diff --git a/.github/workflows/test_and_build.yml b/.github/workflows/test_and_build.yml
index c20530fbe..064dd93d8 100644
--- a/.github/workflows/test_and_build.yml
+++ b/.github/workflows/test_and_build.yml
@@ -171,22 +171,22 @@ jobs:
             npver=$(python -c 'import random ; print(random.choice(["=1.21", "=1.22", "=1.23", "=1.24", ""]))')
             spver=$(python -c 'import random ; print(random.choice(["=1.8", "=1.9", "=1.10", ""]))')
             pdver=$(python -c 'import random ; print(random.choice(["=1.2", "=1.3", "=1.4", "=1.5", "=2.0", ""]))')
-            akver=$(python -c 'import random ; print(random.choice(["=1.9", "=1.10", "=2.0", "=2.1", ""]))')
+            akver=$(python -c 'import random ; print(random.choice(["=1.9", "=1.10", "=2.0", "=2.1", "=2.2", ""]))')
           elif [[ ${{ startsWith(steps.pyver.outputs.selected, '3.9') }} == true ]]; then
             npver=$(python -c 'import random ; print(random.choice(["=1.21", "=1.22", "=1.23", "=1.24", ""]))')
             spver=$(python -c 'import random ; print(random.choice(["=1.8", "=1.9", "=1.10", ""]))')
             pdver=$(python -c 'import random ; print(random.choice(["=1.2", "=1.3", "=1.4", "=1.5", "=2.0", ""]))')
-            akver=$(python -c 'import random ; print(random.choice(["=1.9", "=1.10", "=2.0", "=2.1", ""]))')
+            akver=$(python -c 'import random ; print(random.choice(["=1.9", "=1.10", "=2.0", "=2.1", "=2.2", ""]))')
           elif [[ ${{ startsWith(steps.pyver.outputs.selected, '3.10') }} == true ]]; then
             npver=$(python -c 'import random ; print(random.choice(["=1.21", "=1.22", "=1.23", "=1.24", ""]))')
             spver=$(python -c 'import random ; print(random.choice(["=1.8", "=1.9", "=1.10", ""]))')
             pdver=$(python -c 'import random ; print(random.choice(["=1.3", "=1.4", "=1.5", "=2.0", ""]))')
-            akver=$(python -c 'import random ; print(random.choice(["=1.9", "=1.10", "=2.0", "=2.1", ""]))')
+            akver=$(python -c 'import random ; print(random.choice(["=1.9", "=1.10", "=2.0", "=2.1", "=2.2", ""]))')
           else  # Python 3.11
             npver=$(python -c 'import random ; print(random.choice(["=1.23", "=1.24", ""]))')
             spver=$(python -c 'import random ; print(random.choice(["=1.9", "=1.10", ""]))')
             pdver=$(python -c 'import random ; print(random.choice(["=1.5", "=2.0", ""]))')
-            akver=$(python -c 'import random ; print(random.choice(["=1.10", "=2.0", "=2.1", ""]))')
+            akver=$(python -c 'import random ; print(random.choice(["=1.10", "=2.0", "=2.1", "=2.2", ""]))')
           fi
           if [[ ${{ steps.sourcetype.outputs.selected }} == "source" || ${{ steps.sourcetype.outputs.selected }} == "upstream" ]]; then
             # TODO: there are currently issues with some numpy versions when
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index d995f4253..10fcca649 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -43,7 +43,7 @@ repos:
       - id: isort
   # Let's keep `pyupgrade` even though `ruff --fix` probably does most of it
   - repo: https://github.com/asottile/pyupgrade
-    rev: v3.3.2
+    rev: v3.4.0
     hooks:
       - id: pyupgrade
         args: [--py38-plus]
@@ -58,7 +58,7 @@ repos:
       - id: black
       - id: black-jupyter
   - repo: https://github.com/charliermarsh/ruff-pre-commit
-    rev: v0.0.265
+    rev: v0.0.267
     hooks:
       - id: ruff
         args: [--fix-only, --show-fixes]
@@ -71,7 +71,7 @@ repos:
         additional_dependencies: &flake8_dependencies
         # These versions need updated manually
         - flake8==6.0.0
-        - flake8-bugbear==23.3.23
+        - flake8-bugbear==23.5.9
         - flake8-simplify==0.20.0
   - repo: https://github.com/asottile/yesqa
     rev: v1.4.0
@@ -86,7 +86,7 @@ repos:
         additional_dependencies: [tomli]
         files: ^(graphblas|docs)/
   - repo: https://github.com/charliermarsh/ruff-pre-commit
-    rev: v0.0.265
+    rev: v0.0.267
     hooks:
       - id: ruff
   - repo: https://github.com/sphinx-contrib/sphinx-lint
diff --git a/environment.yml b/environment.yml
index 875ec5cbd..1a7fb6fa8 100644
--- a/environment.yml
+++ b/environment.yml
@@ -94,8 +94,10 @@ dependencies:
     # - python-igraph
     # - python-louvain
     # - pyupgrade
+    # - rich
     # - ruff
     # - scalene
+    # - scikit-network
     # - setuptools-git-versioning
     # - snakeviz
     # - sphinx-lint
diff --git a/graphblas/agg/__init__.py b/graphblas/agg/__init__.py
index c1319facb..9f6ead0b5 100644
--- a/graphblas/agg/__init__.py
+++ b/graphblas/agg/__init__.py
@@ -1,4 +1,4 @@
-"""`graphblas.agg` is an experimental module for exploring Aggregators.
+"""``graphblas.agg`` is an experimental module for exploring Aggregators.
 
 Aggregators may be used in reduce methods:
     - Matrix.reduce_rowwise
@@ -59,9 +59,9 @@
     - ss.argmax
 
 .. deprecated:: 2023.1.0
-    Aggregators `first`, `last`, `first_index`, `last_index`, `argmin`, and `argmax` are
-    deprecated in the `agg` namespace such as `agg.first`. Use them from `agg.ss` namespace
-    instead such as `agg.ss.first`. Will be removed in version 2023.9.0 or later.
+    Aggregators ``first``, ``last``, ``first_index``, ``last_index``, ``argmin``, and ``argmax``
+    are deprecated in the ``agg`` namespace such as ``agg.first``. Use them from ``agg.ss``
+    namespace instead such as ``agg.ss.first``. Will be removed in version 2023.9.0 or later.
 
 # Possible aggregators:
 #   - absolute_deviation, sum(abs(x - mean(x))),  sum_absminus(x, mean(x))
diff --git a/graphblas/core/agg.py b/graphblas/core/agg.py
index b9f1977ab..23848d3b9 100644
--- a/graphblas/core/agg.py
+++ b/graphblas/core/agg.py
@@ -1,8 +1,8 @@
 """graphblas.core.agg namespace is deprecated; please use graphblas.core.operator.agg instead.
 
 .. deprecated:: 2023.3.0
-`graphblas.core.agg` will be removed in a future release.
-Use `graphblas.core.operator.agg` instead.
+``graphblas.core.agg`` will be removed in a future release.
+Use ``graphblas.core.operator.agg`` instead.
 Will be removed in version 2023.11.0 or later.
 
 """
diff --git a/graphblas/core/automethods.py b/graphblas/core/automethods.py
index 98dc61137..937e331fd 100644
--- a/graphblas/core/automethods.py
+++ b/graphblas/core/automethods.py
@@ -1,6 +1,6 @@
 """Define functions to use as property methods on expressions.
 
-These will automatically compute the value and avoid the need for `.new()`.
+These will automatically compute the value and avoid the need for ``.new()``.
 
 To automatically create the functions, run:
 
diff --git a/graphblas/core/mask.py b/graphblas/core/mask.py
index 9ad209095..3bda2188a 100644
--- a/graphblas/core/mask.py
+++ b/graphblas/core/mask.py
@@ -35,7 +35,7 @@ def new(self, dtype=None, *, complement=False, mask=None, name=None, **opts):
         """Return a new object with True values determined by the mask(s).
 
         By default, the result is True wherever the mask(s) would have been applied,
-        and empty otherwise.  If `complement` is True, then these are switched:
+        and empty otherwise.  If ``complement`` is True, then these are switched:
         the result is empty where the mask(s) would have been applied, and True otherwise.
 
