Replace pylint with ruff

.github/workflows/ci.yml

@@ -310,15 +310,14 @@ jobs:
             mv .venv/Scripts .venv/bin    # venv is placed under `Scripts` on Windows
           fi
           source .venv/bin/activate
-          pip3 install maturin black pylint pytest
+          pip3 install maturin ruff pytest
           maturin build -m apis/python/node/Cargo.toml
           pip3 install target/wheels/*
           dora new test_python_project --lang python --internal-create-with-path-dependencies
           cd test_python_project
 
           # Check Compliancy
-          black . --check
-          pylint --disable=C,R **/*.py
+          ruff check .
           pip install -e ./*/
           pytest
 

.github/workflows/node-hub-ci-cd.yml

@@ -86,7 +86,7 @@ jobs:
         run: |
           curl -sSL https://install.python-poetry.org | python3 -
           echo "$HOME/.local/bin" >> $GITHUB_PATH
-          pip install black pylint pytest
+          pip install ruff pytest
 
       - name: Set up Rust
         if: runner.os == 'Linux' || github.event_name == 'workflow_dispatch' || (github.event_name == 'release' && startsWith(github.ref, 'refs/tags/'))

.github/workflows/node_hub_test.sh

@@ -43,8 +43,7 @@ else
             if [ -f "$dir/pyproject.toml" ]; then
             echo "Running linting and tests for Python project in $dir..."
             pip install .
-            poetry run black --check .
-            poetry run pylint --disable=C,R  --ignored-modules=cv2,pyrealsense2 **/*.py
+            ruff check .
             poetry run pytest
             fi
         fi 

binaries/cli/src/template/python/__node-name__/README.md

@@ -10,16 +10,16 @@ pip install -e .
 
 ## Contribution Guide
 
-- Format with [black](https://github.com/psf/black):
+- Format with [ruff](https://docs.astral.sh/ruff/):
 
 ```bash
-black . # Format
+ruff check . --fix
 ```
 
-- Lint with [pylint](https://github.com/pylint-dev/pylint):
+- Lint with ruff:
 
 ```bash
-pylint --disable=C,R --ignored-modules=cv2 . # Lint
+ruff check .
 ```
 
 - Test with [pytest](https://github.com/pytest-dev/pytest)

binaries/cli/src/template/python/__node-name__/pyproject.toml

@@ -12,13 +12,12 @@ packages = [{ include = "__node_name__" }]
 [tool.poetry.dependencies]
 dora-rs = "^0.3.6"
 numpy = "< 2.0.0"
-pyarrow = ">= 5.0.0"
+pyarrow = ">= 15.0.0"
 python = "^3.7"
 
 [tool.poetry.dev-dependencies]
-pytest = ">= 8.3.4"
-pylint = ">= 3.3.2"
-black = ">= 24.10"
+pytest = ">= 6.3.4"
+ruff = ">= 0.9.1"
 
 [tool.poetry.scripts]
 __node-name__ = "__node_name__.main:main"

binaries/cli/src/template/python/mod.rs

@@ -77,9 +77,10 @@ fn create_custom_node(
         .with_context(|| format!("failed to write `{}`", node_path.display()))?;
 
     // tests/tests___node_name__.py
-    let node_path = root
-        .join("tests")
-        .join(format!("test_{}.py", name.replace(" ", "_")));
+    let node_path = root.join("tests").join(format!(
+        "test_{}.py",
+        name.replace(" ", "_").replace("-", "_")
+    ));
     let file = replace_space(_TEST_PY, &name);
     fs::write(&node_path, file)
         .with_context(|| format!("failed to write `{}`", node_path.display()))?;
@@ -90,8 +91,8 @@ fn create_custom_node(
     );
     println!("   cd {}", Path::new(".").join(&root).display());
     println!("   pip install -e . # Install",);
-    println!("   black . # Format");
-    println!("   pylint  --disable=C,R . # Lint",);
+    println!("   ruff check . --fix # Format");
+    println!("   ruff check . # Lint",);
     println!("   pytest . # Test");
 
     Ok(())

examples/piper/dummy_inference_2.py

@@ -1,7 +1,6 @@
 from dora import Node
 
 
-import numpy as np
 import h5py
 
 f = h5py.File("data/episode_0.hdf5", "r")

examples/piper/replay.py

@@ -1,7 +1,6 @@
 from dora import Node
 
 
-import numpy as np
 import h5py
 import os
 

examples/python-operator-dataflow/plot.py

@@ -1,6 +1,5 @@
 import os
 import cv2
-import time
 
 from dora import DoraStatus
 from utils import LABELS

node-hub/dora-argotranslate/dora_argotranslate/__init__.py

@@ -5,7 +5,7 @@
 
 # Read the content of the README file
 try:
-    with open(readme_path, "r", encoding="utf-8") as f:
+    with open(readme_path, encoding="utf-8") as f:
         __doc__ = f.read()
 except FileNotFoundError:
     __doc__ = "README file not found."

