diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
index 968bdc1f0..b553749ad 100644
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -24,6 +24,22 @@ on:
     branches: ["branch-*"]
 
 jobs:
+  build:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v3
+      - name: Install Python
+        uses: actions/setup-python@v4
+        with:
+          python-version: "3.11"
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install ruff
+      # Update output format to enable automatic inline annotations.
+      - name: Run Ruff
+        run: ruff check --output-format=github datafusion
+
   generate-license:
     runs-on: ubuntu-latest
     steps:
diff --git a/.github/workflows/test.yaml b/.github/workflows/test.yaml
index 371f07979..291120bf8 100644
--- a/.github/workflows/test.yaml
+++ b/.github/workflows/test.yaml
@@ -103,13 +103,6 @@ jobs:
           source venv/bin/activate
           pip install -r requirements-311.txt
 
-      - name: Run Python Linters
-        if: ${{ matrix.python-version == '3.10' && matrix.toolchain == 'stable' }}
-        run: |
-          source venv/bin/activate
-          flake8 --exclude venv,benchmarks/db-benchmark --ignore=E501,W503
-          black --line-length 79 --diff --check .
-
       - name: Run tests
         env:
           RUST_BACKTRACE: 1
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index 39049bf49..8509fae2c 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -20,21 +20,14 @@ repos:
         rev: v1.6.23
         hooks:
               - id: actionlint-docker
-      - repo: https://github.com/psf/black
-        rev: 22.3.0
+      - repo: https://github.com/astral-sh/ruff-pre-commit
+        # Ruff version.
+        rev: v0.3.0
         hooks:
-              - id: black
-                files: datafusion/.*
-                # Explicitly specify the pyproject.toml at the repo root, not per-project.
-                args: ["--config", "pyproject.toml", "--line-length", "79", "--diff", "--check", "."]
-      - repo: https://github.com/PyCQA/flake8
-        rev: 5.0.4
-        hooks:
-              - id: flake8
-                files: datafusion/.*$
-                types: [file]
-                types_or: [python]
-                additional_dependencies: ["flake8-force"]
+          # Run the linter.
+          - id: ruff
+          # Run the formatter.
+          - id: ruff-format
       - repo: local
         hooks:
           - id: rust-fmt
diff --git a/README.md b/README.md
index a682f73d5..a2e3efd4e 100644
--- a/README.md
+++ b/README.md
@@ -202,7 +202,7 @@ source venv/bin/activate
 # update pip itself if necessary
 python -m pip install -U pip
 # install dependencies (for Python 3.8+)
-python -m pip install -r requirements-310.txt
+python -m pip install -r requirements.in
 ```
 
 The tests rely on test data in git submodules.
@@ -222,12 +222,27 @@ python -m pytest
 
 ### Running & Installing pre-commit hooks
 
-arrow-datafusion-python takes advantage of [pre-commit](https://pre-commit.com/) to assist developers with code linting to help reduce the number of commits that ultimately fail in CI due to linter errors. Using the pre-commit hooks is optional for the developer but certainly helpful for keeping PRs clean and concise.
+arrow-datafusion-python takes advantage of [pre-commit](https://pre-commit.com/) to assist developers with code linting to help reduce
+the number of commits that ultimately fail in CI due to linter errors. Using the pre-commit hooks is optional for the
+developer but certainly helpful for keeping PRs clean and concise.
 
-Our pre-commit hooks can be installed by running `pre-commit install`, which will install the configurations in your ARROW_DATAFUSION_PYTHON_ROOT/.github directory and run each time you perform a commit, failing to complete the commit if an offending lint is found allowing you to make changes locally before pushing.
+Our pre-commit hooks can be installed by running `pre-commit install`, which will install the configurations in
+your ARROW_DATAFUSION_PYTHON_ROOT/.github directory and run each time you perform a commit, failing to complete
+the commit if an offending lint is found allowing you to make changes locally before pushing.
 
 The pre-commit hooks can also be run adhoc without installing them by simply running `pre-commit run --all-files`
 
+## Running linters without using pre-commit
+
+There are scripts in `ci/scripts` for running Rust and Python linters.
+
+```shell
+./ci/scripts/python_lint.sh
+./ci/scripts/rust_clippy.sh
+./ci/scripts/rust_fmt.sh
+./ci/scripts/rust_toml_fmt.sh
+```
+
 ## How to update dependencies
 
 To change test dependencies, change the `requirements.in` and run
diff --git a/benchmarks/db-benchmark/groupby-datafusion.py b/benchmarks/db-benchmark/groupby-datafusion.py
index 2c35259e8..3a4399f7d 100644
--- a/benchmarks/db-benchmark/groupby-datafusion.py
+++ b/benchmarks/db-benchmark/groupby-datafusion.py
@@ -79,17 +79,13 @@ def execute(df):
 
 data = pacsv.read_csv(
     src_grp,
-    convert_options=pacsv.ConvertOptions(
-        auto_dict_encode=True, column_types=schema
-    ),
+    convert_options=pacsv.ConvertOptions(auto_dict_encode=True, column_types=schema),
 )
 print("dataset loaded")
 
 # create a session context with explicit runtime and config settings
 runtime = (
-    RuntimeConfig()
-    .with_disk_manager_os()
-    .with_fair_spill_pool(64 * 1024 * 1024 * 1024)
+    RuntimeConfig().with_disk_manager_os().with_fair_spill_pool(64 * 1024 * 1024 * 1024)
 )
 config = (
     SessionConfig()
@@ -116,9 +112,7 @@ def execute(df):
 if sql:
     df = ctx.sql("SELECT id1, SUM(v1) AS v1 FROM x GROUP BY id1")
 else:
-    df = ctx.table("x").aggregate(
-        [f.col("id1")], [f.sum(f.col("v1")).alias("v1")]
-    )
+    df = ctx.table("x").aggregate([f.col("id1")], [f.sum(f.col("v1")).alias("v1")])
 ans = execute(df)
 
 shape = ans_shape(ans)
@@ -197,9 +191,7 @@ def execute(df):
 gc.collect()
 t_start = timeit.default_timer()
 if sql:
-    df = ctx.sql(
-        "SELECT id3, SUM(v1) AS v1, AVG(v3) AS v3 FROM x GROUP BY id3"
-    )
+    df = ctx.sql("SELECT id3, SUM(v1) AS v1, AVG(v3) AS v3 FROM x GROUP BY id3")
 else:
     df = ctx.table("x").aggregate(
         [f.col("id3")],
diff --git a/benchmarks/db-benchmark/join-datafusion.py b/benchmarks/db-benchmark/join-datafusion.py
index 602cee697..4d59c7dc2 100755
--- a/benchmarks/db-benchmark/join-datafusion.py
+++ b/benchmarks/db-benchmark/join-datafusion.py
@@ -152,11 +152,7 @@ def ans_shape(batches):
 print(f"q2: {t}")
 t_start = timeit.default_timer()
 df = ctx.create_dataframe([ans])
-chk = (
-    df.aggregate([], [f.sum(col("v1")), f.sum(col("v2"))])
-    .collect()[0]
-    .column(0)[0]
-)
+chk = df.aggregate([], [f.sum(col("v1")), f.sum(col("v2"))]).collect()[0].column(0)[0]
 chkt = timeit.default_timer() - t_start
 m = memory_usage()
 write_log(
@@ -193,11 +189,7 @@ def ans_shape(batches):
 print(f"q3: {t}")
 t_start = timeit.default_timer()
 df = ctx.create_dataframe([ans])
-chk = (
-    df.aggregate([], [f.sum(col("v1")), f.sum(col("v2"))])
-    .collect()[0]
-    .column(0)[0]
-)
+chk = df.aggregate([], [f.sum(col("v1")), f.sum(col("v2"))]).collect()[0].column(0)[0]
 chkt = timeit.default_timer() - t_start
 m = memory_usage()
 write_log(
@@ -234,11 +226,7 @@ def ans_shape(batches):
 print(f"q4: {t}")
 t_start = timeit.default_timer()
 df = ctx.create_dataframe([ans])
-chk = (
-    df.aggregate([], [f.sum(col("v1")), f.sum(col("v2"))])
-    .collect()[0]
-    .column(0)[0]
-)
+chk = df.aggregate([], [f.sum(col("v1")), f.sum(col("v2"))]).collect()[0].column(0)[0]
 chkt = timeit.default_timer() - t_start
 m = memory_usage()
 write_log(
@@ -275,11 +263,7 @@ def ans_shape(batches):
 print(f"q5: {t}")
 t_start = timeit.default_timer()
 df = ctx.create_dataframe([ans])
-chk = (
-    df.aggregate([], [f.sum(col("v1")), f.sum(col("v2"))])
-    .collect()[0]
-    .column(0)[0]
-)
+chk = df.aggregate([], [f.sum(col("v1")), f.sum(col("v2"))]).collect()[0].column(0)[0]
 chkt = timeit.default_timer() - t_start
 m = memory_usage()
 write_log(
diff --git a/benchmarks/tpch/tpch.py b/benchmarks/tpch/tpch.py
index ea830a1ff..7f104a4cb 100644
--- a/benchmarks/tpch/tpch.py
+++ b/benchmarks/tpch/tpch.py
@@ -83,9 +83,7 @@ def bench(data_path, query_path):
                     time_millis = (end - start) * 1000
                     total_time_millis += time_millis
                     print("q{},{}".format(query, round(time_millis, 1)))
-                    results.write(
-                        "q{},{}\n".format(query, round(time_millis, 1))
-                    )
+                    results.write("q{},{}\n".format(query, round(time_millis, 1)))
                     results.flush()
                 except Exception as e:
                     print("query", query, "failed", e)
diff --git a/ci/scripts/python_lint.sh b/ci/scripts/python_lint.sh
new file mode 100755
index 000000000..3f7310ba7
--- /dev/null
+++ b/ci/scripts/python_lint.sh
@@ -0,0 +1,22 @@
+#!/usr/bin/env bash
+#
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements.  See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership.  The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License.  You may obtain a copy of the License at
+#
+#   http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, 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.
