style: allow single-line if statements

examples/http/_bench/benchmark.py

@@ -250,8 +250,7 @@
             f"std_ratio: {std_ratio}",
           )
 
-          if len(m) >= TARGET_MEASUREMENTS and std_ratio <= MAX_STD_RATIO:
-            break
+          if len(m) >= TARGET_MEASUREMENTS and std_ratio <= MAX_STD_RATIO: break
 
         m = remove_outliers(measurements, k=IQR_MULTIPLIER)
         mean_rps = np.mean(m)

notebooks/machine_learning/nmf.py

@@ -28,11 +28,8 @@ def generate_led_digit(
   shape: tuple = (11, 6),
   pad: int = 1,
 ) -> np.ndarray:
-  if digit is not None:
-    segment = segments[digit]
-
-  if segment is None:
-    return np.zeros(shape)
+  if digit is not None: segment = segments[digit]
+  if segment is None: return np.zeros(shape)
 
   height, width = shape
   segment_height = (height - 3) // 2

notebooks/random/simple_benchmarks.py

@@ -6,8 +6,7 @@
 # %%timeit
 total = 0
 
-for _ in range(1_000_000):
-  total += 1  # noqa: SIM113
+for _ in range(1_000_000): total += 1  # noqa: SIM113
 
 # %%
 # %%timeit
@@ -23,8 +22,7 @@ def fibonacci(n: int) -> int:
   a = 0
   b = 1
 
-  if n == 0:
-    return a
+  if n == 0: return a
 
   for _ in range(1, n):
     c = a + b

notebooks/reinforcement_learning/frozen_lake.py

@@ -27,8 +27,7 @@
   state, reward, terminated, _, _ = env.step(action)
   images.append(cast("np.ndarray", env.render()))
 
-  if terminated:
-    print("You reached the goal!")
+  if terminated: print("You reached the goal!")
 
 
 # %%
@@ -92,8 +91,7 @@ def compute_state_value(
     visited_states.append(state)
     value += reward + gamma * value
 
-    if terminate:
-      break
+    if terminate: break
 
     state = next_state
 

packages/config/ruff.toml

@@ -77,6 +77,7 @@ ignore = [
   "E111",  # indentation-with-invalid-multiple
   "E114",  # indentation-with-invalid-multiple-comment
   "E501",  # line-too-long
+  "E701",  # multiple-statements-on-one-line-colon
   "E731",  # lambda-assignment
   "E741",  # ambiguous-variable-name
   "N801",  # invalid-class-name