Use ruff as linter (#741)

* flake8 -> ruff
* fix import rules

.github/workflows/python-app.yml

@@ -25,14 +25,10 @@ jobs:
         uv venv --python ${{ matrix.python-version }}
         source .venv/bin/activate
         uv sync
-    - name: Lint with flake8
+    - name: Lint with ruff
       run: |
         source .venv/bin/activate
-        
-        # stop the build if there are Python syntax errors or undefined names
-        flake8 tensorboardX --count --select=E9,F63,F7,F82 --show-source --statistics
-        # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
-        flake8 tensorboardX --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
+        ruff check tensorboardX/
     - name: Test with pytest
       env:
           MPLBACKEND: Agg

pyproject.toml

@@ -20,7 +20,6 @@ dev = [
     "pytest-cov>=6.0.0",
     "pytest>=8.3.4",
     "protobuf==4.22.3",
-    "flake8>=7.1.1",
     "torch>=2.5.1",
     "torchvision>=0.20.1",
     "numpy>=2.0.2",
@@ -32,5 +31,32 @@ dev = [
     "visdom>=0.2.4",
     "onnx>=1.17.0",
     "imageio==2.27",
+    "ruff>=0.8.4",
 ]
 
+[tool.ruff]
+# Exclude a variety of commonly ignored directories.
+exclude = [
+    "proto",
+]
+
+[tool.ruff.lint]
+# Enable Pyflakes (`F`) and a subset of the pycodestyle (`E`)  codes by default.
+# Unlike Flake8, Ruff doesn't enable pycodestyle warnings (`W`) or
+# McCabe complexity (`C901`) by default.
+select = [
+    # pycodestyle
+    "E",
+    # Pyflakes
+    "F",
+    # pyupgrade
+#    "UP",
+    # flake8-bugbear
+#    "B",
+    # flake8-simplify
+#    "SIM",
+    # isort
+    "I",
+]
+ignore = ["F401", "E501", "E721", "E741"]
+

tensorboardX/__init__.py

@@ -1,10 +1,10 @@
 """A module for visualization with tensorboard
 """
 
+from .global_writer import GlobalSummaryWriter
 from .record_writer import RecordWriter
 from .torchvis import TorchVis
 from .writer import FileWriter, SummaryWriter
-from .global_writer import GlobalSummaryWriter
 
 try:
     from ._version import __version__

tensorboardX/comet_utils.py

@@ -1,10 +1,13 @@
-import logging
-import json
 import functools
+import json
+import logging
 from io import BytesIO
-from google.protobuf.json_format import MessageToJson
+
 import numpy as np
+from google.protobuf.json_format import MessageToJson
+
 from .summary import _clean_tag
+
 try:
     import comet_ml
     comet_installed = True

tensorboardX/embedding.py

@@ -58,10 +58,12 @@ def make_tsv(metadata, save_path, metadata_header=None):
 # https://github.com/tensorflow/tensorboard/issues/44 image label will be squared
 def make_sprite(label_img, save_path):
     import math
+
     import numpy as np
-    from .x2num import make_np
-    from .utils import make_grid
     from PIL import Image
+
+    from .utils import make_grid
+    from .x2num import make_np
     # this ensures the sprite image has correct dimension as described in
     # https://www.tensorflow.org/get_started/embedding_viz
     # There are some constraints for the sprite image:

tensorboardX/event_file_writer.py

@@ -14,16 +14,14 @@
 # ==============================================================================
 """Writes events to disk in a logdir."""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
+from __future__ import absolute_import, division, print_function
 
+import multiprocessing
 import os
+import queue
 import socket
 import threading
 import time
-import multiprocessing
-import queue
 
 from .proto import event_pb2
 from .record_writer import RecordWriter, directory_check

tensorboardX/global_writer.py

@@ -1,6 +1,7 @@
-from .writer import SummaryWriter
-from multiprocessing import Value
 import multiprocessing as mp
+from multiprocessing import Value
+
+from .writer import SummaryWriter
 