         In other words, these are equivalent if complement is False (and mask keyword is None):
@@ -48,14 +48,14 @@ def new(self, dtype=None, *, complement=False, mask=None, name=None, **opts):
         >>> C(self) << expr
         >>> C(~result.S) << expr  # equivalent when complement is True
 
-        This can also efficiently merge two masks by using the `mask=` argument.
+        This can also efficiently merge two masks by using the ``mask=`` argument.
         This is equivalent to the following (but uses more efficient recipes):
 
         >>> val = Matrix(...)
         >>> val(self) << True
         >>> val(mask, replace=True) << val
 
-        If `complement=` argument is True, then the *complement* will be returned.
+        If ``complement=`` argument is True, then the *complement* will be returned.
         This is equivalent to the following (but uses more efficient recipes):
 
         >>> val = Matrix(...)
@@ -83,7 +83,7 @@ def new(self, dtype=None, *, complement=False, mask=None, name=None, **opts):
     def __and__(self, other, **opts):
         """Return the intersection of two masks as a new mask.
 
-        `new_mask = mask1 & mask2` is equivalent to the following:
+        ``new_mask = mask1 & mask2`` is equivalent to the following:
 
         >>> val = Matrix(bool, nrows, ncols)
         >>> val(mask1) << True
@@ -109,7 +109,7 @@ def __and__(self, other, **opts):
     def __or__(self, other, **opts):
         """Return the union of two masks as a new mask.
 
-        `new_mask = mask1 | mask2` is equivalent to the following:
+        ``new_mask = mask1 | mask2`` is equivalent to the following:
 
         >>> val = Matrix(bool, nrows, ncols)
         >>> val(mask1) << True
diff --git a/graphblas/core/matrix.py b/graphblas/core/matrix.py
index 0183893fd..b74ca347a 100644
--- a/graphblas/core/matrix.py
+++ b/graphblas/core/matrix.py
@@ -355,7 +355,7 @@ def isclose(self, other, *, rel_tol=1e-7, abs_tol=0.0, check_dtype=False, **opts
         Returns
         -------
         bool
-            Whether all values of the Matrix are close to the values in `other`.
+            Whether all values of the Matrix are close to the values in ``other``.
         """
         other = self._expect_type(
             other, (Matrix, TransposedMatrix), within="isclose", argname="other"
@@ -448,19 +448,19 @@ def to_values(self, dtype=None, *, rows=True, columns=True, values=True, sort=Tr
         corresponding to the COO format of the Matrix.
 
         .. deprecated:: 2022.11.0
-            `Matrix.to_values` will be removed in a future release.
-            Use `Matrix.to_coo` instead. Will be removed in version 2023.9.0 or later
+            ``Matrix.to_values`` will be removed in a future release.
+            Use ``Matrix.to_coo`` instead. Will be removed in version 2023.9.0 or later
 
         Parameters
         ----------
         dtype :
             Requested dtype for the output values array.
         rows : bool, default=True
-            Whether to return rows; will return `None` for rows if `False`
+            Whether to return rows; will return ``None`` for rows if ``False``
         columns  :bool, default=True
-            Whether to return columns; will return `None` for columns if `False`
+            Whether to return columns; will return ``None`` for columns if ``False``
         values : bool, default=True
-            Whether to return values; will return `None` for values if `False`
+            Whether to return values; will return ``None`` for values if ``False``
         sort : bool, default=True
             Whether to require sorted indices.
             If internally stored rowwise, the sorting will be first by rows, then by column.
@@ -488,11 +488,11 @@ def to_coo(self, dtype=None, *, rows=True, columns=True, values=True, sort=True)
         dtype :
             Requested dtype for the output values array.
         rows : bool, default=True
-            Whether to return rows; will return `None` for rows if `False`
+            Whether to return rows; will return ``None`` for rows if ``False``
         columns  :bool, default=True
-            Whether to return columns; will return `None` for columns if `False`
+            Whether to return columns; will return ``None`` for columns if ``False``
         values : bool, default=True
-            Whether to return values; will return `None` for values if `False`
+            Whether to return values; will return ``None`` for values if ``False``
         sort : bool, default=True
             Whether to require sorted indices.
             If internally stored rowwise, the sorting will be first by rows, then by column.
@@ -559,7 +559,7 @@ def to_edgelist(self, dtype=None, *, values=True, sort=True):
         dtype :
             Requested dtype for the output values array.
         values : bool, default=True
-            Whether to return values; will return `None` for values if `False`
+            Whether to return values; will return ``None`` for values if ``False``
         sort : bool, default=True
             Whether to require sorted indices.
             If internally stored rowwise, the sorting will be first by rows, then by column.
@@ -585,7 +585,7 @@ def build(self, rows, columns, values, *, dup_op=None, clear=False, nrows=None,
         The typical use case is to create a new Matrix and insert values
         at the same time using :meth:`from_coo`.
 
-        All the arguments are used identically in :meth:`from_coo`, except for `clear`, which
+        All the arguments are used identically in :meth:`from_coo`, except for ``clear``, which
         indicates whether to clear the Matrix prior to adding the new values.
         """
         # TODO: accept `dtype` keyword to match the dtype of `values`?
@@ -781,8 +781,8 @@ def from_values(
         """Create a new Matrix from row and column indices and values.
 
         .. deprecated:: 2022.11.0
-            `Matrix.from_values` will be removed in a future release.
-            Use `Matrix.from_coo` instead. Will be removed in version 2023.9.0 or later
+            ``Matrix.from_values`` will be removed in a future release.
+            Use ``Matrix.from_coo`` instead. Will be removed in version 2023.9.0 or later
 
         Parameters
         ----------
@@ -1086,7 +1086,7 @@ def from_csr(
         Parameters
         ----------
         indptr : list or np.ndarray
-            Pointers for each row into col_indices and values; `indptr.size == nrows + 1`.
+            Pointers for each row into col_indices and values; ``indptr.size == nrows + 1``.
         col_indices : list or np.ndarray
             Column indices.
         values : list or np.ndarray or scalar, default 1.0
@@ -1133,7 +1133,7 @@ def from_csc(
         Parameters
         ----------
         indptr : list or np.ndarray
-            Pointers for each column into row_indices and values; `indptr.size == ncols + 1`.
+            Pointers for each column into row_indices and values; ``indptr.size == ncols + 1``.
         col_indices : list or np.ndarray
             Column indices.
         values : list or np.ndarray or scalar, default 1.0
diff --git a/graphblas/core/operator/base.py b/graphblas/core/operator/base.py
index a40438f14..cddee6a33 100644
--- a/graphblas/core/operator/base.py
+++ b/graphblas/core/operator/base.py
@@ -398,7 +398,7 @@ def _find(cls, funcname):
     def _initialize(cls, include_in_ops=True):
         """
         include_in_ops determines whether the operators are included in the
-        `gb.ops` namespace in addition to the defined module.
+        ``gb.ops`` namespace in addition to the defined module.
         """
         if cls._initialized:  # pragma: no cover (safety)
             return
diff --git a/graphblas/core/recorder.py b/graphblas/core/recorder.py
index 2268c31eb..ca776f697 100644
--- a/graphblas/core/recorder.py
+++ b/graphblas/core/recorder.py
@@ -34,7 +34,7 @@ def gbstr(arg):
 class Recorder:
     """Record GraphBLAS C calls.
 
-    The recorder can use `.start()` and `.stop()` to enable/disable recording,
+    The recorder can use ``.start()`` and ``.stop()`` to enable/disable recording,
     or it can be used as a context manager.
 
     For example,
diff --git a/graphblas/core/scalar.py b/graphblas/core/scalar.py
index a7a251a1d..b55d601af 100644
--- a/graphblas/core/scalar.py
+++ b/graphblas/core/scalar.py
@@ -1056,7 +1056,7 @@ def _as_scalar(scalar, dtype=None, *, is_cscalar):
 
 
 def _dict_to_record(np_type, d):
-    """Converts e.g. `{"x": 1, "y": 2.3}` to `(1, 2.3)`."""
+    """Converts e.g. ``{"x": 1, "y": 2.3}`` to ``(1, 2.3)``."""
     rv = []
     for name, (dtype, _) in np_type.fields.items():
         val = d[name]
diff --git a/graphblas/core/ss/descriptor.py b/graphblas/core/ss/descriptor.py
index dffc4dec1..2f7d11ffa 100644
--- a/graphblas/core/ss/descriptor.py
+++ b/graphblas/core/ss/descriptor.py
@@ -132,7 +132,7 @@ def get_descriptor(**opts):
     sort : bool, default False
         A hint for whether methods may return a "jumbled" matrix
     secure_import : bool, default False
-        Whether to trust the data for `import` and `pack` functions.
+        Whether to trust the data for ``import`` and ``pack`` functions.
         When True, checks are performed to ensure input data is valid.
     compression : str, {"none", "default", "lz4", "lz4hc", "zstd"}
         Whether and how to compress the data for serialization.
diff --git a/graphblas/core/ss/matrix.py b/graphblas/core/ss/matrix.py
index cac0296c7..64aa43a96 100644
--- a/graphblas/core/ss/matrix.py
+++ b/graphblas/core/ss/matrix.py
@@ -63,7 +63,7 @@ def head(matrix, n=10, dtype=None, *, sort=False):
 
 
 def _concat_mn(tiles, *, is_matrix=None):
-    """Argument checking for `Matrix.ss.concat` and returns number of tiles in each dimension."""
+    """Argument checking for ``Matrix.ss.concat`` and returns number of tiles in each dimension."""
     from ..matrix import Matrix, TransposedMatrix
     from ..vector import Vector
 
@@ -261,8 +261,8 @@ def build_diag(self, vector, k=0, **opts):
         vector : Vector
             Create a diagonal from this Vector.
         k : int, default 0
-            Diagonal in question.  Use `k>0` for diagonals above the main diagonal,
-            and `k<0` for diagonals below the main diagonal.
+            Diagonal in question.  Use ``k>0`` for diagonals above the main diagonal,
+            and ``k<0`` for diagonals below the main diagonal.
 
