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Removing usage of deprecated TempStore (#249)
* removing usage of deprecated TempStore * updating pre-commit * fixing pixi * fixing linting
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3 files changed

+7
-13
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+7
-13
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.pre-commit-config.yaml

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@@ -1,7 +1,7 @@
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repos:
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# basic pre-commit
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- repo: https://github.com/pre-commit/pre-commit-hooks
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rev: v4.6.0
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rev: v6.0.0
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hooks:
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- id: trailing-whitespace
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- id: end-of-file-fixer
@@ -17,25 +17,25 @@ repos:
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- id: absolufy-imports
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# sorting imports
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- repo: https://github.com/pycqa/isort
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rev: 5.13.2
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rev: 7.0.0
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hooks:
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- id: isort
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args: ["--profile", "black", "--filter-files"]
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# automatic upgrade to newer python versions syntax
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- repo: https://github.com/asottile/pyupgrade
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rev: v3.17.0
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rev: v3.21.2
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hooks:
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- id: pyupgrade
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args: ["--py38-plus", "--keep-runtime-typing"]
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# syntax linting and formatting
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- repo: https://github.com/PyCQA/autoflake
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- repo: https://github.com/myint/autoflake
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rev: v2.3.1
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hooks:
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- id: autoflake
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args: [--in-place, --remove-all-unused-imports,
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--ignore-init-module-imports]
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- repo: https://github.com/PyCQA/flake8
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rev: 7.1.1
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rev: 7.3.0
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hooks:
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- id: flake8
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args: [--max-line-length, '120',
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--min-python-version, '3.9']
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additional_dependencies: [flake8-typing-imports==1.12.0]
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- repo: https://github.com/psf/black
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rev: 24.8.0
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rev: 25.11.0
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hooks:
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- id: black
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pyproject.toml

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@@ -99,7 +99,7 @@ ultrack = "ultrack.cli.main:main"
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ultrack = "ultrack:napari.yaml"
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# pixi config
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[tool.pixi.project]
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[tool.pixi.workspace]
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channels = ["conda-forge", "nvidia", "pytorch", "numba", "gurobi"]
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platforms = ["linux-64", "win-64", "osx-64"]
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preview = ["pixi-build"] # required to use git links

ultrack/widgets/ultrackwidget/workflows.py

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import napari
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import numpy as np
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import pandas as pd
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import zarr
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from napari.layers import Image, Labels, Layer, Tracks
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from napari.types import ArrayLike
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@@ -553,19 +552,14 @@ def _create_temp_detection_and_contours(
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Tuple[ArrayLike, ArrayLike]
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The paths to the temporary detection and contours arrays.
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"""
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detection_store = zarr.TempStore(suffix="detection")
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contours_store = zarr.TempStore(suffix="contours")
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zarr_detection = create_zarr(
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shape=shape,
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dtype=bool,
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store_or_path=detection_store,
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overwrite=True,
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)
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zarr_contours = create_zarr(
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shape=shape,
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dtype=np.float16,
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store_or_path=contours_store,
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overwrite=True,
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)
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