排行
包含漲跌幅、漲跌、高低價差、成交量及成交金額排行。Scanners利用scanner_type去取得不同類型的排行。
Scanners
api.scanners?
Signature:
api.scanners(
scanner_type: shioaji.constant.ScannerType,
date: str = None,
ascending: bool = True,
count: int = 100,
timeout: int = 30000,
cb: Callable[[List[shioaji.data.ScannerItem]], NoneType] = None,
) -> List[shioaji.data.ScannerItem]
Parameters
scanner_type: 排行類型，見下方支援列表
date: 交易日（YYYY-MM-DD），預設今天
ascending: 排序方向（True=由大到小、False=由小到大），預設 True
count: 排行數量（0 ≤ count ≤ 200），預設 100
timeout: 逾時毫秒
cb: 選填，callback 函式，timeout=0 時使用
Scanners
$ shioaji data scanner --help
Get scanner ranking data
Usage: shioaji data scanner [OPTIONS]
Options:
--scanner-type <SCANNER_TYPE> Scanner type [change-percent-rank, change-price-rank, day-range-rank, volume-rank, amount-rank, tick-count-rank] [default: change-percent-rank]
--date <DATE> Trading date (YYYY-MM-DD, default: today) [default: 2026-05-18]
--ascending Sort ascending
--count <COUNT> Number of results (default: 50) [default: 50]
Parameters
--scanner-type: 排行類型，預設 change-percent-rank
--date: 交易日（YYYY-MM-DD），預設今天
--ascending: 選填 flag，加上即由大到小排序（不加為由小到大）
--count: 排行數量，預設 50
Scanners
POST /api/v1/data/scanner
Content-Type: application/json
{
"scanner_type": <ScannerType>,
"date": <string>,
"ascending": <bool>,
"count": <int>
}
Parameters
scanner_type: 排行類型 {'ChangePercentRank', 'ChangePriceRank', 'DayRangeRank', 'VolumeRank', 'AmountRank', 'TickCountRank'}
date: 交易日（YYYY-MM-DD）
ascending: 排序方向（true=由大到小、false=由小到大）
count: 排行數量，預設 200
支援的排行類別
ChangePercentRank: 依價格漲跌幅排序
ChangePriceRank: 依價格漲跌排序
DayRangeRank: 依高低價差排序
VolumeRank: 依成交量排序
AmountRank: 依成交金額排序
TickCountRank: 依成交筆數排序
屬性¶
ScannerItem
date (str): 交易日
code (str): 股票代號
name (str): 股票名稱
ts / datetime: 時間（Python 為 Unix 時間戳，其他語言為 ISO 字串）
open (float): 開盤價
high (float): 最高價
low (float): 最低價
close (float): 收盤價
price_range (float): 價格區間（最高價 - 最低價）
tick_type (int): 內外盤別 {1: 內盤, 2: 外盤, 0: 無法判定}
change_price (float): 價格漲跌
change_type (int): 漲跌 {LimitUp, Up, Unchanged, Down, LimitDown}
average_price (float): 均價
volume (int): 成交量
total_volume (int): 總成交量
amount (int): 成交額
total_amount (int): 總成交額
yesterday_volume (int): 昨日總成交量
volume_ratio (float): 總成交量 / 昨日總成交量
buy_price (float): 委買價
buy_volume (int): 委買量
sell_price (float): 委賣價
sell_volume (int): 委賣量
bid_orders (int): 內盤總成交單量
bid_volumes (int): 內盤總成交量
ask_orders (int): 外盤總成交單量
ask_volumes (int): 外盤總成交量
rank_value (float): 排序值（依 scanner_type 而定）
範例¶
In
scanners = api.scanners(
scanner_type=sj.ScannerType.ChangePercentRank,
count=1
)
scanners
Out
[ScannerItem(
date='2026-05-18',
code='2233',
name='宇隆',
ts=1779114600000000000,
open=291,
high=324.5,
low=290,
close=324.5,
price_range=34.5,
tick_type=1,
change_price=29.5,
change_type=1,
average_price=311.65,
volume=2,
total_volume=1570,
amount=649000,
total_amount=489327500,
yesterday_volume=762,
volume_ratio=2.06,
buy_price=324.5,
buy_volume=40,
sell_price=0,
sell_volume=0,
bid_orders=41,
bid_volumes=1162,
ask_orders=15,
