refactor!: replace python 3.9 with 3.10 as oldest supported version

.github/workflows/run_tests.yml

@@ -20,12 +20,12 @@ jobs:
         # test with oldest and latest supported Python versions
         # NOTE: If bumping the minimum Python version here, also do it in
         # ruff.toml, setup.py and other CI files as well.
-        python-version: ["3.10", "3.12"]
+        python-version: ["3.10", "3.13"]
         runtime-deps: ["latest"]
 
         include:
           - os: ubuntu-latest
-            python-version: "3.12"
+            python-version: "3.10"
             runtime-deps: "oldest"
 
       fail-fast: false
@@ -199,7 +199,7 @@ jobs:
     strategy:
       matrix:
         os: [ubuntu-24.04]
-        python-version: ["3.12"]
+        python-version: ["3.13"]
 
         arch: ["x64"]
         docker-engine: ["docker"]
@@ -214,18 +214,18 @@ jobs:
           # Test on arm to ensure compatibility with Apple M1 chips
           # (OSX runners don't have access to Docker so we use Linux ARM runners instead)
           - os: "ubuntu-24.04"
-            python-version: "3.12"
+            python-version: "3.13"
             arch: "arm"
             docker-engine: "docker"
             unit-tesseract: "base"
           - os: "ubuntu-24.04"
-            python-version: "3.12"
+            python-version: "3.13"
             arch: "arm"
             docker-engine: "docker"
             unit-tesseract: "pyvista-arm64"
           # Run tests using Podman
           - os: "ubuntu-24.04"
-            python-version: "3.12"
+            python-version: "3.13"
             arch: "x64"
             docker-engine: "podman"
             unit-tesseract: "base"

examples/py39/tesseract_api.py → examples/py310/tesseract_api.py

@@ -25,10 +25,10 @@ class OutputSchema(BaseModel):
 
 
 def apply(inputs: InputSchema) -> OutputSchema:
-    # Ensure that the Python version is what we expect (3.9)
+    # Ensure that the Python version is what we expect (3.10)
     import sys
 
-    assert sys.version_info[:2] == (3, 9)
+    assert sys.version_info[:2] == (3, 10)
     return OutputSchema(bar=0)
 
 

examples/py310/tesseract_config.yaml

@@ -0,0 +1,7 @@
+name: "py310"
+version: "0.1.0"
+description: |
+  Empty Tesseract that requires Python 3.10 (set through a custom Docker image).
+
+build_config:
+  base_image: "python:3.10-slim-bookworm"

examples/qp_solve/tesseract_api.py

@@ -4,7 +4,6 @@
 # Tesseract API module for lp_solve
 # Generated by tesseract 0.9.0 on 2025-06-04T13:11:17.208977
 import functools
-from typing import Optional
 
 import jax
 import jax.numpy as jnp
@@ -23,29 +22,29 @@ class InputSchema(BaseModel):
     Q: Differentiable[Array[(None, None), Float32]] = Field(
         description="Quadratic cost matrix Q for the quadratic program."
     )
-    q: Optional[Differentiable[Array[(None,), Float32]]] = Field(
+    q: Differentiable[Array[(None,), Float32]] | None = Field(
         description="Linear cost vector q for the quadratic program.", default=None
     )
-    A: Optional[Differentiable[Array[(None, None), Float32]]] = Field(
+    A: Differentiable[Array[(None, None), Float32]] | None = Field(
         default=None,
         description="Linear equality constraint matrix A for the quadratic program.",
     )
-    b: Optional[Differentiable[Array[(None,), Float32]]] = Field(
+    b: Differentiable[Array[(None,), Float32]] | None = Field(
         default=None,
         description="Linear equality constraint rhs b for the quadratic program.",
     )
-    G: Optional[Differentiable[Array[(None, None), Float32]]] = Field(
+    G: Differentiable[Array[(None, None), Float32]] | None = Field(
         description="Linear inequality constraint matrix G for the quadratic program.",
         default=None,
     )
-    h: Optional[Differentiable[Array[(None,), Float32]]] = Field(
+    h: Differentiable[Array[(None,), Float32]] | None = Field(
         description="Linear inequality constraint rhs h for the quadratic program.",
         default=None,
     )
-    solver_tol: Optional[Float32] = Field(
+    solver_tol: Float32 | None = Field(
         description="Tolerance for the solver convergence.", default=1e-4
     )
-    target_kappa: Optional[Float32] = Field(
+    target_kappa: Float32 | None = Field(
         description="QPAX parameter for QP relaxation.", default=1e-3
     )
 