+
+set -ex
+ruff format datafusion
+ruff check datafusion
\ No newline at end of file
diff --git a/datafusion/__init__.py b/datafusion/__init__.py
index df53b396a..cfb673613 100644
--- a/datafusion/__init__.py
+++ b/datafusion/__init__.py
@@ -208,9 +208,7 @@ def udaf(accum, input_type, return_type, state_type, volatility, name=None):
     Create a new User Defined Aggregate Function
     """
     if not issubclass(accum, Accumulator):
-        raise TypeError(
-            "`accum` must implement the abstract base class Accumulator"
-        )
+        raise TypeError("`accum` must implement the abstract base class Accumulator")
     if name is None:
         name = accum.__qualname__.lower()
     if isinstance(input_type, pa.lib.DataType):
diff --git a/datafusion/cudf.py b/datafusion/cudf.py
index e39daea31..d8bc8e6d0 100644
--- a/datafusion/cudf.py
+++ b/datafusion/cudf.py
@@ -68,9 +68,7 @@ def to_cudf_df(self, plan):
         elif isinstance(node, TableScan):
             return cudf.read_parquet(self.parquet_tables[node.table_name()])
         else:
-            raise Exception(
-                "unsupported logical operator: {}".format(type(node))
-            )
+            raise Exception("unsupported logical operator: {}".format(type(node)))
 
     def create_schema(self, schema_name: str, **kwargs):
         logger.debug(f"Creating schema: {schema_name}")
diff --git a/datafusion/input/base.py b/datafusion/input/base.py
index fb1207896..efcaf7697 100644
--- a/datafusion/input/base.py
+++ b/datafusion/input/base.py
@@ -31,13 +31,9 @@ class BaseInputSource(ABC):
     """
 
     @abstractmethod
-    def is_correct_input(
-        self, input_item: Any, table_name: str, **kwargs
-    ) -> bool:
+    def is_correct_input(self, input_item: Any, table_name: str, **kwargs) -> bool:
         pass
 
     @abstractmethod
-    def build_table(
-        self, input_item: Any, table_name: str, **kwarg
-    ) -> SqlTable:
+    def build_table(self, input_item: Any, table_name: str, **kwarg) -> SqlTable:
         pass
diff --git a/datafusion/input/location.py b/datafusion/input/location.py
index 939c7f415..16e632d1b 100644
--- a/datafusion/input/location.py
+++ b/datafusion/input/location.py
@@ -72,9 +72,7 @@ def build_table(
                 for _ in reader:
                     num_rows += 1
             # TODO: Need to actually consume this row into resonable columns
-            raise RuntimeError(
-                "TODO: Currently unable to support CSV input files."
-            )
+            raise RuntimeError("TODO: Currently unable to support CSV input files.")
         else:
             raise RuntimeError(
                 f"Input of format: `{format}` is currently not supported.\
diff --git a/datafusion/pandas.py b/datafusion/pandas.py
index c2da83ff6..cf1fa6f7b 100644
--- a/datafusion/pandas.py
+++ b/datafusion/pandas.py
@@ -64,9 +64,7 @@ def to_pandas_df(self, plan):
         elif isinstance(node, TableScan):
             return pd.read_parquet(self.parquet_tables[node.table_name()])
         else:
-            raise Exception(
-                "unsupported logical operator: {}".format(type(node))
-            )
+            raise Exception("unsupported logical operator: {}".format(type(node)))
 
     def create_schema(self, schema_name: str, **kwargs):
         logger.debug(f"Creating schema: {schema_name}")
diff --git a/datafusion/polars.py b/datafusion/polars.py
index e4eb966fc..ac5e26e3e 100644
--- a/datafusion/polars.py
+++ b/datafusion/polars.py
@@ -51,9 +51,7 @@ def to_polars_df(self, plan):
             args = [self.to_polars_expr(expr) for expr in node.projections()]
             return inputs[0].select(*args)
         elif isinstance(node, Aggregate):
-            groupby_expr = [
-                self.to_polars_expr(expr) for expr in node.group_by_exprs()
-            ]
+            groupby_expr = [self.to_polars_expr(expr) for expr in node.group_by_exprs()]
             aggs = []
             for expr in node.aggregate_exprs():
                 expr = expr.to_variant()
@@ -67,17 +65,13 @@ def to_polars_df(self, plan):
                             )
                         )
                 else:
-                    raise Exception(
-                        "Unsupported aggregate function {}".format(expr)
-                    )
+                    raise Exception("Unsupported aggregate function {}".format(expr))
             df = inputs[0].groupby(groupby_expr).agg(aggs)
             return df
         elif isinstance(node, TableScan):
             return polars.read_parquet(self.parquet_tables[node.table_name()])
         else:
-            raise Exception(
-                "unsupported logical operator: {}".format(type(node))
-            )
+            raise Exception("unsupported logical operator: {}".format(type(node)))
 
     def create_schema(self, schema_name: str, **kwargs):
         logger.debug(f"Creating schema: {schema_name}")
diff --git a/datafusion/tests/generic.py b/datafusion/tests/generic.py
index 1f984a40a..07399792c 100644
--- a/datafusion/tests/generic.py
+++ b/datafusion/tests/generic.py
@@ -50,9 +50,7 @@ def data_datetime(f):
         datetime.datetime.now() - datetime.timedelta(days=1),
         datetime.datetime.now() + datetime.timedelta(days=1),
     ]
-    return pa.array(
-        data, type=pa.timestamp(f), mask=np.array([False, True, False])
-    )
+    return pa.array(data, type=pa.timestamp(f), mask=np.array([False, True, False]))
 
 
 def data_date32():
@@ -61,9 +59,7 @@ def data_date32():
         datetime.date(1980, 1, 1),
         datetime.date(2030, 1, 1),
     ]
-    return pa.array(
-        data, type=pa.date32(), mask=np.array([False, True, False])
-    )
+    return pa.array(data, type=pa.date32(), mask=np.array([False, True, False]))
 
 
 def data_timedelta(f):
@@ -72,9 +68,7 @@ def data_timedelta(f):
         datetime.timedelta(days=1),
         datetime.timedelta(seconds=1),
     ]
-    return pa.array(
-        data, type=pa.duration(f), mask=np.array([False, True, False])
-    )
+    return pa.array(data, type=pa.duration(f), mask=np.array([False, True, False]))
 
 
 def data_binary_other():
diff --git a/datafusion/tests/test_aggregation.py b/datafusion/tests/test_aggregation.py
index 0a6c90c32..99a470b6b 100644
--- a/datafusion/tests/test_aggregation.py
+++ b/datafusion/tests/test_aggregation.py
@@ -81,9 +81,7 @@ def test_built_in_aggregation(df):
     assert result.column(2) == pa.array([4])
     assert result.column(3) == pa.array([6])
     assert result.column(4) == pa.array([[4, 4, 6]])
-    np.testing.assert_array_almost_equal(
-        result.column(5), np.average(values_a)
-    )
+    np.testing.assert_array_almost_equal(result.column(5), np.average(values_a))
     np.testing.assert_array_almost_equal(
         result.column(6), np.corrcoef(values_a, values_b)[0][1]
     )
@@ -101,35 +99,20 @@ def test_built_in_aggregation(df):
     )
     np.testing.assert_array_almost_equal(result.column(11), np.max(values_a))
     np.testing.assert_array_almost_equal(result.column(12), np.mean(values_b))
-    np.testing.assert_array_almost_equal(
-        result.column(13), np.median(values_b)
-    )
+    np.testing.assert_array_almost_equal(result.column(13), np.median(values_b))
     np.testing.assert_array_almost_equal(result.column(14), np.min(values_a))
     np.testing.assert_array_almost_equal(
         result.column(15), np.sum(values_b.to_pylist())
     )
-    np.testing.assert_array_almost_equal(
-        result.column(16), np.std(values_a, ddof=1)
-    )
-    np.testing.assert_array_almost_equal(
-        result.column(17), np.std(values_b, ddof=0)
-    )
-    np.testing.assert_array_almost_equal(
-        result.column(18), np.std(values_c, ddof=1)
-    )
-    np.testing.assert_array_almost_equal(
-        result.column(19), np.var(values_a, ddof=1)
-    )
-    np.testing.assert_array_almost_equal(
-        result.column(20), np.var(values_b, ddof=0)
-    )
-    np.testing.assert_array_almost_equal(
-        result.column(21), np.var(values_c, ddof=1)
-    )
+    np.testing.assert_array_almost_equal(result.column(16), np.std(values_a, ddof=1))
+    np.testing.assert_array_almost_equal(result.column(17), np.std(values_b, ddof=0))
+    np.testing.assert_array_almost_equal(result.column(18), np.std(values_c, ddof=1))
+    np.testing.assert_array_almost_equal(result.column(19), np.var(values_a, ddof=1))
+    np.testing.assert_array_almost_equal(result.column(20), np.var(values_b, ddof=0))
+    np.testing.assert_array_almost_equal(result.column(21), np.var(values_c, ddof=1))
 
 
 def test_bit_add_or_xor(df):
-
     df = df.aggregate(
         [],
         [
@@ -147,7 +130,6 @@ def test_bit_add_or_xor(df):
 
 
 def test_bool_and_or(df):
-
     df = df.aggregate(
         [],
         [
diff --git a/datafusion/tests/test_config.py b/datafusion/tests/test_config.py
index 960e72c94..12d9fc3ff 100644
--- a/datafusion/tests/test_config.py
+++ b/datafusion/tests/test_config.py
@@ -35,10 +35,7 @@ def test_get_then_set(config):
 
 def test_get_all(config):
     config_dict = config.get_all()
-    assert (
-        config_dict["datafusion.catalog.create_default_catalog_and_schema"]
-        == "true"
-    )
+    assert config_dict["datafusion.catalog.create_default_catalog_and_schema"] == "true"
 
 
 def test_get_invalid_config(config):
diff --git a/datafusion/tests/test_context.py b/datafusion/tests/test_context.py
index 97bff9bb9..d48bdd929 100644
--- a/datafusion/tests/test_context.py
+++ b/datafusion/tests/test_context.py
@@ -36,9 +36,7 @@ def test_create_context_no_args():
 
 
 def test_create_context_with_all_valid_args():
-    runtime = (
-        RuntimeConfig().with_disk_manager_os().with_fair_spill_pool(10000000)
-    )
+    runtime = RuntimeConfig().with_disk_manager_os().with_fair_spill_pool(10000000)
     config = (
         SessionConfig()
         .with_create_default_catalog_and_schema(True)
@@ -357,9 +355,7 @@ def test_read_json_compressed(ctx, tmp_path):
         with gzip.open(gzip_path, "wb") as gzipped_file:
             gzipped_file.writelines(csv_file)
 
-    df = ctx.read_json(
-        gzip_path, file_extension=".gz", file_compression_type="gz"
-    )
+    df = ctx.read_json(gzip_path, file_extension=".gz", file_compression_type="gz")
     result = df.collect()
 
     assert result[0].column(0) == pa.array(["a", "b", "c"])
@@ -381,9 +377,7 @@ def test_read_csv_compressed(ctx, tmp_path):
         with gzip.open(gzip_path, "wb") as gzipped_file:
             gzipped_file.writelines(csv_file)
 
-    csv_df = ctx.read_csv(
-        gzip_path, file_extension=".gz", file_compression_type="gz"
-    )
+    csv_df = ctx.read_csv(gzip_path, file_extension=".gz", file_compression_type="gz")
     csv_df.select(column("c1")).show()
 
 
diff --git a/datafusion/tests/test_dataframe.py b/datafusion/tests/test_dataframe.py
index c9b0f076f..9944abeef 100644
--- a/datafusion/tests/test_dataframe.py
+++ b/datafusion/tests/test_dataframe.py
@@ -151,9 +151,7 @@ def test_with_column(df):
 
 
 def test_with_column_renamed(df):
-    df = df.with_column("c", column("a") + column("b")).with_column_renamed(
-        "c", "sum"
-    )
+    df = df.with_column("c", column("a") + column("b")).with_column_renamed("c", "sum")
 
     result = df.collect()[0]
 
@@ -218,9 +216,7 @@ def test_distinct():
         [pa.array([1, 2, 3]), pa.array([4, 5, 6])],
         names=["a", "b"],
     )
-    df_b = ctx.create_dataframe([[batch]]).sort(
-        column("a").sort(ascending=True)
-    )
+    df_b = ctx.create_dataframe([[batch]]).sort(column("a").sort(ascending=True))
 
     assert df_a.collect() == df_b.collect()
 
@@ -251,9 +247,7 @@ def test_window_functions(df):
             "cume_dist",
         ),
         f.alias(
-            f.window(
-                "ntile", [literal(2)], order_by=[f.order_by(column("c"))]
-            ),
+            f.window("ntile", [literal(2)], order_by=[f.order_by(column("c"))]),
             "ntile",
         ),
         f.alias(
@@ -261,9 +255,7 @@ def test_window_functions(df):
             "previous",
         ),
         f.alias(
-            f.window(
-                "lead", [column("b")], order_by=[f.order_by(column("b"))]
-            ),
+            f.window("lead", [column("b")], order_by=[f.order_by(column("b"))]),
             "next",
         ),
         f.alias(
@@ -275,9 +267,7 @@ def test_window_functions(df):
             "first_value",
         ),
         f.alias(
-            f.window(
-                "last_value", [column("b")], order_by=[f.order_by(column("b"))]
-            ),
+            f.window("last_value", [column("b")], order_by=[f.order_by(column("b"))]),
             "last_value",
         ),
         f.alias(
@@ -418,12 +408,14 @@ def test_optimized_logical_plan(aggregate_df):
 def test_execution_plan(aggregate_df):
     plan = aggregate_df.execution_plan()
 
-    expected = "AggregateExec: mode=FinalPartitioned, gby=[c1@0 as c1], aggr=[SUM(test.c2)]\n"  # noqa: E501
+    expected = (
+        "AggregateExec: mode=FinalPartitioned, gby=[c1@0 as c1], aggr=[SUM(test.c2)]\n"  # noqa: E501
+    )
 
     assert expected == plan.display()
 