node-hub/dora-argotranslate/dora_argotranslate/main.py

@@ -2,10 +2,10 @@
 
 os.environ["ARGOS_DEVICE_TYPE"] = "auto"
 
-from dora import Node
-import pyarrow as pa
 import argostranslate.package
 import argostranslate.translate
+import pyarrow as pa
+from dora import Node
 
 from_code = os.getenv("SOURCE_LANGUAGE", "fr")
 to_code = os.getenv("TARGET_LANGUAGE", "en")
@@ -15,8 +15,8 @@
 available_packages = argostranslate.package.get_available_packages()
 package_to_install = next(
     filter(
-        lambda x: x.from_code == from_code and x.to_code == to_code, available_packages
-    )
+        lambda x: x.from_code == from_code and x.to_code == to_code, available_packages,
+    ),
 )
 argostranslate.package.install_from_path(package_to_install.download())
 

node-hub/dora-distil-whisper/dora_distil_whisper/__init__.py

@@ -5,7 +5,7 @@
 
 # Read the content of the README file
 try:
-    with open(readme_path, "r", encoding="utf-8") as f:
+    with open(readme_path, encoding="utf-8") as f:
         __doc__ = f.read()
 except FileNotFoundError:
     __doc__ = "README file not found."

node-hub/dora-distil-whisper/dora_distil_whisper/main.py

@@ -47,7 +47,8 @@ def load_model():
 
 
 def load_model_mlx():
-    from lightning_whisper_mlx import LightningWhisperMLX  # noqa
+    # noqa: disable: import-error
+    from lightning_whisper_mlx import LightningWhisperMLX
 
     whisper = LightningWhisperMLX(model="distil-large-v3", batch_size=12, quant=None)
     return whisper
@@ -78,7 +79,8 @@ def cut_repetition(text, min_repeat_length=4, max_repeat_length=50):
     if sum(1 for char in text if "\u4e00" <= char <= "\u9fff") / len(text) > 0.5:
         # Chinese text processing
         for repeat_length in range(
-            min_repeat_length, min(max_repeat_length, len(text) // 2)
+            min_repeat_length,
+            min(max_repeat_length, len(text) // 2),
         ):
             for i in range(len(text) - repeat_length * 2 + 1):
                 chunk1 = text[i : i + repeat_length]
@@ -90,7 +92,8 @@ def cut_repetition(text, min_repeat_length=4, max_repeat_length=50):
         # Non-Chinese (space-separated) text processing
         words = text.split()
         for repeat_length in range(
-            min_repeat_length, min(max_repeat_length, len(words) // 2)
+            min_repeat_length,
+            min(max_repeat_length, len(words) // 2),
         ):
             for i in range(len(words) - repeat_length * 2 + 1):
                 chunk1 = " ".join(words[i : i + repeat_length])

node-hub/dora-distil-whisper/pyproject.toml

@@ -28,8 +28,7 @@ dora-distil-whisper = "dora_distil_whisper.main:main"
 
 [tool.poetry.dev-dependencies]
 pytest = ">= 6.3.4"
-pylint = ">= 3.3.2"
-black = ">= 22.10"
+ruff = ">= 0.9.1"
 
 [build-system]
 requires = ["poetry-core>=1.8.0"]

node-hub/dora-distil-whisper/tests/test_distil_whisper.py

@@ -2,7 +2,6 @@
 
 
 def test_import_main():
-
     from dora_distil_whisper.main import main
 
     # Check that everything is working, and catch dora Runtime Exception as we're not running in a dora dataflow.

node-hub/dora-echo/dora_echo/__init__.py

@@ -5,7 +5,7 @@
 
 # Read the content of the README file
 try:
-    with open(readme_path, "r", encoding="utf-8") as f:
+    with open(readme_path, encoding="utf-8") as f:
         __doc__ = f.read()
 except FileNotFoundError:
     __doc__ = "README file not found."

node-hub/dora-echo/dora_echo/main.py

@@ -1,12 +1,12 @@
 import argparse
 import os
+
 from dora import Node
 
 RUNNER_CI = True if os.getenv("CI") == "true" else False
 
 
 def main():
-
     # Handle dynamic nodes, ask for the name of the node in the dataflow, and the same values as the ENV variables.
     parser = argparse.ArgumentParser(description="Simple arrow sender")
 
@@ -20,7 +20,7 @@ def main():
     args = parser.parse_args()
 
     node = Node(
-        args.name
+        args.name,
     )  # provide the name to connect to the dataflow if dynamic node
 
     for event in node:

node-hub/dora-internvl/dora_internvl/__init__.py

@@ -5,7 +5,7 @@
 
 # Read the content of the README file
 try:
-    with open(readme_path, "r", encoding="utf-8") as f:
+    with open(readme_path, encoding="utf-8") as f:
         __doc__ = f.read()
 except FileNotFoundError:
     __doc__ = "README file not found."

