Historical Market Data

Ticks¶

Ticks can get all day, period of time or last counts of the day. The default is get ticks of last trade day .

Ticks

api.ticks?

Signature:
    api.ticks(
        contract: shioaji.contracts.BaseContract,
        date: str = '2022-12-26',
        query_type: shioaji.constant.TicksQueryType = <TicksQueryType.AllDay: 'AllDay'>,
        time_start: Union[str, datetime.time] = None,
        time_end: Union[str, datetime.time] = None,
        last_cnt: int = 0,
        timeout: int = 30000,
        cb: Callable[[shioaji.data.Ticks], NoneType] = None,
    ) -> shioaji.data.Ticks
Docstring:
    get contract tick volumn

By Date¶

In

ticks = api.ticks(
    contract=api.Contracts.Stocks["2330"], 
    date="2023-01-16"
)
ticks

Out

Ticks(
    ts=[1673859600113699000, 1673859600228800000, 1673859600244294000, 1673859600308595000], 
    close=[506.0, 505.0, 506.0, 506.0],
    volume=[3340, 1, 17, 2],
    bid_price=[505.0, 505.0, 506.0, 506.0],
    bid_volume=[122, 320, 60, 58],
    ask_price=[506.0, 506.0, 507.0, 507.0],
    ask_volume=[13, 22, 702, 702]
    tick_type=[1, 2, 1, 2]
)

Ticks

ts (int): timestamp
close (float): close
volume (int): volume
bid_price (float): bid price
bid_volume (int): bid volume
ask_price (float): ask price
ask_volume (int): ask volume
tick_type (int): 內外盤別{1: 外盤, 2: 內盤, 0: 無法判定}

To DataFrame

In

import pandas as pd
df = pd.DataFrame({**ticks})
df.ts = pd.to_datetime(df.ts)
df.head()

Out

ts	ask_price	close	bid_volume	volume	ask_volume	tick_type	bid_price
2023-01-16 09:00:00.113699	506	506	122	3340	13	1	505
2023-01-16 09:00:00.228800	506	505	320	1	22	2	505
2023-01-16 09:00:00.244294	507	506	60	17	702	1	506
2023-01-16 09:00:00.308595	507	506	58	2	702	2	506

Range Time¶

In

ticks = api.ticks(
    contract=api.Contracts.Stocks["2330"], 
    date="2023-01-16",
    query_type=sj.constant.TicksQueryType.RangeTime,
    time_start="09:00:00",
    time_end="09:20:01"
)
ticks

Out

Ticks(
    ts=[1673859600113699000, 1673859600228800000, 1673859600244294000, 1673859600308595000], 
    close=[506.0, 505.0, 506.0, 506.0],
    volume=[3340, 1, 17, 2],
    bid_price=[505.0, 505.0, 506.0, 506.0],
    bid_volume=[122, 320, 60, 58],
    ask_price=[506.0, 506.0, 507.0, 507.0],
    ask_volume=[13, 22, 702, 702]
    tick_type=[1, 2, 1, 2]
)

Last Count¶

In

ticks = api.ticks(
    contract=api.Contracts.Stocks["2330"], 
    date="2023-01-16",
    query_type=sj.constant.TicksQueryType.LastCount,
    last_cnt=4,
)
ticks

Out

Ticks(
    ts=[1673859600113699000, 1673859600228800000, 1673859600244294000, 1673859600308595000], 
    close=[506.0, 505.0, 506.0, 506.0],
    volume=[3340, 1, 17, 2],
    bid_price=[505.0, 505.0, 506.0, 506.0],
    bid_volume=[122, 320, 60, 58],
    ask_price=[506.0, 506.0, 507.0, 507.0],
    ask_volume=[13, 22, 702, 702]
    tick_type=[1, 2, 1, 2]
)

KBar¶

Kbars

api.kbars?

Signature:
api.kbars(
    contract: shioaji.contracts.BaseContract,
    start: str = '2023-01-15',
    end: str = '2023-01-16',
    timeout: int = 30000,
    cb: Callable[[shioaji.data.Kbars], NoneType] = None,
) -> shioaji.data.Kbars
Docstring:
get Kbar

In

kbars = api.kbars(
    contract=api.Contracts.Stocks["2330"], 
    start="2023-01-15", 
    end="2023-01-16", 
)
kbars

Out

Kbars(
    ts=[1673859660000000000, 1673859720000000000, 1673859780000000000, 1673859840000000000],
    Open=[506.0, 505.0, 505.0, 504.0],
    High=[508.0, 506.0, 506.0, 505.0],
    Low=[505.0, 505.0, 504.0, 504.0],
    Close=[505.0, 505.0, 504.0, 504.0],
    Volume=[5308, 1018, 543, 209]
)

Kbars

ts (int): timestamp
Open (float): open price
High (float): the highest price
Low: (float): the lowest price
Close (float): close price
Volume (int): volume

To DataFrame

In

import pandas as pd
df = pd.DataFrame({**kbars})
df.ts = pd.to_datetime(df.ts)
df.head()

Out

Close	Amount	Low	Volume	ts	Open	High
505	2.68731e+09	505	5308	2023-01-16 09:01:00	506	508
505	5.14132e+08	505	1018	2023-01-16 09:02:00	505	506
504	2.74112e+08	504	543	2023-01-16 09:03:00	505	506
504	1.0542e+08	504	209	2023-01-16 09:04:00	504	505

Historical Periods¶

Historical Periods

	Start Date	End Date
Index	2020-03-02	Today
Stock	2020-03-02	Today
Futures	2020-03-22	Today

Continuous Futures¶

Once a futures contract passes its expiration date, the contract is invalid, and it will not exist in your api.Contracts. In order to get historical data for expired futures contract, we provide continuous futures contracts. R1, R2 are continuous near-month and next-to-near-month futures contracts respectively. They will automatically roll contracts on delivery date. You can get historical data by using R1, R2 contracts, ex api.Contracts.Futures.TXF.TXFR1. We show examples below.

Ticks

ticks = api.ticks(
    contract=api.Contracts.Futures.TXF.TXFR1, 
    date="2020-03-22"
)
ticks

Out

Ticks(
    ts=[1616166000030000000, 1616166000140000000, 1616166000140000000, 1616166000190000000], 
    close=[16011.0, 16013.0, 16014.0, 16011.0],
    volume=[49, 2, 2, 1],
    bid_price=[0.0, 16011.0, 16011.0, 16011.0],
    bid_volume=[0, 1, 1, 1],
    ask_price=[0.0, 16013.0, 16013.0, 16013.0],
    ask_volume=[0, 1, 1, 1]
    tick_type=[1, 1, 1, 2]
)

Kbars

kbars = api.kbars(
    contract=api.Contracts.Futures.TXF.TXFR1,
    start="2023-01-15", 
    end="2023-01-16", 
)
kbars

Out

Kbars(
    ts=[1616402760000000000, 1616402820000000000, 1616402880000000000, 1616402940000000000],
    Open=[16018.0, 16018.0, 16000.0, 15992.0],
    High=[16022.0, 16020.0, 16005.0, 15999.0],
    Low=[16004.0, 16000.0, 15975.0, 15989.0],
    Close=[16019.0, 16002.0, 15992.0, 15994.0],
    Volume=[1791, 864, 1183, 342]
)