mirror of
https://code.lenaisten.de/Lenaisten/advent22.git
synced 2024-12-24 13:33:00 +00:00
Merge branch 'develop' into feature/drawrects
This commit is contained in:
commit
f0bac2d168
8 changed files with 54 additions and 63 deletions
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@ -20,25 +20,15 @@
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"vscode": {
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// Set *default* container specific settings.json values on container create.
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"settings": {
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"python.defaultInterpreterPath": "/usr/local/bin/python",
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"python.linting.enabled": true,
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"python.linting.pylintEnabled": true,
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"python.formatting.autopep8Path": "/usr/local/py-utils/bin/autopep8",
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"python.formatting.blackPath": "/usr/local/py-utils/bin/black",
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"python.formatting.yapfPath": "/usr/local/py-utils/bin/yapf",
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"python.linting.banditPath": "/usr/local/py-utils/bin/bandit",
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"python.linting.flake8Path": "/usr/local/py-utils/bin/flake8",
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"python.linting.mypyPath": "/usr/local/py-utils/bin/mypy",
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"python.linting.pycodestylePath": "/usr/local/py-utils/bin/pycodestyle",
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"python.linting.pydocstylePath": "/usr/local/py-utils/bin/pydocstyle",
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"python.linting.pylintPath": "/usr/local/py-utils/bin/pylint"
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"python.defaultInterpreterPath": "/usr/local/bin/python"
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},
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// Add the IDs of extensions you want installed when the container is created.
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"extensions": [
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"be5invis.toml",
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"mhutchie.git-graph",
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"ms-python.python",
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"ms-python.flake8",
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"ms-python.black-formatter",
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// "ms-python.flake8",
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"ms-python.isort",
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"ms-python.vscode-pylance"
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]
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4
api/.flake8
Normal file
4
api/.flake8
Normal file
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@ -0,0 +1,4 @@
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[flake8]
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max-line-length = 80
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select = C,E,F,W,B,B950
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extend-ignore = E203, E501
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31
api/.vscode/settings.json
vendored
31
api/.vscode/settings.json
vendored
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@ -1,17 +1,16 @@
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{
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"python.testing.pytestArgs": [
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"tests"
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],
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"python.testing.unittestEnabled": false,
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"python.testing.pytestEnabled": true,
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"python.linting.enabled": true,
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"python.linting.pylintEnabled": false,
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"python.linting.flake8Enabled": true,
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"python.languageServer": "Pylance",
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"editor.formatOnSave": true,
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"editor.codeActionsOnSave": {
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"source.organizeImports": true
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},
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"git.closeDiffOnOperation": true,
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"python.analysis.typeCheckingMode": "basic"
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}
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"python.linting.enabled": true,
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"python.linting.pylintEnabled": false,
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"python.linting.flake8Enabled": true,
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"python.languageServer": "Pylance",
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"editor.formatOnSave": true,
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"[python]": {
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"editor.defaultFormatter": "ms-python.black-formatter"
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},
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"editor.codeActionsOnSave": {
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"source.organizeImports": true
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},
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"git.closeDiffOnOperation": true,
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"python.analysis.typeCheckingMode": "basic",
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"python.analysis.diagnosticMode": "workspace",
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}
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@ -6,22 +6,20 @@ from webdav3.client import Client as WebDAVclient
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from .settings import SETTINGS
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_WEBDAV_CLIENT = WebDAVclient({
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"webdav_hostname": SETTINGS.webdav.url,
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"webdav_login": SETTINGS.webdav.username,
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"webdav_password": SETTINGS.webdav.password,
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"disable_check": SETTINGS.webdav.disable_check,
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})
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_WEBDAV_CLIENT = WebDAVclient(
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{
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"webdav_hostname": SETTINGS.webdav.url,
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"webdav_login": SETTINGS.webdav.username,
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"webdav_password": SETTINGS.webdav.password,
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"disable_check": SETTINGS.webdav.disable_check,
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}
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)
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@AsyncTTL(time_to_live=SETTINGS.cache_ttl)
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async def dav_list_files(regex: re.Pattern, directory: str = "") -> list[str]:
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ls = _WEBDAV_CLIENT.list(directory)
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return [
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f"{directory}/{path}"
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for path in ls
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if regex.search(path)
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]
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return [f"{directory}/{path}" for path in ls if regex.search(path)]
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@AsyncTTL(time_to_live=SETTINGS.cache_ttl)
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@ -1,5 +1,6 @@
