formatting

gradio/components.py

@@ -1055,8 +1055,11 @@ class Image(Component):
         else:
             self.type = type
 
-        self.default_value = processing_utils.encode_url_or_file_to_base64(
-            default_value) if default_value else None
+        self.default_value = (
+            processing_utils.encode_url_or_file_to_base64(default_value)
+            if default_value
+            else None
+        )
         self.type = type
         self.output_type = "auto"
         self.shape = shape
@@ -1374,8 +1377,11 @@ class Video(Component):
         label (str): component name in interface.
         optional (bool): If True, the interface can be submitted with no uploaded video, in which case the input value is None.
         """
-        self.default_value = processing_utils.encode_url_or_file_to_base64(
-            default_value) if default_value else None
+        self.default_value = (
+            processing_utils.encode_url_or_file_to_base64(default_value)
+            if default_value
+            else None
+        )
         self.type = type
         self.source = source
         super().__init__(label=label, css=css, **kwargs)
@@ -1540,8 +1546,11 @@ class Audio(Component):
         type (str): The format the image is converted to before being passed into the prediction function. "numpy" converts the image to a numpy array with shape (width, height, 3) and values from 0 to 255, "pil" converts the image to a PIL image object, "file" produces a temporary file object whose path can be retrieved by file_obj.name, "filepath" returns the path directly.
         label (str): component name in interface.
         """
-        self.default_value = processing_utils.encode_url_or_file_to_base64(
-            default_value) if default_value else None
+        self.default_value = (
+            processing_utils.encode_url_or_file_to_base64(default_value)
+            if default_value
+            else None
+        )
         self.source = source
         requires_permissions = source == "microphone"
         self.type = type
@@ -1847,8 +1856,11 @@ class File(Component):
         """
         if "keep_filename" in kwargs:
             warnings.warn("keep_filename is deprecated", DeprecationWarning)
-        self.default_value = processing_utils.encode_url_or_file_to_base64(
-            default_value) if default_value else None
+        self.default_value = (
+            processing_utils.encode_url_or_file_to_base64(default_value)
+            if default_value
+            else None
+        )
         self.file_count = file_count
         self.type = type
         self.test_input = None
@@ -2166,9 +2178,7 @@ class Timeseries(Component):
         label (str): component name in interface.
         """
         self.default_value = (
-            pd.read_csv(default_value)
-            if default_value is not None
-            else None
+            pd.read_csv(default_value) if default_value is not None else None
         )
         self.x = x
         if isinstance(y, str):

test/test_inputs.py

@@ -639,7 +639,11 @@ class TestDataframe(unittest.TestCase):
                 "row_count": 3,
                 "col_count": 3,
                 "col_width": None,
-                "default_value": [[None, None, None], [None, None, None], [None, None, None]],
+                "default_value": [
+                    [None, None, None],
+                    [None, None, None],
+                    [None, None, None],
+                ],
                 "name": "dataframe",
                 "label": "Dataframe Input",
                 "max_rows": 20,

test/test_outputs.py

@@ -184,7 +184,7 @@ class TestHighlightedText(unittest.TestCase):
                 "label": None,
                 "show_legend": False,
                 "css": {},
-                "default_value": ""
+                "default_value": "",
             },
         )
         ht = {"pos": "Hello ", "neg": "World"}
@@ -232,11 +232,13 @@ class TestAudio(unittest.TestCase):
         )
         self.assertEqual(
             audio_output.get_template_context(),
-            {"name": "audio", 
-             "label": None, 
-             "source": "upload", 
-             "css": {},
-             "default_value": None},
+            {
+                "name": "audio",
+                "label": None,
+                "source": "upload",
+                "css": {},
+                "default_value": None,
+            },
         )
         self.assertTrue(
             audio_output.deserialize(gr.test_data.BASE64_AUDIO["data"]).endswith(".wav")
@@ -362,7 +364,11 @@ class TestDataframe(unittest.TestCase):
                 "row_count": 3,
                 "col_count": 3,
                 "col_width": None,
-                "default_value": [[None, None, None], [None, None, None], [None, None, None]],
+                "default_value": [
+                    [None, None, None],
+                    [None, None, None],
+                    [None, None, None],
+                ],
                 "name": "dataframe",
             },
         )
@@ -487,8 +493,14 @@ class TestTimeseries(unittest.TestCase):
         timeseries_output = gr.outputs.Timeseries(label="Disease")
         self.assertEqual(
             timeseries_output.get_template_context(),
-            {"x": None, "y": None, "name": "timeseries", "label": "Disease", "css": {},
-             "default_value": None},
+            {
+                "x": None,
+                "y": None,
+                "name": "timeseries",
+                "label": "Disease",
+                "css": {},
+                "default_value": None,
+            },
         )
         data = {"Name": ["Tom", "nick", "krish", "jack"], "Age": [20, 21, 19, 18]}
         df = pd.DataFrame(data)