WHAT IT ANSWERS
这张表适合回答什么
- 查看同日最新可执行判断
- 跟踪 paper position 生命周期
- 检查置信闸门与板块约束
DATASET · research
Daybreak 当日可执行 Calls
research.daybreak_calls_served
实时展示 judge 产生的可执行 Call 及纸面持仓状态、进出场、净超额收益、置信闸门和当时上下文。
字段39
关键字段3
更新口径producer_schedule
时间列
trade_date单页上限5000
分页窄筛选
PIT不支持
规模view
GRAIN & TIME
一行代表什么
- 业务粒度
- 每行代表“Daybreak 当日可执行 Calls”的一条记录；逻辑粒度由 trade_date × instrument_id × direction 共同确定。
- 时间口径
- 以 trade_date 为主要查询时间轴；除下方限制特别说明外，时间戳按 UTC、日期按来源市场日历解释。
- 更新节奏
- 由对应生产任务或事件触发更新，不承诺固定日历频率；查询前先检查最新时间。
KEY FIELDS
先看这些字段
trade_date- 对应市场日历中的交易日。
instrument_id- WarrenHub 统一证券标识；跨证券数据集优先用它联接。
direction- 用于确定该表业务粒度或默认顺序的 direction 字段。
RECOMMENDED JOINS
怎样和其他表关联
ref.instrumenton instrument_id用 instrument_id 补充证券代码、名称、市场、交易所和资产类型。
ref.calendaron market + trade_date（有 market 时）需要计算交易日偏移时联接交易日历；无 market 字段时先确定适用市场。
HOW TO QUERY SAFELY
查询方法与已知限制
先用 catalog 确认当前契约；可按 catalog 中列出的 filters 进一步缩小范围；单页最多 5000 行，该表不提供稳定 cursor，结果过大时必须缩小标的、日期或其他筛选。
- 返回范围仍受 Friends 权限、单页上限和 catalog 中的筛选契约约束。
MACHINE CONTRACT
筛选、排序与分页
- 默认排序
trade_date, instrument_id, direction- 唯一键
—- 读取模式
relation_default- 最大时间窗
- 未单独限制
可用 filters
call_id→ call_id · stringcap_bucket→ cap_bucket · stringcode→ code · stringconviction_suppressed→ conviction_suppressed · integerdata_stale→ data_stale · integerdirection→ direction · stringgate_passed→ gate_passed · integerinstrument_id→ instrument_id · integerposition_status→ position_status · stringprompt_ver→ prompt_ver · stringPOINT IN TIME
可复现读取
该资产没有 PIT 契约。普通 rows 端点仍按当前公开读模式返回数据；不要把它表述成历史时点快照。
COPY-READY CALLS
怎么调用
同一数据集可用 HTTP、Python SDK、CLI 或 MCP；Key 始终只通过环境变量/Bearer Header 传递。
HTTP
curl --fail-with-body -H "Authorization: Bearer $FRIENDS_DATA_API_KEY" "https://api.alphahubs.uk/api/v1/data/datasets/research/daybreak_calls_served/rows?limit=100&code=AAPL&start=2026-08-01&end=2026-08-01"PYTHON SDK
from friends_data_api import FriendsDataClient, Settings
async with FriendsDataClient(Settings.from_env()) as client:
page = await client.get_dataset_rows('research', 'daybreak_calls_served', limit=100, start='2026-08-01', end='2026-08-01', filters={'code': 'AAPL'})
print(page.data)
if page.has_more:
print("next cursor:", page.next_cursor)CLI
friends-data get-dataset-rows research daybreak_calls_served --limit 100 --start 2026-08-01 --end 2026-08-01 --filter code=AAPLMCP TOOL CALL
{
"arguments": {
"dataset": "daybreak_calls_served",
"end": "2026-08-01",
"filters": {
"code": "AAPL"
},
"limit": 100,
"namespace": "research",
"start": "2026-08-01"
},
"tool": "get_dataset_rows"
}FIELD DICTIONARY
39 个返回字段
descriptionSource 可在 JSON 中区分仓库注释、标准术语表和名称推导说明。
| # | 字段 | ClickHouse 类型 | JSON | 可空 | 角色 | 说明 |
|---|---|---|---|---|---|---|
| 1 | call_id | String | string | no | filter | Identifier for call.名称推导 |
| 2 | instrument_id | UInt64 | integer | no | filter, default_order | WarrenHub canonical instrument identifier; use it for cross-dataset joins.标准术语表 |
| 3 | code | LowCardinality(String) | string | no | filter | Source-normalized security or contract code.标准术语表 |
| 4 | trade_datedate | Date | string / date | no | time, default_order | Trading-session date in the dataset's market calendar.标准术语表 |
| 5 | direction | LowCardinality(String) | string | no | filter, default_order | Source-normalized field: direction.名称推导 |
| 6 | confidence | Float64 | number | no | value | Source-normalized field: confidence.名称推导 |
| 7 | target_price | Float64 | number | no | value | Price value for target price.名称推导 |
| 8 | stop_price | Float64 | number | no | value | Price value for stop price.名称推导 |
