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

@@ -17,8 +17,7 @@ python = "^3.7"
 
 [tool.poetry.dev-dependencies]
 pytest = ">= 6.3.4"
-pylint = ">= 3.3.2"
-black = ">= 22.10"
+ruff = ">= 0.9.1"
 
 [tool.poetry.scripts]
 __node-name__ = "__node_name__.main:main"

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

@@ -91,8 +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/main.py

@@ -2,10 +2,10 @@ import os
 
 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")

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

@@ -2,7 +2,6 @@ import pytest
 
 
 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/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")
 

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

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/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 +19,7 @@ def main():
     always_none = node.next(timeout=0.001) is None
     finished = False
 
-    # pylint: disable=unused-argument
+    # noqa
     def callback(indata, frames, time, status):
         nonlocal buffer, node, start_recording_time, finished
 

node-hub/dora-openai-server/dora_openai_server/main.py

@@ -1,11 +1,12 @@
-from fastapi import FastAPI
-from pydantic import BaseModel
+import ast
+import asyncio
 from typing import List, Optional
+
+import pyarrow as pa
 import uvicorn
 from dora import Node
-import asyncio
-import pyarrow as pa
-import ast
+from fastapi import FastAPI
+from pydantic import BaseModel
 
 DORA_RESPONSE_TIMEOUT = 10
 app = FastAPI()

node-hub/dora-openai-server/pyproject.toml

@@ -28,3 +28,6 @@ dora-openai-server = "dora_openai_server.main:main"
 [build-system]
 requires = ["poetry-core>=1.8.0"]
 build-backend = "poetry.core.masonry.api"
+
+[tool.ruff.lint]
+extend-select = ["I"]

node-hub/dora-opus/dora_opus/main.py

@@ -1,10 +1,10 @@
 import os
 from pathlib import Path
-from dora import Node
-import pyarrow as pa
-import numpy as np
-from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 
+import numpy as np
+import pyarrow as pa
+from dora import Node
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
 
 from_code = os.getenv("SOURCE_LANGUAGE", "zh")
 to_code = os.getenv("TARGET_LANGUAGE", "en")

node-hub/dora-outtetts/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)

node-hub/dora-outtetts/dora_outtetts/__main__.py

@@ -1,5 +1,4 @@
 from .main import main
 
-
 if __name__ == "__main__":
     main()

node-hub/dora-outtetts/dora_outtetts/main.py

@@ -1,10 +1,11 @@
-from dora import Node
-import outetts
 import argparse  # Add argparse import
-import pathlib
 import os
-import torch
+import pathlib
+
+import outetts
 import pyarrow as pa
+import torch
+from dora import Node
 
 PATH_SPEAKER = os.getenv("PATH_SPEAKER", "speaker.json")
 

node-hub/dora-outtetts/dora_outtetts/tests/test_main.py

@@ -1,7 +1,5 @@
 import pytest
-
-from dora_outtetts.main import load_interface
-from dora_outtetts.main import main
+from dora_outtetts.main import load_interface, main
 
 
 def test_import_main():

node-hub/dora-outtetts/pyproject.toml

@@ -21,8 +21,7 @@ outetts = "^0.2.3"
 
 [tool.poetry.dev-dependencies]
 pytest = ">= 6.3.4"
-pylint = ">= 3.3.2"
-black = ">= 22.10"
+ruff = ">= 0.9.1"
 
 [tool.poetry.scripts]
 dora-outtetts = "dora_outtetts.main:main"

node-hub/dora-parler/dora_parler/main.py

@@ -1,19 +1,19 @@
-from threading import Thread
-from dora import Node
 import os
+import time
 from pathlib import Path
+from threading import Thread
+
 import numpy as np
-import torch
-import time
 import pyaudio
-
+import torch
+from dora import Node
 from parler_tts import ParlerTTSForConditionalGeneration, ParlerTTSStreamer
 from transformers import (
-    AutoTokenizer,
     AutoFeatureExtractor,
-    set_seed,
+    AutoTokenizer,
     StoppingCriteria,
     StoppingCriteriaList,
+    set_seed,
 )
 
 device = "cuda:0"  # if torch.cuda.is_available() else "mps" if torch.backends.mps.is_available() else "cpu"
@@ -58,7 +58,6 @@ stream = p.open(format=pyaudio.paInt16, channels=1, rate=sampling_rate, output=T
 
 
 def play_audio(audio_array):
-
     if np.issubdtype(audio_array.dtype, np.floating):
         max_val = np.max(np.abs(audio_array))
         audio_array = (audio_array / max_val) * 32767
@@ -109,7 +108,6 @@ def generate_base(
     thread.start()
 
     for new_audio in streamer:
-
         current_time = time.time()
 
         print(f"Time between iterations: {round(current_time - prev_time, 2)} seconds")

node-hub/dora-piper/dora_piper/main.py

@@ -1,10 +1,11 @@
-from piper_sdk import C_PiperInterface
-from dora import Node
-import pyarrow as pa
-import numpy as np
 import os
 import time
 
