:
     }
     if task not in mapping:
         task = project.project_type
+    if project.is_text_project and file_format in [TextLine.name, TextFile.name]:
+        return PlainDataset
     return mapping[task]
 
 
 def load_dataset(task: str, file_format: str, data_files: List[FileName], project: Project, **kwargs) -> Dataset:
     parser = create_parser(file_format, **kwargs)
     reader = Reader(data_files, parser)
-    dataset_class = select_dataset(task, project)
+    dataset_class = select_dataset(project, task, file_format)
     return dataset_class(reader, project, **kwargs)

backend/data_import/tests/test_tasks.py

@@ -132,15 +132,17 @@ class TestImportClassificationData(TestImportData):
         filename = "example.txt"
         file_format = "TextFile"
         dataset = [("exampleA\nexampleB\n\nexampleC\n", [])]
-        self.import_dataset(filename, file_format, self.task)
+        response = self.import_dataset(filename, file_format, self.task)
         self.assert_examples(dataset)
+        self.assertEqual(len(response["error"]), 0)
 
     def test_textline(self):
         filename = "example.txt"
         file_format = "TextLine"
         dataset = [("exampleA", []), ("exampleB", []), ("exampleC", [])]
-        self.import_dataset(filename, file_format, self.task)
+        response = self.import_dataset(filename, file_format, self.task)
         self.assert_examples(dataset)
+        self.assertEqual(len(response["error"]), 1)
 
     def test_wrong_jsonl(self):
         filename = "text_classification/example.json"