 global _writer
 _writer = None

tensorboardX/onnx_graph.py

@@ -1,8 +1,8 @@
+from .proto.attr_value_pb2 import AttrValue
 from .proto.graph_pb2 import GraphDef
 from .proto.node_def_pb2 import NodeDef
-from .proto.versions_pb2 import VersionDef
-from .proto.attr_value_pb2 import AttrValue
 from .proto.tensor_shape_pb2 import TensorShapeProto
+from .proto.versions_pb2 import VersionDef
 
 
 def load_onnx_graph(fname):

tensorboardX/openvino_graph.py

@@ -1,8 +1,8 @@
+from .proto.attr_value_pb2 import AttrValue
 from .proto.graph_pb2 import GraphDef
 from .proto.node_def_pb2 import NodeDef
-from .proto.versions_pb2 import VersionDef
-from .proto.attr_value_pb2 import AttrValue
 from .proto.tensor_shape_pb2 import TensorShapeProto
+from .proto.versions_pb2 import VersionDef
 
 
 def load_openvino_graph(fname):

tensorboardX/record_writer.py

@@ -3,12 +3,13 @@
 The code was borrowed from https://github.com/TeamHG-Memex/tensorboard_logger
 """
 
-import os
 import copy
 import io
+import os
 import os.path
 import re
 import struct
+
 try:
     import boto3
     S3_ENABLED = True
@@ -22,7 +23,6 @@
 
 from .crc32c import crc32c
 
-
 _VALID_OP_NAME_START = re.compile('^[A-Za-z0-9.]')
 _VALID_OP_NAME_PART = re.compile('[A-Za-z0-9_.\\-/]+')
 

tensorboardX/summary.py

@@ -1,25 +1,23 @@
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
+from __future__ import absolute_import, division, print_function
 
 import logging
-import numpy as np
 import os
 import re as _re
 
-# pylint: disable=unused-import
+import numpy as np
 
-from .proto.summary_pb2 import Summary
-from .proto.summary_pb2 import HistogramProto
-from .proto.summary_pb2 import SummaryMetadata
-from .proto.tensor_pb2 import TensorProto
-from .proto.tensor_shape_pb2 import TensorShapeProto
+from .proto import layout_pb2
+from .proto.plugin_mesh_pb2 import MeshPluginData
 from .proto.plugin_pr_curve_pb2 import PrCurvePluginData
 from .proto.plugin_text_pb2 import TextPluginData
-from .proto.plugin_mesh_pb2 import MeshPluginData
-from .proto import layout_pb2
-from .x2num import make_np
+
+# pylint: disable=unused-import
+from .proto.summary_pb2 import HistogramProto, Summary, SummaryMetadata
+from .proto.tensor_pb2 import TensorProto
+from .proto.tensor_shape_pb2 import TensorShapeProto
 from .utils import _prepare_video, convert_to_HWC, convert_to_NTCHW
+from .x2num import make_np
+
 logger = logging.getLogger(__name__)
 
 _INVALID_TAG_CHARACTERS = _re.compile(r'[^-/\w\.]')
@@ -68,8 +66,19 @@ def _draw_single_box(image, xmin, ymin, xmax, ymax, display_str, color='black',
 
 
 def hparams(hparam_dict=None, metric_dict=None):
-    from tensorboardX.proto.plugin_hparams_pb2 import HParamsPluginData, SessionEndInfo, SessionStartInfo
-    from tensorboardX.proto.api_pb2 import Experiment, HParamInfo, MetricInfo, MetricName, Status, DataType
+    from tensorboardX.proto.api_pb2 import (
+        DataType,
+        Experiment,
+        HParamInfo,
+        MetricInfo,
+        MetricName,
+        Status,
+    )
+    from tensorboardX.proto.plugin_hparams_pb2 import (
+        HParamsPluginData,
+        SessionEndInfo,
+        SessionStartInfo,
+    )
 
     PLUGIN_NAME = 'hparams'
     PLUGIN_DATA_VERSION = 0
@@ -322,8 +331,8 @@ def draw_boxes(disp_image, boxes, labels=None):
 def make_image(tensor, rescale=1, rois=None, labels=None):
     """Convert an numpy representation image to Image protobuf"""
     import PIL
-    from PIL import Image
     from packaging.version import parse
+    from PIL import Image
     height, width, channel = tensor.shape
     scaled_height = int(height * rescale)
     scaled_width = int(width * rescale)
@@ -372,9 +381,10 @@ def make_video(tensor, fps):
               "Some packages could be missing [imageio, requests]")
         return
 