     # Check the number of partitions is as expected.
-    assert type(plan.partition_count) is int
+    assert isinstance(plan.partition_count, int)
 
     expected = (
         "ProjectionExec: expr=[c1@0 as c1, SUM(test.c2)@1 as SUM(test.c2)]\n"
@@ -477,9 +469,7 @@ def test_intersect():
         [pa.array([3]), pa.array([6])],
         names=["a", "b"],
     )
-    df_c = ctx.create_dataframe([[batch]]).sort(
-        column("a").sort(ascending=True)
-    )
+    df_c = ctx.create_dataframe([[batch]]).sort(column("a").sort(ascending=True))
 
     df_a_i_b = df_a.intersect(df_b).sort(column("a").sort(ascending=True))
 
@@ -505,9 +495,7 @@ def test_except_all():
         [pa.array([1, 2]), pa.array([4, 5])],
         names=["a", "b"],
     )
-    df_c = ctx.create_dataframe([[batch]]).sort(
-        column("a").sort(ascending=True)
-    )
+    df_c = ctx.create_dataframe([[batch]]).sort(column("a").sort(ascending=True))
 
     df_a_e_b = df_a.except_all(df_b).sort(column("a").sort(ascending=True))
 
@@ -542,9 +530,7 @@ def test_union(ctx):
         [pa.array([1, 2, 3, 3, 4, 5]), pa.array([4, 5, 6, 6, 7, 8])],
         names=["a", "b"],
     )
-    df_c = ctx.create_dataframe([[batch]]).sort(
-        column("a").sort(ascending=True)
-    )
+    df_c = ctx.create_dataframe([[batch]]).sort(column("a").sort(ascending=True))
 
     df_a_u_b = df_a.union(df_b).sort(column("a").sort(ascending=True))
 
@@ -568,9 +554,7 @@ def test_union_distinct(ctx):
         [pa.array([1, 2, 3, 4, 5]), pa.array([4, 5, 6, 7, 8])],
         names=["a", "b"],
     )
-    df_c = ctx.create_dataframe([[batch]]).sort(
-        column("a").sort(ascending=True)
-    )
+    df_c = ctx.create_dataframe([[batch]]).sort(column("a").sort(ascending=True))
 
     df_a_u_b = df_a.union(df_b, True).sort(column("a").sort(ascending=True))
 
@@ -650,7 +634,7 @@ def test_empty_to_arrow_table(df):
 def test_to_pylist(df):
     # Convert datafusion dataframe to Python list
     pylist = df.to_pylist()
-    assert type(pylist) == list
+    assert isinstance(pylist, list)
     assert pylist == [
         {"a": 1, "b": 4, "c": 8},
         {"a": 2, "b": 5, "c": 5},
@@ -661,7 +645,7 @@ def test_to_pylist(df):
 def test_to_pydict(df):
     # Convert datafusion dataframe to Python dictionary
     pydict = df.to_pydict()
-    assert type(pydict) == dict
+    assert isinstance(pydict, dict)
     assert pydict == {"a": [1, 2, 3], "b": [4, 5, 6], "c": [8, 5, 8]}
 
 
@@ -702,9 +686,7 @@ def test_write_parquet(df, tmp_path):
     "compression, compression_level",
     [("gzip", 6), ("brotli", 7), ("zstd", 15)],
 )
-def test_write_compressed_parquet(
-    df, tmp_path, compression, compression_level
-):
+def test_write_compressed_parquet(df, tmp_path, compression, compression_level):
     path = tmp_path
 
     df.write_parquet(
@@ -744,9 +726,7 @@ def test_write_compressed_parquet_wrong_compression_level(
 
 
 @pytest.mark.parametrize("compression", ["brotli", "zstd", "wrong"])
-def test_write_compressed_parquet_missing_compression_level(
-    df, tmp_path, compression
-):
+def test_write_compressed_parquet_missing_compression_level(df, tmp_path, compression):
     path = tmp_path
 
     with pytest.raises(ValueError):
diff --git a/datafusion/tests/test_functions.py b/datafusion/tests/test_functions.py
index eb37692b2..1a18fd823 100644
--- a/datafusion/tests/test_functions.py
+++ b/datafusion/tests/test_functions.py
@@ -74,9 +74,7 @@ def test_lit_arith(df):
     """
     Test literals with arithmetic operations
     """
-    df = df.select(
-        literal(1) + column("b"), f.concat(column("a"), literal("!"))
-    )
+    df = df.select(literal(1) + column("b"), f.concat(column("a"), literal("!")))
     result = df.collect()
     assert len(result) == 1
     result = result[0]
@@ -148,28 +146,16 @@ def test_math_functions():
     np.testing.assert_array_almost_equal(result.column(4), np.arcsin(values))
     np.testing.assert_array_almost_equal(result.column(5), np.arccos(values))
     np.testing.assert_array_almost_equal(result.column(6), np.exp(values))
-    np.testing.assert_array_almost_equal(
-        result.column(7), np.log(values + 1.0)
-    )
-    np.testing.assert_array_almost_equal(
-        result.column(8), np.log2(values + 1.0)
-    )
-    np.testing.assert_array_almost_equal(
-        result.column(9), np.log10(values + 1.0)
-    )
+    np.testing.assert_array_almost_equal(result.column(7), np.log(values + 1.0))
+    np.testing.assert_array_almost_equal(result.column(8), np.log2(values + 1.0))
+    np.testing.assert_array_almost_equal(result.column(9), np.log10(values + 1.0))
     np.testing.assert_array_less(result.column(10), np.ones_like(values))
     np.testing.assert_array_almost_equal(result.column(11), np.arctan(values))
-    np.testing.assert_array_almost_equal(
-        result.column(12), np.arctan2(values, 1.1)
-    )
+    np.testing.assert_array_almost_equal(result.column(12), np.arctan2(values, 1.1))
     np.testing.assert_array_almost_equal(result.column(13), np.ceil(values))
     np.testing.assert_array_almost_equal(result.column(14), np.floor(values))
-    np.testing.assert_array_almost_equal(
-        result.column(15), np.power(values, 3)
-    )
-    np.testing.assert_array_almost_equal(
-        result.column(16), np.power(values, 4)
-    )
+    np.testing.assert_array_almost_equal(result.column(15), np.power(values, 3))
+    np.testing.assert_array_almost_equal(result.column(16), np.power(values, 4))
     np.testing.assert_array_almost_equal(result.column(17), np.round(values))
     np.testing.assert_array_almost_equal(result.column(18), np.sqrt(values))
     np.testing.assert_array_almost_equal(result.column(19), np.sign(values))
@@ -190,9 +176,7 @@ def test_math_functions():
     np.testing.assert_array_almost_equal(result.column(32), np.sinh(values))
     np.testing.assert_array_almost_equal(result.column(33), np.tanh(values))
     np.testing.assert_array_almost_equal(result.column(34), math.factorial(6))
-    np.testing.assert_array_almost_equal(
-        result.column(35), np.isnan(na_values)
-    )
+    np.testing.assert_array_almost_equal(result.column(35), np.isnan(na_values))
     np.testing.assert_array_almost_equal(result.column(36), na_values == 0)
     np.testing.assert_array_almost_equal(
         result.column(37), np.emath.logn(3, values + 1.0)
@@ -202,9 +186,7 @@ def test_math_functions():
 def test_array_functions():
     data = [[1.0, 2.0, 3.0, 3.0], [4.0, 5.0, 3.0], [6.0]]
     ctx = SessionContext()
-    batch = pa.RecordBatch.from_arrays(
-        [np.array(data, dtype=object)], names=["arr"]
-    )
+    batch = pa.RecordBatch.from_arrays([np.array(data, dtype=object)], names=["arr"])
     df = ctx.create_dataframe([[batch]])
 
     def py_indexof(arr, v):
@@ -310,15 +292,11 @@ def py_flatten(arr):
             lambda: [1.0 in r for r in data],
         ],
         [
-            f.array_has_all(
-                col, f.make_array(*[literal(v) for v in [1.0, 3.0, 5.0]])
-            ),
+            f.array_has_all(col, f.make_array(*[literal(v) for v in [1.0, 3.0, 5.0]])),
             lambda: [np.all([v in r for v in [1.0, 3.0, 5.0]]) for r in data],
         ],
         [
-            f.array_has_any(
-                col, f.make_array(*[literal(v) for v in [1.0, 3.0, 5.0]])
-            ),
+            f.array_has_any(col, f.make_array(*[literal(v) for v in [1.0, 3.0, 5.0]])),
