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⬆️🩹 Update patch updates (#710)
Signed-off-by: renovate[bot] <29139614+renovate[bot]@users.noreply.github.com>
1 parent 01d5aac commit 833d342

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.pre-commit-config.yaml

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## Check JSON schemata
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- repo: https://github.com/python-jsonschema/check-jsonschema
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rev: 0.37.2
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rev: 0.37.3
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hooks:
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- id: check-github-workflows
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priority: 0
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## Check pyproject.toml file
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- repo: https://github.com/henryiii/validate-pyproject-schema-store
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rev: 2026.06.12
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rev: 2026.06.14
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hooks:
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- id: validate-pyproject
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priority: 0
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## Ensure uv.lock is up to date
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- repo: https://github.com/astral-sh/uv-pre-commit
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rev: 0.11.19
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rev: 0.11.21
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hooks:
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- id: uv-lock
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priority: 0
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## Format configuration files with prettier
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- repo: https://github.com/rbubley/mirrors-prettier
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rev: v3.8.3
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rev: v3.8.4
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hooks:
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- id: prettier
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types_or: [yaml, markdown, html, css, scss, javascript, json, json5]
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priority: 5
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## Format and lint Python files with ruff
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- repo: https://github.com/astral-sh/ruff-pre-commit
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rev: v0.15.16
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rev: v0.15.17
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hooks:
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- id: ruff-check
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require_serial: true
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## Check Python types with ty
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- repo: https://github.com/astral-sh/ty-pre-commit
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rev: v0.0.47
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rev: v0.0.49
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hooks:
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- id: ty
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args: [--isolated]

tests/conftest.py

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from typing import TYPE_CHECKING
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import pytest
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from mqt.predictor.ml.helper import get_path_training_data as ml_get_path_training_data
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from mqt.predictor.rl.helper import get_path_trained_model as rl_get_path_trained_model
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if TYPE_CHECKING:
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from collections.abc import Generator
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import pytest
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@pytest.fixture(scope="session", autouse=True)
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def clean_rl_models() -> Generator[None]:
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"""Clean up trained RL models after test session."""
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yield
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def pytest_sessionfinish(session: pytest.Session, exitstatus: int) -> None: # noqa: ARG001
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"""Clean up trained RL and ML models after test session."""
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for model in rl_get_path_trained_model().glob("*.zip"):
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model.unlink()
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@pytest.fixture(scope="session", autouse=True)
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def clean_ml_models() -> Generator[None]:
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"""Clean up trained ML models after test session."""
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yield
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for model in (ml_get_path_training_data() / "trained_model").glob("*.joblib"):
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model.unlink()
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