make tidy

Author: Coniferish

test_unstructured_inference/inference/test_layout.py

@@ -305,22 +305,18 @@ def mock_get_elements(self, *args, **kwargs):
 @pytest.mark.slow()
 def test_from_file_with_password(monkeypatch, mock_final_layout):
 
-    doc = layout.DocumentLayout.from_file(
-        "sample-docs/password.pdf",
-        password="password")
+    doc = layout.DocumentLayout.from_file("sample-docs/password.pdf", password="password")
     assert doc
 
-    monkeypatch.setattr(layout, "get_model",
-                        lambda x: MockLayoutModel(mock_final_layout))
+    monkeypatch.setattr(layout, "get_model", lambda x: MockLayoutModel(mock_final_layout))
     with patch(
         "unstructured_inference.inference.layout.UnstructuredObjectDetectionModel",
         MockLayoutModel,
-    ), open("sample-docs/password.pdf",mode="rb") as fp:
+    ), open("sample-docs/password.pdf", mode="rb") as fp:
         doc = layout.process_data_with_model(fp, model_name="fake", password="password")
         assert doc
 
 
-
 def test_from_image_file_raises_with_empty_fn():
     with pytest.raises(FileNotFoundError):
         layout.DocumentLayout.from_image_file("")

unstructured_inference/inference/layout.py

@@ -51,7 +51,7 @@ def from_file(
         filename: str,
         fixed_layouts: Optional[List[Optional[List[TextRegion]]]] = None,
         pdf_image_dpi: int = 200,
-        password:Optional[str] = None,
+        password: Optional[str] = None,
         **kwargs,
     ) -> DocumentLayout:
         """Creates a DocumentLayout from a pdf file."""
@@ -135,7 +135,7 @@ def __init__(
         document_filename: Optional[Union[str, PurePath]] = None,
         detection_model: Optional[UnstructuredObjectDetectionModel] = None,
         element_extraction_model: Optional[UnstructuredElementExtractionModel] = None,
-        password:Optional[str] = None,
+        password: Optional[str] = None,
     ):
         if detection_model is not None and element_extraction_model is not None:
             raise ValueError("Only one of detection_model and extraction_model should be passed.")