mirror of
https://ghfast.top/https://github.com/aeroxw/tick-stock-panel.git
synced 2026-09-12 15:34:16 +08:00
fix(kline): 压缩详情响应并限制无权限分钟回退
This commit is contained in:
0112020179
@@ -70,9 +70,12 @@ def get_index_minute(
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):
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"""实时读取指数分钟 K。不写入股票分钟 parquet。"""
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repo = request.app.state.repo
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capset = request.app.state.capabilities
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info = _index_info(repo, symbol)
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day = trade_date or date.today()
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df = kline_sync.fetch_minute_single(symbol, day, asset_type="index")
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df = kline_sync.fetch_minute_single(
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symbol, day, asset_type="index", capset=capset,
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)
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return {
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"symbol": symbol,
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"name": info.get("name"),
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+91
-42
@@ -27,7 +27,7 @@ router = APIRouter(prefix="/api/kline", tags=["kline"])
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def _gzip_payload(request: Request, payload: dict, *, pref_key: str) -> dict | Response:
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"""大 JSON 响应的传输压缩: 偏好开启 + 客户端接受 gzip + 响应超阈值才压。
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分时/日K批量各自独立偏好键 (网络设置里大开关批量、子开关单独控制)。
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分时/日K各自使用独立偏好键 (沿用已有 *_batch_compress 存储键保证兼容)。
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level 6 实测 13MB ≈ 290ms CPU 压掉 87%; level 9 要 2.5s 不可用。
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datetime → isoformat, 与 FastAPI jsonable_encoder 输出一致
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(前端 since 增量按字符串字典序比较, 格式必须与非压缩路径相同)。
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@@ -393,7 +393,11 @@ def get_daily(
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except Exception as e:
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raise HTTPException(status_code=502, detail=f"TickFlow fetch failed: {e}") from e
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if raw.is_empty():
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return {"symbol": symbol, "name": stock_name, "stock_info": stock_info, "rows": []}
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return _gzip_payload(
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request,
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{"symbol": symbol, "name": stock_name, "stock_info": stock_info, "rows": []},
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pref_key="daily_batch_compress",
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)
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# 拉除权因子做前复权 (Starter+ 有权限), 否则空 df → compute_enriched 退回未复权
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factors = pl.DataFrame()
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capset = getattr(request.app.state, "capabilities", None)
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@@ -408,7 +412,11 @@ def get_daily(
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# 即使 live 模式也尝试追加实时蜡烛
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rows = _maybe_inject_live_candle(request, symbol, rows, asset_type)
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resp = {"symbol": symbol, "name": stock_name, "stock_info": stock_info, "rows": rows, "source": "live"}
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return _attach_ext(resp, repo, symbol, ext_columns)
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return _gzip_payload(
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request,
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_attach_ext(resp, repo, symbol, ext_columns),
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pref_key="daily_batch_compress",
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)
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rows = df.to_dicts()
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@@ -416,7 +424,11 @@ def get_daily(
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rows = _maybe_inject_live_candle(request, symbol, rows, asset_type)
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resp = {"symbol": symbol, "name": stock_name, "stock_info": stock_info, "rows": rows, "source": "enriched"}
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return _attach_ext(resp, repo, symbol, ext_columns)
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return _gzip_payload(
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request,
