fixed 1.12

.pre-commit-config.yaml

@@ -24,3 +24,6 @@ repos:
       types_or: [ python, pyi, jupyter ]
     - id: ruff-format
       types_or: [ python, pyi, jupyter ]
+
+ci:
+    autofix_prs: false

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "finch-tensor"
-version = "0.2.13"
+version = "0.2.14"
 description = "Sparse Tensor Programming in Python powered by Finch.jl"
 readme = "README.md"
 authors = [{name = "Willow Ahrens", email = "willow.marie.ahrens@gmail.com"}]

src/finch/julia.py

@@ -1,11 +1,10 @@
-import juliapkg  # noqa: I001
+import juliapkg  # noqa: I001, F401
 
 # To change the version of Finch used, see the documentation for pyjuliapkg here: https://github.com/JuliaPy/pyjuliapkg
 # Use pyjuliapkg to modify the `juliapkg.json` file in the root of this repo.
 # You can also run `develop.py` to quickly use a local copy of Finch.jl.
 # An example development json is found in `juliapkg_dev.json`
 import juliacall as jc  # noqa: F401
-
 from juliacall import Main as jl  # noqa: E402, F401
 
 jl.seval("using Finch")

src/finch/juliapkg.json

@@ -1,9 +1,9 @@
 {
-  "julia": "1.10 - 1.11",
+  "julia": "1.10 - 1.12",
   "packages": {
     "Finch": {
       "uuid": "9177782c-1635-4eb9-9bfb-d9dfa25e6bce",
-      "version": "1.2.9"
+      "version": "1.2.10"
     },
     "HDF5": {
       "uuid": "f67ccb44-e63f-5c2f-98bd-6dc0ccc4ba2f",

src/finch/juliapkg_dev.json

@@ -1,5 +1,5 @@
 {
-  "julia": "1.10 - 1.11",
+  "julia": "1.10 - 1.12",
   "packages": {
     "Finch": {
       "dev": true,

tests/test_indexing.py

@@ -2,6 +2,7 @@
 
 import numpy as np
 from numpy.testing import assert_equal
+
 import juliacall as jc
 
 import finch

tests/test_ops.py

@@ -230,7 +230,7 @@ def test_elemwise_tensor_ops_2_args(arr3d, meth_name, opt):
         "mean",
         pytest.param("std", marks=pytest.mark.xfail(reason="TODO: to debug")),
         pytest.param("var", marks=pytest.mark.xfail(reason="TODO: to debug")),
-    ]
+    ],
 )
 @pytest.mark.parametrize("axis", [None, -1, 1, (0, 1), (0, 1, 2)])
 def test_reductions(arr3d, func_name, axis, opt):