# coding:gbk

import time





class G():

    pass





g = G()





def init(ContextInfo):

    g.hsa = [item for item in ContextInfo.get_stock_list_in_sector('沪深A股') if not item.endswith('BJ')]

    g.vol_dict = {}

    for stock in g.hsa:

        g.vol_dict[stock] = ContextInfo.get_last_volume(stock)

    ContextInfo.run_time("execution", "1nSecond", "2019-10-14 13:20:00")





def execution(ContextInfo):

    t0 = time.time()

    full_tick = ContextInfo.get_full_tick(g.hsa)

    total_market_value = 0

    total_ratio = 0

    count = 0

    for stock in g.hsa:

        if full_tick[stock]['lastClose'] == 0:

            continue

        ratio = full_tick[stock]['lastPrice'] / full_tick[stock]['lastClose'] - 1

        rise_price = round(full_tick[stock]['lastClose'] * 1.2, 2) if stock[0] == '3' or stock[:3] == '688' else round(

            full_tick[stock]['lastClose'] * 1.1, 2)

        # 如果要打印涨停品种

        if abs(full_tick[stock]['lastPrice'] - rise_price) <0.01:

            print(f"涨停股票 {stock} {ContextInfo.get_stock_name(stock)}")



        market_value = full_tick[stock]['lastPrice'] * g.vol_dict[stock]

        total_ratio += ratio * market_value

        total_market_value += market_value

        count += 1

    # print(count)

    total_ratio /= total_market_value

    total_ratio *= 100

    print(f'A股加权涨幅 {round(total_ratio, 2)}% 函数运行耗时{round(time.time() - t0, 5)}秒')

#-*-coding:gbk-*-

import datetime

code = '838402.BJ'

def init(ContextInfo):

    now = datetime.datetime.now()

    print(now)



def handlebar(ContextInfo):

    index = ContextInfo.barpos

    realtime = ContextInfo.get_bar_timetag(index)

    date = timetag_to_datetime(realtime, "%Y-%m-%d %H:%M:%S")

    info = ContextInfo.get_full_tick(stock_code=["838402.BJ"])

    print(info)

#-*-coding:gbk-*-

import datetime



code = '838402.BJ'

def init(ContextInfo):

    now = datetime.datetime.now()

    print(now)

    download_history_data(code,"1d","20240105","")



def handlebar(ContextInfo):

    index = ContextInfo.barpos

    realtime = ContextInfo.get_bar_timetag(index)

    date = timetag_to_datetime(realtime, "%Y-%m-%d %H:%M:%S")

    print(date)

    hist = ContextInfo.get_market_data_ex(['close'],[code], period = "1d",count = 1)

    print(hist)

import datetime 

import time



RUN_TIME = '09:24'



def execution(context):



    while 1:

        current_second = datetime.datetime.now().strftime('%S')

        if current_second >= '58':

            break

        time.sleep(0.1)



    do_something()



def initialize(context):

    # 初始化策略

    run_daily(context, execution, RUN_TIME)



def handle_data(context, data):

    pass

class a():

	pass

A = a()

class A():

	pass

a = A()

class GlobalCls():

    pass

    

g = GlobalCls()

文件编码声明： #coding:gbk 是指定源文件的编码格式为GBK。在Python 3中，通常使用UTF-8作为文件编码格式，因此可以将该行删除或更改为#coding:utf-8。



类名和函数名： 根据PEP 8命名约定，类名应该使用大写字母开头的驼峰命名法（例如A改为A）。同样，函数名应该使用小写字母开头的小写命名法（例如init改为init，f改为f）。



类和实例： 在代码中定义了一个空类a，但没有给它任何属性或方法。如果不需要这个类，可以将其删除。



缩进和代码格式： Python非常依赖于正确的缩进，以指示代码块的层次结构。请确保代码的缩进是一致的，并使用适当的缩进级别（通常是4个空格）。



代码注释： 代码中有一些注释，但是大部分是被注释掉的。良好的注释可以增加代码的可读性和可维护性，建议在关键部分添加更多有用的注释。



异常处理： 代码中没有包含任何异常处理机制。在实际应用中，建议对可能引发异常的操作进行适当的异常处理，以提高代码的健壮性。

		rise_price = round(full_tick[stock]['lastClose'] *1.2,2) if stock[0] == '3' or stock[:3] == '688' else round(full_tick[stock]['lastClose'] *1.1,2)