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_attach_ext(resp, repo, symbol, ext_columns),
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pref_key="daily_batch_compress",
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)
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def _attach_ext(resp: dict, repo, symbol: str, ext_columns: Optional[str]) -> dict:
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@@ -879,13 +891,21 @@ def get_minute_range(
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# 指数分钟 K 不落本地仓库, 最新分时仍由 /api/index/minute 实时读取。
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if asset_type == "index":
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return {**base_response, "sessions": [], "source": "none"}
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return _gzip_payload(
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request,
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{**base_response, "sessions": [], "source": "none"},
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pref_key="minute_batch_compress",
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)
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end = cn_today()
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start = end - timedelta(days=days * 3 + 20)
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minute = repo.get_minute_range([symbol], start, end, asset_type=asset_type)
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if minute.is_empty() or "datetime" not in minute.columns:
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return {**base_response, "sessions": [], "source": "none"}
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return _gzip_payload(
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request,
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{**base_response, "sessions": [], "source": "none"},
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pref_key="minute_batch_compress",
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)
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minute = minute.with_columns(
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pl.col("datetime").dt.date().alias("_trade_date"),
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@@ -914,11 +934,15 @@ def get_minute_range(
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"rows": rows,
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})
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return {
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**base_response,
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"sessions": sessions,
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"source": "local" if sessions else "none",
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}
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return _gzip_payload(
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request,
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{
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**base_response,
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"sessions": sessions,
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"source": "local" if sessions else "none",
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},
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pref_key="minute_batch_compress",
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)
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@router.get("/minute")
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@@ -931,12 +955,14 @@ def get_minute(
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"""读取某只股票某天的分钟 K 线。
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- 本地有完整数据(240条) → 直接返回
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- 本地无数据或不完整 → 从 TickFlow 实时拉取返回（不写入）
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- 本地无数据或不完整 → 从有效分钟数据源实时拉取返回(不写入)
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- 自定义源失败时, 仅具备 TickFlow 单股分钟能力才回退 TickFlow
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- live=true 且当日连续竞价时段 → 跳过本地优先直接实时拉取:
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盘中分钟增量落盘的本地分区按 ≥60s 轮次更新, 90% 完整度启发式会让
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详情分时图停在上一增量轮, 与行情列表的节奏脱节
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"""
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repo = request.app.state.repo
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capset = request.app.state.capabilities
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asset_type = repo.resolve_asset_type(symbol)
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stock_info = _get_stock_info(repo, symbol) if asset_type == "stock" else _get_asset_info(repo, symbol, asset_type)
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stock_name = stock_info.get("name")
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@@ -961,22 +987,29 @@ def get_minute(
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else:
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trade_date = today
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if trade_date is None:
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# 本地无任何分钟K，尝试从 TickFlow 拉取当天
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# 本地无任何分钟K, 尝试从当前有效分钟源拉取当天
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trade_date = cn_today()
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df = kline_sync.fetch_minute_single(symbol, trade_date, asset_type=asset_type)
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df = kline_sync.fetch_minute_single(
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symbol, trade_date, asset_type=asset_type, capset=capset,
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)
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price_limit = _get_price_limit_info(
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repo, symbol, trade_date, asset_type, stock_name,
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)
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prev_close = _get_previous_closes(
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repo, symbol, [trade_date], asset_type,
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).get(trade_date)
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return {
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"symbol": symbol, "name": stock_name, "stock_info": stock_info,
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"date": str(trade_date), "rows": df.to_dicts(), "source": "live",
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"asset_type": asset_type,
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"price_limit": price_limit,
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"prev_close": prev_close,
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}
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return _gzip_payload(
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request,
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{
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"symbol": symbol, "name": stock_name, "stock_info": stock_info,
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"date": str(trade_date), "rows": df.to_dicts(),
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"source": "live" if not df.is_empty() else "none",
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"asset_type": asset_type,
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"price_limit": price_limit,
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"prev_close": prev_close,
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},
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pref_key="minute_batch_compress",
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)
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prev_close = _get_previous_closes(
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repo, symbol, [trade_date], asset_type,
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@@ -988,14 +1021,20 @@ def get_minute(
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if live and trade_date == cn_today() and in_continuous_session():
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# 详情分时轮询: 当日盘中实时拉取最新一根K, 不落盘; 拉空(源侧延迟/
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# 时段边界)则落回下方本地优先路径。
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live_df = kline_sync.fetch_minute_single(symbol, trade_date, asset_type=asset_type)
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live_df = kline_sync.fetch_minute_single(
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symbol, trade_date, asset_type=asset_type, capset=capset,
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)
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if not live_df.is_empty():
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return {
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"symbol": symbol, "name": stock_name, "stock_info": stock_info,
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"date": str(trade_date), "rows": live_df.to_dicts(),
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"source": "live", "asset_type": asset_type,
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"price_limit": price_limit, "prev_close": prev_close,
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}
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return _gzip_payload(
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request,
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{
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"symbol": symbol, "name": stock_name, "stock_info": stock_info,
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"date": str(trade_date), "rows": live_df.to_dicts(),
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"source": "live", "asset_type": asset_type,
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"price_limit": price_limit, "prev_close": prev_close,
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},
