Only D417 error remain

apis/python/node/dora/__init__.py

@@ -1,5 +1,6 @@
 """ 
-# dora-rs
+# dora-rs.
+
 This is the dora python client for interacting with dora dataflow.
 You can install it via:
 ```bash
@@ -28,8 +29,7 @@ from .dora import (
 
 
 class DoraStatus(Enum):
-    """Dora status to indicate if operator `on_input` loop
-     should be stopped.
+    """Dora status to indicate if operator `on_input` loop should be stopped.
 
     Args:
         Enum (u8): Status signaling to dora operator to

apis/python/node/dora/__init__.pyi

@@ -16,6 +16,7 @@ class Enum:
 @typing.final
 class Node:
     """The custom node API lets you integrate `dora` into your application.
+    
     It allows you to retrieve input and send output in any fashion you want.
 
     Use with:
@@ -28,7 +29,8 @@ class Node:
     """
 
     def __init__(self, node_id: str=None) -> None:
-        """The custom node API lets you integrate `dora` into your application.
+        """Use the custom node API to embed `dora` into your application.
+
         It allows you to retrieve input and send output in any fashion you want.
 
         Use with:
@@ -41,21 +43,23 @@ class Node:
         """
 
     def dataflow_descriptor(self) -> dict:
-        """Returns the full dataflow descriptor that this node is part of.
+        """Return the full dataflow descriptor that this node is part of.
 
         This method returns the parsed dataflow YAML file.
         """
 
     def dataflow_id(self) -> str:
-        """Returns the dataflow id."""
+        """Return the dataflow id."""
 
     def merge_external_events(self, subscription: dora.Ros2Subscription) -> None:
         """Merge an external event stream with dora main loop.
+
         This currently only work with ROS2.
         """
 
     def next(self, timeout: float=None) -> dict:
         """`.next()` gives you the next input that the node has received.
+
         It blocks until the next event becomes available.
         You can use timeout in seconds to return if no input is available.
         It will return `None` when all senders has been dropped.

apis/python/node/dora/cuda.py

@@ -14,7 +14,7 @@ from pyarrow import cuda
 
 
 def torch_to_ipc_buffer(tensor: torch.TensorType) -> tuple[pa.array, dict]:
-    """Converts a Pytorch tensor into a pyarrow buffer containing the IPC handle and its metadata.
+    """Convert a Pytorch tensor into a pyarrow buffer containing the IPC handle and its metadata.
 
     Example Use:
     ```python
@@ -35,7 +35,7 @@ def torch_to_ipc_buffer(tensor: torch.TensorType) -> tuple[pa.array, dict]:
 
 
 def ipc_buffer_to_ipc_handle(handle_buffer: pa.array) -> cuda.IpcMemHandle:
-    """Converts a buffer containing a serialized handler into cuda IPC MemHandle.
+    """Convert a buffer containing a serialized handler into cuda IPC MemHandle.
 
     example use:
     ```python
@@ -57,7 +57,7 @@ def ipc_buffer_to_ipc_handle(handle_buffer: pa.array) -> cuda.IpcMemHandle:
 
 
 def cudabuffer_to_numba(buffer: cuda.CudaBuffer, metadata: dict) -> DeviceNDArray:
-    """Converts a pyarrow CUDA buffer to numba.
+    """Convert a pyarrow CUDA buffer to numba.
 
     example use:
     ```python
@@ -81,7 +81,7 @@ def cudabuffer_to_numba(buffer: cuda.CudaBuffer, metadata: dict) -> DeviceNDArra
 
 
 def cudabuffer_to_torch(buffer: cuda.CudaBuffer, metadata: dict) -> torch.Tensor:
-    """Converts a pyarrow CUDA buffer to a torch tensor.
+    """Convert a pyarrow CUDA buffer to a torch tensor.
 
     example use:
     ```python

binaries/cli/src/template/python/operator/operator-template.py

@@ -7,14 +7,16 @@ class Operator:
     """Template docstring."""
 
     def __init__(self):
-        """Called on initialisation."""
+        """Perform initialization tasks."""
 
     def on_event(
         self,
         dora_event,
         send_output,
     ) -> DoraStatus:
-        """Args:
+        """TODO :Description.
+        
+        Args:
             dora_event: Event containing an `id`, `data` and `metadata`.
             send_output Callable[[str, bytes | pa.Array, Optional[dict]], None]:
                 Function for sending output to the dataflow:
@@ -38,4 +40,4 @@ class Operator:
         return DoraStatus.CONTINUE
 
     def __del__(self):
-        """Called before being deleted."""
