diff --git a/.github/workflows/lint.yml b/.github/workflows/lint.yml
index 435392e..c6e5ecf 100644
--- a/.github/workflows/lint.yml
+++ b/.github/workflows/lint.yml
@@ -21,9 +21,9 @@ jobs:
         uses: astral-sh/setup-uv@v6
       - name: Install project
         run: uv sync --locked --dev
-      - name: Run ruff
+      - name: Run ruff lint
         run: uv run ruff check
-      - name: Run black
-        run: uv run black --check .
+      - name: Run ruff format check
+        run: uv run ruff format --check
       - name: Run mypy
         run: uv run make mypy
diff --git a/Makefile b/Makefile
index 6d32a45..da7cfbc 100644
--- a/Makefile
+++ b/Makefile
@@ -1,11 +1,11 @@
 RUFF_FLAGS =
-BLACK_FLAGS =
+FORMAT_FLAGS =
 MYPY_FLAGS =
 
 MYPY_TARGETS = \
     src/odil/history.py \
 
-default:
+default: lint format
 
 data:
 	git clone -b data --single-branch git@github.com:cselab/odil.git data
@@ -14,10 +14,14 @@ release:
 	V=$$(sed -rn 's/^version = "(.*)"$$/\1/p' pyproject.toml) && git archive --prefix="odil-$$V/" -o "odil-$$V.tar.gz" HEAD
 
 lint:
-	ruff check --fix $(RUFF_FLAGS) .
-	black $(BLACK_FLAGS) .
+	ruff check --fix $(RUFF_FLAGS)
+
+format:
+	ruff format $(FORMAT_FLAGS)
+
+check: lint format
 
 mypy:
 	mypy $(MYPY_FLAGS) $(MYPY_TARGETS)
 
-.PHONY: default release lint mypy
+.PHONY: default data release lint format check mypy
diff --git a/examples/basic/fields.py b/examples/basic/fields.py
index 7196f87..cb31bf7 100755
--- a/examples/basic/fields.py
+++ b/examples/basic/fields.py
@@ -57,7 +57,6 @@ def parse_args():
 
 
 def plot(problem, state, epoch, frame, cbinfo=None):
-
     domain = problem.domain
     fig, ax = plt.subplots(figsize=(4, 2))
     kw = dict(vmin=0, vmax=1, cmap="Greys", clip_on=False, lw=0.5)
diff --git a/pyproject.toml b/pyproject.toml
index d610b68..2b44843 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -40,27 +40,27 @@ jax = ["jax[cuda13]>=0.7.0"]
 [dependency-groups]
 dev = [
     "pytest>=7.4.4",
-    "black[jupyter]>=25.0.0",
     "ruff>=0.14.0",
     "mypy>=1.18.2",
 ]
 
-[tool.black]
+[tool.ruff]
 line-length = 120
-target-version = ['py312']
+target-version = "py312"
 
-[tool.ruff]
-lint.select = [
+[tool.ruff.lint]
+select = [
     "E",  # Style errors
     "W",  # Style warnings
     "F",  # Logical errors
     "I",  # Import sorting
 ]
-lint.ignore = [
+ignore = [
     "E741",  # Ambiguous variable name
 ]
-output-format = 'concise'
-line-length = 120
+
+[tool.ruff.format]
+quote-style = "double"
 
 [tool.mypy]
 python_version = "3.12"
diff --git a/src/odil/backend.py b/src/odil/backend.py
index 8722cb6..32e654d 100644
--- a/src/odil/backend.py
+++ b/src/odil/backend.py
@@ -10,7 +10,6 @@
 
 
 class ModBase:
-
     def __init__(self, mod=None):
         assert mod is not None
         self.mod = mod
@@ -43,7 +42,6 @@ def __init__(self, mod=None):
 
 
 class ModNumpy(ModBase):
-
     def __init__(self, mod=None, modsp=None, jax=None):
         mod = mod or np
         super().__init__(mod)
@@ -183,7 +181,6 @@ def conv_transpose(input, filters, output_shape=None, strides=None, padding=None
 
 
 class ModTensorflow(ModBase):
-
     def __init__(self, mod=None, modsp=None):
         super().__init__(mod)
         self.batch_to_space = mod.batch_to_space
@@ -280,7 +277,6 @@ def csr_matrix(*args, **kwargs):
 