         See Also
         --------
@@ -282,12 +282,12 @@ def split(self, chunks, *, name=None, **opts):
         """
         GxB_Matrix_split.
 
-        Split a Matrix into a 2D array of sub-matrices according to `chunks`.
+        Split a Matrix into a 2D array of sub-matrices according to ``chunks``.
 
         This performs the opposite operation as ``concat``.
 
-        `chunks` is short for "chunksizes" and indicates the chunk sizes for each dimension.
-        `chunks` may be a single integer, or a length 2 tuple or list.  Example chunks:
+        ``chunks`` is short for "chunksizes" and indicates the chunk sizes for each dimension.
+        ``chunks`` may be a single integer, or a length 2 tuple or list.  Example chunks:
 
         - ``chunks=10``
             - Split each dimension into chunks of size 10 (the last chunk may be smaller).
@@ -295,7 +295,7 @@ def split(self, chunks, *, name=None, **opts):
             - Split rows into chunks of size 10 and columns into chunks of size 20.
         - ``chunks=(None, [5, 10])``
             - Don't split rows into chunks, and split columns into two chunks of size 5 and 10.
-        ` ``chunks=(10, [20, None])``
+        - ``chunks=(10, [20, None])``
             - Split columns into two chunks of size 20 and ``ncols - 20``
 
         See Also
@@ -366,9 +366,9 @@ def concat(self, tiles, **opts):
 
         Concatenate a 2D list of Matrix objects into the current Matrix.
         Any existing values in the current Matrix will be discarded.
-        To concatenate into a new Matrix, use `graphblas.ss.concat`.
+        To concatenate into a new Matrix, use ``graphblas.ss.concat``.
 
-        Vectors may be used as `Nx1` Matrix objects.
+        Vectors may be used as ``Nx1`` Matrix objects.
 
         This performs the opposite operation as ``split``.
 
@@ -542,8 +542,8 @@ def export(self, format=None, *, sort=False, give_ownership=False, raw=False, **
         Parameters
         ----------
         format : str, optional
-            If `format` is not specified, this method exports in the currently stored format.
-            To control the export format, set `format` to one of:
+            If ``format`` is not specified, this method exports in the currently stored format.
+            To control the export format, set ``format`` to one of:
                 - "csr"
                 - "csc"
                 - "hypercsr"
@@ -578,7 +578,7 @@ def export(self, format=None, *, sort=False, give_ownership=False, raw=False, **
 
         Returns
         -------
-        dict; keys depend on `format` and `raw` arguments (see below).
+        dict; keys depend on ``format`` and ``raw`` arguments (see below).
 
         See Also
         --------
@@ -732,10 +732,10 @@ def unpack(self, format=None, *, sort=False, raw=False, **opts):
         """
         GxB_Matrix_unpack_xxx.
 
-        `unpack` is like `export`, except that the Matrix remains valid but empty.
-        `pack_*` methods are the opposite of `unpack`.
+        ``unpack`` is like ``export``, except that the Matrix remains valid but empty.
+        ``pack_*`` methods are the opposite of ``unpack``.
 
-        See `Matrix.ss.export` documentation for more details.
+        See ``Matrix.ss.export`` documentation for more details.
         """
         return self._export(
             format, sort=sort, raw=raw, give_ownership=True, method="unpack", opts=opts
@@ -1193,7 +1193,7 @@ def import_csr(
         col_indices : array-like
         is_iso : bool, default False
             Is the Matrix iso-valued (meaning all the same value)?
-            If true, then `values` should be a length 1 array.
+            If true, then ``values`` should be a length 1 array.
         sorted_cols : bool, default False
             Indicate whether the values in "col_indices" are sorted.
         take_ownership : bool, default False
@@ -1210,7 +1210,7 @@ def import_csr(
             read-only and will no longer own the data.
         dtype : dtype, optional
             dtype of the new Matrix.
-            If not specified, this will be inferred from `values`.
+            If not specified, this will be inferred from ``values``.
         format : str, optional
             Must be "csr" or None.  This is included to be compatible with
             the dict returned from exporting.
@@ -1259,10 +1259,10 @@ def pack_csr(
         """
         GxB_Matrix_pack_CSR.
 
-        `pack_csr` is like `import_csr` except it "packs" data into an
+        ``pack_csr`` is like ``import_csr`` except it "packs" data into an
         existing Matrix.  This is the opposite of ``unpack("csr")``
 
-        See `Matrix.ss.import_csr` documentation for more details.
+        See ``Matrix.ss.import_csr`` documentation for more details.
         """
         return self._import_csr(
             indptr=indptr,
@@ -1383,7 +1383,7 @@ def import_csc(
         row_indices : array-like
         is_iso : bool, default False
             Is the Matrix iso-valued (meaning all the same value)?
-            If true, then `values` should be a length 1 array.
+            If true, then ``values`` should be a length 1 array.
         sorted_rows : bool, default False
             Indicate whether the values in "row_indices" are sorted.
         take_ownership : bool, default False
@@ -1400,7 +1400,7 @@ def import_csc(
             read-only and will no longer own the data.
         dtype : dtype, optional
             dtype of the new Matrix.
-            If not specified, this will be inferred from `values`.
+            If not specified, this will be inferred from ``values``.
         format : str, optional
             Must be "csc" or None.  This is included to be compatible with
             the dict returned from exporting.
@@ -1449,10 +1449,10 @@ def pack_csc(
         """
         GxB_Matrix_pack_CSC.
 
-        `pack_csc` is like `import_csc` except it "packs" data into an
+        ``pack_csc`` is like ``import_csc`` except it "packs" data into an
         existing Matrix.  This is the opposite of ``unpack("csc")``
 
-        See `Matrix.ss.import_csc` documentation for more details.
+        See ``Matrix.ss.import_csc`` documentation for more details.
         """
         return self._import_csc(
             indptr=indptr,
@@ -1579,7 +1579,7 @@ def import_hypercsr(
             If not specified, will be set to ``len(rows)``.
         is_iso : bool, default False
             Is the Matrix iso-valued (meaning all the same value)?
-            If true, then `values` should be a length 1 array.
+            If true, then ``values`` should be a length 1 array.
         sorted_cols : bool, default False
             Indicate whether the values in "col_indices" are sorted.
         take_ownership : bool, default False
@@ -1596,7 +1596,7 @@ def import_hypercsr(
             read-only and will no longer own the data.
         dtype : dtype, optional
             dtype of the new Matrix.
-            If not specified, this will be inferred from `values`.
+            If not specified, this will be inferred from ``values``.
         format : str, optional
             Must be "hypercsr" or None.  This is included to be compatible with
             the dict returned from exporting.
@@ -1649,10 +1649,10 @@ def pack_hypercsr(
         """
         GxB_Matrix_pack_HyperCSR.
 
-        `pack_hypercsr` is like `import_hypercsr` except it "packs" data into an
+        ``pack_hypercsr`` is like ``import_hypercsr`` except it "packs" data into an
         existing Matrix.  This is the opposite of ``unpack("hypercsr")``
 
-        See `Matrix.ss.import_hypercsr` documentation for more details.
+        See ``Matrix.ss.import_hypercsr`` documentation for more details.
         """
         return self._import_hypercsr(
             rows=rows,
@@ -1803,7 +1803,7 @@ def import_hypercsc(
             If not specified, will be set to ``len(cols)``.
         is_iso : bool, default False
             Is the Matrix iso-valued (meaning all the same value)?
-            If true, then `values` should be a length 1 array.
+            If true, then ``values`` should be a length 1 array.
         sorted_rows : bool, default False
             Indicate whether the values in "row_indices" are sorted.
         take_ownership : bool, default False
@@ -1820,7 +1820,7 @@ def import_hypercsc(
             read-only and will no longer own the data.
         dtype : dtype, optional
             dtype of the new Matrix.
-            If not specified, this will be inferred from `values`.
+            If not specified, this will be inferred from ``values``.
         format : str, optional
             Must be "hypercsc" or None.  This is included to be compatible with
             the dict returned from exporting.
@@ -1873,10 +1873,10 @@ def pack_hypercsc(
         """
         GxB_Matrix_pack_HyperCSC.
 