             lambda: [np.any([v in r for v in [1.0, 3.0, 5.0]]) for r in data],
         ],
         [
@@ -339,15 +317,11 @@ def py_flatten(arr):
         ],
         [
             f.array_positions(col, literal(1.0)),
-            lambda: [
-                [i + 1 for i, _v in enumerate(r) if _v == 1.0] for r in data
-            ],
+            lambda: [[i + 1 for i, _v in enumerate(r) if _v == 1.0] for r in data],
         ],
         [
             f.list_positions(col, literal(1.0)),
-            lambda: [
-                [i + 1 for i, _v in enumerate(r) if _v == 1.0] for r in data
-            ],
+            lambda: [[i + 1 for i, _v in enumerate(r) if _v == 1.0] for r in data],
         ],
         [
             f.array_ndims(col),
@@ -588,18 +562,9 @@ def test_hash_functions(df):
     )
     assert result.column(2) == pa.array(
         [
-            b(
-                "185F8DB32271FE25F561A6FC938B2E26"
-                "4306EC304EDA518007D1764826381969"
-            ),
-            b(
-                "78AE647DC5544D227130A0682A51E30B"
-                "C7777FBB6D8A8F17007463A3ECD1D524"
-            ),
-            b(
-                "BB7208BC9B5D7C04F1236A82A0093A5E"
-                "33F40423D5BA8D4266F7092C3BA43B62"
-            ),
+            b("185F8DB32271FE25F561A6FC938B2E26" "4306EC304EDA518007D1764826381969"),
+            b("78AE647DC5544D227130A0682A51E30B" "C7777FBB6D8A8F17007463A3ECD1D524"),
+            b("BB7208BC9B5D7C04F1236A82A0093A5E" "33F40423D5BA8D4266F7092C3BA43B62"),
         ]
     )
     assert result.column(3) == pa.array(
@@ -645,34 +610,16 @@ def test_hash_functions(df):
     )
     assert result.column(5) == pa.array(
         [
-            b(
-                "F73A5FBF881F89B814871F46E26AD3FA"
-                "37CB2921C5E8561618639015B3CCBB71"
-            ),
-            b(
-                "B792A0383FB9E7A189EC150686579532"
-                "854E44B71AC394831DAED169BA85CCC5"
-            ),
-            b(
-                "27988A0E51812297C77A433F63523334"
-                "6AEE29A829DCF4F46E0F58F402C6CFCB"
-            ),
+            b("F73A5FBF881F89B814871F46E26AD3FA" "37CB2921C5E8561618639015B3CCBB71"),
+            b("B792A0383FB9E7A189EC150686579532" "854E44B71AC394831DAED169BA85CCC5"),
+            b("27988A0E51812297C77A433F63523334" "6AEE29A829DCF4F46E0F58F402C6CFCB"),
         ]
     )
     assert result.column(6) == pa.array(
         [
-            b(
-                "FBC2B0516EE8744D293B980779178A35"
-                "08850FDCFE965985782C39601B65794F"
-            ),
-            b(
-                "BF73D18575A736E4037D45F9E316085B"
-                "86C19BE6363DE6AA789E13DEAACC1C4E"
-            ),
-            b(
-                "C8D11B9F7237E4034ADBCD2005735F9B"
-                "C4C597C75AD89F4492BEC8F77D15F7EB"
-            ),
+            b("FBC2B0516EE8744D293B980779178A35" "08850FDCFE965985782C39601B65794F"),
+            b("BF73D18575A736E4037D45F9E316085B" "86C19BE6363DE6AA789E13DEAACC1C4E"),
+            b("C8D11B9F7237E4034ADBCD2005735F9B" "C4C597C75AD89F4492BEC8F77D15F7EB"),
         ]
     )
     assert result.column(7) == result.column(1)  # SHA-224
@@ -738,9 +685,7 @@ def test_temporal_functions(df):
 
 def test_case(df):
     df = df.select(
-        f.case(column("b"))
-        .when(literal(4), literal(10))
-        .otherwise(literal(8)),
+        f.case(column("b")).when(literal(4), literal(10)).otherwise(literal(8)),
         f.case(column("a"))
         .when(literal("Hello"), literal("Hola"))
         .when(literal("World"), literal("Mundo"))
diff --git a/datafusion/tests/test_input.py b/datafusion/tests/test_input.py
index 5b1decf26..fb53d86e5 100644
--- a/datafusion/tests/test_input.py
+++ b/datafusion/tests/test_input.py
@@ -23,9 +23,7 @@ def test_location_input():
     location_input = LocationInputPlugin()
 
     cwd = os.getcwd()
-    input_file = (
-        cwd + "/testing/data/parquet/generated_simple_numerics/blogs.parquet"
-    )
+    input_file = cwd + "/testing/data/parquet/generated_simple_numerics/blogs.parquet"
     table_name = "blog"
     tbl = location_input.build_table(input_file, table_name)
     assert "blog" == tbl.name
diff --git a/datafusion/tests/test_sql.py b/datafusion/tests/test_sql.py
index 0c6b26727..9d4c8f677 100644
--- a/datafusion/tests/test_sql.py
+++ b/datafusion/tests/test_sql.py
@@ -86,9 +86,7 @@ def test_register_csv(ctx, tmp_path):
     result = pa.Table.from_batches(result)
     assert result.schema == alternative_schema
 
-    with pytest.raises(
-        ValueError, match="Delimiter must be a single character"
-    ):
+    with pytest.raises(ValueError, match="Delimiter must be a single character"):
         ctx.register_csv("csv4", path, delimiter="wrong")
 
     with pytest.raises(
@@ -134,9 +132,7 @@ def test_register_parquet_partitioned(ctx, tmp_path):
     )
     assert ctx.tables() == {"datapp"}
 
-    result = ctx.sql(
-        "SELECT grp, COUNT(*) AS cnt FROM datapp GROUP BY grp"
-    ).collect()
+    result = ctx.sql("SELECT grp, COUNT(*) AS cnt FROM datapp GROUP BY grp").collect()
     result = pa.Table.from_batches(result)
 
     rd = result.to_pydict()
@@ -240,9 +236,7 @@ def test_execute(ctx, tmp_path):
     assert ctx.tables() == {"t"}
 
     # count
-    result = ctx.sql(
-        "SELECT COUNT(a) AS cnt FROM t WHERE a IS NOT NULL"
-    ).collect()
+    result = ctx.sql("SELECT COUNT(a) AS cnt FROM t WHERE a IS NOT NULL").collect()
 
     expected = pa.array([7], pa.int64())
     expected = [pa.RecordBatch.from_arrays([expected], ["cnt"])]
@@ -280,9 +274,7 @@ def test_execute(ctx, tmp_path):
     ).collect()
     expected_a = pa.array([50.0219, 50.0152], pa.float64())
     expected_cast = pa.array([50, 50], pa.int32())
-    expected = [
-        pa.RecordBatch.from_arrays([expected_a, expected_cast], ["a", "a_int"])
-    ]
+    expected = [pa.RecordBatch.from_arrays([expected_a, expected_cast], ["a", "a_int"])]
     np.testing.assert_equal(expected[0].column(1), expected[0].column(1))
 
 
@@ -302,9 +294,7 @@ def test_cast(ctx, tmp_path):
         "float",
     ]
 
-    select = ", ".join(
-        [f"CAST(9 AS {t}) AS A{i}" for i, t in enumerate(valid_types)]
-    )
+    select = ", ".join([f"CAST(9 AS {t}) AS A{i}" for i, t in enumerate(valid_types)])
 
     # can execute, which implies that we can cast
     ctx.sql(f"SELECT {select} FROM t").collect()
@@ -333,14 +323,10 @@ def test_udf(
     ctx, tmp_path, fn, input_types, output_type, input_values, expected_values
 ):
     # write to disk
-    path = helpers.write_parquet(
-        tmp_path / "a.parquet", pa.array(input_values)
-    )
+    path = helpers.write_parquet(tmp_path / "a.parquet", pa.array(input_values))
     ctx.register_parquet("t", path)
 
-    func = udf(
-        fn, input_types, output_type, name="func", volatility="immutable"
-    )
+    func = udf(fn, input_types, output_type, name="func", volatility="immutable")
     ctx.register_udf(func)
 
     batches = ctx.sql("SELECT func(a) AS tt FROM t").collect()
diff --git a/datafusion/tests/test_substrait.py b/datafusion/tests/test_substrait.py
index 7c7a2c1f2..62f6413a3 100644
--- a/datafusion/tests/test_substrait.py
+++ b/datafusion/tests/test_substrait.py
@@ -38,22 +38,14 @@ def test_substrait_serialization(ctx):
     assert ctx.tables() == {"t"}
 
     # For now just make sure the method calls blow up
-    substrait_plan = ss.substrait.serde.serialize_to_plan(