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pref_key="minute_batch_compress",
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)
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df = repo.get_minute(symbol, trade_date, asset_type=asset_type)
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@@ -1019,24 +1058,34 @@ def get_minute(
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is_complete = not df.is_empty() and len(df) >= expected * 0.9 # 允许 10% 容差
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if is_complete:
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return {
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return _gzip_payload(
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request,
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{
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"symbol": symbol, "name": stock_name, "stock_info": stock_info,
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"date": str(trade_date), "rows": df.to_dicts(), "source": "local",
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"asset_type": asset_type,
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"price_limit": price_limit,
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"prev_close": prev_close,
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},
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pref_key="minute_batch_compress",
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)
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# 本地不完整或无数据 → 从当前有效分钟源实时拉取
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live_df = kline_sync.fetch_minute_single(
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symbol, trade_date, asset_type=asset_type, capset=capset,
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)
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return _gzip_payload(
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request,
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{
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"symbol": symbol, "name": stock_name, "stock_info": stock_info,
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"date": str(trade_date), "rows": df.to_dicts(), "source": "local",
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"date": str(trade_date), "rows": live_df.to_dicts(),
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"source": "live" if not live_df.is_empty() else "none",
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"asset_type": asset_type,
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"price_limit": price_limit,
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"prev_close": prev_close,
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}
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# 本地不完整或无数据 → 从 TickFlow 实时拉取
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live_df = kline_sync.fetch_minute_single(symbol, trade_date, asset_type=asset_type)
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return {
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"symbol": symbol, "name": stock_name, "stock_info": stock_info,
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"date": str(trade_date), "rows": live_df.to_dicts(),
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"source": "live" if not live_df.is_empty() else "none",
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"asset_type": asset_type,
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"price_limit": price_limit,
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"prev_close": prev_close,
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}
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},
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pref_key="minute_batch_compress",
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)
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@router.post("/sync")
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@@ -810,7 +810,7 @@ def update_data_source_job_timeouts(req: DataSourceJobTimeoutPrefs) -> dict:
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@router.put("/preferences/minute-batch-compress")
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def update_minute_batch_compress(req: MinuteBatchCompressPrefs) -> dict:
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"""保存分时批量响应的 gzip 传输压缩开关。逐请求即时读取, 保存后立即生效。"""
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"""保存分时详情与批量响应的 gzip 传输压缩开关。逐请求即时读取, 保存后立即生效。"""
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from app.services import preferences
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preferences.save({"minute_batch_compress": req.minute_batch_compress})
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return {"minute_batch_compress": preferences.get_minute_batch_compress()}
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@@ -818,7 +818,7 @@ def update_minute_batch_compress(req: MinuteBatchCompressPrefs) -> dict:
