prepare for rebase on main

Signed-off-by: dafnapension <dafnashein@yahoo.com>

src/unitxt/loaders.py

@@ -27,7 +27,7 @@
 import tempfile
 from pathlib import Path
 from tempfile import TemporaryDirectory
-from typing import Dict, List, Mapping, Optional, Sequence, Union
+from typing import Any, Dict, List, Mapping, Optional, Sequence, Union
 
 import pandas as pd
 from datasets import load_dataset as hf_load_dataset
@@ -474,3 +474,26 @@ def process(self):
         return FixedFusion(
             origins=self.sources, max_instances_per_origin=self.get_limit()
         ).process()
+
+
+class LoadFromDictionary(Loader):
+    """Allows loading data from dictionary of constants.
+
+    The loader can be used, for example, when debugging or working with small datasets.
+
+    Attributes:
+        data (Dict[str, List[Dict[str, Any]]]): a dictionary of constants from which the data will be loaded
+
+    Examples:
+        data = {
+            "train": {"input": "SomeInput1", "output": "SomeResult1"},
+            "test": {"input": "SomeInput2", "output": "SomeResult2"},
+        }
+        loader = LoadFromDictionary(data=data)
+        multi_stream = loader.process()
+    """
+
+    data: Dict[str, List[Dict[str, Any]]]
+
+    def process(self) -> MultiStream:
+        return MultiStream.from_iterables(self.data)

tests/library/test_loaders.py

@@ -5,7 +5,13 @@
 
 import ibm_boto3
 import pandas as pd
-from unitxt.loaders import LoadCSV, LoadFromIBMCloud, LoadHF, MultipleSourceLoader
+from unitxt.loaders import (
+    LoadCSV,
+    LoadFromDictionary,
+    LoadFromIBMCloud,
+    LoadHF,
+    MultipleSourceLoader,
+)
 from unitxt.logging_utils import get_logger
 
 from tests.utils import UnitxtTestCase
@@ -228,3 +234,20 @@ def test_multiple_source_loader(self):
             ms = loader()
             assert len(dfs["test"]) == len(list(ms["test"]))
             assert len(dfs["train"]) == len(list(ms["train"]))
+
+    def test_load_from_dictionary(self):
+        data = {
+            "train": [
+                {"input": "Input1", "output": "Result1"},
+                {"input": "Input2", "output": "Result2"},
+            ],
+            "test": [
+                {"input": "Input3", "output": "Result3"},
+            ],
+        }
+        loader = LoadFromDictionary(data=data)
+        streams = loader.process()
+
+        for split, instances in data.items():
+            for original_instance, stream_instance in zip(instances, streams[split]):
+                self.assertEqual(original_instance, stream_instance)