-        `pack_hypercsc` is like `import_hypercsc` except it "packs" data into an
+        ``pack_hypercsc`` is like ``import_hypercsc`` except it "packs" data into an
         existing Matrix.  This is the opposite of ``unpack("hypercsc")``
 
-        See `Matrix.ss.import_hypercsc` documentation for more details.
+        See ``Matrix.ss.import_hypercsc`` documentation for more details.
         """
         return self._import_hypercsc(
             cols=cols,
@@ -2028,7 +2028,7 @@ def import_bitmapr(
             If not provided, will be inferred from values or bitmap if either is 2d.
         is_iso : bool, default False
             Is the Matrix iso-valued (meaning all the same value)?
-            If true, then `values` should be a length 1 array.
+            If true, then ``values`` should be a length 1 array.
         take_ownership : bool, default False
             If True, perform a zero-copy data transfer from input numpy arrays
             to GraphBLAS if possible.  To give ownership of the underlying
@@ -2043,7 +2043,7 @@ def import_bitmapr(
             read-only and will no longer own the data.
         dtype : dtype, optional
             dtype of the new Matrix.
-            If not specified, this will be inferred from `values`.
+            If not specified, this will be inferred from ``values``.
         format : str, optional
             Must be "bitmapr" or None.  This is included to be compatible with
             the dict returned from exporting.
@@ -2090,10 +2090,10 @@ def pack_bitmapr(
         """
         GxB_Matrix_pack_BitmapR.
 
-        `pack_bitmapr` is like `import_bitmapr` except it "packs" data into an
+        ``pack_bitmapr`` is like ``import_bitmapr`` except it "packs" data into an
         existing Matrix.  This is the opposite of ``unpack("bitmapr")``
 
-        See `Matrix.ss.import_bitmapr` documentation for more details.
+        See ``Matrix.ss.import_bitmapr`` documentation for more details.
         """
         return self._import_bitmapr(
             bitmap=bitmap,
@@ -2221,7 +2221,7 @@ def import_bitmapc(
             If not provided, will be inferred from values or bitmap if either is 2d.
         is_iso : bool, default False
             Is the Matrix iso-valued (meaning all the same value)?
-            If true, then `values` should be a length 1 array.
+            If true, then ``values`` should be a length 1 array.
         take_ownership : bool, default False
             If True, perform a zero-copy data transfer from input numpy arrays
             to GraphBLAS if possible.  To give ownership of the underlying
@@ -2236,7 +2236,7 @@ def import_bitmapc(
             read-only and will no longer own the data.
         dtype : dtype, optional
             dtype of the new Matrix.
-            If not specified, this will be inferred from `values`.
+            If not specified, this will be inferred from ``values``.
         format : str, optional
             Must be "bitmapc" or None.  This is included to be compatible with
             the dict returned from exporting.
@@ -2283,10 +2283,10 @@ def pack_bitmapc(
         """
         GxB_Matrix_pack_BitmapC.
 
-        `pack_bitmapc` is like `import_bitmapc` except it "packs" data into an
+        ``pack_bitmapc`` is like ``import_bitmapc`` except it "packs" data into an
         existing Matrix.  This is the opposite of ``unpack("bitmapc")``
 
-        See `Matrix.ss.import_bitmapc` documentation for more details.
+        See ``Matrix.ss.import_bitmapc`` documentation for more details.
         """
         return self._import_bitmapc(
             bitmap=bitmap,
@@ -2407,7 +2407,7 @@ def import_fullr(
             If not provided, will be inferred from values if it is 2d.
         is_iso : bool, default False
             Is the Matrix iso-valued (meaning all the same value)?
-            If true, then `values` should be a length 1 array.
+            If true, then ``values`` should be a length 1 array.
         take_ownership : bool, default False
             If True, perform a zero-copy data transfer from input numpy arrays
             to GraphBLAS if possible.  To give ownership of the underlying
@@ -2422,7 +2422,7 @@ def import_fullr(
             read-only and will no longer own the data.
         dtype : dtype, optional
             dtype of the new Matrix.
-            If not specified, this will be inferred from `values`.
+            If not specified, this will be inferred from ``values``.
         format : str, optional
             Must be "fullr" or None.  This is included to be compatible with
             the dict returned from exporting.
@@ -2465,10 +2465,10 @@ def pack_fullr(
         """
         GxB_Matrix_pack_FullR.
 
-        `pack_fullr` is like `import_fullr` except it "packs" data into an
+        ``pack_fullr`` is like ``import_fullr`` except it "packs" data into an
         existing Matrix.  This is the opposite of ``unpack("fullr")``
 
-        See `Matrix.ss.import_fullr` documentation for more details.
+        See ``Matrix.ss.import_fullr`` documentation for more details.
         """
         return self._import_fullr(
             values=values,
@@ -2566,7 +2566,7 @@ def import_fullc(
             If not provided, will be inferred from values if it is 2d.
         is_iso : bool, default False
             Is the Matrix iso-valued (meaning all the same value)?
-            If true, then `values` should be a length 1 array.
+            If true, then ``values`` should be a length 1 array.
         take_ownership : bool, default False
             If True, perform a zero-copy data transfer from input numpy arrays
             to GraphBLAS if possible.  To give ownership of the underlying
@@ -2581,7 +2581,7 @@ def import_fullc(
             read-only and will no longer own the data.
         dtype : dtype, optional
             dtype of the new Matrix.
-            If not specified, this will be inferred from `values`.
+            If not specified, this will be inferred from ``values``.
         format : str, optional
             Must be "fullc" or None.  This is included to be compatible with
             the dict returned from exporting.
@@ -2624,10 +2624,10 @@ def pack_fullc(
         """
         GxB_Matrix_pack_FullC.
 
-        `pack_fullc` is like `import_fullc` except it "packs" data into an
+        ``pack_fullc`` is like ``import_fullc`` except it "packs" data into an
         existing Matrix.  This is the opposite of ``unpack("fullc")``
 
-        See `Matrix.ss.import_fullc` documentation for more details.
+        See ``Matrix.ss.import_fullc`` documentation for more details.
         """
         return self._import_fullc(
             values=values,
@@ -2727,7 +2727,7 @@ def import_coo(
             The number of columns for the Matrix.
         is_iso : bool, default False
             Is the Matrix iso-valued (meaning all the same value)?
-            If true, then `values` should be a length 1 array.
+            If true, then ``values`` should be a length 1 array.
         sorted_rows : bool, default False
             True if rows are sorted or when (cols, rows) are sorted lexicographically
         sorted_cols : bool, default False
@@ -2736,7 +2736,7 @@ def import_coo(
             Ignored.  Zero-copy is not possible for "coo" format.
         dtype : dtype, optional
             dtype of the new Matrix.
-            If not specified, this will be inferred from `values`.
+            If not specified, this will be inferred from ``values``.
         format : str, optional
             Must be "coo" or None.  This is included to be compatible with
             the dict returned from exporting.
@@ -2787,10 +2787,10 @@ def pack_coo(
         """
         GrB_Matrix_build_XXX and GxB_Matrix_build_Scalar.
 
-        `pack_coo` is like `import_coo` except it "packs" data into an
+        ``pack_coo`` is like ``import_coo`` except it "packs" data into an
         existing Matrix.  This is the opposite of ``unpack("coo")``
 
-        See `Matrix.ss.import_coo` documentation for more details.
+        See ``Matrix.ss.import_coo`` documentation for more details.
         """
         return self._import_coo(
             nrows=self._parent._nrows,
@@ -2914,7 +2914,7 @@ def import_coor(
             The number of columns for the Matrix.
         is_iso : bool, default False
             Is the Matrix iso-valued (meaning all the same value)?
-            If true, then `values` should be a length 1 array.
+            If true, then ``values`` should be a length 1 array.
         sorted_cols : bool, default False
             True indicates indices are sorted by column, then row.
         take_ownership : bool, default False
@@ -2932,7 +2932,7 @@ def import_coor(
             For "coor", ownership of "rows" will never change.
         dtype : dtype, optional
             dtype of the new Matrix.
-            If not specified, this will be inferred from `values`.
+            If not specified, this will be inferred from ``values``.
         format : str, optional
             Must be "coor" or None.  This is included to be compatible with
             the dict returned from exporting.
@@ -2983,10 +2983,10 @@ def pack_coor(
         """
         GxB_Matrix_pack_CSR.
 