 
 class ModCupy(ModBase):
-
     def __init__(self, mod=None, modsp=None):
         super().__init__(mod)
         self.cast = lambda x, dtype: mod.array(x, dtype=dtype)
diff --git a/src/odil/cache.py b/src/odil/cache.py
index 7998a63..26db317 100644
--- a/src/odil/cache.py
+++ b/src/odil/cache.py
@@ -61,7 +61,6 @@ def save(content, path):
         raise ValueError("Unrecognized extension '{}', expected .pickle.".format(ext))
 
     def decorator(func):
-
         def inner(*args, **kwargs):
             name, ext = os.path.splitext(targetbase)
             if len(args) and name_with_arg0:
diff --git a/src/odil/core.py b/src/odil/core.py
index 0d71276..e78b6c7 100644
--- a/src/odil/core.py
+++ b/src/odil/core.py
@@ -9,7 +9,6 @@
 
 
 class Domain:
-
     def __init__(
         self,
         cshape,
@@ -504,7 +503,6 @@ def get_context(self, state, extra=None, tracers=None):
 
 
 class Field:
-
     def __init__(self, array=None, loc=None, cshape=None):
         """
         array: `ndarray`
@@ -527,7 +525,6 @@ def __repr__(self):
 
 
 class MultigridField:
-
     def __init__(self, terms=None, loc=None, factors=None, axes=None, method=None):
         """
         terms: `list` of `Field`
@@ -550,7 +547,6 @@ def __init__(self, terms=None, loc=None, factors=None, axes=None, method=None):
 
 
 class NeuralNet:
-
     def __init__(self, weights=None, biases=None, func_in=None, func_out=None, activation=None):
         """
         weights: `list` of `ndarray`
@@ -574,7 +570,6 @@ def __init__(self, weights=None, biases=None, func_in=None, func_out=None, activ
 
 
 class Array:
-
     def __init__(self, array=None, shape=None):
         """
         array: `ndarray`
@@ -593,7 +588,6 @@ def __repr__(self):
 
 
 class State:
-
     def __init__(self, fields=None, initialized=False):
         """
         fields: A dict mapping field names to state variables
@@ -863,9 +857,7 @@ def eval_neural_net(net: NeuralNet, inputs, mod, frozen=False):
 
 
 class Context:
-
     class Raw:
-
         def __init__(self, value):
             self.value = value
 
@@ -991,7 +983,6 @@ def res(*inputs):
 
 
 class Problem:
-
     def __init__(self, operator, domain, extra=None, tracers=None, jit=None):
         """
         operator: callable(mod, ctx)
@@ -1055,7 +1046,8 @@ def func(arrays):
                 assert len(nonempty) == len(set(nonempty)), "Name of fields must be unique, got {}".format(nonempty)
                 values = [f[1] if isinstance(f, tuple) else f for f in ff]
                 terms = [
-                    mod.mean(v.value) if isinstance(v, Context.Raw) else mod.mean(mod.square(v)) for v in values  #
+                    mod.mean(v.value) if isinstance(v, Context.Raw) else mod.mean(mod.square(v))
+                    for v in values  #
                 ]
                 loss = sum(terms)
                 norms = [t if isinstance(v, Context.Raw) else mod.sqrt(t) for t, v in zip(terms, values)]  #
@@ -1321,7 +1313,6 @@ def _eval_operator_grad_tf(self, state):
 
         def func(arrays, tracers):
             with tf.GradientTape(persistent=True, watch_accessed_variables=False) as tape:
-
                 domain.arrays_to_state(arrays, cache["state"])
                 ctx = Context(
                     domain,
@@ -1477,7 +1468,6 @@ def latin_hypercube(ndim, size, dtype):
 
 
 class Approx:
-
     def __init__(self, domain):
         self.domain = domain
         self.mod = domain.mod
diff --git a/src/odil/core_min.py b/src/odil/core_min.py
index 7fea3f6..0054631 100644
--- a/src/odil/core_min.py
+++ b/src/odil/core_min.py
@@ -4,7 +4,6 @@
 
 
 class Domain:
-
     def __init__(self, domain=None, ndim=None, lower=None, upper=None, dimnames=None, dtype=None, cshape=None):
         domain = domain or Namespace(ndim=None, lower=0.0, upper=1.0, dimnames=None, dtype=None, cshape=None)
         dtype = dtype or domain.dtype
diff --git a/src/odil/history.py b/src/odil/history.py
index 6894212..928b21e 100644
--- a/src/odil/history.py
+++ b/src/odil/history.py
@@ -7,7 +7,6 @@
 
