Upgrade dependencies

.github/workflows/ci.yml

@@ -7,7 +7,7 @@ on:
       - master
 
 env:
-  uv-version: "0.8.3"
+  uv-version: "0.9.0"
 
 jobs:
   test:

.github/workflows/release.yml

@@ -6,7 +6,7 @@ on:
       - 'v*'
 
 env:
-  uv-version: "0.8.3"
+  uv-version: "0.9.0"
 
 jobs:
   pypi-publish:

pyproject.toml

@@ -27,11 +27,11 @@ classifiers = [
     "Topic :: Software Development :: Libraries :: Python Modules",
 ]
 dependencies = [
-    "returns >= 0.20,<0.26",
+    "returns >= 0.20,<0.27",
     "cffi ~= 1.16",
-    "llvmlite == 0.44.*",
+    "llvmlite == 0.45.*",
     "parsita == 2.*",
-    "typer == 0.15.*",
+    "typer == 0.19.*",
 ]
 
 [project.optional-dependencies]
@@ -67,7 +67,7 @@ fuzz = [
     "hypofuzz == 24.*"
 ]
 lint = [
-    "ruff == 0.6.*"
+    "ruff == 0.14.*"
 ]
 docs = [
     "mkdocs-material == 9.*"

src/tensora/_stable_set.py

@@ -1,6 +1,6 @@
 from __future__ import annotations
 
-__all__ = ["StableSet", "StableFrozenSet"]
+__all__ = ["StableFrozenSet", "StableSet"]
 
 from typing import AbstractSet, Hashable, Iterator, MutableSet, TypeVar
 
@@ -10,7 +10,7 @@
 class StableSet(MutableSet[Element]):
     def __init__(self, *items: Element):
         # Rely on stable dictionary
-        self._items = {item: None for item in items}
+        self._items = dict.fromkeys(items, None)
 
     def __len__(self) -> int:
         return len(self._items)

src/tensora/cli.py

@@ -35,15 +35,15 @@ def tensora(
                 "Unmentioned tensors are be assumed to be all dense."
             ),
         ),
-    ] = [],  # noqa: B006; Typer does not support Sequence or tuple
+    ] = [],  # noqa: B006 Typer does not support Sequence or tuple
     kernel_types: Annotated[
         list[KernelType],
         typer.Option(
             "--type",
             "-t",
             help="The type of kernel that will be generated. Can be mentioned multiple times.",
         ),
-    ] = [KernelType.compute],  # noqa: B006; Typer does not support Sequence or tuple
+    ] = [KernelType.compute],  # noqa: B006 Typer does not support Sequence or tuple
     language: Annotated[
         Language,
         typer.Option(

src/tensora/codegen/_ir_to_c.py

@@ -1,4 +1,4 @@
-__all__ = ["ir_to_c_statement", "ir_to_c_function_definition", "ir_to_c"]
+__all__ = ["ir_to_c", "ir_to_c_function_definition", "ir_to_c_statement"]
 
 from functools import singledispatch
 

src/tensora/codegen/_type_to_llvm.py

@@ -1,11 +1,11 @@
 __all__ = [
-    "llvm_integer_type",
-    "llvm_float_type",
+    "attribute_indexes",
     "llvm_boolean_type",
+    "llvm_float_type",
+    "llvm_integer_type",
     "llvm_mode_type",
     "llvm_size_type",
     "type_to_llvm",
-    "attribute_indexes",
 ]
 
 from functools import singledispatch

src/tensora/compile/_cffi_ownership.py

@@ -1,10 +1,10 @@
 __all__ = [
     "allocate_taco_structure",
     "taco_structure_to_cffi",
+    "taco_type_header",
     "take_ownership_of_arrays",
-    "take_ownership_of_tensor_members",
     "take_ownership_of_tensor",
-    "taco_type_header",
+    "take_ownership_of_tensor_members",
     "tensor_cdefs",
 ]
 

src/tensora/compile/_porcelain.py

@@ -1,4 +1,4 @@
-__all__ = ["tensor_method", "evaluate", "evaluate_cffi", "evaluate_tensora"]
+__all__ = ["evaluate", "evaluate_cffi", "evaluate_tensora", "tensor_method"]
 
 from functools import lru_cache
 

src/tensora/compile/_tensor_method.py

@@ -1,7 +1,7 @@
 __all__ = [
-    "TensorMethod",
     "BackendCompiler",
     "BroadcastTargetIndexError",
+    "TensorMethod",
 ]
 