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@router.put("/preferences/daily-batch-compress")
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def update_daily_batch_compress(req: DailyBatchCompressPrefs) -> dict:
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"""保存日K批量响应的 gzip 传输压缩开关 (与分时独立)。逐请求即时读取。"""
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"""保存日K详情与批量响应的 gzip 传输压缩开关 (与分时独立)。逐请求即时读取。"""
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from app.services import preferences
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preferences.save({"daily_batch_compress": req.daily_batch_compress})
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return {"daily_batch_compress": preferences.get_daily_batch_compress()}
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@@ -761,10 +761,8 @@ def _try_custom_minute(
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(None, True) → 未配自定义源 / 未配 minute dataset / 自定义源异常 → 走 TickFlow
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(df, False) → 自定义源成功(含空 df) → 直接用, 不回退
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降级策略 (C): 自定义源异常时无条件 fall through 到 TickFlow,
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由 TickFlow 路径自身 try/except 兜底。Pro+ 用户 TickFlow 成功返回数据,
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None 档用户 TickFlow 失败返回空。不显式判断 tier, 避免 #126 augmented
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capability 逻辑干扰。
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自定义源异常时返回 fallback=True。单股拉取调用方另行检查 TickFlow 原生
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能力, 避免自定义源增广能力误放行无权限请求。
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resolver 异常边界由 _resolve_minute_provider 统一兜底; 业务调用
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(provider.get_minute) 仍在本函数 try 块内, 与 resolver 异常分离
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@@ -1220,8 +1218,14 @@ def fetch_minute_single(
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symbol: str,
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trade_date: date,
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asset_type: AssetType = "stock",
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*,
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capset: CapabilitySet,
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) -> pl.DataFrame:
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"""实时拉取单股单日分钟 K(不写入本地)。优先自定义分钟源, 回退 TickFlow。"""
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"""实时拉取单股单日分钟 K(不写入本地)。
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优先使用当前自定义分钟源。仅当 TickFlow 原生单股分钟能力存在时才允许
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回退 TickFlow; 自定义源增广只授予 batch 能力, 不会误放行该回退路径。
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"""
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from datetime import datetime
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# 北京时间窗口必须带时区: naive datetime 会被 .timestamp() 按服务器本地时区解释,
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# UTC 容器上窗口整体偏移 8 小时, 分时补拉必然为空。
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@@ -1238,6 +1242,9 @@ def fetch_minute_single(
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# 见 sync_minute_batch 同分支注释: df 在此必非 None。
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return df if df is not None else pl.DataFrame()
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if not capset.has(Cap.KLINE_MINUTE_BY_SYMBOL):
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return pl.DataFrame()
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tf = get_client()
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try:
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raw = tf.klines.batch(
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@@ -248,7 +248,7 @@ def get_data_source_long_job_timeout_s() -> int:
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def get_minute_batch_compress() -> bool:
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"""分时批量响应是否启用 gzip 传输压缩。默认开启 (公网部署传输是大头);
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"""分时详情与批量响应是否启用 gzip 传输压缩。默认开启 (公网部署传输是大头);
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本机/内网可关闭省服务端 CPU。每次请求即时读取, 开关保存后立即生效。
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"""
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raw = load().get("minute_batch_compress", True)
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@@ -256,7 +256,7 @@ def get_minute_batch_compress() -> bool:
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def get_daily_batch_compress() -> bool:
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"""日K批量响应是否启用 gzip 传输压缩 (与分时各自独立配置)。默认开启。"""
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"""日K详情与批量响应是否启用 gzip 传输压缩 (与分时各自独立配置)。默认开启。"""
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raw = load().get("daily_batch_compress", True)
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return bool(raw)
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@@ -0,0 +1,235 @@