examples/univariate/optimize.py

@@ -37,6 +37,6 @@ def rosenbrock_gradient(x: np.ndarray) -> np.ndarray:
     callback=lambda xs: trajectory.append(xs.tolist()),
 )
 
-anim = make_animation(*list(zip(*trajectory)))
+anim = make_animation(*list(zip(*trajectory, strict=True)))
 # anim.save("rosenbrock_optimization.gif", writer="pillow", fps=2, dpi=150)
 plt.show()

pyproject.toml

@@ -59,6 +59,7 @@ filterwarnings = [
     "ignore:numpy.ufunc size changed",
     # sometimes, dependencies leak resources
     "ignore:.*socket\\.socket.*:pytest.PytestUnraisableExceptionWarning",
+    "ignore:.*sqlite3\\.Connection.*:pytest.PytestUnraisableExceptionWarning",
 ]
 
 [tool.coverage.run]

ruff.toml

@@ -1,6 +1,5 @@
 # Set to the lowest supported Python version.
-# !! tesseract_runtime still supports Python 3.9 !!
-target-version = "py39"
+target-version = "py310"
 
 # Set the target line length for formatting.
 line-length = 88

tesseract_core/runtime/array_encoding.py

@@ -4,7 +4,7 @@
 import re
 from collections.abc import Sequence
 from pathlib import Path
-from typing import Annotated, Any, Literal, Optional, Union, get_args
+from typing import Annotated, Any, Literal, get_args
 from uuid import uuid4
 
 import numpy as np
@@ -45,8 +45,8 @@
     "complex128",
 ]
 EllipsisType = type(Ellipsis)
-ArrayLike = Union[np.ndarray, np.number, np.bool_]
-ShapeType = Union[tuple[Optional[int], ...], EllipsisType]
+ArrayLike = np.ndarray | np.number | np.bool_
+ShapeType = tuple[int | None, ...] | EllipsisType
 
 MAX_BINREF_BUFFER_SIZE = 100 * 1024 * 1024  # 100 MB
 
@@ -94,12 +94,12 @@ class EncodedArrayModel(BaseModel):
     object_type: Literal["array"]
     shape: tuple[PositiveInt, ...]
     dtype: AllowedDtypes
-    data: Union[BinrefArrayData, Base64ArrayData, JsonArrayData]
+    data: BinrefArrayData | Base64ArrayData | JsonArrayData
     model_config = ConfigDict(extra="forbid")
 
 
 def get_array_model(
-    expected_shape: ShapeType, expected_dtype: Optional[str], flags: Sequence[str]
+    expected_shape: ShapeType, expected_dtype: str | None, flags: Sequence[str]
 ) -> type[EncodedArrayModel]:
     """Create a Pydantic model for an encoded array that does validation on the given expected shape and dtype."""
     if expected_dtype is None:
@@ -177,7 +177,7 @@ def get_array_model(
         ),
         # Choose the appropriate data structure based on the encoding
         "data": (
-            Union[BinrefArrayData, Base64ArrayData, JsonArrayData],
+            BinrefArrayData | Base64ArrayData | JsonArrayData,
             Field(discriminator="encoding"),
         ),
         "model_config": (ConfigDict, config),
@@ -203,12 +203,12 @@ def get_array_model(
 