 from dataclasses import dataclass

src/tensora/desugar/ast.py

@@ -1,13 +1,13 @@
 __all__ = [
+    "Add",
+    "Assignment",
+    "Contract",
     "Expression",
-    "Literal",
-    "Integer",
     "Float",
-    "Tensor",
-    "Add",
+    "Integer",
+    "Literal",
     "Multiply",
-    "Contract",
-    "Assignment",
+    "Tensor",
 ]
 
 from dataclasses import dataclass

src/tensora/expression/_exceptions.py

@@ -1,4 +1,4 @@
-__all__ = ["MutatingAssignmentError", "InconsistentDimensionsError", "NameConflictError"]
+__all__ = ["InconsistentDimensionsError", "MutatingAssignmentError", "NameConflictError"]
 
 from dataclasses import dataclass
 

src/tensora/expression/ast.py

@@ -1,15 +1,15 @@
 from __future__ import annotations
 
 __all__ = [
+    "Add",
+    "Assignment",
     "Expression",
-    "Literal",
-    "Integer",
     "Float",
-    "Tensor",
-    "Add",
-    "Subtract",
+    "Integer",
+    "Literal",
     "Multiply",
-    "Assignment",
+    "Subtract",
+    "Tensor",
 ]
 
 from abc import abstractmethod

src/tensora/format/_format.py

@@ -1,6 +1,6 @@
 from __future__ import annotations
 
-__all__ = ["Mode", "Format"]
+__all__ = ["Format", "Mode"]
 
 from dataclasses import dataclass
 from enum import Enum

src/tensora/generate/_base.py

@@ -1,4 +1,4 @@
-__all__ = ["generate_code", "Language"]
+__all__ = ["Language", "generate_code"]
 
 from enum import Enum
 

src/tensora/ir/_peephole.py

@@ -19,7 +19,7 @@
 * redundant_assignment: a = a => {}
 """
 
-__all__ = ["peephole_function_definition", "peephole_statement", "peephole"]
+__all__ = ["peephole", "peephole_function_definition", "peephole_statement"]
 
 from dataclasses import replace
 from functools import singledispatch

src/tensora/ir/ast.py

@@ -1,40 +1,40 @@
 from __future__ import annotations
 
 __all__ = [
-    "Statement",
-    "Expression",
+    "Add",
+    "And",
+    "ArrayAllocate",
+    "ArrayIndex",
+    "ArrayReallocate",
     "Assignable",
-    "Variable",
+    "Assignment",
     "AttributeAccess",
-    "ArrayIndex",
-    "IntegerLiteral",
-    "FloatLiteral",
+    "Block",
     "BooleanLiteral",
-    "Add",
-    "Subtract",
-    "Multiply",
+    "BooleanToInteger",
+    "Branch",
+    "Declaration",
+    "DeclarationAssignment",
     "Equal",
-    "NotEqual",
+    "Expression",
+    "FloatLiteral",
+    "FunctionDefinition",
     "GreaterThan",
     "GreaterThanOrEqual",
+    "IntegerLiteral",
     "LessThan",
     "LessThanOrEqual",
-    "And",
-    "Or",
+    "Loop",
     "Max",
     "Min",
-    "BooleanToInteger",
-    "ArrayAllocate",
-    "ArrayReallocate",
-    "Declaration",
-    "Assignment",
-    "DeclarationAssignment",
-    "Block",
-    "Branch",
-    "Loop",
-    "Return",
-    "FunctionDefinition",
     "Module",
+    "Multiply",
+    "NotEqual",
+    "Or",
+    "Return",
+    "Statement",
+    "Subtract",
+    "Variable",
 ]
 
 from dataclasses import dataclass

src/tensora/ir/types.py

@@ -1,16 +1,16 @@
 __all__ = [
-    "Type",
-    "Integer",
-    "integer",
+    "Array",
+    "FixedArray",
     "Float",
-    "float",
-    "Tensor",
-    "tensor",
+    "Integer",
     "Mode",
-    "mode",
     "Pointer",
-    "Array",
-    "FixedArray",
+    "Tensor",
+    "Type",
+    "float",
+    "integer",
+    "mode",
+    "tensor",
 ]
 
 from dataclasses import dataclass

src/tensora/iteration_graph/_generate_ir.py

@@ -384,9 +384,7 @@ def to_ir_sum(self: SumNode, output: Output, kernel_type: KernelType):
 
