🔖 Release 1.0.0.a4

🔖 1.0.0.a2

.github/dependabot.yml

@@ -7,6 +7,6 @@ version: 2
 updates:
   - package-ecosystem: "pip" # See documentation for possible values
     directory: "/" # Location of package manifests
-    target-branch: "dev"
+    target-branch: "main"
     schedule:
       interval: "daily"

.github/workflows/Release.yml

@@ -8,18 +8,41 @@ on:
 jobs:
   release:
     runs-on: ubuntu-latest
+    permissions:
+      id-token: write
+      contents: write
     steps:
       - uses: actions/checkout@v3
+
       - uses: actions/setup-python@v4
         with:
           python-version: '3.11'
+          cache: "poetry"
+
       - name: Install Poetry
         shell: bash
         run: |
           pip install poetry
-      - name: Build
-        shell: bash
-        run: |
           poetry install
-          poetry env use python
+
-          poetry publish --build -u ${{ secrets.USERNAME }} -p ${{ secrets.PASSWORD }} -n
+      - name: Get Version
+        id: version
+        run: |
+          echo "VERSION=$(poetry version -s)" >> $GITHUB_OUTPUT
+          echo "TAG_VERSION=${GITHUB_REF#refs/tags/v}" >> $GITHUB_OUTPUT
+          echo "TAG_NAME=${GITHUB_REF#refs/tags/}" >> $GITHUB_OUTPUT
+
+      - name: Check Version
+        if: steps.version.outputs.VERSION != steps.version.outputs.TAG_VERSION
+        run: exit 1
+
+      - name: Build Package
+        run: poetry build
+
+      - name: Publish Package to PyPI
+        uses: pypa/gh-action-pypi-publish@release/v1
+
+      - name: Publish Package to GitHub Release
+        run: gh release upload --clobber ${{ steps.version.outputs.TAG_NAME }} dist/*.tar.gz dist/*.whl
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

nonebot_plugin_tetris_stats/game_data_processor/io_data_processor/__init__.py

@@ -3,7 +3,7 @@ from datetime import timedelta
 from arclet.alconna import Alconna, Arg, ArgFlag, Args, CommandMeta, Option
 from nonebot.adapters import Bot, Event
 from nonebot.matcher import Matcher
-from nonebot_plugin_alconna import AlcMatches, At, on_alconna
+from nonebot_plugin_alconna import At, on_alconna
 from nonebot_plugin_orm import get_session
 from sqlalchemy import select
 
@@ -177,11 +177,3 @@ async def _(event: Event, matcher: Matcher, rank: Rank):
 @alc.handle()
 async def _(matcher: Matcher, account: MessageFormatError):
     await matcher.finish(str(account))
-
-
-@alc.handle()
-async def _(matcher: Matcher, matches: AlcMatches):
-    if matches.head_matched:
-        await matcher.finish(
-            f'{matches.error_info!r}\n' if matches.error_info is not None else '' + '输入"io --help"查看帮助'
-        )

nonebot_plugin_tetris_stats/game_data_processor/io_data_processor/processor.py

@@ -24,7 +24,7 @@ from .constant import BASE_URL, GAME_TYPE, RANK_PERCENTILE
 from .model import IORank
 from .schemas.league_all import FailedModel as LeagueAllFailed
 from .schemas.league_all import LeagueAll
-from .schemas.league_all import User as LeagueAllUser
+from .schemas.league_all import ValidUser as LeagueAllUser
 from .schemas.user_info import FailedModel as InfoFailed
 from .schemas.user_info import (
     NeverPlayedLeague,
@@ -216,7 +216,7 @@ async def get_io_rank_data() -> None:
         user = sort(users, field)
         return asdict(User(ID=user.id, name=user.username)), field(user)
 
-    users = league_all.data.users
+    users = [i for i in league_all.data.users if isinstance(i, LeagueAllUser)]
     rank_to_users: defaultdict[Rank, list[LeagueAllUser]] = defaultdict(list)
     for i in users:
         rank_to_users[i.league.rank].append(i)

nonebot_plugin_tetris_stats/game_data_processor/io_data_processor/schemas/league_all.py