-        "SELECT * FROM t", ctx
-    )
+    substrait_plan = ss.substrait.serde.serialize_to_plan("SELECT * FROM t", ctx)
     substrait_bytes = substrait_plan.encode()
-    assert type(substrait_bytes) is bytes
-    substrait_bytes = ss.substrait.serde.serialize_bytes(
-        "SELECT * FROM t", ctx
-    )
+    assert isinstance(substrait_bytes, bytes)
+    substrait_bytes = ss.substrait.serde.serialize_bytes("SELECT * FROM t", ctx)
     substrait_plan = ss.substrait.serde.deserialize_bytes(substrait_bytes)
-    logical_plan = ss.substrait.consumer.from_substrait_plan(
-        ctx, substrait_plan
-    )
+    logical_plan = ss.substrait.consumer.from_substrait_plan(ctx, substrait_plan)
 
     # demonstrate how to create a DataFrame from a deserialized logical plan
     df = ctx.create_dataframe_from_logical_plan(logical_plan)
 
-    substrait_plan = ss.substrait.producer.to_substrait_plan(
-        df.logical_plan(), ctx
-    )
+    substrait_plan = ss.substrait.producer.to_substrait_plan(df.logical_plan(), ctx)
diff --git a/dev/release/check-rat-report.py b/dev/release/check-rat-report.py
index 30a01116b..d3dd7c5dd 100644
--- a/dev/release/check-rat-report.py
+++ b/dev/release/check-rat-report.py
@@ -23,9 +23,7 @@
 import xml.etree.ElementTree as ET
 
 if len(sys.argv) != 3:
-    sys.stderr.write(
-        "Usage: %s exclude_globs.lst rat_report.xml\n" % sys.argv[0]
-    )
+    sys.stderr.write("Usage: %s exclude_globs.lst rat_report.xml\n" % sys.argv[0])
     sys.exit(1)
 
 exclude_globs_filename = sys.argv[1]
diff --git a/dev/release/generate-changelog.py b/dev/release/generate-changelog.py
index e97f00304..01d640669 100755
--- a/dev/release/generate-changelog.py
+++ b/dev/release/generate-changelog.py
@@ -27,9 +27,7 @@ def print_pulls(repo_name, title, pulls):
         print("**{}:**".format(title))
         print()
         for pull, commit in pulls:
-            url = "https://github.com/{}/pull/{}".format(
-                repo_name, pull.number
-            )
+            url = "https://github.com/{}/pull/{}".format(repo_name, pull.number)
             print(
                 "- {} [#{}]({}) ({})".format(
                     pull.title, pull.number, url, commit.author.login
@@ -40,9 +38,7 @@ def print_pulls(repo_name, title, pulls):
 
 def generate_changelog(repo, repo_name, tag1, tag2):
     # get a list of commits between two tags
-    print(
-        f"Fetching list of commits between {tag1} and {tag2}", file=sys.stderr
-    )
+    print(f"Fetching list of commits between {tag1} and {tag2}", file=sys.stderr)
     comparison = repo.compare(tag1, tag2)
 
     # get the pull requests for these commits
diff --git a/examples/sql-on-polars.py b/examples/sql-on-polars.py
index dd7a9e021..ffcb12b70 100644
--- a/examples/sql-on-polars.py
+++ b/examples/sql-on-polars.py
@@ -20,7 +20,5 @@
 
 ctx = SessionContext()
 ctx.register_table("taxi", "yellow_tripdata_2021-01.parquet")
-df = ctx.sql(
-    "select passenger_count, count(*) from taxi group by passenger_count"
-)
+df = ctx.sql("select passenger_count, count(*) from taxi group by passenger_count")
 print(df)
diff --git a/examples/sql-using-python-udaf.py b/examples/sql-using-python-udaf.py
index 3326c4a1c..7ccf5d3cb 100644
--- a/examples/sql-using-python-udaf.py
+++ b/examples/sql-using-python-udaf.py
@@ -30,15 +30,11 @@ def __init__(self):
 
     def update(self, values: pa.Array) -> None:
         # not nice since pyarrow scalars can't be summed yet. This breaks on `None`
-        self._sum = pa.scalar(
-            self._sum.as_py() + pa.compute.sum(values).as_py()
-        )
+        self._sum = pa.scalar(self._sum.as_py() + pa.compute.sum(values).as_py())
 
     def merge(self, states: pa.Array) -> None:
         # not nice since pyarrow scalars can't be summed yet. This breaks on `None`
-        self._sum = pa.scalar(
-            self._sum.as_py() + pa.compute.sum(states).as_py()
-        )
+        self._sum = pa.scalar(self._sum.as_py() + pa.compute.sum(states).as_py())
 
     def state(self) -> pa.Array:
         return pa.array([self._sum.as_py()])
diff --git a/examples/substrait.py b/examples/substrait.py
index c579751d2..23cd74649 100644
--- a/examples/substrait.py
+++ b/examples/substrait.py
@@ -23,9 +23,7 @@
 ctx = SessionContext()
 
 # Register table with context
-ctx.register_csv(
-    "aggregate_test_data", "./testing/data/csv/aggregate_test_100.csv"
-)
+ctx.register_csv("aggregate_test_data", "./testing/data/csv/aggregate_test_100.csv")
 
 substrait_plan = ss.substrait.serde.serialize_to_plan(
     "SELECT * FROM aggregate_test_data", ctx
@@ -49,9 +47,7 @@
 substrait_plan = ss.substrait.serde.deserialize_bytes(substrait_bytes)
 
 # type(df_logical_plan) -> <class 'substrait.LogicalPlan'>
-df_logical_plan = ss.substrait.consumer.from_substrait_plan(
-    ctx, substrait_plan
-)
+df_logical_plan = ss.substrait.consumer.from_substrait_plan(ctx, substrait_plan)
 
 # Back to Substrait Plan just for demonstration purposes
 # type(substrait_plan) -> <class 'datafusion.substrait.plan'>
diff --git a/requirements-310.txt b/requirements-310.txt
index 517c31905..915f74d54 100644
--- a/requirements-310.txt
+++ b/requirements-310.txt
@@ -2,32 +2,16 @@
 # This file is autogenerated by pip-compile with Python 3.10
 # by the following command:
 #
-#    pip-compile --generate-hashes --resolver=backtracking requirements.in
+#    pip-compile --generate-hashes --output-file=requirements-310.txt
 #
 attrs==21.2.0 \
     --hash=sha256:149e90d6d8ac20db7a955ad60cf0e6881a3f20d37096140088356da6c716b0b1 \
     --hash=sha256:ef6aaac3ca6cd92904cdd0d83f629a15f18053ec84e6432106f7a4d04ae4f5fb
     # via pytest
-black==21.9b0 \
-    --hash=sha256:380f1b5da05e5a1429225676655dddb96f5ae8c75bdf91e53d798871b902a115 \
-    --hash=sha256:7de4cfc7eb6b710de325712d40125689101d21d25283eed7e9998722cf10eb91
-    # via -r requirements.in
-click==8.0.3 \
-    --hash=sha256:353f466495adaeb40b6b5f592f9f91cb22372351c84caeb068132442a4518ef3 \
-    --hash=sha256:410e932b050f5eed773c4cda94de75971c89cdb3155a72a0831139a79e5ecb5b
-    # via black
-flake8==4.0.1 \
-    --hash=sha256:479b1304f72536a55948cb40a32dce8bb0ffe3501e26eaf292c7e60eb5e0428d \
-    --hash=sha256:806e034dda44114815e23c16ef92f95c91e4c71100ff52813adf7132a6ad870d
-    # via -r requirements.in
 iniconfig==1.1.1 \
     --hash=sha256:011e24c64b7f47f6ebd835bb12a743f2fbe9a26d4cecaa7f53bc4f35ee9da8b3 \
     --hash=sha256:bc3af051d7d14b2ee5ef9969666def0cd1a000e121eaea580d4a313df4b37f32
     # via pytest
-isort==5.9.3 \
-    --hash=sha256:9c2ea1e62d871267b78307fe511c0838ba0da28698c5732d54e2790bf3ba9899 \
-    --hash=sha256:e17d6e2b81095c9db0a03a8025a957f334d6ea30b26f9ec70805411e5c7c81f2
-    # via -r requirements.in
 maturin==0.15.1 \
     --hash=sha256:0e89a87549d671056f9358832c8aa1bb522abcf13eeca83327a58b091d4f5a98 \
     --hash=sha256:229d7eb6e14455a3c69a10a4546f082c7bd5490b8ec7f50d5d10edcea600dc64 \
@@ -43,10 +27,6 @@ maturin==0.15.1 \
     --hash=sha256:dabb8ff46461c6fb1d68e8972a172cf1dede3c9825a41e4a6caecc95c26ca3b4 \
     --hash=sha256:f604b65fd9f0b94856e88cf8b345e21a27276297e6df4ad9305937887feda13b
     # via -r requirements.in
-mccabe==0.6.1 \
-    --hash=sha256:ab8a6258860da4b6677da4bd2fe5dc2c659cff31b3ee4f7f5d64e79735b80d42 \
-    --hash=sha256:dd8d182285a0fe56bace7f45b5e7d1a6ebcbf524e8f3bd87eb0f125271b8831f
-    # via flake8
 mypy==0.910 \
     --hash=sha256:088cd9c7904b4ad80bec811053272986611b84221835e079be5bcad029e79dd9 \