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import colorsys
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from dataclasses import dataclass
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from typing import Self
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import numpy as np
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from PIL import Image, ImageDraw, ImageFont
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@ -10,7 +11,7 @@ class AdventImage:
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img: Image.Image
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@classmethod
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async def load_standard(cls, fp) -> "AdventImage":
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async def load_standard(cls, fp) -> Self:
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"""
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Bild laden und einen quadratischen Ausschnitt
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aus der Mitte nehmen
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@ -24,16 +25,18 @@ class AdventImage:
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square = min(width, height)
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# Bild zuschneiden und skalieren
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img = img.crop(box=(
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int((width - square)/2),
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int((height - square)/2),
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int((width + square)/2),
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int((height + square)/2),
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))
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img = img.crop(
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box=(
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int((width - square) / 2),
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int((height - square) / 2),
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int((width + square) / 2),
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int((height + square) / 2),
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)
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)
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img = img.resize(
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size=(500, 500),
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resample=Image.ANTIALIAS,
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resample=Image.LANCZOS,
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)
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# Farbmodell festlegen
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"""
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pixel_data = self.img.crop(box).getdata()
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mean_color: np.ndarray = np.mean(pixel_data, axis=0)
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mean_color: np.ndarray = np.mean(a=pixel_data, axis=0)
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return tuple(mean_color.astype(int).tolist())
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# betroffenen Bildbereich bestimmen
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text_box = await self.get_text_box(
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xy=xy,
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text=text,
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font=font,
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anchor=anchor,
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**text_kwargs
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xy=xy, text=text, font=font, anchor=anchor, **text_kwargs
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)
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if text_box is not None:
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@ -131,5 +130,5 @@ class AdventImage:
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font=font,
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fill=text_color,
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anchor=anchor,
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**text_kwargs
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**text_kwargs,
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)
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@ -1,7 +1,7 @@
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import itertools
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import random
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import re
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from typing import Any, Sequence
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from typing import Any, Self, Sequence
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from fastapi import Depends
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from PIL import ImageFont
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@ -17,7 +17,7 @@ from ._image import AdventImage
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class Random(random.Random):
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@classmethod
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async def get(cls, bonus_salt: Any = "") -> "Random":
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async def get(cls, bonus_salt: Any = "") -> Self:
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cfg = await get_config()
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return cls(f"{cfg.puzzle.solution}{bonus_salt}")
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# Elemente mischen
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return rnd.sample(seq, len(seq))
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#########
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# IMAGE #
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#########
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@ -22,8 +22,10 @@ async def uwe(
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) -> str:
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kurix = await get_kurix(kgs)
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return f"UWE hat bei {firma} einen beachtlichen Haufen von " \
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return (
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f"UWE hat bei {firma} einen beachtlichen Haufen von "
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f"{kgs} Kg ({kurix:.3f} Kurix) auf den Läufer geschissen."
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)
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@router.get("/torsten/{ding}")
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status.HTTP_418_IM_A_TEAPOT: {
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"description": "Commit Sudoku",
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"content": None,
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}
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}
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},
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},
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)
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async def kys() -> None:
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"""
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@ -13,9 +13,7 @@ async def user_is_admin(
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credentials: HTTPBasicCredentials = Depends(security),
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config: Config = Depends(get_config),
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) -> bool:
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username_correct = secrets.compare_digest(
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credentials.username, config.admin.name
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)
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username_correct = secrets.compare_digest(credentials.username, config.admin.name)
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password_correct = secrets.compare_digest(
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credentials.password, config.admin.password
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