@@ -7,7 +7,7 @@ from .base import SuccessModel as BaseSuccessModel
 
 class SuccessModel(BaseSuccessModel):
     class Data(BaseModel):
-        class User(BaseModel):
+        class ValidUser(BaseModel):
             class League(BaseModel):
                 gamesplayed: int
                 gameswon: int
@@ -30,10 +30,34 @@ class SuccessModel(BaseSuccessModel):
             verified: bool
             country: str | None
 
-        users: list[User]
+        class InvalidUser(BaseModel):
+            class League(BaseModel):
+                gamesplayed: int
+                gameswon: int
+                rating: float
+                glicko: float | None
+                rd: float | None
+                rank: Rank
+                bestrank: Rank
+                apm: float | None
+                pps: float | None
+                vs: float | None
+                decaying: bool
+
+            id: str = Field(..., alias='_id')
+            username: str
+            role: str
+            xp: float
+            league: League
+            supporter: bool
+            verified: bool
+            country: str | None
+
+        users: list[ValidUser | InvalidUser]
 
     data: Data
 
 
 LeagueAll = SuccessModel | FailedModel
-User = SuccessModel.Data.User
+ValidUser = SuccessModel.Data.ValidUser
+InvalidUser = SuccessModel.Data.InvalidUser

nonebot_plugin_tetris_stats/game_data_processor/io_data_processor/schemas/user_records.py

@@ -19,6 +19,7 @@ class EndContext(BaseModel):
         doubles: int
         triples: int
         quads: int
+        pentas: int | None
         realtspins: int
         minitspins: int
         minitspinsingles: int
@@ -32,7 +33,7 @@ class EndContext(BaseModel):
     class Garbage(BaseModel):
         sent: int
         received: int
-        attack: int
+        attack: int | None
         cleared: int
 
     class Finesse(BaseModel):
@@ -45,18 +46,18 @@ class EndContext(BaseModel):
     level_lines: int
     level_lines_needed: int
     inputs: int
-    holds: int
+    holds: int | None
     time: Time
     score: int
     zenlevel: int
     zenprogress: int
     level: int
     combo: int
-    currentcombopower: int  # WTF
+    currentcombopower: int | None  # WTF
     topcombo: int
     btb: int
     topbtb: int
-    currentbtbchainpower: int | None  # WTF * 2 40l 里有 但是 blitz 没有
+    currentbtbchainpower: int | None  # WTF * 2
     tspins: int
     piecesplaced: int
     clears: Clears

nonebot_plugin_tetris_stats/game_data_processor/top_data_processor/__init__.py

@@ -1,7 +1,7 @@
 from arclet.alconna import Alconna, Arg, ArgFlag, Args, CommandMeta, Option
 from nonebot.adapters import Bot, Event
 from nonebot.matcher import Matcher
-from nonebot_plugin_alconna import AlcMatches, At, on_alconna
+from nonebot_plugin_alconna import At, on_alconna
 from nonebot_plugin_orm import get_session
 
 from ...db import query_bind_info
@@ -116,11 +116,3 @@ async def _(event: Event, matcher: Matcher, account: User):
 @alc.handle()
 async def _(matcher: Matcher, account: MessageFormatError):
     await matcher.finish(str(account))
-
-
-@alc.handle()
-async def _(matcher: Matcher, matches: AlcMatches):
-    if matches.head_matched:
-        await matcher.finish(
-            f'{matches.error_info!r}\n' if matches.error_info is not None else '' + '输入"top --help"查看帮助'
-        )

nonebot_plugin_tetris_stats/game_data_processor/tos_data_processor/__init__.py

@@ -1,7 +1,7 @@
 from arclet.alconna import Alconna, Arg, ArgFlag, Args, CommandMeta, Option
 from nonebot.adapters import Bot, Event
 from nonebot.matcher import Matcher
-from nonebot_plugin_alconna import AlcMatches, At, on_alconna
+from nonebot_plugin_alconna import At, on_alconna
 from nonebot_plugin_orm import get_session
 