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"""个股详情 K 线传输压缩与分钟源能力门控回归测试。"""
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from __future__ import annotations
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from datetime import date, datetime, timedelta
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from unittest.mock import MagicMock
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import polars as pl
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import pytest
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from fastapi import FastAPI
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from fastapi.testclient import TestClient
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from app.api import indices, kline
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from app.tickflow.capabilities import Cap, CapabilityLimits, CapabilitySet
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_SYMBOL = "600000.SH"
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_TRADE_DATE = date(2026, 1, 15)
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@pytest.fixture(autouse=True)
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def _isolated_settings_and_clock(monkeypatch):
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monkeypatch.setattr("app.services.preferences.get_daily_batch_compress", lambda: True)
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monkeypatch.setattr("app.services.preferences.get_minute_batch_compress", lambda: True)
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monkeypatch.setattr(kline, "cn_today", lambda: _TRADE_DATE)
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monkeypatch.setattr(kline, "cn_now", lambda: datetime(2026, 1, 15, 10, 30))
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monkeypatch.setattr(kline, "in_continuous_session", lambda: True)
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def _minute_rows(count: int = 240) -> pl.DataFrame:
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start = datetime(2026, 1, 15, 9, 30)
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return pl.DataFrame(
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{
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"symbol": [_SYMBOL] * count,
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"datetime": [start + timedelta(minutes=i) for i in range(count)],
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"open": [10.0] * count,
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"high": [10.1] * count,
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"low": [9.9] * count,
|
||||
"close": [10.05] * count,
|
||||
"volume": [1_000.0] * count,
|
||||
"amount": [10_050.0] * count,
|
||||
}
|
||||
)
|
||||
|
||||
|
||||
class _DetailRepo:
|
||||
def __init__(self, minute: pl.DataFrame | None = None) -> None:
|
||||
self.minute = minute if minute is not None else _minute_rows()
|
||||
|
||||
def resolve_asset_type(self, symbol: str) -> str:
|
||||
return "stock"
|
||||
|
||||
def get_instruments(self) -> pl.DataFrame:
|
||||
return pl.DataFrame(
|
||||
{
|
||||
"symbol": [_SYMBOL],
|
||||
"name": ["浦发银行"],
|
||||
"total_shares": [1.0],
|
||||
"float_shares": [1.0],
|
||||
}
|
||||
)
|
||||
|
||||
def get_daily_asset(self, asset_type, symbol, start, end, columns=None):
|
||||
frame = pl.DataFrame(
|
||||
{
|
||||
"symbol": [_SYMBOL] * 30,
|
||||
"date": [date(2025, 12, 15) + timedelta(days=i) for i in range(30)],
|
||||
"open": [10.0] * 30,
|
||||
"high": [10.2] * 30,
|
||||
"low": [9.8] * 30,
|
||||
"close": [10.1] * 30,
|
||||
"volume": [1_000.0] * 30,
|
||||
"amount": [10_100.0] * 30,
|
||||
"ma5": [10.0] * 30,
|
||||
"ma10": [10.0] * 30,
|
||||
"ma20": [10.0] * 30,
|
||||
}
|
||||
)
|
||||
return frame.select(columns) if columns else frame
|
||||
|
||||
def get_minute(self, symbol, trade_date, asset_type="stock") -> pl.DataFrame:
|
||||
return self.minute
|
||||
|
||||
def get_minute_range(self, symbols, start, end, asset_type="stock") -> pl.DataFrame:
|
||||
return self.minute
|
||||
|
||||
|
||||
class _IndexRepo:
|
||||
def get_index_instruments(self) -> pl.DataFrame:
|
||||
return pl.DataFrame({"symbol": ["000001.SH"], "name": ["上证指数"]})
|
||||
|
||||
|
||||
def _client(repo, capset: CapabilitySet | None = None) -> TestClient:
|
||||
app = FastAPI()
|
||||
app.include_router(kline.router)
|
||||
app.include_router(indices.router)
|
||||
app.state.repo = repo
|
||||
app.state.capabilities = capset or CapabilitySet()
|
||||
app.state.quote_service = None
|
||||
return TestClient(app)
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
("path", "daily_compress", "minute_compress"),
|
||||
[
|
||||
(f"/api/kline/daily?symbol={_SYMBOL}&days=120", True, False),
|
||||
(f"/api/kline/minute?symbol={_SYMBOL}&date={_TRADE_DATE}", False, True),
|
||||
(f"/api/kline/minute-range?symbol={_SYMBOL}&days=10", False, True),
|
||||
],
|
||||
)
|
||||
def test_detail_kline_responses_use_configured_gzip(
|
||||
monkeypatch,
|
||||
path,
|
||||