ask_volumes=408,
rank_value=10
)]
轉成 DataFrame（以 polars 示範）
In
scanners = api.scanners(
scanner_type=sj.ScannerType.ChangePercentRank,
count=5
)
import polars as pl
df = pl.DataFrame(s.dict() for s in scanners).with_columns(
pl.col("ts").cast(pl.Datetime("ns"))
)
df
Out
| date | code | name | ts | open | high | low | close | price_range | tick_type | change_price | change_type | average_price | volume | total_volume | amount | total_amount | yesterday_volume | volume_ratio | buy_price | buy_volume | sell_price | sell_volume | bid_orders | bid_volumes | ask_orders | ask_volumes | rank_value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 2026-05-18 | 2233 | 宇隆 | 2026-05-18 14:30:00 | 291.0 | 324.5 | 290.0 | 324.5 | 34.5 | 1 | 29.5 | 1 | 311.65 | 2 | 1570 | 649000 | 489327500 | 762.0 | 2.06 | 324.5 | 40 | 0.0 | 0 | 41 | 1162 | 15 | 408 | 10.0 |
| 2026-05-18 | 3663 | 鑫科 | 2026-05-18 14:30:00 | 68.2 | 75.9 | 66.7 | 75.9 | 9.2 | 1 | 6.9 | 1 | 73.26 | 1 | 5501 | 75900 | 403048100 | 3614.0 | 1.52 | 75.9 | 519 | 0.0 | 0 | 1126 | 4287 | 680 | 1214 | 10.0 |
| 2026-05-18 | 6285 | 啟碁 | 2026-05-18 14:30:00 | 254.0 | 286.0 | 254.0 | 286.0 | 32.0 | 1 | 26.0 | 1 | 277.48 | 34 | 38135 | 9724000 | 10582011500 | 20370.0 | 1.87 | 286.0 | 5212 | 0.0 | 0 | 6589 | 28976 | 2876 | 9159 | 10.0 |
| 2026-05-18 | 6719 | 力智 | 2026-05-18 14:30:00 | 198.0 | 220.0 | 197.0 | 220.0 | 23.0 | 1 | 20.0 | 1 | 214.6 | 99 | 3621 | 21780000 | 777081500 | 1392.0 | 2.6 | 219.5 | 5 | 220.0 | 80 | 930 | 2567 | 547 | 1054 | 10.0 |
| 2026-05-18 | 8064 | 東捷 | 2026-05-18 14:30:00 | 118.0 | 132.0 | 117.5 | 132.0 | 14.5 | 1 | 12.0 | 1 | 127.16 | 29 | 5154 | 3828000 | 655530500 | 6111.0 | 0.84 | 131.5 | 60 | 132.0 | 618 | 33 | 3471 | 22 | 1683 | 10.0 |
In
shioaji data scanner --scanner-type change-percent-rank --count 1 --ascending
Out
[1]{date,code,name,datetime,open,high,low,close,price_range,tick_type,change_price,change_type,average_price,volume,total_volume,amount,total_amount,yesterday_volume,volume_ratio,buy_price,buy_volume,sell_price,sell_volume,bid_orders,bid_volumes,ask_orders,ask_volumes,rank_value}:
"2026-05-18","2233","宇隆 ",2026-05-18T14:30:00,291,324.5,290,324.5,34.5,1,29.5,1,311.65,2,1570,649000,489327500,762,2.06,324.5,40,0,0,41,1162,15,408,10
In
curl -X POST http://localhost:8080/api/v1/data/scanner \
-H 'Content-Type: application/json' \
-d '{
"scanner_type": "ChangePercentRank",
"date": "2026-05-18",
"ascending": true,
"count": 1
}'
Out
[{"date":"2026-05-18","code":"2233","name":"宇隆 ","datetime":"2026-05-18T14:30:00","open":291.0,"high":324.5,"low":290.0,"close":324.5,"price_range":34.5,"tick_type":1,"change_price":29.5,"change_type":1,"average_price":311.65,"volume":2,"total_volume":1570,"amount":649000,"total_amount":489327500,"yesterday_volume":762,"volume_ratio":2.06,"buy_price":324.5,"buy_volume":40,"sell_price":0.0,"sell_volume":0,"bid_orders":41,"bid_volumes":1162,"ask_orders":15,"ask_volumes":408,"rank_value":10.0}]