| 9 | horizon_days | UInt16 | integer | no | value | Source-normalized field: horizon days.名称推导 |
| 10 | vehicle | LowCardinality(String) | string | no | value | Source-normalized field: vehicle.名称推导 |
| 11 | date_window_start | Date | string / date | no | value | Source-normalized field: date window start.名称推导 |
| 12 | date_window_end | Date | string / date | no | value | Source-normalized field: date window end.名称推导 |
| 13 | invalidation_condition | String | string | no | value | Source-normalized field: invalidation condition.名称推导 |
| 14 | evidence_json | String | string | no | value | Source-normalized field: evidence json.名称推导 |
| 15 | prompt_ver | LowCardinality(String) | string | no | filter | Source-normalized field: prompt ver.名称推导 |
| 16 | computed_atUTC_datetime | DateTime64(3, 'UTC') | string / date-time | no | value | UTC timestamp for computed at.名称推导 |
| 17 | served_basis | String | string | no | value | Source-normalized field: served basis.名称推导 |
| 18 | gate_passed | UInt8 | integer | no | filter | Source-normalized field: gate passed.名称推导 |
| 19 | conviction_suppressed | UInt8 | integer | no | filter | Source-normalized field: conviction suppressed.名称推导 |
| 20 | data_stale | UInt8 | integer | no | filter | Source-normalized field: data stale.名称推导 |
| 21 | stale_hours | Nullable(Float64) | number | yes | value | Source-normalized field: stale hours.名称推导 |
| 22 | claude_verdict | LowCardinality(String) | string | no | value | Source-normalized field: claude verdict.名称推导 |
| 23 | claude_article | String | string | no | value | Source-normalized field: claude article.名称推导 |
| 24 | cap_bucket | LowCardinality(String) | string | no | filter | Source-normalized field: cap bucket.名称推导 |
| 25 | sector | LowCardinality(String) | string | no | value | Source-normalized field: sector.名称推导 |
| 26 | industry | LowCardinality(String) | string | no | value | Source-normalized field: industry.名称推导 |
| 27 | intensity_score | Float64 | number | no | value | Source-normalized field: intensity score.名称推导 |
| 28 | conviction_concentration | Float64 | number | no | value | Source-normalized field: conviction concentration.名称推导 |
| 29 | conviction_long_v2 | Nullable(Float64) | number | yes | value | Source-normalized field: conviction long v2.名称推导 |
| 30 | conviction_short_v2 | Nullable(Float64) | number | yes | value | Source-normalized field: conviction short v2.名称推导 |
| 31 | n_slots_long_v2 | UInt16 | integer | no | value | Count of slots long v2.名称推导 |
| 32 | n_slots_short_v2 | UInt16 | integer | no | value | Count of slots short v2.名称推导 |
| 33 | conviction_direction_v2 | LowCardinality(String) | string | no | value | Source-normalized field: conviction direction v2.名称推导 |
| 34 | entry_datedate | Date | string / date | no | value | Calendar date for entry date (YYYY-MM-DD).名称推导 |
| 35 | entry_px | Float64 | number | no | value | Source-normalized field: entry px.名称推导 |
| 36 | exit_px | Nullable(Float64) | number | yes | value | Source-normalized field: exit px.名称推导 |
| 37 | net_excess_return | Nullable(Float64) | number | yes | value | Source-normalized field: net excess return.名称推导 |
| 38 | position_status | LowCardinality(String) | string | no | filter | Source-normalized field: position status.名称推导 |
| 39 | book_run_id | String | string | no | value | Identifier for book run.名称推导 |
没有匹配字段
换一个字段名、类型或角色。
结构来自 Friends 只读身份可见的真实 serving relation；权限、过滤、排序、PIT 与分页来自可执行 DatasetSpec。Schema observed at 2026-10-06T18:08:52Z。