Scanners

Scanners can use parameter of scannertype to get the rank of ChangePercent, ChangePrice, DayRange, Volume and Amount.

Scanners

>> api.scanners?

Signature:
api.scanners(
    scanner_type: shioaji.constant.ScannerType, 
    ascending: bool = True,
    date: str = None,
    count: shioaji.shioaji.ConstrainedIntValue = 100, # 0 <= count <= 200
    timeout: int = 30000,
    cb: Callable[[List[shioaji.data.ChangePercentRank]], NoneType] = None,
) -> List[shioaji.data.ChangePercentRank]

Ascending is sorted from largest to smallest by default, and the value of ascending is True. Set ascending to False to sort in descending order, and the other ranking methods are the same. count is how many ranks you get.

Supported Scanner Type

ChangePercentRank: rank by price percentage change
ChangePriceRank: rank by price change
DayRangeRank: rank by day range
VolumeRank: rank by volume
AmountRank: rank by amount

Example

ChangePercentRank

scanners = api.scanners(
    scanner_type=sj.constant.ScannerType.ChangePercentRank,
    count=1
)
scanners

Out

[
    ChangePercentRank(
        date='2021-04-09', 
        code='5211', 
        name='蒙恬', 
        ts=1617978600000000000, 
        open=16.4, 
        high=17.6, 
        low=16.35, 
        close=17.6, 
        price_range=1.25, 
        tick_type=1, 
        change_price=1.6, 
        change_type=1, 
        average_price=17.45, 
        volume=7, 
        total_volume=1742, 
        amount=123200, 
        total_amount=30397496, 
        yesterday_volume=514, 
        volume_ratio=3.39, 
        buy_price=17.6, 
        buy_volume=723, 
        sell_price=0.0, 
        sell_volume=0, 
        bid_orders=237, 
        bid_volumes=82, 
        ask_orders=33, 
        ask_volumes=64
    )
]

To DataFrame

In

scanners = api.scanners(
    scanner_type=sj.constant.ScannerType.ChangePercentRank, 
    count=5
)
df = pd.DataFrame(s.__dict__ for s in scanners)
df.ts = pd.to_datetime(df.ts)
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
2023-01-17	6259	百徽	2023-01-17 11:11:41.030000	22.8	23.75	22.45	23.75	1.3	1	2.15	1	23.58	4	137	95000	3230900	26	5.27	0	8	0	0	65	211	5	11
2023-01-17	6788	華景電	2023-01-17 11:19:01.924000	107	116	107	116	9	1	10.5	1	113.61	1	4292	116000	487606000	682	6.29	0	1053	0	0	1044	3786	501	1579
2023-01-17	2540	愛山林	2023-01-17 11:17:39.435000	85.2	85.2	83	85.2	2.2	1	7.7	1	85.04	1	1226	85200	104253800	702	1.75	0	142	0	0	362	5779	121	1831
2023-01-17	8478	東哥遊艇	2023-01-17 11:18:33.702000	350.5	378	347	378	31	1	34	1	363.39	1	12115	378000	4402427500	8639	1.4	0	3307	0	0	3754	235724	1906	29843
2023-01-17	6612	奈米醫材	2023-01-17 11:15:32.752000	102	109	102	109	7	1	9.7	1	106.95	1	1329	109000	142134500	1022	1.3	0	298	0	0	467	22718	162	1016

Attributes

ChangePercentRank

date (str): date 
code (str): code
name (str): name
ts (int): timestamp
open (float): open price
high (float): high price
low (float): low price
close (float): close price
price_range (float): range of price
tick_type (int): 內外盤別{1: 外盤, 2: 內盤, 0: 無法判定}
change_price (float): change in price
change_type (int): 
    {LimitUp, Up, Unchanged, Dowm, LimitDown}
average_price (float): average price
volume (int): volume
total_volume (int): total volume since market open
amount (int): amount
total_amount (int): total amount since market open
yesterday_volume (int): yesterday volume
volume_ratio (float): total_volume/yestoday_volume
buy_price (float): bid
buy_volume (int): bid volume
sell_price (float): ask
sell_volume (int): ask volume
bid_orders (int): number of orders that deal at bid
bid_volumes (int): total volume that deal at bid
ask_orders (int): number of orders that deal at ask
ask_volumes (int): total volume that deal at ask