     --hash=sha256:0aadfb2d3935988ec3815952e44058a3100499f5be5b28c34ac9d79f002a4a9a \
@@ -75,9 +55,7 @@ mypy==0.910 \
 mypy-extensions==0.4.3 \
     --hash=sha256:090fedd75945a69ae91ce1303b5824f428daf5a028d2f6ab8a299250a846f15d \
     --hash=sha256:2d82818f5bb3e369420cb3c4060a7970edba416647068eb4c5343488a6c604a8
-    # via
-    #   black
-    #   mypy
+    # via mypy
 numpy==1.21.3 \
     --hash=sha256:043e83bfc274649c82a6f09836943e4a4aebe5e33656271c7dbf9621dd58b8ec \
     --hash=sha256:160ccc1bed3a8371bf0d760971f09bfe80a3e18646620e9ded0ad159d9749baa \
@@ -119,14 +97,6 @@ packaging==21.0 \
     --hash=sha256:7dc96269f53a4ccec5c0670940a4281106dd0bb343f47b7471f779df49c2fbe7 \
     --hash=sha256:c86254f9220d55e31cc94d69bade760f0847da8000def4dfe1c6b872fd14ff14
     # via pytest
-pathspec==0.9.0 \
-    --hash=sha256:7d15c4ddb0b5c802d161efc417ec1a2558ea2653c2e8ad9c19098201dc1c993a \
-    --hash=sha256:e564499435a2673d586f6b2130bb5b95f04a3ba06f81b8f895b651a3c76aabb1
-    # via black
-platformdirs==2.4.0 \
-    --hash=sha256:367a5e80b3d04d2428ffa76d33f124cf11e8fff2acdaa9b43d545f5c7d661ef2 \
-    --hash=sha256:8868bbe3c3c80d42f20156f22e7131d2fb321f5bc86a2a345375c6481a67021d
-    # via black
 pluggy==1.0.0 \
     --hash=sha256:4224373bacce55f955a878bf9cfa763c1e360858e330072059e10bad68531159 \
     --hash=sha256:74134bbf457f031a36d68416e1509f34bd5ccc019f0bcc952c7b909d06b37bd3
@@ -135,52 +105,44 @@ py==1.10.0 \
     --hash=sha256:21b81bda15b66ef5e1a777a21c4dcd9c20ad3efd0b3f817e7a809035269e1bd3 \
     --hash=sha256:3b80836aa6d1feeaa108e046da6423ab8f6ceda6468545ae8d02d9d58d18818a
     # via pytest
-pyarrow==6.0.0 \
-    --hash=sha256:004185e0babc6f3c3fba6ba4f106e406a0113d0f82bb9ad9a8571a1978c45d04 \
-    --hash=sha256:0204e80777ab8f4e9abd3a765a8ec07ed1e3c4630bacda50d2ce212ef0f3826f \
-    --hash=sha256:072c1a0fca4509eefd7d018b78542fb7e5c63aaf5698f1c0a6e45628ae17ba44 \
-    --hash=sha256:15dc0d673d3f865ca63c877bd7a2eced70b0a08969fb733a28247134b8a1f18b \
-    --hash=sha256:1c38263ea438a1666b13372e7565450cfeec32dbcd1c2595749476a58465eaec \
-    --hash=sha256:281ce5fa03621d786a9beb514abb09846db7f0221b50eabf543caa24037eaacd \
-    --hash=sha256:2d2c681659396c745e4f1988d5dd41dcc3ad557bb8d4a8c2e44030edafc08a91 \
-    --hash=sha256:376c4b5f248ae63df21fe15c194e9013753164be2d38f4b3fb8bde63ac5a1958 \
-    --hash=sha256:465f87fa0be0b2928b2beeba22b5813a0203fb05d90fd8563eea48e08ecc030e \
-    --hash=sha256:477c746ef42c039348a288584800e299456c80c5691401bb9b19aa9c02a427b7 \
-    --hash=sha256:5144bd9db2920c7cb566c96462d62443cc239104f94771d110f74393f2fb42a2 \
-    --hash=sha256:5408fa8d623e66a0445f3fb0e4027fd219bf99bfb57422d543d7b7876e2c5b55 \
-    --hash=sha256:5be62679201c441356d3f2a739895dcc8d4d299f2a6eabcd2163bfb6a898abba \
-    --hash=sha256:5c666bc6a1cebf01206e2dc1ab05f25f39f35d3a499e0ef5cd635225e07306ca \
-    --hash=sha256:6163d82cca7541774b00503c295fe86a1722820eddb958b57f091bb6f5b0a6db \
-    --hash=sha256:6a1d9a2f4ee812ed0bd4182cabef99ea914ac297274f0de086f2488093d284ef \
-    --hash=sha256:7a683f71b848eb6310b4ec48c0def55dac839e9994c1ac874c9b2d3d5625def1 \
-    --hash=sha256:82fe80309e01acf29e3943a1f6d3c98ec109fe1d356bc1ac37d639bcaadcf684 \
-    --hash=sha256:8c23f8cdecd3d9e49f9b0f9a651ae5549d1d32fd4901fb1bdc2d327edfba844f \
-    --hash=sha256:8d41dfb09ba9236cca6245f33088eb42f3c54023da281139241e0f9f3b4b754e \
-    --hash=sha256:a19e58dfb04e451cd8b7bdec3ac8848373b95dfc53492c9a69789aa9074a3c1b \
-    --hash=sha256:a50d2f77b86af38ceabf45617208b9105d20e7a5eebc584e7c8c0acededd82ce \
-    --hash=sha256:a5bed4f948c032c40597302e9bdfa65f62295240306976ecbe43a54924c6f94f \
-    --hash=sha256:ac941a147d14993987cc8b605b721735a34b3e54d167302501fb4db1ad7382c7 \
-    --hash=sha256:b86d175262db1eb46afdceb36d459409eb6f8e532d3dec162f8bf572c7f57623 \
-    --hash=sha256:bf3400780c4d3c9cb43b1e8a1aaf2e1b7199a0572d0a645529d2784e4d0d8497 \
-    --hash=sha256:c7a6e7e0bf8779e9c3428ced85507541f3da9a0675e2f4781d4eb2c7042cbf81 \
-    --hash=sha256:cc1d4a70efd583befe92d4ea6f74ed2e0aa31ccdde767cd5cae8e77c65a1c2d4 \
-    --hash=sha256:d046dc78a9337baa6415be915c5a16222505233e238a1017f368243c89817eea \
-    --hash=sha256:da7860688c33ca88ac05f1a487d32d96d9caa091412496c35f3d1d832145675a \
-    --hash=sha256:ddf2e6e3b321adaaf716f2d5af8e92d205a9671e0cb7c0779710a567fd1dd580 \
-    --hash=sha256:e81508239a71943759cee272ce625ae208092dd36ef2c6713fccee30bbcf52bb \
-    --hash=sha256:ea64a48a85c631eb2a0ea13ccdec5143c85b5897836b16331ee4289d27a57247 \
-    --hash=sha256:ed0be080cf595ea15ff1c9ff4097bbf1fcc4b50847d98c0a3c0412fbc6ede7e9 \
-    --hash=sha256:fb701ec4a94b92102606d4e88f0b8eba34f09a5ad8e014eaa4af76f42b7f62ae \
-    --hash=sha256:fbda7595f24a639bcef3419ecfac17216efacb09f7b0f1b4c4c97f900d65ca0e
+pyarrow==15.0.0 \
+    --hash=sha256:001fca027738c5f6be0b7a3159cc7ba16a5c52486db18160909a0831b063c4e4 \
+    --hash=sha256:003d680b5e422d0204e7287bb3fa775b332b3fce2996aa69e9adea23f5c8f970 \
+    --hash=sha256:036a7209c235588c2f07477fe75c07e6caced9b7b61bb897c8d4e52c4b5f9555 \
+    --hash=sha256:07eb7f07dc9ecbb8dace0f58f009d3a29ee58682fcdc91337dfeb51ea618a75b \
+    --hash=sha256:0a524532fd6dd482edaa563b686d754c70417c2f72742a8c990b322d4c03a15d \
+    --hash=sha256:0ca9cb0039923bec49b4fe23803807e4ef39576a2bec59c32b11296464623dc2 \
+    --hash=sha256:17d53a9d1b2b5bd7d5e4cd84d018e2a45bc9baaa68f7e6e3ebed45649900ba99 \
+    --hash=sha256:19a8918045993349b207de72d4576af0191beef03ea655d8bdb13762f0cd6eac \
+    --hash=sha256:1f500956a49aadd907eaa21d4fff75f73954605eaa41f61cb94fb008cf2e00c6 \
+    --hash=sha256:2bd8a0e5296797faf9a3294e9fa2dc67aa7f10ae2207920dbebb785c77e9dbe5 \
+    --hash=sha256:47af7036f64fce990bb8a5948c04722e4e3ea3e13b1007ef52dfe0aa8f23cf7f \
+    --hash=sha256:5b8d43e31ca16aa6e12402fcb1e14352d0d809de70edd185c7650fe80e0769e3 \
+    --hash=sha256:5db1769e5d0a77eb92344c7382d6543bea1164cca3704f84aa44e26c67e320fb \
+    --hash=sha256:60a6bdb314affa9c2e0d5dddf3d9cbb9ef4a8dddaa68669975287d47ece67642 \
+    --hash=sha256:66958fd1771a4d4b754cd385835e66a3ef6b12611e001d4e5edfcef5f30391e2 \
+    --hash=sha256:6eda9e117f0402dfcd3cd6ec9bfee89ac5071c48fc83a84f3075b60efa96747f \
+    --hash=sha256:6f87d9c4f09e049c2cade559643424da84c43a35068f2a1c4653dc5b1408a929 \
+    --hash=sha256:85239b9f93278e130d86c0e6bb455dcb66fc3fd891398b9d45ace8799a871a1e \
+    --hash=sha256:876858f549d540898f927eba4ef77cd549ad8d24baa3207cf1b72e5788b50e83 \
+    --hash=sha256:8780b1a29d3c8b21ba6b191305a2a607de2e30dab399776ff0aa09131e266340 \
+    --hash=sha256:93768ccfff85cf044c418bfeeafce9a8bb0cee091bd8fd19011aff91e58de540 \
+    --hash=sha256:972a0141be402bb18e3201448c8ae62958c9c7923dfaa3b3d4530c835ac81aed \
+    --hash=sha256:9950a9c9df24090d3d558b43b97753b8f5867fb8e521f29876aa021c52fda351 \
+    --hash=sha256:9a3a6180c0e8f2727e6f1b1c87c72d3254cac909e609f35f22532e4115461177 \
+    --hash=sha256:9ed5a78ed29d171d0acc26a305a4b7f83c122d54ff5270810ac23c75813585e4 \
+    --hash=sha256:c8c287d1d479de8269398b34282e206844abb3208224dbdd7166d580804674b7 \
+    --hash=sha256:d0ec076b32bacb6666e8813a22e6e5a7ef1314c8069d4ff345efa6246bc38593 \
+    --hash=sha256:d1c48648f64aec09accf44140dccb92f4f94394b8d79976c426a5b79b11d4fa7 \
+    --hash=sha256:d31c1d45060180131caf10f0f698e3a782db333a422038bf7fe01dace18b3a31 \
+    --hash=sha256:e2617e3bf9df2a00020dd1c1c6dce5cc343d979efe10bc401c0632b0eef6ef5b \
+    --hash=sha256:e8ebed6053dbe76883a822d4e8da36860f479d55a762bd9e70d8494aed87113e \
