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Increase ruff coverage (#23644)
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* Pin ruff * Add python upgrade fixes This enables python upgrade checks in ruff to look for deprecated types and patterns. This namely fixes: - usage of deprecated `Typing` which is now built in - some specific exceptions which are caught and have new aliases Some specific UP checks were also ignored as they are stylistic / unimportant and likely to cause bugs * Remove async blocking calls Use asyncio.to_thread on two remaining blocking calls to fix hanging event thread loop. Enable this specific rule to block it in the future. * Use proper logging mechanism * Correctly format logs * Raise with context When raising an exception include the from context to improve debugging * Cleanup
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+12
-14
@@ -15,7 +15,7 @@ from collections import deque
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from collections.abc import Mapping
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from multiprocessing.managers import ValueProxy
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from pathlib import Path
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from typing import TYPE_CHECKING, Any, Dict, Optional, Tuple, Union
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from typing import TYPE_CHECKING, Any
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import numpy as np
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from ruamel.yaml import YAML
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@@ -152,7 +152,7 @@ def get_record_segment_time(config: "CameraConfig") -> int:
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def load_labels(
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path: Optional[str], encoding="utf-8", prefill=91, indexed: bool | None = None
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path: str | None, encoding="utf-8", prefill=91, indexed: bool | None = None
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):
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"""Loads labels from file (with or without index numbers).
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Args:
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@@ -164,7 +164,7 @@ def load_labels(
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if path is None:
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return {}
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with open(path, "r", encoding=encoding) as f:
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with open(path, encoding=encoding) as f:
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labels = {index: "unknown" for index in range(prefill)}
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lines = f.readlines()
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if not lines:
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@@ -180,8 +180,8 @@ def load_labels(
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def to_relative_box(
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width: int, height: int, box: Tuple[int, int, int, int]
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) -> Tuple[int | float, int | float, int | float, int | float]:
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width: int, height: int, box: tuple[int, int, int, int]
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) -> tuple[int | float, int | float, int | float, int | float]:
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return (
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box[0] / width, # x
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box[1] / height, # y
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@@ -195,7 +195,7 @@ def create_mask(frame_shape, mask):
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mask_img[:] = 255
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def process_config_query_string(query_string: Dict[str, list]) -> Dict[str, Any]:
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def process_config_query_string(query_string: dict[str, list]) -> dict[str, Any]:
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updates = {}
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for key_path_str, new_value_list in query_string.items():
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# use the string key as-is for updates dictionary
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@@ -213,8 +213,8 @@ def process_config_query_string(query_string: Dict[str, list]) -> Dict[str, Any]
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def flatten_config_data(
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config_data: Dict[str, Any], parent_key: str = ""
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) -> Dict[str, Any]:
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config_data: dict[str, Any], parent_key: str = ""
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) -> dict[str, Any]:
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items = []
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for key, value in config_data.items():
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escaped_key = escape_config_key_segment(str(key))
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@@ -261,12 +261,12 @@ def split_config_key_path(key_path_str: str) -> list[str]:
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return parts
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def update_yaml_file_bulk(file_path: str, updates: Dict[str, Any]):
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def update_yaml_file_bulk(file_path: str, updates: dict[str, Any]):
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yaml = YAML()
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yaml.indent(mapping=2, sequence=4, offset=2)
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try:
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with open(file_path, "r") as f:
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with open(file_path) as f:
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data = yaml.load(f)
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except FileNotFoundError:
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logger.error(
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@@ -438,9 +438,7 @@ def generate_color_palette(n):
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return colors
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def serialize(
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vector: Union[list[float], np.ndarray, float], pack: bool = True
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) -> bytes:
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def serialize(vector: list[float] | np.ndarray | float, pack: bool = True) -> bytes:
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"""Serializes a list of floats, numpy array, or single float into a compact "raw bytes" format"""
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if isinstance(vector, np.ndarray):
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# Convert numpy array to list of floats
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@@ -459,7 +457,7 @@ def serialize(
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else:
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return vector
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except struct.error as e:
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raise ValueError(f"Failed to pack vector: {e}. Vector: {vector}")
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raise ValueError(f"Failed to pack vector: {e}. Vector: {vector}") from e
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def deserialize(bytes_data: bytes) -> list[float]:
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