-        `pack_coor` is like `import_coor` except it "packs" data into an
+        ``pack_coor`` is like ``import_coor`` except it "packs" data into an
         existing Matrix.  This is the opposite of ``unpack("coor")``
 
-        See `Matrix.ss.import_coor` documentation for more details.
+        See ``Matrix.ss.import_coor`` documentation for more details.
         """
         return self._import_coor(
             rows=rows,
@@ -3083,7 +3083,7 @@ def import_cooc(
             The number of columns for the Matrix.
         is_iso : bool, default False
             Is the Matrix iso-valued (meaning all the same value)?
-            If true, then `values` should be a length 1 array.
+            If true, then ``values`` should be a length 1 array.
         sorted_rows : bool, default False
             True indicates indices are sorted by column, then row.
         take_ownership : bool, default False
@@ -3101,7 +3101,7 @@ def import_cooc(
             For "cooc", ownership of "cols" will never change.
         dtype : dtype, optional
             dtype of the new Matrix.
-            If not specified, this will be inferred from `values`.
+            If not specified, this will be inferred from ``values``.
         format : str, optional
             Must be "cooc" or None.  This is included to be compatible with
             the dict returned from exporting.
@@ -3152,10 +3152,10 @@ def pack_cooc(
         """
         GxB_Matrix_pack_CSC.
 
-        `pack_cooc` is like `import_cooc` except it "packs" data into an
+        ``pack_cooc`` is like ``import_cooc`` except it "packs" data into an
         existing Matrix.  This is the opposite of ``unpack("cooc")``
 
-        See `Matrix.ss.import_cooc` documentation for more details.
+        See ``Matrix.ss.import_cooc`` documentation for more details.
         """
         return self._import_cooc(
             ncols=self._parent._ncols,
@@ -3255,7 +3255,7 @@ def import_any(
         GxB_Matrix_import_xxx.
 
         Dispatch to appropriate import method inferred from inputs.
-        See the other import functions and `Matrix.ss.export`` for details.
+        See the other import functions and ``Matrix.ss.export`` for details.
 
         Returns
         -------
@@ -3352,10 +3352,10 @@ def pack_any(
         """
         GxB_Matrix_pack_xxx.
 
-        `pack_any` is like `import_any` except it "packs" data into an
+        ``pack_any`` is like ``import_any`` except it "packs" data into an
         existing Matrix.  This is the opposite of ``unpack()``
 
-        See `Matrix.ss.import_any` documentation for more details.
+        See ``Matrix.ss.import_any`` documentation for more details.
         """
         return self._import_any(
             values=values,
@@ -3701,8 +3701,8 @@ def head(self, n=10, dtype=None, *, sort=False):
     def scan(self, op=monoid.plus, order="rowwise", *, name=None, **opts):
         """Perform a prefix scan across rows (default) or columns with the given monoid.
 
-        For example, use `monoid.plus` (the default) to perform a cumulative sum,
-        and `monoid.times` for cumulative product.  Works with any monoid.
+        For example, use ``monoid.plus`` (the default) to perform a cumulative sum,
+        and ``monoid.times`` for cumulative product.  Works with any monoid.
 
         Returns
         -------
@@ -3718,12 +3718,12 @@ def scan_columnwise(self, op=monoid.plus, *, name=None, **opts):
         """Perform a prefix scan across columns with the given monoid.
 
         .. deprecated:: 2022.11.1
-            `Matrix.ss.scan_columnwise` will be removed in a future release.
-            Use `Matrix.ss.scan(order="columnwise")` instead.
+            ``Matrix.ss.scan_columnwise`` will be removed in a future release.
+            Use ``Matrix.ss.scan(order="columnwise")`` instead.
             Will be removed in version 2023.7.0 or later
 
-        For example, use `monoid.plus` (the default) to perform a cumulative sum,
-        and `monoid.times` for cumulative product.  Works with any monoid.
+        For example, use ``monoid.plus`` (the default) to perform a cumulative sum,
+        and ``monoid.times`` for cumulative product.  Works with any monoid.
 
         Returns
         -------
@@ -3741,12 +3741,12 @@ def scan_rowwise(self, op=monoid.plus, *, name=None, **opts):
         """Perform a prefix scan across rows with the given monoid.
 
         .. deprecated:: 2022.11.1
-            `Matrix.ss.scan_rowwise` will be removed in a future release.
-            Use `Matrix.ss.scan` instead.
+            ``Matrix.ss.scan_rowwise`` will be removed in a future release.
+            Use ``Matrix.ss.scan`` instead.
             Will be removed in version 2023.7.0 or later
 
-        For example, use `monoid.plus` (the default) to perform a cumulative sum,
-        and `monoid.times` for cumulative product.  Works with any monoid.
+        For example, use ``monoid.plus`` (the default) to perform a cumulative sum,
+        and ``monoid.times`` for cumulative product.  Works with any monoid.
 
         Returns
         -------
@@ -3904,8 +3904,8 @@ def selectk_rowwise(self, how, k, *, name=None):  # pragma: no cover (deprecated
         """Select (up to) k elements from each row.
 
         .. deprecated:: 2022.11.1
-            `Matrix.ss.selectk_rowwise` will be removed in a future release.
-            Use `Matrix.ss.selectk` instead.
+            ``Matrix.ss.selectk_rowwise`` will be removed in a future release.
+            Use ``Matrix.ss.selectk`` instead.
             Will be removed in version 2023.7.0 or later
 
         Parameters
@@ -3950,8 +3950,8 @@ def selectk_columnwise(self, how, k, *, name=None):  # pragma: no cover (depreca
         """Select (up to) k elements from each column.
 
         .. deprecated:: 2022.11.1
-            `Matrix.ss.selectk_columnwise` will be removed in a future release.
-            Use `Matrix.ss.selectk(order="columnwise")` instead.
+            ``Matrix.ss.selectk_columnwise`` will be removed in a future release.
+            Use ``Matrix.ss.selectk(order="columnwise")`` instead.
             Will be removed in version 2023.7.0 or later
 
         Parameters
@@ -4216,23 +4216,23 @@ def sort(self, op=binary.lt, order="rowwise", *, values=True, permutation=True,
         """GxB_Matrix_sort to sort values along the rows (default) or columns of the Matrix.
 
         Sorting moves all the elements to the left (if rowwise) or top (if columnwise) just
-        like `compactify`. The returned matrices will be the same shape as the input Matrix.
+        like ``compactify``. The returned matrices will be the same shape as the input Matrix.
 
         Parameters
         ----------
         op : :class:`~graphblas.core.operator.BinaryOp`, optional
             Binary operator with a bool return type used to sort the values.
-            For example, `binary.lt` (the default) sorts the smallest elements first.
+            For example, ``binary.lt`` (the default) sorts the smallest elements first.
             Ties are broken according to indices (smaller first).
         order : {"rowwise", "columnwise"}, optional
             Whether to sort rowwise or columnwise. Rowwise shifts all values to the left,
             and columnwise shifts all values to the top. The default is "rowwise".
         values : bool, default=True
-            Whether to return values; will return `None` for values if `False`.
+            Whether to return values; will return ``None`` for values if ``False``.
         permutation : bool, default=True
             Whether to compute the permutation Matrix that has the original column
             indices (if rowwise) or row indices (if columnwise) of the sorted values.
-            Will return None if `False`.
+            Will return None if ``False``.
         nthreads : int, optional
             The maximum number of threads to use for this operation.
             None, 0 or negative nthreads means to use the default number of threads.
@@ -4301,7 +4301,7 @@ def serialize(self, compression="default", level=None, **opts):
             None, 0 or negative nthreads means to use the default number of threads.
 
         For best performance, this function returns a numpy array with uint8 dtype.
-        Use `Matrix.ss.deserialize(blob)` to create a Matrix from the result of serialization
+        Use ``Matrix.ss.deserialize(blob)`` to create a Matrix from the result of serialization
 
         This method is intended to support all serialization options from SuiteSparse:GraphBLAS.
 
@@ -4327,7 +4327,7 @@ def deserialize(cls, data, dtype=None, *, name=None, **opts):
         """Deserialize a Matrix from bytes, buffer, or numpy array using GxB_Matrix_deserialize.
 