daily_compress,
|
||||
minute_compress,
|
||||
):
|
||||
monkeypatch.setattr(
|
||||
"app.services.preferences.get_daily_batch_compress",
|
||||
lambda: daily_compress,
|
||||
)
|
||||
monkeypatch.setattr(
|
||||
"app.services.preferences.get_minute_batch_compress",
|
||||
lambda: minute_compress,
|
||||
)
|
||||
|
||||
response = _client(_DetailRepo()).get(
|
||||
path,
|
||||
headers={"Accept-Encoding": "gzip"},
|
||||
)
|
||||
|
||||
assert response.status_code == 200
|
||||
assert response.headers["content-encoding"] == "gzip"
|
||||
assert response.json()["symbol"] == _SYMBOL
|
||||
plain = _client(_DetailRepo()).get(path, headers={"Accept-Encoding": "identity"})
|
||||
assert "content-encoding" not in plain.headers
|
||||
assert response.json() == plain.json()
|
||||
assert int(response.headers["content-length"]) < len(plain.content)
|
||||
|
||||
monkeypatch.setattr("app.services.preferences.get_daily_batch_compress", lambda: False)
|
||||
monkeypatch.setattr("app.services.preferences.get_minute_batch_compress", lambda: False)
|
||||
disabled = _client(_DetailRepo()).get(path, headers={"Accept-Encoding": "gzip"})
|
||||
assert "content-encoding" not in disabled.headers
|
||||
assert disabled.json() == plain.json()
|
||||
|
||||
|
||||
@pytest.mark.parametrize("live", [False, True])
|
||||
def test_free_tier_skips_tickflow_minute_fallback(monkeypatch, live):
|
||||
get_client = MagicMock(side_effect=AssertionError("must not call TickFlow"))
|
||||
monkeypatch.setattr("app.services.preferences.get_minute_data_provider", lambda: "tickflow")
|
||||
monkeypatch.setattr("app.services.kline_sync.get_client", get_client)
|
||||
|
||||
response = _client(_DetailRepo(pl.DataFrame())).get(
|
||||
"/api/kline/minute",
|
||||
params={"symbol": _SYMBOL, "date": str(_TRADE_DATE), "live": live},
|
||||
)
|
||||
|
||||
assert response.status_code == 200
|
||||
assert response.json()["source"] == "none"
|
||||
get_client.assert_not_called()
|
||||
|
||||
|
||||
def test_custom_minute_source_remains_available_without_tickflow_capability(monkeypatch):
|
||||
provider = MagicMock()
|
||||
provider.get_minute.return_value = _minute_rows(1)
|
||||
monkeypatch.setattr("app.services.preferences.get_minute_data_provider", lambda: "custom")
|
||||
monkeypatch.setattr(
|
||||
"app.data_providers.custom.provider_has_dataset", lambda name, dataset: True
|
||||
)
|
||||
monkeypatch.setattr("app.data_providers.custom.get_provider", lambda name: provider)
|
||||
get_client = MagicMock(side_effect=AssertionError("must not call TickFlow"))
|
||||
monkeypatch.setattr("app.services.kline_sync.get_client", get_client)
|
||||
|
||||
response = _client(_DetailRepo(pl.DataFrame())).get(
|
||||
"/api/kline/minute",
|
||||
params={"symbol": _SYMBOL, "date": str(_TRADE_DATE)},
|
||||
)
|
||||
|
||||
assert response.status_code == 200
|
||||
assert response.json()["source"] == "live"
|
||||
provider.get_minute.assert_called_once()
|
||||
get_client.assert_not_called()
|
||||
|
||||
|
||||
def test_failed_custom_source_does_not_fall_back_to_unsupported_tickflow(monkeypatch):
|
||||
provider = MagicMock()
|
||||
provider.get_minute.side_effect = RuntimeError("custom source unavailable")
|
||||
monkeypatch.setattr("app.services.preferences.get_minute_data_provider", lambda: "custom")
|
||||
monkeypatch.setattr(
|
||||
"app.data_providers.custom.provider_has_dataset", lambda name, dataset: True
|
||||
)
|
||||
monkeypatch.setattr("app.data_providers.custom.get_provider", lambda name: provider)
|
||||
get_client = MagicMock(side_effect=AssertionError("must not call TickFlow"))
|
||||
monkeypatch.setattr("app.services.kline_sync.get_client", get_client)
|
||||
|
||||
capset = CapabilitySet({Cap.KLINE_MINUTE_BATCH: CapabilityLimits()})
|
||||
response = _client(_DetailRepo(pl.DataFrame()), capset).get(
|
||||
"/api/kline/minute",
|
||||
params={"symbol": _SYMBOL, "date": str(_TRADE_DATE)},
|
||||
)
|
||||
|
||||
assert response.status_code == 200
|
||||
assert response.json()["source"] == "none"
|
||||
get_client.assert_not_called()
|
||||
|
||||
|
||||
def test_pro_tier_keeps_tickflow_minute_fallback(monkeypatch):
|
||||
capset = CapabilitySet({Cap.KLINE_MINUTE_BY_SYMBOL: CapabilityLimits()})
|
||||
tickflow = MagicMock()
|
||||
tickflow.klines.batch.side_effect = RuntimeError("upstream unavailable")
|
||||
get_client = MagicMock(return_value=tickflow)
|
||||
monkeypatch.setattr("app.services.preferences.get_minute_data_provider", lambda: "tickflow")
|
||||
monkeypatch.setattr("app.services.kline_sync.get_client", get_client)
|
||||
|
||||
response = _client(_DetailRepo(pl.DataFrame()), capset).get(
|
||||
"/api/kline/minute",
|
||||
params={"symbol": _SYMBOL, "date": str(_TRADE_DATE)},
|
||||
)
|
||||
|
||||
assert response.status_code == 200
|
||||
assert response.json()["source"] == "none"
|
||||
get_client.assert_called_once()
|
||||
|
||||
|
||||
def test_free_tier_skips_tickflow_index_minute_fallback(monkeypatch):
|
||||
get_client = MagicMock(side_effect=AssertionError("must not call TickFlow"))
