midterm

from collections import defaultdict, deque
from shioaji import BidAskFOPv1, Exchange
import shioaji as sj
import datetime
import pandas as pd
import talib as ta
import time
from math import ceil
import pysimulation


api = sj.Shioaji(simulation=True)
accounts = api.login(
    api_key="6YugfETBuBogK1jSTPXR7KQh6eeY8RawEK42QEYCZG8E",
    secret_key="CyAMsKj115UJNQuFPujqAxSQJjvGaj3ameZQWjr1CeYS",
)

order = pysimulation.order('')  # student id

contract = min(
    [
        x for x in api.Contracts.Futures.TXF
        if x.code[-2:] not in ["R1", "R2"]
    ],
    key=lambda x: x.delivery_date
)

msg_queue = defaultdict(deque)
api.set_context(msg_queue)


@api.on_bidask_fop_v1(bind=True)
def quote_callback(self, exchange: Exchange, bidask: BidAskFOPv1):
    # append quote to message queue
    self['bidask'].append(bidask)


api.quote.subscribe(
    contract,
    quote_type=sj.constant.QuoteType.BidAsk,
    version=sj.constant.QuoteVersion.v1
)

time.sleep(2.5)

# get maximum strategy kbars to dataframe, extra 30 it's for safety
bars = 65 + 30

# since every day has 60 kbars (only from 8:45 to 13:45), for 5 minuts kbars
days = ceil(bars/60)

df_5min = []
while(len(df_5min) < bars):
    kbars = api.kbars(
        contract=api.Contracts.Futures.TXF.TXFR1,
        start=(datetime.date.today() -
               datetime.timedelta(days=days)).strftime("%Y-%m-%d"),
        end=datetime.date.today().strftime("%Y-%m-%d"),
    )
    df = pd.DataFrame({**kbars})
    df.ts = pd.to_datetime(df.ts)
    df = df.set_index('ts')
    df.index.name = None
    df = df[['Open', 'High', 'Low', 'Close', 'Volume']]
    df = df.between_time('08:44:00', '13:45:01')
    df_5min = df.resample('5T', label='right', closed='right').agg(
        {'Open': 'first',
            'High': 'max',
            'Low': 'min',
            'Close': 'last',
            'Volume': 'sum'
         })
    df_5min.dropna(axis=0, inplace=True)
    days += 1

ts = datetime.datetime.now()
support, resistence = None, None

while datetime.datetime.now().time() < datetime.time(13, 40):

    # this place can add stop or limit order
    self_list_positions = order.list_positions(msg_queue['bidask'][-1])
    self_position = 'None' if len(self_list_positions) == 0 else self_list_positions['direction']

    # local time > next kbars time
    if(datetime.datetime.now() >= ts):

        kbars = api.kbars(
            contract=api.Contracts.Futures.TXF.TXFR1,
            start=datetime.date.today().strftime("%Y-%m-%d"),
            end=datetime.date.today().strftime("%Y-%m-%d"),
        )
        df = pd.DataFrame({**kbars})
        df.ts = pd.to_datetime(df.ts)
        df = df.set_index('ts')
        df.index.name = None
        df = df[['Open', 'High', 'Low', 'Close', 'Volume']]
        df = df.between_time('08:44:00', '13:45:01')
        df = df.resample('5T', label='right', closed='right').agg({
            'Open': 'first',
            'High': 'max',
            'Low': 'min',
            'Close': 'last',
            'Volume': 'sum'})
        df.dropna(axis=0, inplace=True)
        df_5min.update(df)
        to_be_added = df.loc[df.index.difference(df_5min.index)]
        df_5min = pd.concat([df_5min, to_be_added])
        ts = df_5min.iloc[-1].name.to_pydatetime()

        # next kbar time update and local time < next kbar time
        if (datetime.datetime.now().minute != ts.minute):
            # Exit conditions
            if self_position == 'Buy':
                minimal = min([df_5min["Low":-i] for i in range(2, 5)])
                if df_5min['Close':-1] < minimal:
                    order.place_order(msg_queue['bidask'][-1], 'Sell', 'Close')

            if self_position == 'Sell':
                maximal = max([df_5min["High":-i] for i in range(2, 5)])
                if df_5min['Close':-1] > maximal:
                    order.place_order(msg_queue['bidask'][-1], 'Buy', 'Close')

            # Make df_5min the latest kbar
            df_5min = df_5min.iloc[-1]
            kbar = {
                    'Open': df_5min['Open'],
                    'High': df_5min['High'],
                    'Low': df_5min['Low'],
                    'Close': df_5min['Close']
            }
            print(kbar)

            # Caculate the support and resistence
            if datetime.datetime.now().time() < datetime.time(9, 30):
                support = df_5min['Low'] if support is None else min(df_5min['Low'], support)
                resistence = df_5min['High'] if resistence is None else max(df_5min['High'], resistence)

            # Entry conditions
            if datetime.time(9, 30) <= datetime.datetime.now().time() <= datetime.time(12, 00) and self_position == 'None':
                # Breakout then stop order in
                if resistence is not None and df_5min['Close'] > resistence:
                    order.place_order(msg_queue['bidask'][-1], 'Buy', 'New')
                    support, resistence = None, None

                if support is not None and df_5min['Close'] < support:
                    order.place_order(msg_queue['bidask'][-1], 'Sell', 'New')
                    support, resistence = None, None


api.quote.unsubscribe(
    contract,
    quote_type=sj.constant.QuoteType.BidAsk,
    version=sj.constant.QuoteVersion.v1
)

api.logout()