     if kernel_type.is_compute():
         # No assembly is currently allowed downstream of a Sum node
-        next_output, next_output_declarations, next_output_cleanup = output.next_output(
-            None, kernel_type
-        )
+        next_output, next_output_declarations, _ = output.next_output(None, kernel_type)
         source.append(next_output_declarations)
 
         for term in self.terms:

src/tensora/iteration_graph/_names.py

@@ -1,16 +1,16 @@
 from __future__ import annotations
 
 __all__ = [
-    "dimension_name",
-    "pos_name",
-    "crd_name",
-    "vals_name",
-    "pos_capacity_name",
     "crd_capacity_name",
-    "vals_capacity_name",
+    "crd_name",
+    "dimension_name",
     "layer_pointer",
+    "pos_capacity_name",
+    "pos_name",
     "previous_layer_pointer",
     "sparse_end_name",
+    "vals_capacity_name",
+    "vals_name",
     "value_from_crd",
 ]
 

src/tensora/iteration_graph/_write_sparse_ir.py

@@ -1,8 +1,8 @@
 __all__ = [
-    "write_sparse_initialization",
     "write_crd_assembly",
-    "write_pos_assembly",
     "write_pos_allocation",
+    "write_pos_assembly",
+    "write_sparse_initialization",
 ]
 
 from ..format import Mode

src/tensora/iteration_graph/identifiable_expression/ast.py

@@ -1,4 +1,4 @@
-__all__ = ["Expression", "Literal", "Integer", "Float", "Tensor", "Add", "Multiply"]
+__all__ = ["Add", "Expression", "Float", "Integer", "Literal", "Multiply", "Tensor"]
 
 from dataclasses import dataclass
 

src/tensora/iteration_graph/iteration_graph.py

@@ -1,6 +1,6 @@
 from __future__ import annotations
 
-__all__ = ["IterationGraph", "TerminalNode", "IterationNode", "SumNode"]
+__all__ = ["IterationGraph", "IterationNode", "SumNode", "TerminalNode"]
 
 from abc import abstractmethod
 from dataclasses import dataclass, replace

src/tensora/iteration_graph/outputs/_bucket.py

@@ -68,10 +68,10 @@ def ravel_indexes(self, dimensions: list[Variable], indexes: list[Variable]):
         return Add.join(list(reversed(terms)))
 
     def name(self) -> Variable:
-        return Variable(f'bucket_{self.output.id}{"".join(f"_{x}" for x in self.layers)}')
+        return Variable(f"bucket_{self.output.id}{''.join(f'_{x}' for x in self.layers)}")
 
     def loop_name(self) -> Variable:
-        return Variable(f'i_bucket_{self.output.id}{"".join(f"_{x}" for x in self.layers)}')
+        return Variable(f"i_bucket_{self.output.id}{''.join(f'_{x}' for x in self.layers)}")
 
     def dimension_names(self):
         return [dimension_name(self.output.indexes[layer]) for layer in self.layers]

src/tensora/problem.py

@@ -1,9 +1,9 @@
 __all__ = [
-    "Problem",
-    "make_problem",
     "IncorrectDimensionsError",
+    "Problem",
     "UndefinedReferenceError",
     "UnusedFormatError",
+    "make_problem",
 ]
 
 from dataclasses import dataclass

src/tensora/tensor.py

@@ -612,7 +612,7 @@ def default_format_given_nnz(dimensions: Tuple[int, ...], nnz: int) -> Format:
     # than the product of those dimensions.
     needed_dense = 0
     required_threshold = 1
-    for needed_dense, dimension in enumerate(dimensions):  # noqa: B007; needed_dense is used
+    for needed_dense, dimension in enumerate(dimensions):  # noqa: B007 needed_dense is used
         required_threshold *= dimension
         if nnz < required_threshold:
             break

tests/test_tensor.py

@@ -336,13 +336,13 @@ def test_binary_mismatched_dimensions():
     a = Tensor.from_lol([3, 2, 5])
     b = Tensor.from_lol([1, 2, 0, 4])
 
-    with pytest.raises(ValueError, match="Cannot apply operator +"):
+    with pytest.raises(ValueError, match="Cannot apply operator \\+"):
         _ = a + b
 
     with pytest.raises(ValueError, match="Cannot apply operator -"):
         _ = a - b
 
-    with pytest.raises(ValueError, match="Cannot apply operator *"):
+    with pytest.raises(ValueError, match="Cannot apply operator \\*"):
         _ = a * b