+import numpy as np
+import pyarrow as pa
+from dora import Node
+from piper_sdk import C_PiperInterface
+
 TEACH_MODE = os.getenv("TEACH_MODE", "False") in ["True", "true"]
 
 
@@ -144,7 +145,6 @@ def main():
                 )
 
         elif event["type"] == "STOP":
-
             if not TEACH_MODE:
                 piper.MotionCtrl_2(0x01, 0x01, 50, 0x00)
                 piper.JointCtrl(0, 0, 0, 0, 0, 0)

node-hub/dora-pyaudio/README.md

@@ -22,16 +22,16 @@ 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)

node-hub/dora-pyaudio/pyproject.toml

@@ -18,8 +18,8 @@ pyaudio = ">= 0.1.0"
 
 [tool.poetry.dev-dependencies]
 pytest = ">= 6.3.4"
-pylint = ">= 2.5.2"
-black = ">= 22.10"
+ruff = ">= 0.9.1"
+
 
 [tool.poetry.scripts]
 dora-pyaudio = "dora_pyaudio.main:main"

node-hub/dora-pyorbbecksdk/dora_pyorbbecksdk/main.py

@@ -13,18 +13,25 @@
 #  See the License for the specific language governing permissions and
 #  limitations under the License.
 # ******************************************************************************
-import cv2
 import os
+
+import cv2
 import numpy as np
+import pyarrow as pa
+from dora import Node
 
 try:
-    from pyorbbecsdk import Context
-    from pyorbbecsdk import Config
-    from pyorbbecsdk import OBError
-    from pyorbbecsdk import OBSensorType, OBFormat
-    from pyorbbecsdk import Pipeline, FrameSet
-    from pyorbbecsdk import VideoStreamProfile
-    from pyorbbecsdk import VideoFrame
+    from pyorbbecsdk import (
+        Config,
+        Context,
+        FrameSet,
+        OBError,
+        OBFormat,
+        OBSensorType,
+        Pipeline,
+        VideoFrame,
+        VideoStreamProfile,
+    )
 except ImportError as err:
     print(
         "Please install pyorbbecsdk first by following the instruction at: https://github.com/orbbec/pyorbbecsdk"
@@ -120,9 +127,6 @@ def frame_to_bgr_image(frame: VideoFrame):
     return image
 
 
-from dora import Node
-import pyarrow as pa
-
 ESC_KEY = 27
 MIN_DEPTH_METERS = 0.01
 MAX_DEPTH_METERS = 15.0

node-hub/dora-pyrealsense/dora_pyrealsense/main.py

@@ -4,11 +4,10 @@ import time
 import cv2
 import numpy as np
 import pyarrow as pa
-
+import pyrealsense2 as rs
 from dora import Node
 
 RUNNER_CI = True if os.getenv("CI") == "true" else False
-import pyrealsense2 as rs
 
 
 def main():
@@ -53,7 +52,6 @@ def main():
     pa.array([])  # initialize pyarrow array
 
     for event in node:
-
         # Run this example in the CI for 10 seconds only.
         if RUNNER_CI and time.time() - start_time > 10:
             break

node-hub/dora-pyrealsense/tests/test_dora_pyrealsense.py

@@ -2,7 +2,6 @@ import pytest
 
 
 def test_import_main():
-
     from dora_pyrealsense.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-qwenvl/dora_qwenvl/main.py

@@ -1,13 +1,14 @@
 import os
-from dora import Node
-import torch
-from transformers import Qwen2VLForConditionalGeneration, AutoProcessor
-from qwen_vl_utils import process_vision_info
+from pathlib import Path
+
+import cv2
 import numpy as np
 import pyarrow as pa
+import torch
+from dora import Node
 from PIL import Image
-from pathlib import Path
-import cv2
+from qwen_vl_utils import process_vision_info
+from transformers import AutoProcessor, Qwen2VLForConditionalGeneration
 
 DEFAULT_PATH = "Qwen/Qwen2-VL-2B-Instruct"
 
@@ -27,7 +28,7 @@ ADAPTER_PATH = os.getenv("ADAPTER_PATH", "")
 