 from ...db import query_bind_info
@@ -141,11 +141,3 @@ async def _(event: Event, matcher: Matcher, account: User):
 @alc.handle()
 async def _(matcher: Matcher, account: MessageFormatError):
     await matcher.finish(str(account))
-
-
-@alc.handle()
-async def _(matcher: Matcher, matches: AlcMatches):
-    if matches.head_matched:
-        await matcher.finish(
-            f'{matches.error_info!r}\n' if matches.error_info is not None else '' + '输入"茶服 --help"查看帮助'
-        )

poetry.lock

@@ -197,6 +197,16 @@ typing-extensions = ">=4.5.0"
 [package.extras]
 all = ["email-validator (>=2.0.0)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)", "jinja2 (>=2.11.2)", "orjson (>=3.2.1)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.5)", "pyyaml (>=5.3.1)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0)", "uvicorn[standard] (>=0.12.0)"]
 
+[[package]]
+name = "fleep"
+version = "1.0.1"
+description = "File format determination library"
+optional = false
+python-versions = ">=3.1"
+files = [
+    {file = "fleep-1.0.1.tar.gz", hash = "sha256:c8f62b258ee5364d7f6c1ed1f3f278e99020fc3f0a60a24ad1e10846e31d104c"},
+]
+
 [[package]]
 name = "greenlet"
 version = "3.0.0"
@@ -868,18 +878,19 @@ nonebot2 = ">=2.1.0"
 
 [[package]]
 name = "nonebot-plugin-alconna"
-version = "0.32.0"
+version = "0.33.3"
 description = "Alconna Adapter for Nonebot"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "nonebot_plugin_alconna-0.32.0-py3-none-any.whl", hash = "sha256:3126b845ebbb4118a46513977a6ce91783a4c6158febba03a4b00ac565a6756b"},
+    {file = "nonebot_plugin_alconna-0.33.3-py3-none-any.whl", hash = "sha256:f04baa7b97a431c815b070bf12abfd5590d2763531eec4464798af2a1e907608"},
-    {file = "nonebot_plugin_alconna-0.32.0.tar.gz", hash = "sha256:ab53fadec56f2a5fcf75adb95a5312db48620217c3b3dcd90878ab0394062ff8"},
+    {file = "nonebot_plugin_alconna-0.33.3.tar.gz", hash = "sha256:8be755008fcd7277b23f9594135c9f5c2de3bf0856cede60f5baee6f22053afc"},
 ]
 
 [package.dependencies]
 arclet-alconna = ">=1.7.31,<2.0.0"
 arclet-alconna-tools = ">=0.6.7,<0.7.0"
+fleep = ">=1.0.1"
 nepattern = ">=0.5.14,<0.6.0"
 nonebot2 = ">=2.1.0"
 
@@ -1015,6 +1026,51 @@ files = [
     {file = "numpy-1.26.1.tar.gz", hash = "sha256:c8c6c72d4a9f831f328efb1312642a1cafafaa88981d9ab76368d50d07d93cbe"},
 ]
 
