[ruff] isort (#3294)

### Changes

Use ruff isort instead of direct isort

Author: AlexanderDokuchaev

.pre-commit-config.yaml

@@ -14,12 +14,6 @@ repos:
       - id: black
         files: '^.*\.py'
 
-  - repo: https://github.com/pycqa/isort
-    rev: 5.13.0
-    hooks:
-      - id: isort
-        name: isort (python)
-
   - repo: https://github.com/igorshubovych/markdownlint-cli
     rev: v0.43.0
     hooks:

docs/styleguide/PyGuide.md

@@ -61,15 +61,15 @@ the [PEP 8 -- Style Guide for Python Code](https://www.python.org/dev/peps/pep-0
 ## 2 Automating Code Formatting
 
 To maintain consistency and readability throughout the codebase, we use the [black](https://github.com/psf/black)
-and [isort](https://github.com/PyCQA/isort) tools for formatting. Before committing any changes,
+and [ruff](https://docs.astral.sh/ruff/) tools for formatting. Before committing any changes,
 it's important to run a pre-commit command to ensure that the code is properly formatted.
 You can use the following commands for this:
 
 ```bash
 make pre-commit
 ```
 
-Also recommend configuring your IDE to run Black and isort tools automatically when saving files.
+Also recommend configuring your IDE to run Black and Ruff tools automatically when saving files.
 
 Automatic code formatting is mandatory for all Python files, but you can disable it for specific cases if required:
 

examples/post_training_quantization/torch/ssd300_vgg16/main.py

@@ -8,7 +8,7 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-
+# isort: off
 import re
 import subprocess
 from pathlib import Path

nncf/experimental/torch/nas/bootstrapNAS/elasticity/multi_elasticity_handler.py

@@ -10,9 +10,8 @@
 # limitations under the License.
 import inspect
 from collections import OrderedDict
-from typing import Any, Dict, List, Optional
+from typing import Any, Dict, List, Optional, Tuple
 from typing import OrderedDict as OrderedDictType
-from typing import Tuple
 
 from nncf.common.logging import nncf_logger
 from nncf.common.pruning.weights_flops_calculator import WeightsFlopsCalculator

pyproject.toml

@@ -78,14 +78,6 @@ line-length = 120
 [tool.md_dead_link_check]
 exclude_files = ["ReleaseNotes.md"]
 
-[tool.isort]
-line_length = 120
-force_single_line = true
-profile = "black"
-single_line_exclusions = "typing"
-skip_glob = "examples/post_training_quantization/torch/ssd300_vgg16/main.py"
-known_third_party = "datasets"
-
 [tool.mypy]
 follow_imports = "silent"
 strict = true
@@ -153,15 +145,16 @@ ignore = [
     "D417", # undocumented-param
 ]
 select = [
-    "E", # pycodestyle rules
-    "F", # pyflakes rules
     "CPY001", # copyright check
-    "NPY", # numpy rules
-    "UP", # pyupgrade
+    "D", # pydocstyle
+    "E", # pycodestyle rules
     "EM",  # flake8-errmsg
+    "F", # pyflakes rules
+    "I",  # isort
     "INP", # flake8-no-pep420
     "ISC", # flake8-implicit-str-concat
-    "D", # pydocstyle
+    "NPY", # numpy rules
+    "UP", # pyupgrade
 ]
 extend-select = [
     "SIM", # https://pypi.org/project/flake8-simplify
@@ -189,6 +182,11 @@ notice-rgx = """\
 # limitations under the License.
 """
 
+[tool.ruff.lint.isort]
+force-single-line = true
+known-third-party = ["datasets"]
+single-line-exclusions = ["typing"]
+
 [tool.pytest.ini_options]
 pythonpath = "."
 

tests/cross_fw/sdl/fuzz/quantize_api.py

@@ -14,9 +14,10 @@
 from tests.cross_fw.shared.paths import TEST_ROOT
 
 with atheris.instrument_imports():
-    import nncf
     import sys
 
+    import nncf
+
 from random import randint
 from random import seed
 

tests/torch2/function_hook/quantization/test_quantized_graphs.py

@@ -24,10 +24,10 @@
 from tests.cross_fw.test_templates.helpers import RoPEModel
 from tests.cross_fw.test_templates.helpers import ScaledDotProductAttentionModel
 from tests.torch import test_models
-from tests.torch2.utils import compare_with_reference_file
-from tests.torch2.utils import to_comparable_nx_graph
 from tests.torch.quantization.test_algo_quantization import SharedLayersModel
 from tests.torch.test_compressed_graph import ModelDesc
+from tests.torch2.utils import compare_with_reference_file
+from tests.torch2.utils import to_comparable_nx_graph
 
 REF_DIR = TEST_ROOT / "torch2" / "data" / "quantization" / "test_quantized_graphs"