         The data should have been previously serialized with a compatible version of
-        SuiteSparse:GraphBLAS.  For example, from the result of `data = matrix.ss.serialize()`.
+        SuiteSparse:GraphBLAS.  For example, from the result of ``data = matrix.ss.serialize()``.
 
         Examples
         --------
diff --git a/graphblas/core/ss/vector.py b/graphblas/core/ss/vector.py
index 2b1e8bf05..1babc556e 100644
--- a/graphblas/core/ss/vector.py
+++ b/graphblas/core/ss/vector.py
@@ -155,8 +155,8 @@ def build_diag(self, matrix, k=0, **opts):
         matrix : Matrix or TransposedMatrix
             Extract a diagonal from this matrix.
         k : int, default 0
-            Diagonal in question.  Use `k>0` for diagonals above the main diagonal,
-            and `k<0` for diagonals below the main diagonal.
+            Diagonal in question.  Use ``k>0`` for diagonals above the main diagonal,
+            and ``k<0`` for diagonals below the main diagonal.
 
         See Also
         --------
@@ -185,12 +185,12 @@ def split(self, chunks, *, name=None, **opts):
         """
         GxB_Matrix_split.
 
-        Split a Vector into a 1D array of sub-vectors according to `chunks`.
+        Split a Vector into a 1D array of sub-vectors according to ``chunks``.
 
         This performs the opposite operation as ``concat``.
 
-        `chunks` is short for "chunksizes" and indicates the chunk sizes.
-        `chunks` may be a single integer, or a tuple or list.  Example chunks:
+        ``chunks`` is short for "chunksizes" and indicates the chunk sizes.
+        ``chunks`` may be a single integer, or a tuple or list.  Example chunks:
 
         - ``chunks=10``
             - Split vector into chunks of size 10 (the last chunk may be smaller).
@@ -253,7 +253,7 @@ def concat(self, tiles, **opts):
 
         Concatenate a 1D list of Vector objects into the current Vector.
         Any existing values in the current Vector will be discarded.
-        To concatenate into a new Vector, use `graphblas.ss.concat`.
+        To concatenate into a new Vector, use ``graphblas.ss.concat``.
 
         This performs the opposite operation as ``split``.
 
@@ -415,8 +415,8 @@ def export(self, format=None, *, sort=False, give_ownership=False, raw=False, **
         Parameters
         ----------
         format : str or None, default None
-            If `format` is not specified, this method exports in the currently stored format.
-            To control the export format, set `format` to one of:
+            If ``format`` is not specified, this method exports in the currently stored format.
+            To control the export format, set ``format`` to one of:
                 - "sparse"
                 - "bitmap"
                 - "full"
@@ -434,7 +434,7 @@ def export(self, format=None, *, sort=False, give_ownership=False, raw=False, **
 
         Returns
         -------
-        dict; keys depend on `format` and `raw` arguments (see below).
+        dict; keys depend on ``format`` and ``raw`` arguments (see below).
 
         See Also
         --------
@@ -442,7 +442,7 @@ def export(self, format=None, *, sort=False, give_ownership=False, raw=False, **
         Vector.ss.import_any
 
         Return values
-            - Note: for `raw=True`, arrays may be larger than specified.
+            - Note: for ``raw=True``, arrays may be larger than specified.
             - "sparse" format
                 - indices : ndarray(dtype=uint64, size=nvals)
                 - values : ndarray(size=nvals)
@@ -481,10 +481,10 @@ def unpack(self, format=None, *, sort=False, raw=False, **opts):
         """
         GxB_Vector_unpack_xxx.
 
-        `unpack` is like `export`, except that the Vector remains valid but empty.
-        `pack_*` methods are the opposite of `unpack`.
+        ``unpack`` is like ``export``, except that the Vector remains valid but empty.
+        ``pack_*`` methods are the opposite of ``unpack``.
 
-        See `Vector.ss.export` documentation for more details.
+        See ``Vector.ss.export`` documentation for more details.
         """
         return self._export(
             format=format, sort=sort, give_ownership=True, raw=raw, method="unpack", opts=opts
@@ -658,7 +658,7 @@ def import_any(
         GxB_Vector_import_xxx.
 
         Dispatch to appropriate import method inferred from inputs.
-        See the other import functions and `Vector.ss.export`` for details.
+        See the other import functions and ``Vector.ss.export`` for details.
 
         Returns
         -------
@@ -724,10 +724,10 @@ def pack_any(
         """
         GxB_Vector_pack_xxx.
 
-        `pack_any` is like `import_any` except it "packs" data into an
+        ``pack_any`` is like ``import_any`` except it "packs" data into an
         existing Vector.  This is the opposite of ``unpack()``
 
-        See `Vector.ss.import_any` documentation for more details.
+        See ``Vector.ss.import_any`` documentation for more details.
         """
         return self._import_any(
             values=values,
@@ -858,7 +858,7 @@ def import_sparse(
             If not specified, will be set to ``len(values)``.
         is_iso : bool, default False
             Is the Vector iso-valued (meaning all the same value)?
-            If true, then `values` should be a length 1 array.
+            If true, then ``values`` should be a length 1 array.
         sorted_index : bool, default False
             Indicate whether the values in "col_indices" are sorted.
         take_ownership : bool, default False
@@ -875,7 +875,7 @@ def import_sparse(
             read-only and will no longer own the data.
         dtype : dtype, optional
             dtype of the new Vector.
-            If not specified, this will be inferred from `values`.
+            If not specified, this will be inferred from ``values``.
         format : str, optional
             Must be "sparse" or None.  This is included to be compatible with
             the dict returned from exporting.
@@ -922,10 +922,10 @@ def pack_sparse(
         """
         GxB_Vector_pack_CSC.
 
-        `pack_sparse` is like `import_sparse` except it "packs" data into an
+        ``pack_sparse`` is like ``import_sparse`` except it "packs" data into an
         existing Vector.  This is the opposite of ``unpack("sparse")``
 
-        See `Vector.ss.import_sparse` documentation for more details.
+        See ``Vector.ss.import_sparse`` documentation for more details.
         """
         return self._import_sparse(
             indices=indices,
@@ -1045,7 +1045,7 @@ def import_bitmap(
             If not specified, it will be set to the size of values.
         is_iso : bool, default False
             Is the Vector iso-valued (meaning all the same value)?
-            If true, then `values` should be a length 1 array.
+            If true, then ``values`` should be a length 1 array.
         take_ownership : bool, default False
             If True, perform a zero-copy data transfer from input numpy arrays
             to GraphBLAS if possible.  To give ownership of the underlying
@@ -1060,7 +1060,7 @@ def import_bitmap(
             read-only and will no longer own the data.
         dtype : dtype, optional
             dtype of the new Vector.
-            If not specified, this will be inferred from `values`.
+            If not specified, this will be inferred from ``values``.
         format : str, optional
             Must be "bitmap" or None.  This is included to be compatible with
             the dict returned from exporting.
@@ -1105,10 +1105,10 @@ def pack_bitmap(
         """
         GxB_Vector_pack_Bitmap.
 
-        `pack_bitmap` is like `import_bitmap` except it "packs" data into an
+        ``pack_bitmap`` is like ``import_bitmap`` except it "packs" data into an
         existing Vector.  This is the opposite of ``unpack("bitmap")``
 
-        See `Vector.ss.import_bitmap` documentation for more details.
+        See ``Vector.ss.import_bitmap`` documentation for more details.
         """
         return self._import_bitmap(
             bitmap=bitmap,
@@ -1226,7 +1226,7 @@ def import_full(
             If not specified, it will be set to the size of values.
         is_iso : bool, default False
             Is the Vector iso-valued (meaning all the same value)?
-            If true, then `values` should be a length 1 array.
+            If true, then ``values`` should be a length 1 array.
         take_ownership : bool, default False
             If True, perform a zero-copy data transfer from input numpy arrays
             to GraphBLAS if possible.  To give ownership of the underlying
@@ -1241,7 +1241,7 @@ def import_full(
             read-only and will no longer own the data.
         dtype : dtype, optional
             dtype of the new Vector.
-            If not specified, this will be inferred from `values`.
+            If not specified, this will be inferred from ``values``.
         format : str, optional
             Must be "full" or None.  This is included to be compatible with
             the dict returned from exporting.
@@ -1282,10 +1282,10 @@ def pack_full(
         """
         GxB_Vector_pack_Full.
 
-        `pack_full` is like `import_full` except it "packs" data into an
+        ``pack_full`` is like ``import_full`` except it "packs" data into an
         existing Vector.  This is the opposite of ``unpack("full")``
 
-        See `Vector.ss.import_full` documentation for more details.
+        See ``Vector.ss.import_full`` documentation for more details.
         """
         return self._import_full(
             values=values,
@@ -1364,8 +1364,8 @@ def head(self, n=10, dtype=None, *, sort=False):
     def scan(self, op=monoid.plus, *, name=None, **opts):
         """Perform a prefix scan with the given monoid.
 
-        For example, use `monoid.plus` (the default) to perform a cumulative sum,
-        and `monoid.times` for cumulative product.  Works with any monoid.
+        For example, use ``monoid.plus`` (the default) to perform a cumulative sum,
+        and ``monoid.times`` for cumulative product.  Works with any monoid.
 
         Returns
         -------
@@ -1561,20 +1561,20 @@ def compactify(self, how="first", size=None, *, reverse=False, asindex=False, na
     def sort(self, op=binary.lt, *, values=True, permutation=True, **opts):
         """GxB_Vector_sort to sort values of the Vector.
 
-        Sorting moves all the elements to the left just like `compactify`.
+        Sorting moves all the elements to the left just like ``compactify``.
         The returned vectors will be the same size as the input Vector.
 
         Parameters
         ----------
         op : :class:`~graphblas.core.operator.BinaryOp`, optional
             Binary operator with a bool return type used to sort the values.
-            For example, `binary.lt` (the default) sorts the smallest elements first.
+            For example, ``binary.lt`` (the default) sorts the smallest elements first.
             Ties are broken according to indices (smaller first).
         values : bool, default=True
-            Whether to return values; will return `None` for values if `False`.
+            Whether to return values; will return ``None`` for values if ``False``.
         permutation : bool, default=True
             Whether to compute the permutation Vector that has the original indices of the
-            sorted values. Will return None if `False`.
+            sorted values. Will return None if ``False``.
         nthreads : int, optional
             The maximum number of threads to use for this operation.
             None, 0 or negative nthreads means to use the default number of threads.
@@ -1642,7 +1642,7 @@ def serialize(self, compression="default", level=None, **opts):
             None, 0 or negative nthreads means to use the default number of threads.
 
         For best performance, this function returns a numpy array with uint8 dtype.
-        Use `Vector.ss.deserialize(blob)` to create a Vector from the result of serialization·
+        Use ``Vector.ss.deserialize(blob)`` to create a Vector from the result of serialization·
 
         This method is intended to support all serialization options from SuiteSparse:GraphBLAS.
 
@@ -1668,7 +1668,7 @@ def deserialize(cls, data, dtype=None, *, name=None, **opts):
         """Deserialize a Vector from bytes, buffer, or numpy array using GxB_Vector_deserialize.
 
         The data should have been previously serialized with a compatible version of
-        SuiteSparse:GraphBLAS.  For example, from the result of `data = vector.ss.serialize()`.
+        SuiteSparse:GraphBLAS.  For example, from the result of ``data = vector.ss.serialize()``.
 
         Examples
         --------
diff --git a/graphblas/core/utils.py b/graphblas/core/utils.py
index 77c64a7ac..74e03f2f9 100644
--- a/graphblas/core/utils.py
+++ b/graphblas/core/utils.py
@@ -22,7 +22,7 @@ def libget(name):
 
 
 def wrapdoc(func_with_doc):
-    """Decorator to copy `__doc__` from a function onto the wrapped function."""
+    """Decorator to copy ``__doc__`` from a function onto the wrapped function."""
 
     def inner(func_wo_doc):
         func_wo_doc.__doc__ = func_with_doc.__doc__
@@ -159,7 +159,7 @@ def get_order(order):
 
 
 def normalize_chunks(chunks, shape):
-    """Normalize chunks argument for use by `Matrix.ss.split`.
+    """Normalize chunks argument for use by ``Matrix.ss.split``.
 
     Examples
     --------
@@ -249,17 +249,17 @@ def normalize_chunks(chunks, shape):
 
 
 def ensure_type(x, types):
-    """Try to ensure `x` is one of the given types, computing if necessary.
+    """Try to ensure ``x`` is one of the given types, computing if necessary.
 
-    `types` must be a type or a tuple of types as used in `isinstance`.
+    ``types`` must be a type or a tuple of types as used in ``isinstance``.
 
-    For example, if `types` is a Vector, then a Vector input will be returned,
-    and a `VectorExpression` input will be computed and returned as a Vector.
+    For example, if ``types`` is a Vector, then a Vector input will be returned,
+    and a ``VectorExpression`` input will be computed and returned as a Vector.
 
     TypeError will be raised if the input is not or can't be converted to types.
 
-    This function ignores `graphblas.config["autocompute"]`; it always computes
-    if the return type will match `types`.
+    This function ignores ``graphblas.config["autocompute"]``; it always computes
+    if the return type will match ``types``.
     """
     if isinstance(x, types):
         return x
@@ -358,6 +358,7 @@ def _autogenerate_code(
     specializer=None,
     begin="# Begin auto-generated code",
     end="# End auto-generated code",
+    callblack=True,
 ):
     """Super low-tech auto-code generation used by automethods.py and infixmethods.py."""
     with filepath.open() as f:  # pragma: no branch (flaky)
@@ -384,7 +385,8 @@ def _autogenerate_code(
         f.write(new_text)
     import subprocess
 
-    try:
-        subprocess.check_call(["black", filepath])
-    except FileNotFoundError:  # pragma: no cover (safety)
-        pass  # It's okay if `black` isn't installed; pre-commit hooks will do linting
+    if callblack:
+        try:
+            subprocess.check_call(["black", filepath])
+        except FileNotFoundError:  # pragma: no cover (safety)
+            pass  # It's okay if `black` isn't installed; pre-commit hooks will do linting
diff --git a/graphblas/core/vector.py b/graphblas/core/vector.py
index 57851420d..d2ddee372 100644
--- a/graphblas/core/vector.py
+++ b/graphblas/core/vector.py
@@ -453,17 +453,17 @@ def to_values(self, dtype=None, *, indices=True, values=True, sort=True):
         """Extract the indices and values as a 2-tuple of numpy arrays.
 
         .. deprecated:: 2022.11.0
-            `Vector.to_values` will be removed in a future release.
-            Use `Vector.to_coo` instead. Will be removed in version 2023.9.0 or later
+            ``Vector.to_values`` will be removed in a future release.
+            Use ``Vector.to_coo`` instead. Will be removed in version 2023.9.0 or later
 
         Parameters
         ----------
         dtype :
             Requested dtype for the output values array.
         indices :bool, default=True
-            Whether to return indices; will return `None` for indices if `False`
+            Whether to return indices; will return ``None`` for indices if ``False``
         values : bool, default=True
-            Whether to return values; will return `None` for values if `False`
+            Whether to return values; will return ``None`` for values if ``False``
         sort : bool, default=True
             Whether to require sorted indices.
 
@@ -487,9 +487,9 @@ def to_coo(self, dtype=None, *, indices=True, values=True, sort=True):
         dtype :
             Requested dtype for the output values array.
         indices :bool, default=True
-            Whether to return indices; will return `None` for indices if `False`
+            Whether to return indices; will return ``None`` for indices if ``False``
         values : bool, default=True
-            Whether to return values; will return `None` for values if `False`
+            Whether to return values; will return ``None`` for values if ``False``
         sort : bool, default=True
             Whether to require sorted indices.
 
@@ -539,7 +539,7 @@ def build(self, indices, values, *, dup_op=None, clear=False, size=None):
         """Rarely used method to insert values into an existing Vector. The typical use case
         is to create a new Vector and insert values at the same time using :meth:`from_coo`.
 
-        All the arguments are used identically in :meth:`from_coo`, except for `clear`, which
+        All the arguments are used identically in :meth:`from_coo`, except for ``clear``, which
         indicates whether to clear the Vector prior to adding the new values.
         """
         # TODO: accept `dtype` keyword to match the dtype of `values`?
@@ -695,8 +695,8 @@ def from_values(cls, indices, values, dtype=None, *, size=None, dup_op=None, nam
         """Create a new Vector from indices and values.
 
         .. deprecated:: 2022.11.0
-            `Vector.from_values` will be removed in a future release.
-            Use `Vector.from_coo` instead. Will be removed in version 2023.9.0 or later
+            ``Vector.from_values`` will be removed in a future release.
+            Use ``Vector.from_coo`` instead. Will be removed in version 2023.9.0 or later
 
         Parameters
         ----------
diff --git a/graphblas/io/_numpy.py b/graphblas/io/_numpy.py
index 1c40e1633..954d28df7 100644
--- a/graphblas/io/_numpy.py
+++ b/graphblas/io/_numpy.py
@@ -11,14 +11,14 @@ def from_numpy(m):  # pragma: no cover (deprecated)
     """Create a sparse Vector or Matrix from a dense numpy array.
 
     .. deprecated:: 2023.2.0
-        `from_numpy` will be removed in a future release.
-        Use `Vector.from_dense` or `Matrix.from_dense` instead.
+        ``from_numpy`` will be removed in a future release.
+        Use ``Vector.from_dense`` or ``Matrix.from_dense`` instead.
         Will be removed in version 2023.10.0 or later
 
     A value of 0 is considered as "missing".
 
-    - m.ndim == 1 returns a `Vector`
-    - m.ndim == 2 returns a `Matrix`
+    - m.ndim == 1 returns a ``Vector``
+    - m.ndim == 2 returns a ``Matrix``
     - m.ndim > 2 raises an error
 
     dtype is inferred from m.dtype
@@ -65,8 +65,8 @@ def to_numpy(m):  # pragma: no cover (deprecated)
     """Create a dense numpy array from a sparse Vector or Matrix.
 
     .. deprecated:: 2023.2.0
-        `to_numpy` will be removed in a future release.
-        Use `Vector.to_dense` or `Matrix.to_dense` instead.
+        ``to_numpy`` will be removed in a future release.
+        Use ``Vector.to_dense`` or ``Matrix.to_dense`` instead.
         Will be removed in version 2023.10.0 or later
 
     Missing values will become 0 in the output.
diff --git a/graphblas/select/__init__.py b/graphblas/select/__init__.py
index c7a1897f5..72aa8d226 100644
--- a/graphblas/select/__init__.py
+++ b/graphblas/select/__init__.py
@@ -57,9 +57,9 @@ def _resolve_expr(expr, callname, opname):
 
 
 def _match_expr(parent, expr):
-    """Match expressions to rewrite `A.select(A < 5)` into select expression.
+    """Match expressions to rewrite ``A.select(A < 5)`` into select expression.
 
-    The argument must match the parent, so this _won't_ be rewritten: `A.select(B < 5)`
+    The argument must match the parent, so this _won't_ be rewritten: ``A.select(B < 5)``
     """
     args = expr.args
     op = expr.op
@@ -83,7 +83,7 @@ def value(expr):
     Example usage:
     >>> gb.select.value(A > 0)
 
-    The example will dispatch to `gb.select.valuegt(A, 0)`
+    The example will dispatch to ``gb.select.valuegt(A, 0)``
     while being nicer to read.
     """
     return _resolve_expr(expr, "value", "value")
@@ -97,7 +97,7 @@ def row(expr):
     Example usage:
     >>> gb.select.row(A <= 5)
 
-    The example will dispatch to `gb.select.rowle(A, 5)`
+    The example will dispatch to ``gb.select.rowle(A, 5)``
     while being potentially nicer to read.
     """
     return _resolve_expr(expr, "row", "row")
@@ -111,7 +111,7 @@ def column(expr):
     Example usage:
     >>> gb.select.column(A <= 5)
 
-    The example will dispatch to `gb.select.colle(A, 5)`
+    The example will dispatch to ``gb.select.colle(A, 5)``
     while being potentially nicer to read.
     """
     return _resolve_expr(expr, "column", "col")
@@ -125,7 +125,7 @@ def index(expr):
     Example usage:
     >>> gb.select.index(v <= 5)
 
-    The example will dispatch to `gb.select.indexle(v, 5)`
+    The example will dispatch to ``gb.select.indexle(v, 5)``
     while being potentially nicer to read.
     """
     return _resolve_expr(expr, "index", "index")
diff --git a/graphblas/ss/_core.py b/graphblas/ss/_core.py
index 441458a42..ec5a89504 100644
--- a/graphblas/ss/_core.py
+++ b/graphblas/ss/_core.py
@@ -12,7 +12,7 @@
 
 
 class _graphblas_ss:
-    """Used in `_expect_type`."""
+    """Used in ``_expect_type``."""
 
 
 _graphblas_ss.__name__ = "graphblas.ss"
@@ -33,8 +33,8 @@ def diag(x, k=0, dtype=None, *, name=None, **opts):
         The Vector to assign to the diagonal, or the Matrix from which to
         extract the diagonal.
     k : int, default 0
-        Diagonal in question.  Use `k>0` for diagonals above the main diagonal,
-        and `k<0` for diagonals below the main diagonal.
+        Diagonal in question.  Use ``k>0`` for diagonals above the main diagonal,
+        and ``k<0`` for diagonals below the main diagonal.
 
     See Also
     --------
@@ -71,9 +71,9 @@ def concat(tiles, dtype=None, *, name=None, **opts):
 
     Concatenate a 2D list of Matrix objects into a new Matrix, or a 1D list of
     Vector objects into a new Vector.  To concatenate into existing objects,
-    use ``Matrix.ss.concat`` or `Vector.ss.concat`.
+    use ``Matrix.ss.concat`` or ``Vector.ss.concat``.
 
-    Vectors may be used as `Nx1` Matrix objects when creating a new Matrix.
+    Vectors may be used as ``Nx1`` Matrix objects when creating a new Matrix.
 
     This performs the opposite operation as ``split``.
 
diff --git a/graphblas/tests/test_io.py b/graphblas/tests/test_io.py
index 24df55e9d..df94c6469 100644
--- a/graphblas/tests/test_io.py
+++ b/graphblas/tests/test_io.py
@@ -167,7 +167,11 @@ def test_matrix_to_from_networkx():
 def test_mmread_mmwrite(engine):
     if engine == "fmm" and fmm is None:  # pragma: no cover (import)
         pytest.skip("needs fast_matrix_market")
-    from scipy.io.tests import test_mmio
+    try:
+        from scipy.io.tests import test_mmio
+    except ImportError:
+        # Test files are mysteriously missing from some conda-forge builds
+        pytest.skip("scipy.io.tests.test_mmio unavailable :(")
 
     p31 = 2**31
     p63 = 2**63
diff --git a/graphblas/viz.py b/graphblas/viz.py
index d8a96d343..fafeae5f0 100644
--- a/graphblas/viz.py
+++ b/graphblas/viz.py
@@ -67,7 +67,7 @@ def draw(m):  # pragma: no cover
 
 
 def spy(M, *, centered=False, show=True, figure=None, axes=None, figsize=None, **kwargs):
-    """Plot the sparsity pattern of a Matrix using `matplotlib.spy`.
+    """Plot the sparsity pattern of a Matrix using ``matplotlib.spy``.
 
     See:
     - https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.spy.html
@@ -106,8 +106,8 @@ def spy(M, *, centered=False, show=True, figure=None, axes=None, figsize=None, *
 def datashade(M, agg="count", *, width=None, height=None, opts_kwargs=None, **kwargs):
     """Interactive plot of the sparsity pattern of a Matrix using hvplot and datashader.
 
-    The `datashader` library rasterizes large data into a 2d grid of pixels.  Each pixel
-    may contain multiple data points, which are combined by an aggregator (`agg="count"`).
+    The ``datashader`` library rasterizes large data into a 2d grid of pixels.  Each pixel
+    may contain multiple data points, which are combined by an aggregator (``agg="count"``).
     Common aggregators are "count", "sum", "mean", "min", and "max".  See full list here:
     - https://datashader.org/api.html#reductions
 
diff --git a/scripts/check_versions.sh b/scripts/check_versions.sh
index 3809eb805..dda7adbaa 100755
--- a/scripts/check_versions.sh
+++ b/scripts/check_versions.sh
@@ -7,11 +7,11 @@ conda search 'numpy[channel=conda-forge]>=1.24.3'
 conda search 'pandas[channel=conda-forge]>=2.0.1'
 conda search 'scipy[channel=conda-forge]>=1.10.1'
 conda search 'networkx[channel=conda-forge]>=3.1'
-conda search 'awkward[channel=conda-forge]>=2.1.4'
+conda search 'awkward[channel=conda-forge]>=2.2.0'
 conda search 'sparse[channel=conda-forge]>=0.14.0'
 conda search 'fast_matrix_market[channel=conda-forge]>=1.5.1'
 conda search 'numba[channel=conda-forge]>=0.56.4'
 conda search 'pyyaml[channel=conda-forge]>=6.0'
-conda search 'flake8-bugbear[channel=conda-forge]>=23.3.23'
+conda search 'flake8-bugbear[channel=conda-forge]>=23.5.9'
 conda search 'flake8-simplify[channel=conda-forge]>=0.20.0'
 # conda search 'python[channel=conda-forge]>=3.8 *pypy*'