 
 def _dump_binref_arraydict(
-    arr: Union[np.ndarray, np.number, np.bool_],
-    base_dir: Union[Path, str],
-    subdir: Optional[Union[Path, str]],
+    arr: np.ndarray | np.number | np.bool_,
+    base_dir: Path | str,
+    subdir: Path | str | None,
     current_binref_uuid: str,
     max_file_size: int = MAX_BINREF_BUFFER_SIZE,
-) -> tuple[dict[str, Union[str, dict[str, str]]], str]:
+) -> tuple[dict[str, str | dict[str, str]], str]:
     """Dump array to json+binref encoded array dict.
 
     Writes a .bin file and returns json encoded data.
@@ -243,8 +243,8 @@ def _dump_binref_arraydict(
 
 
 def _dump_base64_arraydict(
-    arr: Union[np.ndarray, np.number, np.bool_],
-) -> dict[str, Union[str, dict[str, str]]]:
+    arr: np.ndarray | np.number | np.bool_,
+) -> dict[str, str | dict[str, str]]:
     """Dump array to json+base64 encoded array dict."""
     data = {
         "buffer": pybase64.b64encode(arr.tobytes()).decode(),
@@ -260,8 +260,8 @@ def _dump_base64_arraydict(
 
 
 def _dump_json_arraydict(
-    arr: Union[np.ndarray, np.number, np.bool_],
-) -> dict[str, Union[str, dict[str, str]]]:
+    arr: np.ndarray | np.number | np.bool_,
+) -> dict[str, str | dict[str, str]]:
     """Dump array to json encoded array dict."""
     data = {
         "buffer": arr.tolist(),
@@ -282,7 +282,7 @@ def _load_base64_arraydict(val: dict) -> np.ndarray:
     return np.frombuffer(buffer, dtype=val["dtype"]).reshape(val["shape"])
 
 
-def _load_binref_arraydict(val: dict, base_dir: Union[str, Path, None]) -> np.ndarray:
+def _load_binref_arraydict(val: dict, base_dir: str | Path | None) -> np.ndarray:
     """Load array from json+binref encoded array dict."""
     path_match = re.match(r"^(?P<path>.+?)(\:(?P<offset>\d+))?$", val["data"]["buffer"])
     if not path_match:
@@ -316,7 +316,7 @@ def _load_binref_arraydict(val: dict, base_dir: Union[str, Path, None]) -> np.nd
 
 
 def _coerce_shape_dtype(
-    arr: ArrayLike, expected_shape: ShapeType, expected_dtype: Optional[str]
+    arr: ArrayLike, expected_shape: ShapeType, expected_dtype: str | None
 ) -> ArrayLike:
     """Coerce the shape and dtype of the passed array to the expected values."""
     if expected_shape is Ellipsis:
@@ -363,7 +363,7 @@ def _coerce_shape_dtype(
 
 
 def python_to_array(
-    val: Any, expected_shape: ShapeType, expected_dtype: Optional[str]
+    val: Any, expected_shape: ShapeType, expected_dtype: str | None
 ) -> ArrayLike:
     """Convert a Python object to a NumPy array."""
     val = np.asarray(val, order="C")
@@ -380,7 +380,7 @@ def decode_array(
     val: EncodedArrayModel,
     info: ValidationInfo,
     expected_shape: ShapeType,
-    expected_dtype: Optional[str],
+    expected_dtype: str | None,
 ) -> ArrayLike:
     """Decode an EncodedArrayModel to a NumPy array."""
     from tesseract_core.runtime.config import get_config
@@ -422,8 +422,8 @@ def decode_array(
 
 
 def encode_array(
-    arr: ArrayLike, info: Any, expected_shape: ShapeType, expected_dtype: Optional[str]
-) -> Union[EncodedArrayModel, ArrayLike]:
+    arr: ArrayLike, info: Any, expected_shape: ShapeType, expected_dtype: str | None
+) -> EncodedArrayModel | ArrayLike:
     """Encode a NumPy array as an EncodedArrayModel."""
     from tesseract_core.runtime.config import get_config
 