node-hub/dora-internvl/dora_internvl/main.py

@@ -1,9 +1,10 @@
 import os
-from dora import Node
+
 import numpy as np
 import pyarrow as pa
 import torch
 import torchvision.transforms as T
+from dora import Node
 from PIL import Image
 from torchvision.transforms.functional import InterpolationMode
 from transformers import AutoModel, AutoTokenizer
@@ -20,7 +21,7 @@ def build_transform(input_size):
             T.Resize((input_size, input_size), interpolation=InterpolationMode.BICUBIC),
             T.ToTensor(),
             T.Normalize(mean=MEAN, std=STD),
-        ]
+        ],
     )
     return transform
 
@@ -42,7 +43,7 @@ def find_closest_aspect_ratio(aspect_ratio, target_ratios, width, height, image_
 
 
 def dynamic_preprocess(
-    image, min_num=1, max_num=12, image_size=448, use_thumbnail=False
+    image, min_num=1, max_num=12, image_size=448, use_thumbnail=False,
 ):
     orig_width, orig_height = image.size
     aspect_ratio = orig_width / orig_height
@@ -59,7 +60,7 @@ def dynamic_preprocess(
 
     # find the closest aspect ratio to the target
     target_aspect_ratio = find_closest_aspect_ratio(
-        aspect_ratio, target_ratios, orig_width, orig_height, image_size
+        aspect_ratio, target_ratios, orig_width, orig_height, image_size,
     )
 
     # calculate the target width and height
@@ -91,7 +92,7 @@ def load_image(image_array: np.array, input_size=448, max_num=12):
     image = Image.fromarray(image_array).convert("RGB")
     transform = build_transform(input_size=input_size)
     images = dynamic_preprocess(
-        image, image_size=input_size, use_thumbnail=True, max_num=max_num
+        image, image_size=input_size, use_thumbnail=True, max_num=max_num,
     )
     pixel_values = [transform(image) for image in images]
     pixel_values = torch.stack(pixel_values)
@@ -116,7 +117,7 @@ def main():
         .to(device)
     )
     tokenizer = AutoTokenizer.from_pretrained(
-        model_path, trust_remote_code=True, use_fast=False
+        model_path, trust_remote_code=True, use_fast=False,
     )
 
     node = Node()
@@ -138,10 +139,7 @@ def main():
                 width = metadata["width"]
                 height = metadata["height"]
 
-                if encoding == "bgr8":
-                    channels = 3
-                    storage_type = np.uint8
-                elif encoding == "rgb8":
+                if encoding == "bgr8" or encoding == "rgb8":
                     channels = 3
                     storage_type = np.uint8
                 else:
@@ -168,7 +166,7 @@ def main():
                     )
                     generation_config = dict(max_new_tokens=1024, do_sample=True)
                     response = model.chat(
-                        tokenizer, pixel_values, question, generation_config
+                        tokenizer, pixel_values, question, generation_config,
                     )
                     node.send_output(
                         "text",

node-hub/dora-keyboard/dora_keyboard/__init__.py

@@ -5,7 +5,7 @@
 
 # Read the content of the README file
 try:
-    with open(readme_path, "r", encoding="utf-8") as f:
+    with open(readme_path, encoding="utf-8") as f:
         __doc__ = f.read()
 except FileNotFoundError:
     __doc__ = "README file not found."

node-hub/dora-keyboard/dora_keyboard/main.py

@@ -1,7 +1,7 @@
-from pynput import keyboard
-from pynput.keyboard import Events
 import pyarrow as pa
 from dora import Node
+from pynput import keyboard
+from pynput.keyboard import Events
 
 
 def main():

node-hub/dora-microphone/dora_microphone/__init__.py

@@ -5,7 +5,7 @@
 
 # Read the content of the README file
 try:
-    with open(readme_path, "r", encoding="utf-8") as f:
+    with open(readme_path, encoding="utf-8") as f:
         __doc__ = f.read()
 except FileNotFoundError:
     __doc__ = "README file not found."

node-hub/dora-microphone/dora_microphone/main.py

@@ -1,9 +1,9 @@
-import sounddevice as sd
-import numpy as np
-import pyarrow as pa
-import time as tm
 import os
+import time as tm
 
+import numpy as np
+import pyarrow as pa
+import sounddevice as sd
 from dora import Node
 
 MAX_DURATION = float(os.getenv("MAX_DURATION", "0.1"))
@@ -19,7 +19,6 @@ def main():
     always_none = node.next(timeout=0.001) is None
     finished = False
 
-    # pylint: disable=unused-argument
     def callback(indata, frames, time, status):
         nonlocal buffer, node, start_recording_time, finished
 
@@ -36,7 +35,7 @@ def callback(indata, frames, time, status):
 
     # Start recording
     with sd.InputStream(
-        callback=callback, dtype=np.int16, channels=1, samplerate=SAMPLE_RATE
+        callback=callback, dtype=np.int16, channels=1, samplerate=SAMPLE_RATE,
     ):
         while not finished:
-            sd.sleep(int(1000))
+            sd.sleep(1000)