+[[package]]
+name = "numpy"
+version = "1.26.2"
+description = "Fundamental package for array computing in Python"
+optional = false
+python-versions = ">=3.9"
+files = [
+    {file = "numpy-1.26.2-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:3703fc9258a4a122d17043e57b35e5ef1c5a5837c3db8be396c82e04c1cf9b0f"},
+    {file = "numpy-1.26.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:cc392fdcbd21d4be6ae1bb4475a03ce3b025cd49a9be5345d76d7585aea69440"},
+    {file = "numpy-1.26.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:36340109af8da8805d8851ef1d74761b3b88e81a9bd80b290bbfed61bd2b4f75"},
+    {file = "numpy-1.26.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bcc008217145b3d77abd3e4d5ef586e3bdfba8fe17940769f8aa09b99e856c00"},
+    {file = "numpy-1.26.2-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:3ced40d4e9e18242f70dd02d739e44698df3dcb010d31f495ff00a31ef6014fe"},
+    {file = "numpy-1.26.2-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:b272d4cecc32c9e19911891446b72e986157e6a1809b7b56518b4f3755267523"},
+    {file = "numpy-1.26.2-cp310-cp310-win32.whl", hash = "sha256:22f8fc02fdbc829e7a8c578dd8d2e15a9074b630d4da29cda483337e300e3ee9"},
+    {file = "numpy-1.26.2-cp310-cp310-win_amd64.whl", hash = "sha256:26c9d33f8e8b846d5a65dd068c14e04018d05533b348d9eaeef6c1bd787f9919"},
+    {file = "numpy-1.26.2-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:b96e7b9c624ef3ae2ae0e04fa9b460f6b9f17ad8b4bec6d7756510f1f6c0c841"},
+    {file = "numpy-1.26.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:aa18428111fb9a591d7a9cc1b48150097ba6a7e8299fb56bdf574df650e7d1f1"},
+    {file = "numpy-1.26.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:06fa1ed84aa60ea6ef9f91ba57b5ed963c3729534e6e54055fc151fad0423f0a"},
+    {file = "numpy-1.26.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:96ca5482c3dbdd051bcd1fce8034603d6ebfc125a7bd59f55b40d8f5d246832b"},
+    {file = "numpy-1.26.2-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:854ab91a2906ef29dc3925a064fcd365c7b4da743f84b123002f6139bcb3f8a7"},
+    {file = "numpy-1.26.2-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:f43740ab089277d403aa07567be138fc2a89d4d9892d113b76153e0e412409f8"},
+    {file = "numpy-1.26.2-cp311-cp311-win32.whl", hash = "sha256:a2bbc29fcb1771cd7b7425f98b05307776a6baf43035d3b80c4b0f29e9545186"},
+    {file = "numpy-1.26.2-cp311-cp311-win_amd64.whl", hash = "sha256:2b3fca8a5b00184828d12b073af4d0fc5fdd94b1632c2477526f6bd7842d700d"},
+    {file = "numpy-1.26.2-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:a4cd6ed4a339c21f1d1b0fdf13426cb3b284555c27ac2f156dfdaaa7e16bfab0"},
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+    {file = "numpy-1.26.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:aa317b2325f7aa0a9471663e6093c210cb2ae9c0ad824732b307d2c51983d5b6"},
+    {file = "numpy-1.26.2-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:174a8880739c16c925799c018f3f55b8130c1f7c8e75ab0a6fa9d41cab092fd6"},
+    {file = "numpy-1.26.2-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:f79b231bf5c16b1f39c7f4875e1ded36abee1591e98742b05d8a0fb55d8a3eec"},
+    {file = "numpy-1.26.2-cp312-cp312-win32.whl", hash = "sha256:4a06263321dfd3598cacb252f51e521a8cb4b6df471bb12a7ee5cbab20ea9167"},
+    {file = "numpy-1.26.2-cp312-cp312-win_amd64.whl", hash = "sha256:b04f5dc6b3efdaab541f7857351aac359e6ae3c126e2edb376929bd3b7f92d7e"},
+    {file = "numpy-1.26.2-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:4eb8df4bf8d3d90d091e0146f6c28492b0be84da3e409ebef54349f71ed271ef"},
+    {file = "numpy-1.26.2-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:1a13860fdcd95de7cf58bd6f8bc5a5ef81c0b0625eb2c9a783948847abbef2c2"},
+    {file = "numpy-1.26.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:64308ebc366a8ed63fd0bf426b6a9468060962f1a4339ab1074c228fa6ade8e3"},
+    {file = "numpy-1.26.2-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:baf8aab04a2c0e859da118f0b38617e5ee65d75b83795055fb66c0d5e9e9b818"},
+    {file = "numpy-1.26.2-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:d73a3abcac238250091b11caef9ad12413dab01669511779bc9b29261dd50210"},
+    {file = "numpy-1.26.2-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:b361d369fc7e5e1714cf827b731ca32bff8d411212fccd29ad98ad622449cc36"},
+    {file = "numpy-1.26.2-cp39-cp39-win32.whl", hash = "sha256:bd3f0091e845164a20bd5a326860c840fe2af79fa12e0469a12768a3ec578d80"},
+    {file = "numpy-1.26.2-cp39-cp39-win_amd64.whl", hash = "sha256:2beef57fb031dcc0dc8fa4fe297a742027b954949cabb52a2a376c144e5e6060"},
+    {file = "numpy-1.26.2-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:1cc3d5029a30fb5f06704ad6b23b35e11309491c999838c31f124fee32107c79"},
+    {file = "numpy-1.26.2-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:94cc3c222bb9fb5a12e334d0479b97bb2df446fbe622b470928f5284ffca3f8d"},
+    {file = "numpy-1.26.2-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:fe6b44fb8fcdf7eda4ef4461b97b3f63c466b27ab151bec2366db8b197387841"},
+    {file = "numpy-1.26.2.tar.gz", hash = "sha256:f65738447676ab5777f11e6bbbdb8ce11b785e105f690bc45966574816b6d3ea"},
+]
+
 [[package]]
 name = "objprint"
 version = "0.2.3"
@@ -1028,50 +1084,50 @@ files = [
 