+    --hash=sha256:f01fc5cf49081426429127aa2d427d9d98e1cb94a32cb961d583a70b7c4504e6 \
+    --hash=sha256:f6ee87fd6892700960d90abb7b17a72a5abb3b64ee0fe8db6c782bcc2d0dc0b4 \
+    --hash=sha256:f75fce89dad10c95f4bf590b765e3ae98bcc5ba9f6ce75adb828a334e26a3d40 \
+    --hash=sha256:fa7cd198280dbd0c988df525e50e35b5d16873e2cdae2aaaa6363cdb64e3eec5 \
+    --hash=sha256:fe0ec198ccc680f6c92723fadcb97b74f07c45ff3fdec9dd765deb04955ccf19
     # via -r requirements.in
-pycodestyle==2.8.0 \
-    --hash=sha256:720f8b39dde8b293825e7ff02c475f3077124006db4f440dcbc9a20b76548a20 \
-    --hash=sha256:eddd5847ef438ea1c7870ca7eb78a9d47ce0cdb4851a5523949f2601d0cbbe7f
-    # via flake8
-pyflakes==2.4.0 \
-    --hash=sha256:05a85c2872edf37a4ed30b0cce2f6093e1d0581f8c19d7393122da7e25b2b24c \
-    --hash=sha256:3bb3a3f256f4b7968c9c788781e4ff07dce46bdf12339dcda61053375426ee2e
-    # via flake8
 pyparsing==3.0.3 \
     --hash=sha256:9e3511118010f112a4b4b435ae50e1eaa610cda191acb9e421d60cf5fde83455 \
     --hash=sha256:f8d3fe9fc404576c5164f0f0c4e382c96b85265e023c409c43d48f65da9d60d0
@@ -189,44 +151,25 @@ pytest==6.2.5 \
     --hash=sha256:131b36680866a76e6781d13f101efb86cf674ebb9762eb70d3082b6f29889e89 \
     --hash=sha256:7310f8d27bc79ced999e760ca304d69f6ba6c6649c0b60fb0e04a4a77cacc134
     # via -r requirements.in
-regex==2021.10.23 \
-    --hash=sha256:0c186691a7995ef1db61205e00545bf161fb7b59cdb8c1201c89b333141c438a \
-    --hash=sha256:0dcc0e71118be8c69252c207630faf13ca5e1b8583d57012aae191e7d6d28b84 \
-    --hash=sha256:0f7552429dd39f70057ac5d0e897e5bfe211629652399a21671e53f2a9693a4e \
-    --hash=sha256:129472cd06062fb13e7b4670a102951a3e655e9b91634432cfbdb7810af9d710 \
-    --hash=sha256:13ec99df95003f56edcd307db44f06fbeb708c4ccdcf940478067dd62353181e \
-    --hash=sha256:1f2b59c28afc53973d22e7bc18428721ee8ca6079becf1b36571c42627321c65 \
-    --hash=sha256:2b20f544cbbeffe171911f6ce90388ad36fe3fad26b7c7a35d4762817e9ea69c \
-    --hash=sha256:2fb698037c35109d3c2e30f2beb499e5ebae6e4bb8ff2e60c50b9a805a716f79 \
-    --hash=sha256:34d870f9f27f2161709054d73646fc9aca49480617a65533fc2b4611c518e455 \
-    --hash=sha256:391703a2abf8013d95bae39145d26b4e21531ab82e22f26cd3a181ee2644c234 \
-    --hash=sha256:450dc27483548214314640c89a0f275dbc557968ed088da40bde7ef8fb52829e \
-    --hash=sha256:45b65d6a275a478ac2cbd7fdbf7cc93c1982d613de4574b56fd6972ceadb8395 \
-    --hash=sha256:5095a411c8479e715784a0c9236568ae72509450ee2226b649083730f3fadfc6 \
-    --hash=sha256:530fc2bbb3dc1ebb17f70f7b234f90a1dd43b1b489ea38cea7be95fb21cdb5c7 \
-    --hash=sha256:56f0c81c44638dfd0e2367df1a331b4ddf2e771366c4b9c5d9a473de75e3e1c7 \
-    --hash=sha256:5e9c9e0ce92f27cef79e28e877c6b6988c48b16942258f3bc55d39b5f911df4f \
-    --hash=sha256:6d7722136c6ed75caf84e1788df36397efdc5dbadab95e59c2bba82d4d808a4c \
-    --hash=sha256:74d071dbe4b53c602edd87a7476ab23015a991374ddb228d941929ad7c8c922e \
-    --hash=sha256:7b568809dca44cb75c8ebb260844ea98252c8c88396f9d203f5094e50a70355f \
-    --hash=sha256:80bb5d2e92b2258188e7dcae5b188c7bf868eafdf800ea6edd0fbfc029984a88 \
-    --hash=sha256:8d1cdcda6bd16268316d5db1038965acf948f2a6f43acc2e0b1641ceab443623 \
-    --hash=sha256:9f665677e46c5a4d288ece12fdedf4f4204a422bb28ff05f0e6b08b7447796d1 \
-    --hash=sha256:a30513828180264294953cecd942202dfda64e85195ae36c265daf4052af0464 \
-    --hash=sha256:a7a986c45d1099a5de766a15de7bee3840b1e0e1a344430926af08e5297cf666 \
-    --hash=sha256:a940ca7e7189d23da2bfbb38973832813eab6bd83f3bf89a977668c2f813deae \
-    --hash=sha256:ab7c5684ff3538b67df3f93d66bd3369b749087871ae3786e70ef39e601345b0 \
-    --hash=sha256:be04739a27be55631069b348dda0c81d8ea9822b5da10b8019b789e42d1fe452 \
-    --hash=sha256:c0938ddd60cc04e8f1faf7a14a166ac939aac703745bfcd8e8f20322a7373019 \
-    --hash=sha256:cb46b542133999580ffb691baf67410306833ee1e4f58ed06b6a7aaf4e046952 \
-    --hash=sha256:d134757a37d8640f3c0abb41f5e68b7cf66c644f54ef1cb0573b7ea1c63e1509 \
-    --hash=sha256:de557502c3bec8e634246588a94e82f1ee1b9dfcfdc453267c4fb652ff531570 \
-    --hash=sha256:ded0c4a3eee56b57fcb2315e40812b173cafe79d2f992d50015f4387445737fa \
-    --hash=sha256:e1dae12321b31059a1a72aaa0e6ba30156fe7e633355e445451e4021b8e122b6 \
-    --hash=sha256:eb672217f7bd640411cfc69756ce721d00ae600814708d35c930930f18e8029f \
-    --hash=sha256:ee684f139c91e69fe09b8e83d18b4d63bf87d9440c1eb2eeb52ee851883b1b29 \
-    --hash=sha256:f3f9a91d3cc5e5b0ddf1043c0ae5fa4852f18a1c0050318baf5fc7930ecc1f9c
-    # via black
+ruff==0.3.0 \
+    --hash=sha256:0886184ba2618d815067cf43e005388967b67ab9c80df52b32ec1152ab49f53a \
+    --hash=sha256:128265876c1d703e5f5e5a4543bd8be47c73a9ba223fd3989d4aa87dd06f312f \
+    --hash=sha256:19eacceb4c9406f6c41af806418a26fdb23120dfe53583df76d1401c92b7c14b \
+    --hash=sha256:23dbb808e2f1d68eeadd5f655485e235c102ac6f12ad31505804edced2a5ae77 \
+    --hash=sha256:2f7dbba46e2827dfcb0f0cc55fba8e96ba7c8700e0a866eb8cef7d1d66c25dcb \
+    --hash=sha256:3ef655c51f41d5fa879f98e40c90072b567c666a7114fa2d9fe004dffba00932 \
+    --hash=sha256:5da894a29ec018a8293d3d17c797e73b374773943e8369cfc50495573d396933 \
+    --hash=sha256:755c22536d7f1889be25f2baf6fedd019d0c51d079e8417d4441159f3bcd30c2 \
+    --hash=sha256:7deb528029bacf845bdbb3dbb2927d8ef9b4356a5e731b10eef171e3f0a85944 \
+    --hash=sha256:9343690f95710f8cf251bee1013bf43030072b9f8d012fbed6ad702ef70d360a \
+    --hash=sha256:a1f3ed501a42f60f4dedb7805fa8d4534e78b4e196f536bac926f805f0743d49 \
+    --hash=sha256:b08b356d06a792e49a12074b62222f9d4ea2a11dca9da9f68163b28c71bf1dd4 \
+    --hash=sha256:cc30a9053ff2f1ffb505a585797c23434d5f6c838bacfe206c0e6cf38c921a1e \
+    --hash=sha256:d0d3d7ef3d4f06433d592e5f7d813314a34601e6c5be8481cccb7fa760aa243e \
+    --hash=sha256:dd73fe7f4c28d317855da6a7bc4aa29a1500320818dd8f27df95f70a01b8171f \
+    --hash=sha256:e1e0d4381ca88fb2b73ea0766008e703f33f460295de658f5467f6f229658c19 \
+    --hash=sha256:e3a4a6d46aef0a84b74fcd201a4401ea9a6cd85614f6a9435f2d33dd8cefbf83
+    # via -r requirements.in
 toml==0.10.2 \
     --hash=sha256:806143ae5bfb6a3c6e736a764057db0e6a0e05e338b5630894a5f779cabb4f9b \
     --hash=sha256:b3bda1d108d5dd99f4a20d24d9c348e91c4db7ab1b749200bded2f839ccbe68f
@@ -237,13 +180,9 @@ toml==0.10.2 \
 tomli==1.2.2 \
     --hash=sha256:c6ce0015eb38820eaf32b5db832dbc26deb3dd427bd5f6556cf0acac2c214fee \
     --hash=sha256:f04066f68f5554911363063a30b108d2b5a5b1a010aa8b6132af78489fe3aade
-    # via
-    #   black
-    #   maturin
+    # via maturin
 typing-extensions==3.10.0.2 \
     --hash=sha256:49f75d16ff11f1cd258e1b988ccff82a3ca5570217d7ad8c5f48205dd99a677e \
     --hash=sha256:d8226d10bc02a29bcc81df19a26e56a9647f8b0a6d4a83924139f4a8b01f17b7 \
     --hash=sha256:f1d25edafde516b146ecd0613dabcc61409817af4766fbbcfb8d1ad4ec441a34
-    # via
-    #   black
-    #   mypy
+    # via mypy
diff --git a/requirements-311.txt b/requirements-311.txt
index c5ae2ef79..876311e6c 100644
--- a/requirements-311.txt
+++ b/requirements-311.txt
@@ -4,46 +4,10 @@
 #
 #    pip-compile --generate-hashes --output-file=requirements-311.txt
 #
-black==24.2.0 \
-    --hash=sha256:057c3dc602eaa6fdc451069bd027a1b2635028b575a6c3acfd63193ced20d9c8 \
-    --hash=sha256:08654d0797e65f2423f850fc8e16a0ce50925f9337fb4a4a176a7aa4026e63f8 \
-    --hash=sha256:163baf4ef40e6897a2a9b83890e59141cc8c2a98f2dda5080dc15c00ee1e62cd \
-    --hash=sha256:1e08fb9a15c914b81dd734ddd7fb10513016e5ce7e6704bdd5e1251ceee51ac9 \
-    --hash=sha256:4dd76e9468d5536abd40ffbc7a247f83b2324f0c050556d9c371c2b9a9a95e31 \
