[CHORE#86] CI ruff 버전을 uv.lock 과 고정, 0.17 포맷 드리프트 정리

.claude/rules/04-error-handling.md

@@ -60,15 +60,19 @@ except FileNotFoundError:
 class GraphLMError(Exception):
     """GraphLM 패키지의 모든 사용자 정의 예외 base."""
 
+
 class DataLoadError(GraphLMError):
     """데이터 로드 실패."""
 
+
 class ConfigError(GraphLMError):
     """잘못된 실험 설정."""
 
+
 class ModelError(GraphLMError):
     """모델 정의/forward 단계 오류."""
 
+
 class ReproducibilityError(GraphLMError):
     """시드 고정 실패 / 결정론 깨짐 감지."""
 ```
@@ -84,13 +88,13 @@ base 클래스가 있으면 호출자가 `except GraphLMError` 로 라이브러
 ```python
 from tenacity import retry, stop_after_attempt, wait_exponential
 
+
 @retry(
     stop=stop_after_attempt(3),
     wait=wait_exponential(multiplier=1, min=1, max=10),
     reraise=True,
 )
-def download_dataset(url: str) -> Path:
-    ...
+def download_dataset(url: str) -> Path: ...
 ```
 
 학습 루프 안의 NaN/Inf 감지 같은 "재시도하면 의미 없는" 케이스는 retry 대신 즉시 fail.
@@ -121,6 +125,7 @@ import logging
 
 logger = logging.getLogger(__name__)
 
+
 def train_epoch(model, loader, optimizer) -> dict:
     logger.info("epoch 시작", extra={"n_batches": len(loader)})
     for batch_idx, batch in enumerate(loader):
@@ -149,12 +154,15 @@ def train_epoch(model, loader, optimizer) -> dict:
 
 ```python
 # Good
-logger.info("eval 완료", extra={
-    "split": "test",
-    "accuracy": 0.873,
-    "loss": 0.42,
-    "n_samples": 1024,
-})
+logger.info(
+    "eval 완료",
+    extra={
+        "split": "test",
+        "accuracy": 0.873,
+        "loss": 0.42,
+        "n_samples": 1024,
+    },
+)
 
 # Bad — 검색·집계 불가
 logger.info(f"eval 완료: test split, acc=0.873, loss=0.42, n=1024")
@@ -202,9 +210,7 @@ def assert_deterministic(seed: int, run_fn) -> None:
     set_seed(seed)
     result_b = run_fn()
     if not torch.allclose(result_a, result_b):
-        raise ReproducibilityError(
-            f"동일 시드 ({seed}) 에서 결과 불일치 — 결정론 깨짐"
-        )
+        raise ReproducibilityError(f"동일 시드 ({seed}) 에서 결과 불일치 — 결정론 깨짐")
 ```
 
 CI 또는 디버깅 모드에서 활성화. 매 학습마다는 비용 과다.

.claude/rules/05-testing.md

@@ -121,18 +121,18 @@ def small_graph():
 
 ```python
 @pytest.mark.slow
-def test_full_epoch_runs():
-    ...
+def test_full_epoch_runs(): ...
+
 
 @pytest.mark.gpu
 def test_cuda_forward():
     if not torch.cuda.is_available():
         pytest.skip("CUDA 미사용")
     ...
 
+
 @pytest.mark.network
-def test_hf_hub_download():
-    ...
+def test_hf_hub_download(): ...
 ```
 
 `pyproject.toml` 에 마커 등록:

.claude/rules/06-code-style.md

@@ -60,6 +60,7 @@ def normalize_features(
 ) -> Tensor:
     return x / (x.norm(dim=-1, keepdim=True) + eps)
 
+
 # Bad — 타입 없음
 def normalize_features(x, eps=1e-6):
     return x / (x.norm(dim=-1, keepdim=True) + eps)
@@ -70,8 +71,8 @@ def normalize_features(x, eps=1e-6):
 ```python
 from typing import TypeAlias
 