 [[package]]
 name = "pandas"
-version = "2.1.1"
+version = "2.1.3"
 description = "Powerful data structures for data analysis, time series, and statistics"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "pandas-2.1.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:58d997dbee0d4b64f3cb881a24f918b5f25dd64ddf31f467bb9b67ae4c63a1e4"},
+    {file = "pandas-2.1.3-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:acf08a73b5022b479c1be155d4988b72f3020f308f7a87c527702c5f8966d34f"},
-    {file = "pandas-2.1.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:02304e11582c5d090e5a52aec726f31fe3f42895d6bfc1f28738f9b64b6f0614"},
+    {file = "pandas-2.1.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:3cc4469ff0cf9aa3a005870cb49ab8969942b7156e0a46cc3f5abd6b11051dfb"},
-    {file = "pandas-2.1.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ffa8f0966de2c22de408d0e322db2faed6f6e74265aa0856f3824813cf124363"},
+    {file = "pandas-2.1.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:35172bff95f598cc5866c047f43c7f4df2c893acd8e10e6653a4b792ed7f19bb"},
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 ]
 
 [package.dependencies]
 numpy = [
-    {version = ">=1.22.4", markers = "python_version < \"3.11\""},
+    {version = ">=1.22.4,<2", markers = "python_version < \"3.11\""},
-    {version = ">=1.23.2", markers = "python_version == \"3.11\""},
+    {version = ">=1.23.2,<2", markers = "python_version == \"3.11\""},
-    {version = ">=1.26.0", markers = "python_version >= \"3.12\""},
+    {version = ">=1.26.0,<2", markers = "python_version >= \"3.12\""},
 ]
 python-dateutil = ">=2.8.2"
 pytz = ">=2020.1"
 tzdata = ">=2022.1"
 