 
 class History:
-
     def __init__(self, csvpath: str | None = None, warmup: int = 0):
         """
         warmup: `int`
diff --git a/src/odil/linsolver.py b/src/odil/linsolver.py
index 553ffa2..538c23c 100644
--- a/src/odil/linsolver.py
+++ b/src/odil/linsolver.py
@@ -119,9 +119,7 @@ def add_arguments(parser):
     parser.add_argument("--smooth_pre", type=int, default=2, help="Pre-smoothing steps")
     parser.add_argument("--smooth_post", type=int, default=2, help="Post-smoothing steps")
     parser.add_argument("--omega", type=float, default=0.6, help="Jacobi smoother relaxation factor")
-    parser.add_argument(
-        "--ndirect", type=int, default=3, help="Systems on smaller grids " "are solved with direct solver"
-    )
+    parser.add_argument("--ndirect", type=int, default=3, help="Systems on smaller grids are solved with direct solver")
     parser.add_argument(
         "--restriction",
         type=str,
diff --git a/src/odil/optimizer.py b/src/odil/optimizer.py
index d8bc1c7..47cfeb3 100644
--- a/src/odil/optimizer.py
+++ b/src/odil/optimizer.py
@@ -4,7 +4,6 @@
 
 
 class Optimizer:
-
     def __init__(self, name=None, displayname=None, dtype=None):
         self.name = name
         self.displayname = displayname if displayname is not None else name
@@ -20,14 +19,12 @@ def run(self, x0, loss_grad, epochs, callback=None, epoch_start=0, **kwargs):
 
 
 class EarlyStopError(Exception):
-
     def __init__(self, msg, optinfo):
         super().__init__(msg)
         self.optinfo = optinfo
 
 
 class LbfgsbOptimizer(Optimizer):
-
     def __init__(self, pgtol=1e-16, m=50, maxls=50, factr=0, dtype=None, mod=None, **kwargs):
         """
         pgtol: `float`
@@ -118,7 +115,6 @@ def func_wrap(x):
 
 
 class LbfgsOptimizer(Optimizer):
-
     def __init__(self, pgtol=1e-16, m=50, maxls=50, factr=0, dtype=None, mod=None, **kwargs):
         """
         pgtol: `float`
@@ -206,18 +202,15 @@ def stopping_condition(converged, failed):
 
 
 class AdamTfOptimizer(Optimizer):
-
     def __init__(self, dtype=None, mod=None, **kwargs):
         super().__init__(name="adam_tf", displayname="AdamTf", dtype=dtype)
         self.mod = mod
 
     def run(self, x0, loss_grad, epochs=None, callback=None, lr=1e-3, epoch_start=0, **kwargs):
-
         mod = self.mod
         tf = mod.tf
 
         class CustomModel(tf.keras.Model):
-
             def __init__(self, x):
                 super().__init__()
                 self.x = x
@@ -238,7 +231,6 @@ def train_step(self, _):
         model = CustomModel(x)
 
         class CustomCallback(tf.keras.callbacks.Callback):
-
             def on_epoch_end(self, epoch, logs=None):
                 model.epoch = epoch_start + epoch
                 if epoch > 0 and callback:
@@ -254,13 +246,11 @@ def on_epoch_end(self, epoch, logs=None):
 
 
 class GdOptimizer(Optimizer):
-
     def __init__(self, dtype=None, mod=None, **kwargs):
         super().__init__(name="gd", displayname="GD", dtype=dtype)
         self.mod = mod
 
     def run(self, x0, loss_grad, epochs=None, callback=None, lr=1e-3, epoch_start=0, **kwargs):
-
         mod = self.mod
         x = [mod.copy(e) for e in x0]
         for epoch in range(epoch_start + 1, epoch_start + epochs + 1):
@@ -278,7 +268,6 @@ def run(self, x0, loss_grad, epochs=None, callback=None, lr=1e-3, epoch_start=0,
 
 
 class AdamNativeOptimizer(Optimizer):
-
     def __init__(self, dtype=None, mod=None, **kwargs):
         super().__init__(name="adamn", displayname="AdamNative", dtype=dtype)
         self.mod = mod
diff --git a/src/odil/runtime.py b/src/odil/runtime.py
index 4aab80b..20a35fc 100644
--- a/src/odil/runtime.py
+++ b/src/odil/runtime.py
@@ -7,7 +7,7 @@
 