-NodeFeatures: TypeAlias = Tensor          # shape: [n_nodes, feat_dim]
-EdgeIndex: TypeAlias = Tensor             # shape: [2, n_edges]
+NodeFeatures: TypeAlias = Tensor  # shape: [n_nodes, feat_dim]
+EdgeIndex: TypeAlias = Tensor  # shape: [2, n_edges]
 GraphBatch: TypeAlias = dict[str, Tensor]
 ```
 
@@ -90,6 +91,7 @@ def process(item: Item) -> Result:
         return item.cache
     return compute(item)
 
+
 # Bad — else 중첩
 def process(item: Item) -> Result:
     if item.valid:
@@ -143,8 +145,8 @@ class GraphEncoder(nn.Module):
         super().__init__()
         ...
 
-    def forward(self, x: Tensor, edge_index: Tensor) -> Tensor:
-        ...
+    def forward(self, x: Tensor, edge_index: Tensor) -> Tensor: ...
+
 
 # Bad — 모델이 데이터 로드까지
 class GraphEncoder(nn.Module):
@@ -287,6 +289,7 @@ def append_item(item, items=[]):
     items.append(item)
     return items
 
+
 # Good
 def append_item(item, items=None):
     if items is None:
@@ -319,6 +322,7 @@ def is_valid(s: str) -> bool:
     result = len(s) > 0
     return result
 
+
 # Good
 def is_valid(s: str) -> bool:
     return len(s) > 0
@@ -478,16 +482,16 @@ from graphlm.utils import set_seed
 logger = logging.getLogger(__name__)
 DEFAULT_HIDDEN_DIM = 128
 
+
 # 5. Public API (클래스 / 함수)
-class GraphEncoder(nn.Module):
-    ...
+class GraphEncoder(nn.Module): ...
+
+
+def aggregate(x: Tensor, edge_index: Tensor) -> Tensor: ...
 
-def aggregate(x: Tensor, edge_index: Tensor) -> Tensor:
-    ...
 
 # 6. Private helpers
-def _normalize(x: Tensor) -> Tensor:
-    ...
+def _normalize(x: Tensor) -> Tensor: ...
 ```
 
 ## Code Review Checklist

.github/copilot-instructions.md

@@ -174,10 +174,12 @@ def process(item: Item) -> Result:
 
 ```python
 # ❌ Magic numbers
-if score > 0.85: ...
+if score > 0.85:
+    ...
 # ✅ Named constants
 ACCEPT_THRESHOLD = 0.85
-if score > ACCEPT_THRESHOLD: ...
+if score > ACCEPT_THRESHOLD:
+    ...
 ```
 
 ```python
@@ -192,17 +194,21 @@ def append(item, items=None):
 
 ```python
 # ❌ bare except
-try: risky()
-except: pass
+try:
+    risky()
+except:
+    pass
 # ✅ 구체적 예외
-try: risky()
+try:
+    risky()
 except (ValueError, RuntimeError) as err:
     logger.warning("recovered", exc_info=err)
 ```
 
 ```python
 # ❌ wildcard import
 from graphlm.models import *
+
 # ✅ 명시적 import
 from graphlm.models import GraphEncoder
 ```
@@ -267,14 +273,18 @@ except FileNotFoundError as err:
 
 ```python
 import logging
+
 logger = logging.getLogger(__name__)
 
 # Good — structured
-logger.info("eval 완료", extra={
-    "split": "test",
-    "accuracy": 0.873,
-    "n_samples": 1024,
-})
+logger.info(
+    "eval 완료",
+    extra={
+        "split": "test",
+        "accuracy": 0.873,
+        "n_samples": 1024,
+    },
+)
 
 # Bad — 문자열 보간
 logger.info(f"eval 완료: acc=0.873, n=1024")
@@ -307,10 +317,13 @@ def test_load_dataset_returns_expected_size(tmp_path):
 ### Parametrize
 
 ```python
-@pytest.mark.parametrize("input_, expected", [
-    ("http://example.com", "https://example.com"),
-    ("https://www.example.com", "https://example.com"),
-])
+@pytest.mark.parametrize(
+    "input_, expected",
+    [
+        ("http://example.com", "https://example.com"),
+        ("https://www.example.com", "https://example.com"),
+    ],
+)
 def test_normalize_url(input_, expected):
     assert normalize_url(input_) == expected
 ```

.github/workflows/ci-quality.yml

@@ -27,7 +27,9 @@ jobs:
           cache: pip
 
       - name: Install ruff
-        run: pip install ruff
+        # uv.lock 의 ruff 버전과 맞춘다 — 버전이 다르면 로컬과 CI 의 포맷 판정이 어긋난다 (이슈 #86).
+        # ruff 를 올릴 때는 uv.lock · 이 줄 · 포맷 결과를 같은 PR 에서 함께 바꾼다.
+        run: pip install "ruff==0.17.0"
 
       - name: Check ruff format
         run: |