+        """Perform actions before being deleted."""

examples/python-operator-dataflow/llm_op.py

@@ -66,7 +66,7 @@ tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME_OR_PATH, use_fast=True)
 
 
 def extract_python_code_blocks(text):
-    """Extracts Python code blocks from the given text that are enclosed in triple backticks with a python language identifier.
+    """Extract Python code blocks from the given text that are enclosed in triple backticks with a python language identifier.
 
     Parameters
     ----------
@@ -90,7 +90,7 @@ def extract_python_code_blocks(text):
 
 
 def extract_json_code_blocks(text):
-    """Extracts json code blocks from the given text that are enclosed in triple backticks with a json language identifier.
+    """Extract json code blocks from the given text that are enclosed in triple backticks with a json language identifier.
 
     Parameters
     ----------
@@ -113,7 +113,7 @@ def extract_json_code_blocks(text):
 
 
 def remove_last_line(python_code):
-    """Removes the last line from a given string of Python code.
+    """Remove the last line from a given string of Python code.
 
     Parameters
     ----------
@@ -132,6 +132,7 @@ def remove_last_line(python_code):
 
 def calculate_similarity(source, target):
     """Calculate a similarity score between the source and target strings.
+
     This uses the edit distance relative to the length of the strings.
     """
     edit_distance = pylcs.edit_distance(source, target)
@@ -142,9 +143,7 @@ def calculate_similarity(source, target):
 
 
 def find_best_match_location(source_code, target_block):
-    """Find the best match for the target_block within the source_code by searching line by line,
-    considering blocks of varying lengths.
-    """
+    """Find the best match for the target_block within the source_code by searching line by line, considering blocks of varying lengths."""
     source_lines = source_code.split("\n")
     target_lines = target_block.split("\n")
 

examples/python-operator-dataflow/sentence_transformers_op.py

@@ -47,7 +47,7 @@ def search(query_embedding, corpus_embeddings, paths, raw, k=5, file_extension=N
 
 
 class Operator:
-    """ """
+    """TODO: Add docstring."""
 
     def __init__(self):
         ## TODO: Add a initialisation step

examples/reachy2/parse_bbox.py

@@ -13,7 +13,7 @@ IMAGE_RESIZE_RATIO = float(os.getenv("IMAGE_RESIZE_RATIO", "1.0"))
 
 
 def extract_bboxes(json_text):
-    """Extracts bounding boxes from a JSON string with markdown markers and returns them as a NumPy array.
+    """Extract bounding boxes from a JSON string with markdown markers and return them as a NumPy array.
 
     Parameters
     ----------

examples/reachy2/parse_bbox_minimal.py

@@ -13,7 +13,7 @@ IMAGE_RESIZE_RATIO = float(os.getenv("IMAGE_RESIZE_RATIO", "1.0"))
 
 
 def extract_bboxes(json_text) -> (np.ndarray, np.ndarray):
-    """Extracts bounding boxes from a JSON string with markdown markers and returns them as a NumPy array.
+    """Extract bounding boxes from a JSON string with markdown markers and return them as a NumPy array.
 
     Parameters
     ----------

examples/reachy2/pick_place.py

@@ -82,7 +82,7 @@ stop = True
 
 
 def extract_bboxes(json_text) -> (np.ndarray, np.ndarray):
-    """Extracts bounding boxes from a JSON string with markdown markers and returns them as a NumPy array.
+    """Extract bounding boxes from a JSON string with markdown markers and return them as a NumPy array.
 
     Parameters
     ----------

node-hub/dora-ios-lidar/dora_ios_lidar/main.py

@@ -21,7 +21,7 @@ class DemoApp:
         self.stop = False
 
     def on_new_frame(self):
-        """This method is called from non-main thread, therefore cannot be used for presenting UI."""
+        """on_new_frame method is called from non-main thread, therefore cannot be used for presenting UI."""
         self.event.set()  # Notify the main thread to stop waiting and process new frame.
 
     def on_stream_stopped(self):

node-hub/dora-pyaudio/dora_pyaudio/main.py

@@ -34,7 +34,7 @@ def play_audio(
 
 
 def main():
-    """Main function for the node."""
+    """Run main function for the node."""
     node = Node()
     stream = None
     audio = np.array([])