[Datumaro] Reducing nesting of tests (#1875)

* Add `Dataset.from_iterable` constructor
* Simplify creation of `Dataset` objects in common simple cases
* Refactor tests

datumaro/datumaro/components/extractor.py

@@ -72,6 +72,33 @@ def __eq__(self, other):
 class LabelCategories(Categories):
     Category = namedtuple('Category', ['name', 'parent', 'attributes'])
 
+    @classmethod
+    def from_iterable(cls, iterable):
+        """Generation of LabelCategories from iterable object
+
+        Args:
+            iterable ([type]): This iterable object can be:
+            1)simple str - will generate one Category with str as name
+            2)list of str - will interpreted as list of Category names
+            3)list of positional argumetns - will generate Categories
+            with this arguments
+
+
+        Returns:
+            LabelCategories: LabelCategories object
+        """
+        temp_categories = cls()
+
+        if isinstance(iterable, str):
+            iterable = [[iterable]]
+
+        for category in iterable:
+            if isinstance(category, str):
+                category = [category]
+            temp_categories.add(*category)
+
+        return temp_categories
+
     def __init__(self, items=None, attributes=None):
         super().__init__(attributes=attributes)
 
@@ -482,6 +509,31 @@ def iou(self, other):
 class PointsCategories(Categories):
     Category = namedtuple('Category', ['labels', 'joints'])
 
+    @classmethod
+    def from_iterable(cls, iterable):
+        """Generation of PointsCategories from iterable object
+
+        Args:
+            iterable ([type]): This iterable object can be:
+            1)simple int - will generate one Category with int as label
+            2)list of int - will interpreted as list of Category labels
+            3)list of positional argumetns - will generate Categories
+            with this arguments
+
+        Returns:
+            PointsCategories: PointsCategories object
+        """
+        temp_categories = cls()
+
+        if isinstance(iterable, int):
+            iterable = [[iterable]]
+
+        for category in iterable:
+            if isinstance(category, int):
+                category = [category]
+            temp_categories.add(*category)
+        return temp_categories
+
     def __init__(self, items=None, attributes=None):
         super().__init__(attributes=attributes)
 

datumaro/datumaro/components/project.py

@@ -18,7 +18,8 @@
 from datumaro.components.config import Config, DEFAULT_FORMAT
 from datumaro.components.config_model import (Model, Source,
     PROJECT_DEFAULT_CONFIG, PROJECT_SCHEMA)
-from datumaro.components.extractor import Extractor
+from datumaro.components.extractor import Extractor, LabelCategories,\
+    AnnotationType
 from datumaro.components.launcher import ModelTransform
 from datumaro.components.dataset_filter import \
     XPathDatasetFilter, XPathAnnotationsFilter
@@ -319,6 +320,35 @@ def categories(self):
         return self._parent.categories()
 
 class Dataset(Extractor):
+    @classmethod
+    def from_iterable(cls, iterable, categories=None):
+        """Generation of Dataset from iterable object
+
+        Args:
+            iterable: Iterable object contains DatasetItems
+            categories (dict, optional): You can pass dict of categories or
+            you can pass list of names. It'll interpreted as list of names of
+            LabelCategories. Defaults to {}.
+
+        Returns:
+            Dataset: Dataset object
+        """
+
+        if isinstance(categories, list):
+            categories = {AnnotationType.label : LabelCategories.from_iterable(categories)}
+
+        if not categories:
+            categories = {}
+
+        class tmpExtractor(Extractor):
+            def __iter__(self):
+                return iter(iterable)
+
+            def categories(self):
+                return categories
+
+        return cls.from_extractors(tmpExtractor())
+
     @classmethod
     def from_extractors(cls, *sources):
         # merge categories