tesseract_core/runtime/cli.py

@@ -16,7 +16,6 @@
     Annotated,
     Any,
     Literal,
-    Optional,
     get_args,
     get_origin,
 )
@@ -219,23 +218,23 @@ def check_gradients(
         ),
     ],
     input_paths: Annotated[
-        Optional[list[str]],
+        list[str] | None,
         typer.Option(
             "--input-paths",
             help="Paths to differentiable inputs to check gradients for.",
             show_default="check all",
         ),
     ] = None,
     output_paths: Annotated[
-        Optional[list[str]],
+        list[str] | None,
         typer.Option(
             "--output-paths",
             help="Paths to differentiable outputs to check gradients for.",
             show_default="check all",
         ),
     ] = None,
     endpoints: Annotated[
-        Optional[list[str]],
+        list[str] | None,
         typer.Option(
             "--endpoints",
             help="Endpoints to check gradients for.",
@@ -275,7 +274,7 @@ def check_gradients(
         ),
     ] = 10,
     seed: Annotated[
-        Optional[int],
+        int | None,
         typer.Option(
             "--seed",
             help="Seed for random number generator. If not set, a random seed is used.",
@@ -367,7 +366,7 @@ def serve(
 
 
 def _create_user_defined_cli_command(
-    app: typer.Typer, user_function: Callable, out_stream: Optional[io.TextIOBase]
+    app: typer.Typer, user_function: Callable, out_stream: io.TextIOBase | None
 ) -> None:
     """Creates a click command which sends requests to Tesseract endpoints.
 
@@ -459,9 +458,7 @@ def command_func():
     decorator(command_func)
 
 
-def _add_user_commands_to_cli(
-    app: typer.Typer, out_stream: Optional[io.IOBase]
-) -> None:
+def _add_user_commands_to_cli(app: typer.Typer, out_stream: io.IOBase | None) -> None:
     tesseract_package = get_tesseract_api()
     endpoints = create_endpoints(tesseract_package)
 

tesseract_core/runtime/core.py

@@ -9,7 +9,7 @@
 from io import TextIOBase
 from pathlib import Path
 from types import ModuleType
-from typing import Any, TextIO, Union
+from typing import Any, TextIO
 
 from pydantic import BaseModel
 
@@ -22,9 +22,7 @@
 
 
 @contextmanager
-def redirect_fd(
-    from_: TextIO, to_: Union[TextIO, int]
-) -> Generator[TextIO, None, None]:
+def redirect_fd(from_: TextIO, to_: TextIO | int) -> Generator[TextIO, None, None]:
     """Redirect a file descriptor at OS level.
 
     Args:
@@ -49,7 +47,7 @@ def redirect_fd(
         orig_fd_file.close()
 
 
-def load_module_from_path(path: Union[Path, str]) -> ModuleType:
+def load_module_from_path(path: Path | str) -> ModuleType:
     """Load a module from a file path.
 
     Temporarily puts the module's parent folder on PYTHONPATH to ensure local imports work as expected.

tesseract_core/runtime/experimental.py

@@ -2,13 +2,11 @@
 # SPDX-License-Identifier: Apache-2.0
 
 import json
-from collections.abc import Iterator, Sequence
+from collections.abc import Callable, Iterator, Sequence
 from pathlib import Path
 from typing import (
     Annotated,
     Any,
-    Callable,
-    Union,
     get_args,
     get_origin,
 )
@@ -114,7 +112,7 @@ def __get_pydantic_core_schema__(
         Does most of the heavy lifting for validation and serialization.
         """
 
-        def create_sequence(maybe_path: Union[str, Sequence[Any]]) -> LazySequence:
+        def create_sequence(maybe_path: str | Sequence[Any]) -> LazySequence:
             """Expand a glob pattern into a LazySequence if needed."""
             validator = SchemaValidator(item_schema)