 if not int(os.environ.get("ODIL_MT", 0)):
     os.environ["OMP_NUM_THREADS"] = "1"
-    os.environ["XLA_FLAGS"] = "--xla_cpu_multi_thread_eigen=false " "intra_op_parallelism_threads=1"
+    os.environ["XLA_FLAGS"] = "--xla_cpu_multi_thread_eigen=false intra_op_parallelism_threads=1"
     os.environ["TENSORFLOW_INTER_OP_PARALLELISM"] = "1"
     os.environ["TENSORFLOW_INTRA_OP_PARALLELISM"] = "1"
 
diff --git a/src/odil/util.py b/src/odil/util.py
index 5810b74..b74e5bb 100644
--- a/src/odil/util.py
+++ b/src/odil/util.py
@@ -37,7 +37,6 @@ def printlog(*msg):
 
 
 class Timer:
-
     def __init__(self):
         self._starts = []  # Stack of pairs (key, time).
         self.counters = dict()  # Key to time.
@@ -47,9 +46,9 @@ def push(self, key=None):
 
     def pop(self, key=None):
         start = self._starts.pop()
-        assert (
-            start[0] is None or key is None or start[0] == key
-        ), "Inconsistent keys passed to push() and pop(): " "{:} and {:}".format(start[0], key)
+        assert start[0] is None or key is None or start[0] == key, (
+            "Inconsistent keys passed to push() and pop(): {:} and {:}".format(start[0], key)
+        )
         if key is None:
             key = start[0]
         dt = time.time() - start[1]
@@ -69,7 +68,7 @@ def get_error(u, v):
 
 def add_arguments(parser):
     parser.add_argument(
-        "--epochs", type=int, default=None, help="Maximum epochs, " "defaults to product of plot_every and frames"
+        "--epochs", type=int, default=None, help="Maximum epochs, defaults to product of plot_every and frames"
     )
     parser.add_argument("--every_factor", type=float, default=1, help="Multiplier for all *_every options")
     parser.add_argument("--plot_every", type=int, default=5, help="Epochs between plots")
@@ -82,9 +81,7 @@ def add_arguments(parser):
     parser.add_argument("--seed", default=1000, type=int, help="Seed for numpy.random and tensorflow.random")
     parser.add_argument("--plot_title", type=int, default=0, help="Enable title in plots")
     parser.add_argument("--plotext", type=str, default="pdf", help="Extension of plots")
-    parser.add_argument(
-        "--history_full", type=int, default=0, help="Number of epochs to write " "history at every point"
-    )
+    parser.add_argument("--history_full", type=int, default=0, help="Number of epochs to write history at every point")
     parser.add_argument("--montage", type=int, default=1, help="Run montage after plotting")
     parser.add_argument("--double", type=int, default=None, help="Double precision. Defaults to runtime.dtype")
     parser.add_argument("--echo", type=int, default=0, help="Echo log to stderr")
@@ -121,11 +118,9 @@ def add_arguments(parser):
     )
     parser.add_argument("--dump_data", type=int, default=1, help="Dump data_*.pickle with every plot")
     parser.add_argument(
-        "--jac_nsmp0", type=int, default=50, help="Number of samples " "for initialization of Jacobi optimizer"
-    )
-    parser.add_argument(
-        "--jac_nsmp1", type=int, default=1, help="Number of samples " "for each step of Jacobi optimizer"
+        "--jac_nsmp0", type=int, default=50, help="Number of samples for initialization of Jacobi optimizer"
     )
+    parser.add_argument("--jac_nsmp1", type=int, default=1, help="Number of samples for each step of Jacobi optimizer")
     parser.add_argument(
         "--jac_factor",
         type=float,
@@ -138,7 +133,7 @@ def add_arguments(parser):
         "--jac_epsilon",
         type=float,
         default=1e-8,
-        help="Parameter epsilon in Jacobi optimizer. " "Added to the diagonal to avoid division by zero",
+        help="Parameter epsilon in Jacobi optimizer. Added to the diagonal to avoid division by zero",
     )
     parser.add_argument(
         "--nn_initializer",
diff --git a/tests/test_io.py b/tests/test_io.py
index af38efa..9b8fd60 100755
--- a/tests/test_io.py
+++ b/tests/test_io.py
@@ -8,7 +8,6 @@
 
 
 class TestIO(unittest.TestCase):
-
     def test_raw_xmf(self):
         name = "foo"
         xmfpath = "data.xdmf2"
diff --git a/uv.lock b/uv.lock
index d676005..8478e41 100644
--- a/uv.lock
+++ b/uv.lock
@@ -15,15 +15,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/8f/aa/ba0014cc4659328dc818a28827be78e6d97312ab0cb98105a770924dc11e/absl_py-2.3.1-py3-none-any.whl", hash = "sha256:eeecf07f0c2a93ace0772c92e596ace6d3d3996c042b2128459aaae2a76de11d", size = 135811, upload-time = "2025-07-03T09:31:42.253Z" },
 ]
 
