chore: replace black/isort/flake8 by ruff

Author: raphael0202

.github/workflows/ci.yml

@@ -36,8 +36,7 @@ jobs:
 
     - name: Launch quality checks
       run: |
-        poetry run flake8 .
-        poetry run black --check .
+        poetry run ruff check .
         poetry run mypy .
         poetry run isort --check .
     - name: Test with pytest

openfoodfacts/api.py

@@ -397,7 +397,8 @@ def parse_ingredients(
 
         if not api_version.startswith("v3"):
             logger.warning(
-                "ingredient parsing is only available in v3 of the API (here: %s), using v3",
+                "ingredient parsing is only available in v3 of the API (here: %s), "
+                "using v3",
                 self.api_config.version,
             )
             api_version = "v3"
@@ -431,11 +432,12 @@ def parse_ingredients(
         ) as e:
             raise RuntimeError(
                 f"Unable to parse ingredients: error during HTTP request: {e}"
-            )
+            ) from e
 
         if not r.ok:
             raise RuntimeError(
-                f"Unable to parse ingredients (non-200 status code): {r.status_code}, {r.text}"
+                "Unable to parse ingredients (non-200 status code): "
+                f"{r.status_code}, {r.text}"
             )
 
         response_data = r.json()
@@ -486,8 +488,9 @@ def upload_image(
         api_version = self.api_config.version
         if not self.api_config.version.startswith("v3"):
             warnings.warn(
-                "image upload is only available in v3 of the API (here: %s), forcing use of v3"
-                % self.api_config.version,
+                "image upload is only available in v3 of the API (here: %s), "
+                "forcing use of v3" % self.api_config.version,
+                stacklevel=2,
             )
             api_version = "v3"
 
@@ -534,7 +537,8 @@ def upload_image(
                         )
                     if not isinstance(value, dict):
                         raise ValueError(
-                            f"selected[{key}][{lang_code}] must be a dict, got {type(value)}"
+                            f"selected[{key}][{lang_code}] must be a dict, got "
+                            f"{type(value)}"
                         )
 
         # copy the config but force v3 of the API
@@ -665,11 +669,12 @@ def parse_ingredients(text: str, lang: str, api_config: APIConfig) -> list[JSONT
     ) as e:
         raise RuntimeError(
             f"Unable to parse ingredients: error during HTTP request: {e}"
-        )
+        ) from e
 
     if not r.ok:
         raise RuntimeError(
-            f"Unable to parse ingredients (non-200 status code): {r.status_code}, {r.text}"
+            "Unable to parse ingredients (non-200 status code): "
+            f"{r.status_code}, {r.text}"
         )
 
     response_data = r.json()

openfoodfacts/images.py

@@ -216,7 +216,9 @@ def download_image(
     :return: the downloaded image, or an `ImageDownloadItem` object if
         `return_struct` is True.
 
-    >>> download_image("https://images.openfoodfacts.org/images/products/324/227/210/2359/4.jpg")  # noqa
+    >>> download_image(
+      "https://images.openfoodfacts.org/images/products/324/227/210/2359/4.jpg"
+    )
     <PIL.JpegImagePlugin.JpegImageFile image mode=RGB size=1244x1500>
 
     >>> download_image(("3242272102359", "4"))

openfoodfacts/ml/image_classification.py

@@ -157,7 +157,8 @@ def postprocess(
 
         if len(response.raw_output_contents) != 1:
             raise Exception(
-                f"expected 1 raw output content, got {len(response.raw_output_contents)}"
+                "expected 1 raw output content, got "
+                f"{len(response.raw_output_contents)}"
             )
 
         output_index = {output.name: i for i, output in enumerate(response.outputs)}

openfoodfacts/ml/object_detection.py

@@ -140,7 +140,10 @@ def to_list(self) -> list[JSONType]:
         """Convert the detection results to a JSON serializable format."""
         results = []
         for bounding_box, score, label in zip(
-            self.detection_boxes, self.detection_scores, self.detection_classes
+            self.detection_boxes,
+            self.detection_scores,
+            self.detection_classes,
+            strict=True,
         ):
             label_int = int(label)
             label_str = self.label_names[label_int]
@@ -329,7 +332,8 @@ def postprocess(
 
         if len(response.raw_output_contents) != 1:
             raise ValueError(
-                f"expected 1 raw output content, got {len(response.raw_output_contents)}"
+                "expected 1 raw output content, got "
+                f"{len(response.raw_output_contents)}"
             )
 
         if nms_threshold is None:

openfoodfacts/ml/triton.py

@@ -72,7 +72,7 @@ def serialize_byte_tensor(input_tensor):
             # don't convert it to str as Python will encode the
             # bytes which may distort the meaning
             if input_tensor.dtype == np.object_:
-                if type(obj.item()) == bytes:
+                if type(obj.item()) is bytes:
                     s = obj.item()
                 else:
                     s = str(obj.item()).encode("utf-8")

openfoodfacts/utils/__init__.py

@@ -400,15 +400,15 @@ def get_image_from_url(
                 image_bytes=content_bytes,
             )
         return image
-    except PIL.UnidentifiedImageError:
+    except PIL.UnidentifiedImageError as e:
         error_message = f"Cannot identify image {image_url}"
         if error_raise:
-            raise AssetLoadingException(error_message)
+            raise AssetLoadingException(error_message) from e
         logger.info(error_message)
-    except PIL.Image.DecompressionBombError:
+    except PIL.Image.DecompressionBombError as e:
         error_message = f"Decompression bomb error for image {image_url}"
         if error_raise:
-            raise AssetLoadingException(error_message)
+            raise AssetLoadingException(error_message) from e
         logger.info(error_message)
 
     if return_struct: