Drop Python 3.9, add 3.12; update pre-commit

Author: eriknw

.github/workflows/publish_pypi.yml

@@ -20,7 +20,7 @@ jobs:
       - name: Set up Python
         uses: actions/setup-python@v4
         with:
-          python-version: "3.9"
+          python-version: "3.10"
       - name: Install build dependencies
         run: |
           python -m pip install --upgrade pip

.github/workflows/test.yml

@@ -15,7 +15,7 @@ jobs:
       fail-fast: true
       matrix:
         os: ["ubuntu-latest", "macos-latest", "windows-latest"]
-        python-version: ["3.9", "3.10", "3.11"]
+        python-version: ["3.10", "3.11", "3.12"]
     steps:
       - name: Checkout
         uses: actions/checkout@v4

.pre-commit-config.yaml

@@ -44,26 +44,26 @@ repos:
       - id: autoflake
         args: [--in-place]
   - repo: https://github.com/pycqa/isort
-    rev: 5.12.0
+    rev: 5.13.1
     hooks:
       - id: isort
   - repo: https://github.com/asottile/pyupgrade
     rev: v3.15.0
     hooks:
       - id: pyupgrade
-        args: [--py39-plus]
+        args: [--py310-plus]
   - repo: https://github.com/MarcoGorelli/auto-walrus
     rev: v0.2.2
     hooks:
       - id: auto-walrus
         args: [--line-length, "100"]
   - repo: https://github.com/psf/black
-    rev: 23.10.0
+    rev: 23.12.0
     hooks:
       - id: black
       # - id: black-jupyter
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.1.0
+    rev: v0.1.7
     hooks:
       - id: ruff
         args: [--fix-only, --show-fixes]
@@ -74,7 +74,7 @@ repos:
         additional_dependencies: &flake8_dependencies
         # These versions need updated manually
         - flake8==6.1.0
-        - flake8-bugbear==23.9.16
+        - flake8-bugbear==23.12.2
         - flake8-simplify==0.21.0
   - repo: https://github.com/asottile/yesqa
     rev: v1.5.0
@@ -89,7 +89,7 @@ repos:
         additional_dependencies: [tomli]
         files: ^(graphblas_algorithms|docs)/
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.1.0
+    rev: v0.1.7
     hooks:
       - id: ruff
   # `pyroma` may help keep our package standards up to date if best practices change.

graphblas_algorithms/algorithms/operators/binary.py

@@ -67,7 +67,7 @@ def intersection(G, H, *, name="intersection"):
     ids = H.list_to_ids(keys)
     B = H._A[ids, ids].new(dtypes.unify(A.dtype, H._A.dtype), mask=A.S, name=name)
     B << unary.one(B)
-    return type(G)(B, key_to_id=dict(zip(keys, range(len(keys)))))
+    return type(G)(B, key_to_id=dict(zip(keys, range(len(keys)), strict=True)))
 
 
 def difference(G, H, *, name="difference"):
@@ -142,7 +142,7 @@ def compose(G, H, *, name="compose"):
         C[A.nrows :, A.ncols :] = B[ids, ids]
         # Now make new `key_to_id`
         ids += A.nrows
-        key_to_id = dict(zip(newkeys, ids.tolist()))
+        key_to_id = dict(zip(newkeys, ids.tolist(), strict=True))
         key_to_id.update(G._key_to_id)
     return type(G)(C, key_to_id=key_to_id)
 

graphblas_algorithms/algorithms/shortest_paths/weighted.py

@@ -199,7 +199,7 @@ def bellman_ford_path_lengths(G, nodes=None, *, expand_output=False):
 
 def _reconstruct_path_from_parents(G, parents, src, dst):
     indices, values = parents.to_coo(sort=False)
-    d = dict(zip(indices.tolist(), values.tolist()))
+    d = dict(zip(indices.tolist(), values.tolist(), strict=True))
     if dst not in d:
         return []
     cur = dst

graphblas_algorithms/classes/_utils.py

@@ -61,7 +61,7 @@ def dict_to_vector(self, d, *, size=None, dtype=None, name=None):
     if size is None:
         size = len(self)
     key_to_id = self._key_to_id
-    indices, values = zip(*((key_to_id[key], val) for key, val in d.items()))
+    indices, values = zip(*((key_to_id[key], val) for key, val in d.items()), strict=True)
     return Vector.from_coo(indices, values, size=size, dtype=dtype, name=name)
 
 
@@ -116,7 +116,7 @@ def vector_to_dict(self, v, *, mask=None, fill_value=None):
     elif fill_value is not None and v.nvals < v.size:
         v(mask=~v.S) << fill_value
     id_to_key = self.id_to_key
-    return {id_to_key[index]: value for index, value in zip(*v.to_coo(sort=False))}
+    return {id_to_key[index]: value for index, value in zip(*v.to_coo(sort=False), strict=True)}
 
 
 def vector_to_list(self, v, *, values_are_keys=False):
@@ -198,26 +198,29 @@ def matrix_to_dicts(self, A, *, use_row_index=False, use_column_index=False, val
     id_to_key = self.id_to_key
     if values_are_keys:
         values = [id_to_key[val] for val in values]
-    it = zip(rows, np.lib.stride_tricks.sliding_window_view(indptr, 2).tolist())
+    it = zip(rows, np.lib.stride_tricks.sliding_window_view(indptr, 2).tolist(), strict=True)
     if use_row_index and use_column_index:
         return {
-            row: dict(zip(col_indices[start:stop], values[start:stop])) for row, (start, stop) in it
+            row: dict(zip(col_indices[start:stop], values[start:stop], strict=True))
+            for row, (start, stop) in it
         }
     if use_row_index:
         return {
             row: {
-                id_to_key[col]: val for col, val in zip(col_indices[start:stop], values[start:stop])
+                id_to_key[col]: val
+                for col, val in zip(col_indices[start:stop], values[start:stop], strict=True)
             }
             for row, (start, stop) in it
         }
     if use_column_index:
         return {
-            id_to_key[row]: dict(zip(col_indices[start:stop], values[start:stop]))
+            id_to_key[row]: dict(zip(col_indices[start:stop], values[start:stop], strict=True))
             for row, (start, stop) in it
         }
     return {
         id_to_key[row]: {
-            id_to_key[col]: val for col, val in zip(col_indices[start:stop], values[start:stop])
+            id_to_key[col]: val
+            for col, val in zip(col_indices[start:stop], values[start:stop], strict=True)
         }
         for row, (start, stop) in it
     }
@@ -239,9 +242,9 @@ def to_networkx(self, edge_attribute="weight"):
     rows = (id_to_key[row] for row in rows.tolist())
     cols = (id_to_key[col] for col in cols.tolist())
     if edge_attribute is None:
-        G.add_edges_from(zip(rows, cols))
+        G.add_edges_from(zip(rows, cols, strict=True))
     else:
-        G.add_weighted_edges_from(zip(rows, cols, vals), weight=edge_attribute)
+        G.add_weighted_edges_from(zip(rows, cols, vals, strict=True), weight=edge_attribute)
     # What else should we copy over?
     return G
 
@@ -258,4 +261,4 @@ def renumber_key_to_id(self, indices):
     return {id_to_key[index]: i for i, index in enumerate(indices)}
     # Alternative (about the same performance)
     # keys = self.list_to_keys(indices)
-    # return dict(zip(keys, range(len(indices))))
+    # return dict(zip(keys, range(len(indices)), strict=True))

graphblas_algorithms/nxapi/boundary.py

@@ -29,15 +29,19 @@ def edge_boundary(G, nbunch1, nbunch2=None, data=False, keys=False, default=None
             (id_to_key[col] for col in cols),
             # Unsure about this; data argument may mean *all* edge attributes
             ({weight: val} for val in vals),
+            strict=True,
         )
     else:
         it = zip(
             (id_to_key[row] for row in rows),
             (id_to_key[col] for col in cols),
+            strict=True,
         )
     if is_multigraph:
         # Edge weights indicate number of times to repeat edges
-        it = itertools.chain.from_iterable(itertools.starmap(itertools.repeat, zip(it, vals)))
+        it = itertools.chain.from_iterable(
+            itertools.starmap(itertools.repeat, zip(it, vals, strict=True))
+        )
     return it
 
 

pyproject.toml

@@ -10,7 +10,7 @@ name = "graphblas-algorithms"
 dynamic = ["version"]
 description = "Graph algorithms written in GraphBLAS and backend for NetworkX"
 readme = "README.md"
-requires-python = ">=3.9"
+requires-python = ">=3.10"
 license = {file = "LICENSE"}
 authors = [
     {name = "Erik Welch", email = "erik.n.welch@gmail.com"},
@@ -43,7 +43,6 @@ classifiers = [
     "Operating System :: Microsoft :: Windows",
     "Programming Language :: Python",
     "Programming Language :: Python :: 3",
-    "Programming Language :: Python :: 3.9",
     "Programming Language :: Python :: 3.10",
     "Programming Language :: Python :: 3.11",
     "Programming Language :: Python :: 3.12",
@@ -134,7 +133,7 @@ dirty_template = "{tag}+{ccount}.g{sha}.dirty"
 
 [tool.black]
 line-length = 100
-target-version = ["py39", "py310", "py311", "py312"]
+target-version = ["py310", "py311", "py312"]
 
 [tool.isort]
 sections = ["FUTURE", "STDLIB", "THIRDPARTY", "FIRSTPARTY", "LOCALFOLDER"]
@@ -177,7 +176,7 @@ exclude_lines = [
 [tool.ruff]
 # https://github.com/charliermarsh/ruff/
 line-length = 100
-target-version = "py39"
+target-version = "py310"
 unfixable = [
     "F841"  # unused-variable (Note: can leave useless expression)
 ]
@@ -205,6 +204,7 @@ ignore = [
     # "SIM401",  # Use dict.get ... instead of if-else-block (Note: if-else better for coverage and sometimes clearer)
     # "TRY004",  # Prefer `TypeError` exception for invalid type (Note: good advice, but not worth the nuisance)
     # "TRY200",  # Use `raise from` to specify exception cause (Note: sometimes okay to raise original exception)
+    "UP038",  # Use `X | Y` in `isinstance` call instead of `(X, Y)` (Note: using `|` seems to be slower)
 
     # Intentionally ignored
     "COM812",  # Trailing comma missing

scripts/scipy_impl.py

@@ -50,7 +50,7 @@ def pagerank(
         err = np.absolute(x - xlast).sum()
         if err < N * tol:
             return x
-            # return dict(zip(nodelist, map(float, x)))
+            # return dict(zip(nodelist, map(float, x), strict=True))
     raise nx.PowerIterationFailedConvergence(max_iter)