-    --hash=sha256:4f9de21bafcba9683853f6c96c2d515e364aee631b178eaa5145fc1c61a3cc92 \
-    --hash=sha256:61a0391772490ddfb8a693c067df1ef5227257e72b0e4108482b8d41b5aee13f \
-    --hash=sha256:6981eae48b3b33399c8757036c7f5d48a535b962a7c2310d19361edeef64ce29 \
-    --hash=sha256:7e53a8c630f71db01b28cd9602a1ada68c937cbf2c333e6ed041390d6968faf4 \
-    --hash=sha256:810d445ae6069ce64030c78ff6127cd9cd178a9ac3361435708b907d8a04c693 \
-    --hash=sha256:93601c2deb321b4bad8f95df408e3fb3943d85012dddb6121336b8e24a0d1218 \
-    --hash=sha256:992e451b04667116680cb88f63449267c13e1ad134f30087dec8527242e9862a \
-    --hash=sha256:9db528bccb9e8e20c08e716b3b09c6bdd64da0dd129b11e160bf082d4642ac23 \
-    --hash=sha256:a0057f800de6acc4407fe75bb147b0c2b5cbb7c3ed110d3e5999cd01184d53b0 \
-    --hash=sha256:ba15742a13de85e9b8f3239c8f807723991fbfae24bad92d34a2b12e81904982 \
-    --hash=sha256:bce4f25c27c3435e4dace4815bcb2008b87e167e3bf4ee47ccdc5ce906eb4894 \
-    --hash=sha256:ca610d29415ee1a30a3f30fab7a8f4144e9d34c89a235d81292a1edb2b55f540 \
-    --hash=sha256:d533d5e3259720fdbc1b37444491b024003e012c5173f7d06825a77508085430 \
-    --hash=sha256:d84f29eb3ee44859052073b7636533ec995bd0f64e2fb43aeceefc70090e752b \
-    --hash=sha256:e37c99f89929af50ffaf912454b3e3b47fd64109659026b678c091a4cd450fb2 \
-    --hash=sha256:e8a6ae970537e67830776488bca52000eaa37fa63b9988e8c487458d9cd5ace6 \
-    --hash=sha256:faf2ee02e6612577ba0181f4347bcbcf591eb122f7841ae5ba233d12c39dcb4d
-    # via -r requirements.in
-click==8.1.7 \
-    --hash=sha256:ae74fb96c20a0277a1d615f1e4d73c8414f5a98db8b799a7931d1582f3390c28 \
-    --hash=sha256:ca9853ad459e787e2192211578cc907e7594e294c7ccc834310722b41b9ca6de
-    # via black
-flake8==7.0.0 \
-    --hash=sha256:33f96621059e65eec474169085dc92bf26e7b2d47366b70be2f67ab80dc25132 \
-    --hash=sha256:a6dfbb75e03252917f2473ea9653f7cd799c3064e54d4c8140044c5c065f53c3
-    # via -r requirements.in
 iniconfig==2.0.0 \
     --hash=sha256:2d91e135bf72d31a410b17c16da610a82cb55f6b0477d1a902134b24a455b8b3 \
     --hash=sha256:b6a85871a79d2e3b22d2d1b94ac2824226a63c6b741c88f7ae975f18b6778374
     # via pytest
-isort==5.13.2 \
-    --hash=sha256:48fdfcb9face5d58a4f6dde2e72a1fb8dcaf8ab26f95ab49fab84c2ddefb0109 \
-    --hash=sha256:8ca5e72a8d85860d5a3fa69b8745237f2939afe12dbf656afbcb47fe72d947a6
-    # via -r requirements.in
 maturin==1.4.0 \
     --hash=sha256:01473dc30aed8f2cee3572b3e99e3ea75bf09c84b028bf6077f7643a189699c8 \
     --hash=sha256:076970a73da7fa3648204a584cd347b899c1ea67f8124b212bccd06728e63ed9 \
@@ -59,10 +23,6 @@ maturin==1.4.0 \
     --hash=sha256:ff95a4494d9e57b6e74d4d7f8a9a2ee8ed29bd7f0e61855656ad959a432c0efc \
     --hash=sha256:ffe4e967080ceb83c156e73a37d3974b30cad01c376a86dc39a76a0c6bccf9b0
     # via -r requirements.in
-mccabe==0.7.0 \
-    --hash=sha256:348e0240c33b60bbdf4e523192ef919f28cb2c3d7d5c7794f74009290f236325 \
-    --hash=sha256:6c2d30ab6be0e4a46919781807b4f0d834ebdd6c6e3dca0bda5a15f863427b6e
-    # via flake8
 mypy==1.8.0 \
     --hash=sha256:028cf9f2cae89e202d7b6593cd98db6759379f17a319b5faf4f9978d7084cdc6 \
     --hash=sha256:2afecd6354bbfb6e0160f4e4ad9ba6e4e003b767dd80d85516e71f2e955ab50d \
@@ -95,9 +55,7 @@ mypy==1.8.0 \
 mypy-extensions==1.0.0 \
     --hash=sha256:4392f6c0eb8a5668a69e23d168ffa70f0be9ccfd32b5cc2d26a34ae5b844552d \
     --hash=sha256:75dbf8955dc00442a438fc4d0666508a9a97b6bd41aa2f0ffe9d2f2725af0782
-    # via
-    #   black
-    #   mypy
+    # via mypy
 numpy==1.26.4 \
     --hash=sha256:03a8c78d01d9781b28a6989f6fa1bb2c4f2d51201cf99d3dd875df6fbd96b23b \
     --hash=sha256:08beddf13648eb95f8d867350f6a018a4be2e5ad54c8d8caed89ebca558b2818 \
@@ -141,17 +99,7 @@ numpy==1.26.4 \
 packaging==23.2 \
     --hash=sha256:048fb0e9405036518eaaf48a55953c750c11e1a1b68e0dd1a9d62ed0c092cfc5 \
     --hash=sha256:8c491190033a9af7e1d931d0b5dacc2ef47509b34dd0de67ed209b5203fc88c7
-    # via
-    #   black
-    #   pytest
-pathspec==0.12.1 \
-    --hash=sha256:a0d503e138a4c123b27490a4f7beda6a01c6f288df0e4a8b79c7eb0dc7b4cc08 \
-    --hash=sha256:a482d51503a1ab33b1c67a6c3813a26953dbdc71c31dacaef9a838c4e29f5712
-    # via black
-platformdirs==4.2.0 \
-    --hash=sha256:0614df2a2f37e1a662acbd8e2b25b92ccf8632929bc6d43467e17fe89c75e068 \
-    --hash=sha256:ef0cc731df711022c174543cb70a9b5bd22e5a9337c8624ef2c2ceb8ddad8768
-    # via black
+    # via pytest
 pluggy==1.4.0 \
     --hash=sha256:7db9f7b503d67d1c5b95f59773ebb58a8c1c288129a88665838012cfb07b8981 \
     --hash=sha256:8c85c2876142a764e5b7548e7d9a0e0ddb46f5185161049a79b7e974454223be
@@ -194,18 +142,29 @@ pyarrow==15.0.0 \
     --hash=sha256:fa7cd198280dbd0c988df525e50e35b5d16873e2cdae2aaaa6363cdb64e3eec5 \
     --hash=sha256:fe0ec198ccc680f6c92723fadcb97b74f07c45ff3fdec9dd765deb04955ccf19
     # via -r requirements.in
-pycodestyle==2.11.1 \
-    --hash=sha256:41ba0e7afc9752dfb53ced5489e89f8186be00e599e712660695b7a75ff2663f \
-    --hash=sha256:44fe31000b2d866f2e41841b18528a505fbd7fef9017b04eff4e2648a0fadc67
-    # via flake8
-pyflakes==3.2.0 \
-    --hash=sha256:1c61603ff154621fb2a9172037d84dca3500def8c8b630657d1701f026f8af3f \
-    --hash=sha256:84b5be138a2dfbb40689ca07e2152deb896a65c3a3e24c251c5c62489568074a
-    # via flake8
 pytest==8.0.2 \
     --hash=sha256:d4051d623a2e0b7e51960ba963193b09ce6daeb9759a451844a21e4ddedfc1bd \
     --hash=sha256:edfaaef32ce5172d5466b5127b42e0d6d35ebbe4453f0e3505d96afd93f6b096
     # via -r requirements.in
+ruff==0.3.0 \
+    --hash=sha256:0886184ba2618d815067cf43e005388967b67ab9c80df52b32ec1152ab49f53a \
+    --hash=sha256:128265876c1d703e5f5e5a4543bd8be47c73a9ba223fd3989d4aa87dd06f312f \
+    --hash=sha256:19eacceb4c9406f6c41af806418a26fdb23120dfe53583df76d1401c92b7c14b \
+    --hash=sha256:23dbb808e2f1d68eeadd5f655485e235c102ac6f12ad31505804edced2a5ae77 \
+    --hash=sha256:2f7dbba46e2827dfcb0f0cc55fba8e96ba7c8700e0a866eb8cef7d1d66c25dcb \
+    --hash=sha256:3ef655c51f41d5fa879f98e40c90072b567c666a7114fa2d9fe004dffba00932 \
+    --hash=sha256:5da894a29ec018a8293d3d17c797e73b374773943e8369cfc50495573d396933 \
+    --hash=sha256:755c22536d7f1889be25f2baf6fedd019d0c51d079e8417d4441159f3bcd30c2 \
+    --hash=sha256:7deb528029bacf845bdbb3dbb2927d8ef9b4356a5e731b10eef171e3f0a85944 \
+    --hash=sha256:9343690f95710f8cf251bee1013bf43030072b9f8d012fbed6ad702ef70d360a \
+    --hash=sha256:a1f3ed501a42f60f4dedb7805fa8d4534e78b4e196f536bac926f805f0743d49 \
+    --hash=sha256:b08b356d06a792e49a12074b62222f9d4ea2a11dca9da9f68163b28c71bf1dd4 \
+    --hash=sha256:cc30a9053ff2f1ffb505a585797c23434d5f6c838bacfe206c0e6cf38c921a1e \
+    --hash=sha256:d0d3d7ef3d4f06433d592e5f7d813314a34601e6c5be8481cccb7fa760aa243e \
+    --hash=sha256:dd73fe7f4c28d317855da6a7bc4aa29a1500320818dd8f27df95f70a01b8171f \
+    --hash=sha256:e1e0d4381ca88fb2b73ea0766008e703f33f460295de658f5467f6f229658c19 \
+    --hash=sha256:e3a4a6d46aef0a84b74fcd201a4401ea9a6cd85614f6a9435f2d33dd8cefbf83
+    # via -r requirements.in
 toml==0.10.2 \
     --hash=sha256:806143ae5bfb6a3c6e736a764057db0e6a0e05e338b5630894a5f779cabb4f9b \
     --hash=sha256:b3bda1d108d5dd99f4a20d24d9c348e91c4db7ab1b749200bded2f839ccbe68f
diff --git a/requirements.in b/requirements.in
index 09872b03b..2365d23e0 100644
--- a/requirements.in
+++ b/requirements.in
@@ -15,13 +15,11 @@
 # specific language governing permissions and limitations
 # under the License.
 
-black
-flake8
-isort
 maturin>=0.15
 mypy
 numpy
 pyarrow>=11.0.0
 pytest
+ruff
 toml
 importlib_metadata; python_version < "3.8"