-[[package]]
-name = "asttokens"
-version = "3.0.0"
-source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/4a/e7/82da0a03e7ba5141f05cce0d302e6eed121ae055e0456ca228bf693984bc/asttokens-3.0.0.tar.gz", hash = "sha256:0dcd8baa8d62b0c1d118b399b2ddba3c4aff271d0d7a9e0d4c1681c79035bbc7", size = 61978, upload-time = "2024-11-30T04:30:14.439Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/25/8a/c46dcc25341b5bce5472c718902eb3d38600a903b14fa6aeecef3f21a46f/asttokens-3.0.0-py3-none-any.whl", hash = "sha256:e3078351a059199dd5138cb1c706e6430c05eff2ff136af5eb4790f9d28932e2", size = 26918, upload-time = "2024-11-30T04:30:10.946Z" },
-]
-
 [[package]]
 name = "astunparse"
 version = "1.6.3"
@@ -37,37 +28,6 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/2b/03/13dde6512ad7b4557eb792fbcf0c653af6076b81e5941d36ec61f7ce6028/astunparse-1.6.3-py2.py3-none-any.whl", hash = "sha256:c2652417f2c8b5bb325c885ae329bdf3f86424075c4fd1a128674bc6fba4b8e8", size = 12732, upload-time = "2019-12-22T18:12:11.297Z" },
 ]
 
-[[package]]
-name = "black"
-version = "25.9.0"
-source = { registry = "https://pypi.org/simple" }
-dependencies = [
-    { name = "click" },
-    { name = "mypy-extensions" },
-    { name = "packaging" },
-    { name = "pathspec" },
-    { name = "platformdirs" },
-    { name = "pytokens" },
-]
-sdist = { url = "https://files.pythonhosted.org/packages/4b/43/20b5c90612d7bdb2bdbcceeb53d588acca3bb8f0e4c5d5c751a2c8fdd55a/black-25.9.0.tar.gz", hash = "sha256:0474bca9a0dd1b51791fcc507a4e02078a1c63f6d4e4ae5544b9848c7adfb619", size = 648393, upload-time = "2025-09-19T00:27:37.758Z" }
-wheels = [
-    { url = "https://files.pythonhosted.org/packages/fb/8e/319cfe6c82f7e2d5bfb4d3353c6cc85b523d677ff59edc61fdb9ee275234/black-25.9.0-cp312-cp312-macosx_10_13_x86_64.whl", hash = "sha256:1b9dc70c21ef8b43248f1d86aedd2aaf75ae110b958a7909ad8463c4aa0880b0", size = 1742012, upload-time = "2025-09-19T00:33:08.678Z" },
-    { url = "https://files.pythonhosted.org/packages/94/cc/f562fe5d0a40cd2a4e6ae3f685e4c36e365b1f7e494af99c26ff7f28117f/black-25.9.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:8e46eecf65a095fa62e53245ae2795c90bdecabd53b50c448d0a8bcd0d2e74c4", size = 1581421, upload-time = "2025-09-19T00:35:25.937Z" },
-    { url = "https://files.pythonhosted.org/packages/84/67/6db6dff1ebc8965fd7661498aea0da5d7301074b85bba8606a28f47ede4d/black-25.9.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:9101ee58ddc2442199a25cb648d46ba22cd580b00ca4b44234a324e3ec7a0f7e", size = 1655619, upload-time = "2025-09-19T00:30:49.241Z" },
-    { url = "https://files.pythonhosted.org/packages/10/10/3faef9aa2a730306cf469d76f7f155a8cc1f66e74781298df0ba31f8b4c8/black-25.9.0-cp312-cp312-win_amd64.whl", hash = "sha256:77e7060a00c5ec4b3367c55f39cf9b06e68965a4f2e61cecacd6d0d9b7ec945a", size = 1342481, upload-time = "2025-09-19T00:31:29.625Z" },
-    { url = "https://files.pythonhosted.org/packages/48/99/3acfea65f5e79f45472c45f87ec13037b506522719cd9d4ac86484ff51ac/black-25.9.0-cp313-cp313-macosx_10_13_x86_64.whl", hash = "sha256:0172a012f725b792c358d57fe7b6b6e8e67375dd157f64fa7a3097b3ed3e2175", size = 1742165, upload-time = "2025-09-19T00:34:10.402Z" },
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