|
||||
monkeypatch.setattr("app.services.preferences.get_minute_data_provider", lambda: "tickflow")
|
||||
monkeypatch.setattr("app.services.kline_sync.get_client", get_client)
|
||||
|
||||
response = _client(_IndexRepo()).get(
|
||||
"/api/index/minute",
|
||||
params={"symbol": "000001.SH", "date": str(_TRADE_DATE)},
|
||||
)
|
||||
|
||||
assert response.status_code == 200
|
||||
assert response.json()["source"] == "none"
|
||||
get_client.assert_not_called()
|
||||
@@ -15,6 +15,7 @@ from fastapi.testclient import TestClient
|
||||
|
||||
from app.api.kline import router
|
||||
from app.market_time import CN_TZ, in_continuous_session
|
||||
from app.tickflow.capabilities import Cap, CapabilityLimits, CapabilitySet
|
||||
|
||||
# 2026-08-26 是周三; 10:00 处于上午连续竞价, expected(已交易分钟) = 30
|
||||
_NOW = datetime(2026, 8, 26, 10, 0, tzinfo=CN_TZ)
|
||||
@@ -48,6 +49,9 @@ def _client() -> TestClient:
|
||||
app = FastAPI()
|
||||
app.include_router(router)
|
||||
app.state.repo = _FakeRepo()
|
||||
app.state.capabilities = CapabilitySet({
|
||||
Cap.KLINE_MINUTE_BY_SYMBOL: CapabilityLimits(),
|
||||
})
|
||||
return TestClient(app)
|
||||
|
||||
|
||||
@@ -62,7 +66,7 @@ def _patch_market(monkeypatch, *, in_session: bool) -> None:
|
||||
def _patch_live_fetch(monkeypatch) -> None:
|
||||
import app.api.kline as kline_api
|
||||
|
||||
def _fake_fetch(symbol, trade_date, asset_type="stock"):
|
||||
def _fake_fetch(symbol, trade_date, asset_type="stock", *, capset):
|
||||
return pl.DataFrame({
|
||||
"datetime": [datetime(2026, 8, 26, 9, 59)],
|
||||
"close": [11.11],
|
||||
|
||||
@@ -9,6 +9,7 @@ from datetime import date, datetime
|
||||
|
||||
from app.market_time import CN_TZ
|
||||
from app.services import kline_sync
|
||||
from app.tickflow.capabilities import Cap, CapabilityLimits, CapabilitySet
|
||||
|
||||
|
||||
def test_fetch_minute_single_window_is_beijing_wall_clock(monkeypatch):
|
||||
@@ -30,7 +31,11 @@ def test_fetch_minute_single_window_is_beijing_wall_clock(monkeypatch):
|
||||
monkeypatch.setattr(kline_sync, "_try_custom_minute", _fake_try_custom_minute)
|
||||
monkeypatch.setattr(kline_sync, "get_client", lambda: _FakeClient())
|
||||
|
||||
kline_sync.fetch_minute_single("600000.SH", date(2026, 8, 14))
|
||||
kline_sync.fetch_minute_single(
|
||||
"600000.SH",
|
||||
date(2026, 8, 14),
|
||||
capset=CapabilitySet({Cap.KLINE_MINUTE_BY_SYMBOL: CapabilityLimits()}),
|
||||
)
|
||||
|
||||
start = datetime.fromtimestamp(captured["start_ms"] / 1000, tz=CN_TZ)
|
||||
end = datetime.fromtimestamp(captured["end_ms"] / 1000, tz=CN_TZ)
|
||||
|
||||
@@ -40,6 +40,18 @@ def _mock_minute_df(symbol: str = "600519.SH") -> pl.DataFrame:
|
||||
})
|
||||
|
||||
|
||||
def _empty_capset():
|
||||
from app.tickflow.capabilities import CapabilitySet
|
||||
|
||||
return CapabilitySet()
|
||||
|
||||
|
||||
def _tickflow_minute_capset():
|
||||
from app.tickflow.capabilities import Cap, CapabilityLimits, CapabilitySet
|
||||
|
||||
return CapabilitySet({Cap.KLINE_MINUTE_BY_SYMBOL: CapabilityLimits()})
|
||||
|
||||
|
||||
def _setup_custom_provider(monkeypatch, provider: object, has_dataset: bool = True) -> None:
|
||||
"""统一 mock 自定义分钟源路由前置: preferences + provider_has_dataset + get_provider。
|
||||
|
||||
@@ -131,6 +143,7 @@ def test_custom_provider_exception_no_500(monkeypatch):
|
||||
# fetch_minute_single: 自定义源异常 → fall through → TickFlow 异常 → 返回空
|
||||
df_single = kline_sync.fetch_minute_single(
|
||||
"600519.SH", date(2026, 1, 15), asset_type="stock",
|
||||
capset=_tickflow_minute_capset(),
|
||||
)
|
||||
assert isinstance(df_single, pl.DataFrame)
|
||||
assert df_single.is_empty()
|
||||
@@ -173,9 +186,15 @@ def test_asset_type_threaded_to_provider(monkeypatch):
|
||||
_setup_custom_provider(monkeypatch, mock_provider, has_dataset=True)
|
||||
|
||||
# 三次调用不同 asset_type
|
||||
kline_sync.fetch_minute_single("600519.SH", date(2026, 1, 15), asset_type="stock")
|
||||
kline_sync.fetch_minute_single("510300.SH", date(2026, 1, 15), asset_type="etf")
|
||||
kline_sync.fetch_minute_single("000001.SH", date(2026, 1, 15), asset_type="index")
|
||||
kline_sync.fetch_minute_single(
|
||||
"600519.SH", date(2026, 1, 15), asset_type="stock", capset=_empty_capset(),
|
||||
)
|
||||
kline_sync.fetch_minute_single(
|
||||
"510300.SH", date(2026, 1, 15), asset_type="etf", capset=_empty_capset(),
|
||||
)
|
||||
kline_sync.fetch_minute_single(
|
||||
"000001.SH", date(2026, 1, 15), asset_type="index", capset=_empty_capset(),
|
||||
)
|
||||
|
||||
# spy 被调 3 次, 每次收到对应 asset_type
|
||||
assert spy.call_count == 3
|
||||
@@ -197,7 +216,7 @@ def test_custom_success_skips_tickflow(monkeypatch):
|
||||
monkeypatch.setattr(kline_sync, "get_client", get_client_spy)
|
||||
|
||||
df = kline_sync.fetch_minute_single(
|
||||
"600519.SH", date(2026, 1, 15), asset_type="stock",
|
||||
"600519.SH", date(2026, 1, 15), asset_type="stock", capset=_empty_capset(),
|
||||
)
|
||||
|
||||
# 返回的是 mock provider 的 df
|
||||
|
||||
Reference in New Issue
Block a user