diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index eedf6d939748..744efc55f41b 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -11,12 +11,12 @@ repos:
       - id: requirements-txt-fixer
 
   - repo: https://github.com/MarcoGorelli/auto-walrus
-    rev: 0.3.3
+    rev: 0.3.4
     hooks:
       - id: auto-walrus
 
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.4.1
+    rev: v0.4.2
     hooks:
       - id: ruff
       - id: ruff-format
@@ -47,7 +47,7 @@ repos:
       - id: validate-pyproject
 
   - repo: https://github.com/pre-commit/mirrors-mypy
-    rev: v1.9.0
+    rev: v1.10.0
     hooks:
       - id: mypy
         args:
diff --git a/data_structures/arrays/sudoku_solver.py b/data_structures/arrays/sudoku_solver.py
index 5c1cff06f9d4..a8157a520c97 100644
--- a/data_structures/arrays/sudoku_solver.py
+++ b/data_structures/arrays/sudoku_solver.py
@@ -150,7 +150,7 @@ def time_solve(grid):
             display(grid_values(grid))
             if values:
                 display(values)
-            print("(%.5f seconds)\n" % t)
+            print(f"({t:.5f} seconds)\n")
         return (t, solved(values))
 
     times, results = zip(*[time_solve(grid) for grid in grids])
@@ -217,4 +217,4 @@ def shuffled(seq):
         start = time.monotonic()
         solve(puzzle)
         t = time.monotonic() - start
-        print("Solved: %.5f sec" % t)
+        print(f"Solved: {t:.5f} sec")
diff --git a/neural_network/input_data.py b/neural_network/input_data.py
index d189e3f9e0d9..f90287fe3f5b 100644
--- a/neural_network/input_data.py
+++ b/neural_network/input_data.py
@@ -156,7 +156,8 @@ def __init__(
         self._rng = np.random.default_rng(seed1 if seed is None else seed2)
         dtype = dtypes.as_dtype(dtype).base_dtype
         if dtype not in (dtypes.uint8, dtypes.float32):
-            raise TypeError("Invalid image dtype %r, expected uint8 or float32" % dtype)
+            msg = f"Invalid image dtype {dtype!r}, expected uint8 or float32"
+            raise TypeError(msg)
         if fake_data:
             self._num_examples = 10000
             self.one_hot = one_hot