mirror of
https://ghfast.top/https://github.com/aeroxw/tick-stock-panel.git
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kevin9327
7755ab3a7d
_dimension_rank 用 `_finite(...) or -999` 作为排序键, 0.00% 是假值, 会被替换成 -999 排到所有下跌股之后。板块整体下跌、最强的一只恰好平盘时, 看板/复盘的「领涨」显示成跌幅最小的下跌股, 而不是那只平盘股。 改为显式区分 None 与 0.0 (缺涨跌幅 → -inf), 与 sector_monitor _dimension_snapshot 的 `max(valid_rows, key=lambda row: row["change_pct"])` 同口径。
90 lines
3.2 KiB
Python
90 lines
3.2 KiB
Python
"""市场总览「领涨股」选取: 涨跌幅 0.00% 是有效值, 不能被当成缺失值。"""
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from __future__ import annotations
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import json
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import polars as pl
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from app.services.market_overview_builder import _dimension_rank
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def _fake_repo(tmp_path):
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import types
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return types.SimpleNamespace(store=types.SimpleNamespace(data_dir=tmp_path))
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def _write_concept_ext(tmp_path, mapping: dict[str, str]) -> None:
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"""写一张 snapshot 模式的概念扩展表 (symbol → 所属概念)。"""
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cfg_dir = tmp_path / "ext_data" / "concept_tbl"
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cfg_dir.mkdir(parents=True, exist_ok=True)
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cfg_dir.joinpath("config.json").write_text(
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json.dumps({
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"id": "concept_tbl",
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"label": "概念表",
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"mode": "snapshot",
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"fields": [{"name": "所属概念", "dtype": "string", "label": "所属概念"}],
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}, ensure_ascii=False),
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encoding="utf-8",
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)
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pl.DataFrame({
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"symbol": list(mapping.keys()),
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"所属概念": list(mapping.values()),
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}).write_parquet(cfg_dir / "part.parquet")
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def test_flat_stock_can_be_leader_of_a_falling_concept(tmp_path):
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"""全概念下跌、最强的一只恰好平盘(0.00%)时, 领涨股必须是那只平盘股。"""
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_write_concept_ext(tmp_path, {
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"000001.SZ": "人工智能",
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"000002.SZ": "人工智能",
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"000003.SZ": "人工智能",
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})
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rows = [
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{"symbol": "000001.SZ", "name": "跌一", "change_pct": -0.01, "amount": 1e8},
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{"symbol": "000002.SZ", "name": "平盘", "change_pct": 0.0, "amount": 2e8},
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{"symbol": "000003.SZ", "name": "跌三", "change_pct": -0.03, "amount": 3e8},
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]
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result = _dimension_rank(rows, _fake_repo(tmp_path), "concept")
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items = {item["name"]: item for item in result["lagging"]}
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assert "人工智能" in items
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leader = items["人工智能"]["leader"]
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assert leader["name"] == "平盘"
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assert leader["change_pct"] == 0.0
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def test_leader_falls_back_to_none_pct_last(tmp_path):
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"""change_pct 缺失(None)的成分股仍排在所有有值的成分股之后。"""
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_write_concept_ext(tmp_path, {
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"000001.SZ": "芯片",
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"000002.SZ": "芯片",
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})
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rows = [
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{"symbol": "000001.SZ", "name": "无行情", "change_pct": None, "amount": 1e8},
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{"symbol": "000002.SZ", "name": "微跌", "change_pct": -0.02, "amount": 1e8},
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]
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result = _dimension_rank(rows, _fake_repo(tmp_path), "concept")
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items = {item["name"]: item for item in result["lagging"]}
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assert items["芯片"]["leader"]["name"] == "微跌"
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def test_leader_still_picks_max_when_all_positive(tmp_path):
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"""普通情形不受影响: 全部上涨时仍取涨幅最大的一只。"""
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_write_concept_ext(tmp_path, {
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"000001.SZ": "光伏",
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"000002.SZ": "光伏",
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})
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rows = [
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{"symbol": "000001.SZ", "name": "涨多", "change_pct": 0.05, "amount": 1e8},
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{"symbol": "000002.SZ", "name": "涨少", "change_pct": 0.01, "amount": 1e8},
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]
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result = _dimension_rank(rows, _fake_repo(tmp_path), "concept")
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items = {item["name"]: item for item in result["leading"]}
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assert items["光伏"]["leader"]["name"] == "涨多"
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