-    import moviepy.version
     import tempfile
 
+    import moviepy.version
+
     t, h, w, c = tensor.shape
 
     # encode sequence of images into gif string
@@ -410,6 +420,7 @@ def audio(tag, tensor, sample_rate=44100):
         The values should between [-1, 1]. We also accepts 1-D tensor.
     """
     import io
+
     import soundfile
     tensor = make_np(tensor)
     if abs(tensor).max() > 1:
@@ -435,9 +446,7 @@ def audio(tag, tensor, sample_rate=44100):
 
 
 def custom_scalars(layout):
-    categoriesnames = layout.keys()
     categories = []
-    layouts = []
     for k, v in layout.items():
         charts = []
         for chart_name, chart_meatadata in v.items():

tensorboardX/torchvis.py

@@ -1,15 +1,11 @@
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-from __future__ import unicode_literals
+from __future__ import absolute_import, division, print_function, unicode_literals
 
 import gc
 import time
-
 from functools import wraps
-from .writer import SummaryWriter
-from .visdom_writer import VisdomWriter
 
+from .visdom_writer import VisdomWriter
+from .writer import SummaryWriter
 
 # Supports both TensorBoard and Visdom (no embedding or graph visualization with Visdom)
 vis_formats = {'tensorboard': SummaryWriter, 'visdom': VisdomWriter}

tensorboardX/utils.py

@@ -13,8 +13,8 @@ def figure_to_image(figures, close=True):
     """
     import numpy as np
     try:
-        import matplotlib.pyplot as plt
         import matplotlib.backends.backend_agg as plt_backend_agg
+        import matplotlib.pyplot as plt
     except ModuleNotFoundError:
         print('please install matplotlib')
 

tensorboardX/visdom_writer.py

@@ -1,9 +1,10 @@
 import gc
-import numpy as np
-import math
 import json
+import math
 import time
 
+import numpy as np
+
 from .summary import compute_curve
 from .utils import figure_to_image
 from .x2num import make_np

tensorboardX/writer.py

@@ -1,31 +1,41 @@
 """Provides an API for writing protocol buffers to event files to be
 consumed by TensorBoard for visualization."""
 
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
+from __future__ import absolute_import, division, print_function
 
+import atexit
 import json
+import logging
 import os
-import numpy
 import time
-import logging
-import atexit
-from typing import Union, Optional, Dict, List
+from typing import Dict, List, Optional, Union
+
+import numpy
 
 from .comet_utils import CometLogger
-from .embedding import make_mat, make_sprite, make_tsv, append_pbtxt
+from .embedding import append_pbtxt, make_mat, make_sprite, make_tsv
 from .event_file_writer import EventFileWriter
 from .onnx_graph import load_onnx_graph
 from .openvino_graph import load_openvino_graph
-from .proto import event_pb2
-from .proto import summary_pb2
-from .proto.event_pb2 import SessionLog, Event
-from .utils import figure_to_image
+from .proto import event_pb2, summary_pb2
+from .proto.event_pb2 import Event, SessionLog
 from .summary import (
-    scalar, histogram, histogram_raw, image, audio, text,
-    pr_curve, pr_curve_raw, video, custom_scalars, image_boxes, mesh, hparams
+    audio,
+    custom_scalars,
+    histogram,
+    histogram_raw,
+    hparams,
+    image,
+    image_boxes,
+    mesh,
+    pr_curve,
+    pr_curve_raw,
+    scalar,
+    text,
+    video,
 )
+from .utils import figure_to_image
+
 logger = logging.getLogger(__name__)
 
 numpy_compatible = numpy.ndarray
@@ -712,7 +722,7 @@ def add_images(
             import torch
             try:
                 img_tensor = torch.stack(img_tensor, 0)
-            except TypeError as e:
+            except TypeError:
                 import numpy as np
                 img_tensor = np.stack(img_tensor, 0)
 

tensorboardX/x2num.py

@@ -1,10 +1,10 @@
 # DO NOT alter/distruct/free input object !
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
+from __future__ import absolute_import, division, print_function
 
 import logging
+
 import numpy as np
+
 logger = logging.getLogger(__name__)