 # Check if flash_attn is installed
 try:
-    import flash_attn as _
+    import flash_attn as _  # noqa
 
     model = Qwen2VLForConditionalGeneration.from_pretrained(
         MODEL_NAME_OR_PATH,
@@ -118,7 +119,6 @@ def main():
         event_type = event["type"]
 
         if event_type == "INPUT":
-
             event_id = event["id"]
 
             if "image" in event_id:

node-hub/dora-rdt-1b/dora_rdt_1b/RoboticsDiffusionTransformer

@@ -1 +1 @@
-Subproject commit 198374ea8c4a2ec2ddae86c35448d21aa9756f37
+Subproject commit b2889e65cfe62571ced3ce88f00e7d80b41fee69

node-hub/dora-rdt-1b/dora_rdt_1b/main.py

@@ -1,17 +1,18 @@
 # install dependencies as shown in the README here https://github.com/alik-git/RoboticsDiffusionTransformer?tab=readme-ov-file#installation
-import yaml
-import torch
+import os
+from pathlib import Path
+
+import cv2
 import numpy as np
+import pyarrow as pa
+import torch
+import yaml
+from dora import Node
 from PIL import Image
 
 from dora_rdt_1b.RoboticsDiffusionTransformer.configs.state_vec import (
     STATE_VEC_IDX_MAPPING,
 )
-from dora import Node
-import cv2
-import pyarrow as pa
-import os
-from pathlib import Path
 
 VISION_DEFAULT_PATH = "robotics-diffusion-transformer/rdt-1b"
 ROBOTIC_MODEL_NAME_OR_PATH = os.getenv(
@@ -174,15 +175,15 @@ def get_states(proprio):
     )
 
     state_elem_mask[:, STATE_INDICES] = True
-    states, state_elem_mask = states.to(DEVICE, dtype=DTYPE), state_elem_mask.to(
-        DEVICE, dtype=DTYPE
+    states, state_elem_mask = (
+        states.to(DEVICE, dtype=DTYPE),
+        state_elem_mask.to(DEVICE, dtype=DTYPE),
     )
     states = states[:, -1:, :]  # only use the last state
     return states, state_elem_mask, STATE_INDICES
 
 
 def main():
-
     rdt = get_policy()
     lang_embeddings = get_language_embeddings()
     vision_encoder, image_processor = get_vision_model()
@@ -195,11 +196,9 @@ def main():
     frames = {}
     joints = {}
     with torch.no_grad():
-
         for event in node:
             event_type = event["type"]
             if event_type == "INPUT":
-
                 event_id = event["id"]
 
                 if "image" in event_id:

node-hub/dora-rdt-1b/pyproject.toml

@@ -29,12 +29,9 @@ huggingface_hub = "0.23.5"
 # flash_attn = "^2.6.1" # Install using: pip install -U flash-attn --no-build-isolation
 
 
-[tool.pylint.MASTER]
-ignore-paths = '^dora_rdt_1b/RoboticsDiffusionTransformer.*$'
-
 [tool.poetry.dev-dependencies]
 pytest = "^8.3.4"
-pylint = "^3.3.2"
+ruff = ">= 0.9.1"
 
 [tool.black]
 extend-exclude = 'dora_rdt_1b/RoboticsDiffusionTransformer'
@@ -46,3 +43,6 @@ dora-rdt-1b = "dora_rdt_1b.main:main"
 [build-system]
 requires = ["poetry-core>=1.8.0"]
 build-backend = "poetry.core.masonry.api"
+
+[tool.ruff]
+exclude = ["dora_rdt_1b/RoboticsDiffusionTransformer"]

node-hub/dora-rdt-1b/tests/test_dora_rdt_1b.py

@@ -1,10 +1,10 @@
+import os
+
+import numpy as np
 import pytest
 import torch
-import numpy as np
 from PIL import Image
 from torchvision import transforms
-import os
-
 
 CI = os.environ.get("CI")
 
@@ -20,8 +20,8 @@ def test_import_main():
     # Check that everything is working, and catch dora Runtime Exception as we're not running in a dora dataflow.
     # with pytest.raises(RuntimeError):
     # main()
-    import dora_rdt_1b.RoboticsDiffusionTransformer as _
-    import dora_rdt_1b as _
+    import dora_rdt_1b.RoboticsDiffusionTransformer as _  # noqa
+    import dora_rdt_1b as _  # noqa
 
 
 def test_download_policy():
@@ -44,7 +44,6 @@ def test_download_vision_model():
 
 
 def test_download_language_embeddings():
-
     ## in the future we should add this test within CI
     if CI:
         return
@@ -55,7 +54,6 @@ def test_download_language_embeddings():
 
 
 def test_load_dummy_image():
-
     from dora_rdt_1b.main import config
 
     # Load pretrained model (in HF style)
@@ -187,8 +185,9 @@ def test_dummy_states():
     ]
 
     state_elem_mask[:, STATE_INDICES] = True
-    states, state_elem_mask = states.to(DEVICE, dtype=DTYPE), state_elem_mask.to(
-        DEVICE, dtype=DTYPE
+    states, state_elem_mask = (
+        states.to(DEVICE, dtype=DTYPE),
+        state_elem_mask.to(DEVICE, dtype=DTYPE),
     )
     states = states[:, -1:, :]  # only use the last state
     pytest.states = states