 [package.extras]
-all = ["PyQt5 (>=5.15.6)", "SQLAlchemy (>=1.4.36)", "beautifulsoup4 (>=4.11.1)", "bottleneck (>=1.3.4)", "dataframe-api-compat (>=0.1.7)", "fastparquet (>=0.8.1)", "fsspec (>=2022.05.0)", "gcsfs (>=2022.05.0)", "html5lib (>=1.1)", "hypothesis (>=6.46.1)", "jinja2 (>=3.1.2)", "lxml (>=4.8.0)", "matplotlib (>=3.6.1)", "numba (>=0.55.2)", "numexpr (>=2.8.0)", "odfpy (>=1.4.1)", "openpyxl (>=3.0.10)", "pandas-gbq (>=0.17.5)", "psycopg2 (>=2.9.3)", "pyarrow (>=7.0.0)", "pymysql (>=1.0.2)", "pyreadstat (>=1.1.5)", "pytest (>=7.3.2)", "pytest-asyncio (>=0.17.0)", "pytest-xdist (>=2.2.0)", "pyxlsb (>=1.0.9)", "qtpy (>=2.2.0)", "s3fs (>=2022.05.0)", "scipy (>=1.8.1)", "tables (>=3.7.0)", "tabulate (>=0.8.10)", "xarray (>=2022.03.0)", "xlrd (>=2.0.1)", "xlsxwriter (>=3.0.3)", "zstandard (>=0.17.0)"]
+all = ["PyQt5 (>=5.15.6)", "SQLAlchemy (>=1.4.36)", "beautifulsoup4 (>=4.11.1)", "bottleneck (>=1.3.4)", "dataframe-api-compat (>=0.1.7)", "fastparquet (>=0.8.1)", "fsspec (>=2022.05.0)", "gcsfs (>=2022.05.0)", "html5lib (>=1.1)", "hypothesis (>=6.46.1)", "jinja2 (>=3.1.2)", "lxml (>=4.8.0)", "matplotlib (>=3.6.1)", "numba (>=0.55.2)", "numexpr (>=2.8.0)", "odfpy (>=1.4.1)", "openpyxl (>=3.0.10)", "pandas-gbq (>=0.17.5)", "psycopg2 (>=2.9.3)", "pyarrow (>=7.0.0)", "pymysql (>=1.0.2)", "pyreadstat (>=1.1.5)", "pytest (>=7.3.2)", "pytest-xdist (>=2.2.0)", "pyxlsb (>=1.0.9)", "qtpy (>=2.2.0)", "s3fs (>=2022.05.0)", "scipy (>=1.8.1)", "tables (>=3.7.0)", "tabulate (>=0.8.10)", "xarray (>=2022.03.0)", "xlrd (>=2.0.1)", "xlsxwriter (>=3.0.3)", "zstandard (>=0.17.0)"]
 aws = ["s3fs (>=2022.05.0)"]
 clipboard = ["PyQt5 (>=5.15.6)", "qtpy (>=2.2.0)"]
 compression = ["zstandard (>=0.17.0)"]
@@ -1091,7 +1147,7 @@ plot = ["matplotlib (>=3.6.1)"]
 postgresql = ["SQLAlchemy (>=1.4.36)", "psycopg2 (>=2.9.3)"]
 spss = ["pyreadstat (>=1.1.5)"]
 sql-other = ["SQLAlchemy (>=1.4.36)"]
-test = ["hypothesis (>=6.46.1)", "pytest (>=7.3.2)", "pytest-asyncio (>=0.17.0)", "pytest-xdist (>=2.2.0)"]
+test = ["hypothesis (>=6.46.1)", "pytest (>=7.3.2)", "pytest-xdist (>=2.2.0)"]
 xml = ["lxml (>=4.8.0)"]
 
 [[package]]
@@ -2093,4 +2149,4 @@ multidict = ">=4.0"
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "fe5add372ec41e79b27a990ab27afbdcceb625dc81f3ebd20a28e0b8129f6942"
+content-hash = "90fd550637cb1f381015128bbdeb8e644ab56ca493ed1751bead31a75999b2de"

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = 'nonebot-plugin-tetris-stats'
-version = '1.0.0.a1'
+version = '1.0.0.a4'
 description = '一款基于 NoneBot2 的用于查询 Tetris 相关游戏数据的插件'
 authors = ['scdhh <wallfjjd@gmail.com>']
 readme = 'README.md'
@@ -19,7 +19,7 @@ aiofiles = "^23.2.1"
 nonebot-plugin-orm = ">=0.1.1,<0.6.0"
 nonebot-plugin-localstore = "^0.5.1"
 httpx = "^0.25.0"
-nonebot-plugin-alconna = ">=0.30,<0.33"
+nonebot-plugin-alconna = ">=0.30,<0.34"
 nonebot-plugin-apscheduler = "^0.3.0"
 
 [tool.poetry.group.dev.dependencies]