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https://github.com/A-Minos/nonebot-plugin-tetris-stats.git
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✨ 历史tr图表 (#499)
* ✨ 实现获取 leagueflow * ✨ TETR.IO 适配 v1 模板 * ✨ 限制 v2 history 数量
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呵呵です
172
nonebot_plugin_tetris_stats/games/tetrio/query/v1.py
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172
nonebot_plugin_tetris_stats/games/tetrio/query/v1.py
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from asyncio import gather
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from datetime import datetime, timedelta
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from hashlib import md5
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from math import ceil, floor
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from zoneinfo import ZoneInfo
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from yarl import URL
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from ....utils.exception import FallbackError
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from ....utils.host import HostPage, get_self_netloc
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from ....utils.render import render
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from ....utils.render.schemas.base import Avatar, Ranking
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from ....utils.render.schemas.tetrio.user.base import TetraLeagueHistoryData
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from ....utils.render.schemas.tetrio.user.info_v1 import Info, Radar, TetraLeague, TetraLeagueHistory, User
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from ....utils.screenshot import screenshot
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from ..api import Player
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from ..api.schemas.summaries.league import RatedData
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from ..constant import TR_MAX, TR_MIN
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from .tools import flow_to_history, get_league_data
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def get_value_bounds(values: list[int | float]) -> tuple[int, int]:
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value_max = 10 * ceil(max(values) / 10)
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value_min = 10 * floor(min(values) / 10)
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return value_max, value_min
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def get_split(value_max: int, value_min: int) -> tuple[int, int]:
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offset = 0
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overflow = 0
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while True:
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if (new_max_value := value_max + offset + overflow) > TR_MAX:
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overflow -= 1
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continue
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if (new_min_value := value_min - offset + overflow) < TR_MIN:
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overflow += 1
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continue
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if ((new_max_value - new_min_value) / 40).is_integer():
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split_value = int((value_max + offset - (value_min - offset)) / 4)
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break
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offset += 1
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return split_value, offset + overflow
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def get_specified_point(
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previous_point: TetraLeagueHistoryData,
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behind_point: TetraLeagueHistoryData,
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point_time: datetime,
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) -> TetraLeagueHistoryData:
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"""根据给出的 previous_point 和 behind_point, 推算 point_time 点处的数据
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Args:
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previous_point (Data): 前面的数据点
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behind_point (Data): 后面的数据点
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point_time (datetime): 要推算的点的位置
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Returns:
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Data: 要推算的点的数据
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"""
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# 求两个点的斜率
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slope = (behind_point.tr - previous_point.tr) / (
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datetime.timestamp(behind_point.record_at) - datetime.timestamp(previous_point.record_at)
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)
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return TetraLeagueHistoryData(
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record_at=point_time,
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tr=previous_point.tr + slope * (datetime.timestamp(point_time) - datetime.timestamp(previous_point.record_at)),
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)
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def handle_history_data(data: list[TetraLeagueHistoryData]) -> list[TetraLeagueHistoryData]:
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data.sort(key=lambda x: x.record_at)
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right_border = datetime.now(ZoneInfo('Asia/Shanghai')).replace(hour=0, minute=0, second=0, microsecond=0)
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left_border = right_border - timedelta(days=9)
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lefts: list[TetraLeagueHistoryData] = []
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in_border: list[TetraLeagueHistoryData] = []
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rights: list[TetraLeagueHistoryData] = []
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for i in data:
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if i.record_at < left_border:
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lefts.append(i)
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elif i.record_at < right_border:
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in_border.append(i)
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else:
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rights.append(i)
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ret: list[TetraLeagueHistoryData] = []
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if lefts:
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ret.append(get_specified_point(lefts[-1], in_border[0], left_border))
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else:
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ret.append(TetraLeagueHistoryData(tr=in_border[0].tr, record_at=left_border))
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ret.extend(in_border)
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if rights:
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ret.append(get_specified_point(in_border[-1], rights[0], right_border.replace(microsecond=1000)))
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else:
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ret.append(TetraLeagueHistoryData(tr=in_border[-1].tr, record_at=right_border.replace(microsecond=1000)))
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return ret
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async def make_query_image_v1(player: Player) -> bytes:
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(
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(user, user_info, league, sprint, blitz, leagueflow),
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(avatar_revision,),
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) = await gather(
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gather(player.user, player.get_info(), player.league, player.sprint, player.blitz, player.get_leagueflow()),
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gather(player.avatar_revision),
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)
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league_data = get_league_data(league, RatedData)
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if league_data.vs is None:
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raise FallbackError
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histories = flow_to_history(leagueflow, handle_history_data)
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value_max, value_min = get_value_bounds([i.tr for i in histories])
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split_value, offset = get_split(value_max, value_min)
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if sprint.data.record is not None:
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duration = timedelta(milliseconds=sprint.data.record.results.stats.finaltime).total_seconds()
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sprint_value = f'{duration:.3f}s' if duration < 60 else f'{duration // 60:.0f}m {duration % 60:.3f}s' # noqa: PLR2004
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else:
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sprint_value = 'N/A'
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blitz_value = f'{blitz.data.record.results.stats.score:,}' if blitz.data.record is not None else 'N/A'
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netloc = get_self_netloc()
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async with HostPage(
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page=await render(
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'v1/tetrio/info',
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Info(
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user=User(
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avatar=str(
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URL(f'http://{netloc}/host/resource/tetrio/avatars/{user.ID}') % {'revision': avatar_revision}
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)
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if avatar_revision is not None and avatar_revision != 0
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else Avatar(
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type='identicon',
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hash=md5(user.ID.encode()).hexdigest(), # noqa: S324
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),
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name=user.name.upper(),
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bio=user_info.data.bio,
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),
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ranking=Ranking(
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rating=round(league_data.glicko, 2),
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rd=round(league_data.rd, 2),
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),
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tetra_league=TetraLeague(
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rank=league_data.rank,
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tr=round(league_data.tr, 2),
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global_rank=league_data.standing,
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pps=league_data.pps,
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lpm=round(lpm := (league_data.pps * 24), 2),
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apm=league_data.apm,
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apl=round(league_data.apm / lpm, 2),
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vs=league_data.vs,
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adpm=round(adpm := (league_data.vs * 0.6), 2),
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adpl=round(adpm / lpm, 2),
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),
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tetra_league_history=TetraLeagueHistory(
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data=histories,
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split_interval=split_value,
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min_tr=value_min,
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max_tr=value_max,
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offset=offset,
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),
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radar=Radar(
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app=(app := (league_data.apm / (60 * league_data.pps))),
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dsps=(dsps := ((league_data.vs / 100) - (league_data.apm / 60))),
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dspp=(dspp := (dsps / league_data.pps)),
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ci=150 * dspp - 125 * app + 50 * (league_data.vs / league_data.apm) - 25,
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ge=2 * ((app * dsps) / league_data.pps),
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),
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sprint=sprint_value,
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blitz=blitz_value,
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),
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)
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) as page_hash:
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return await screenshot(f'http://{netloc}/host/{page_hash}.html')
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