node-hub/dora-ugv/dora_ugv/main.py

@@ -7,10 +7,11 @@ except ImportError as err:
     )
     raise err
 
-from dora import Node
-import pyarrow as pa
 import os
 
+import pyarrow as pa
+from dora import Node
+
 
 def main():
     # Create an instance of HunterRobot

node-hub/dora-vad/dora_vad/main.py

@@ -1,9 +1,10 @@
-from dora import Node
-import pyarrow as pa
-import numpy as np
 import os
-from silero_vad import load_silero_vad, get_speech_timestamps
+
+import numpy as np
+import pyarrow as pa
 import torch
+from dora import Node
+from silero_vad import get_speech_timestamps, load_silero_vad
 
 model = load_silero_vad()
 MIN_SILENCE_DURATION_MS = int(os.getenv("MIN_SILENCE_DURATION_MS", "200"))
@@ -38,7 +39,6 @@ def main():
                 len(speech_timestamps) > 0
                 and len(last_audios) > MIN_AUDIO_SAMPLING_DURAION_S
             ):
-
                 # Check if the audio is not cut at the end. And only return if there is a long time spent
                 if speech_timestamps[-1]["end"] == len(audio):
                     continue

node-hub/dora-yolo/dora_yolo/main.py

@@ -3,9 +3,8 @@ import os
 
 import numpy as np
 import pyarrow as pa
-from ultralytics import YOLO
-
 from dora import Node
+from ultralytics import YOLO
 
 
 def main():

node-hub/llama-factory-recorder/llama_factory_recorder/main.py

@@ -1,11 +1,12 @@
-import os
 import json
-from dora import Node
+import os
+from pathlib import Path
+
+import cv2
 import numpy as np
 import pyarrow as pa
+from dora import Node
 from PIL import Image
-from pathlib import Path
-import cv2
 
 DEFAULT_QUESTION = os.getenv(
     "DEFAULT_QUESTION",
@@ -94,9 +95,9 @@ def main():
     pa.array([])  # initialize pyarrow array
     node = Node()
 
-    assert os.getenv(
-        "LLAMA_FACTORY_ROOT_PATH"
-    ), "LLAMA_FACTORY_ROOT_PATH is not set, Either git clone the repo or set the environment variable"
+    assert os.getenv("LLAMA_FACTORY_ROOT_PATH"), (
+        "LLAMA_FACTORY_ROOT_PATH is not set, Either git clone the repo or set the environment variable"
+    )
     llama_factory_root_path = Path(os.getenv("LLAMA_FACTORY_ROOT_PATH")) / "data"
 
     entry_name = os.getenv("ENTRY_NAME", "dora_demo")

node-hub/opencv-plot/opencv_plot/main.py

@@ -4,7 +4,6 @@ import os
 import cv2
 import numpy as np
 import pyarrow as pa
-
 from dora import Node
 
 RUNNER_CI = True if os.getenv("CI") == "true" else False
@@ -76,7 +75,6 @@ def yuv420p_to_bgr_opencv(yuv_array, width, height):
 
 
 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="OpenCV Plotter: This node is used to plot text and bounding boxes on an image."
@@ -168,7 +166,6 @@ def main():
                     plot.frame = cv2.imdecode(storage, cv2.IMREAD_COLOR)
 
                 elif encoding == "yuv420":
-
                     storage = storage.to_numpy()
 
                     # Convert back to BGR results in more saturated image.

node-hub/opencv-video-capture/opencv_video_capture/main.py

@@ -5,7 +5,6 @@ import time
 import cv2
 import numpy as np
 import pyarrow as pa
-
 from dora import Node
 
 RUNNER_CI = True if os.getenv("CI") == "true" else False
@@ -77,7 +76,6 @@ def main():
     pa.array([])  # initialize pyarrow array
 
     for event in node:
-
         # Run this example in the CI for 10 seconds only.
         if RUNNER_CI and time.time() - start_time > 10:
             break

node-hub/pyarrow-assert/pyarrow_assert/main.py

@@ -1,6 +1,6 @@
 import argparse
-import os
 import ast
+import os
 
 import pyarrow as pa
 from dora import Node
@@ -9,7 +9,6 @@ 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")
 

node-hub/pyarrow-sender/pyarrow_sender/main.py

@@ -1,16 +1,14 @@
 import argparse
-import os
 import ast
+import os
 
 import pyarrow as pa
-
 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")
 

node-hub/terminal-input/terminal_input/main.py

@@ -1,16 +1,15 @@
 import argparse
-import os
 import ast
+import os
 import time
-import pyarrow as pa
 
+import pyarrow as pa
 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")