#-*-coding:gbk-*-

import time

start = False

ACCOUNT = ''



def init(ContextInfo):

    now = time.ctime()

    print(now)

    ContextInfo.run_time("execution","30nSecond","2023-04-14 13:20:00")





def execution(ContextInfo):

    data = ContextInfo.get_stock_list_in_sector('沪深A股')

    print(len(data))



def handlebar(ContextInfo):

    pass

【2023-10-25 15:18:45.533】  start trading mode

【2023-10-25 15:18:45.533】  Wed Oct 25 15:18:45 2023



【2023-10-25 15:18:45.533】  5074

['000001.SZ', '000002.SZ', '000004.SZ', '000005.SZ', '000006.SZ', '000007.SZ', '000008.SZ', '000009.SZ', '000010.SZ', '000011.SZ', '000012.SZ', '000014.SZ', '000016.SZ', '000017.SZ', '000019.SZ', '000020.SZ', '000021.SZ', '000023.SZ', '000025.SZ', '000026.SZ', '000027.SZ', '000028.SZ', '000029.SZ', '000030.SZ', '000031.SZ', '000032.SZ', '000034.SZ', '000035.SZ', '000036.SZ', '000037.SZ', '000039.SZ', '000040.SZ', '000042.SZ', '000045.SZ', '000046.SZ', '000048.SZ', '000049.SZ', '000050.SZ', '000055.SZ', '000056.SZ', '000058.SZ', '000059.SZ', '000060.SZ', '000061.SZ', '000062.SZ', '000063.SZ', '000065.SZ', '000066.SZ', '000068.SZ', '000069.SZ', '000070.SZ', '000078.SZ', '000088.SZ', '000089.SZ', '000090.SZ', '000096.SZ', '000099.SZ', '000100.SZ', '000151.SZ', '000153.SZ', '000155.SZ', '000156.SZ', '000157.SZ', '000158.SZ', '000159.SZ', '000166.SZ', '000301.SZ', '000333.SZ', '000338.SZ', '000400.SZ', '000401.SZ', '000402.SZ', '000403.SZ', '000404.SZ', '000407.SZ', '000408.SZ', '000409.SZ', '000410.SZ', '000411.SZ', '000413.SZ', '000415.SZ', '000416.SZ', '000417.SZ', '000419.SZ', '000420.SZ', '000421.SZ', '000422.SZ', '000423.SZ', '000425.SZ', '000426.SZ',

 2023-10-18 09:25:12 - ERROR - 全局对象g持久化对象保存失败，对象名：TARGET_STOCK_CODE，错误原因：Traceback (most recent call last):
  File "./fly_docker/IQEngine/utils/global_variable.py", line 50, in save
_pickle.PicklingError: Can't pickle <class 'IQEngine.user_module.PositionManager'>: attribute lookup PositionManager on IQEngine.user_module failed

up_px:涨停价格(str:float)；

down_px:跌停价格(str:float)；

使用场景

该函数仅在交易模块可用。



接口说明

该接口用于标识当日股票的涨跌停情况。



注意事项：



无



参数

security：单只股票代码或者多只股票代码组成的列表，必填字段(list[str]/str)；



返回

正常返回一个dict类型数据，包含每只股票代码的涨停状态。多只股票代码查询时其中部分股票代码查询异常则该代码返回既不涨停也不跌停状态0。(dict[str:int])



涨跌停状态说明：



2：触板涨停（已经是涨停价格，但还有卖盘）；

1：涨停；

0：既不涨停也不跌停；

-1：跌停；

-2：触板跌停（已经是跌停价格，但还有买盘）；

def initialize(context):

    g.security = '600570.SS'

    set_universe(g.security)



def handle_data(context, data):

    # 代码涨跌停状态

    stock_flag = check_limit(g.security)

    log.info(stock_flag)

    def modify_code(self, x):

        return x + '.SZ' if x.startswith('12') else x + '.SS'

 

仿真账户： ***** / ******  量化回测：支持1分钟、日线回测。 量化交易：支持LEVEL1 tick股票交易。 量化研究：提供云Ipython Notebook研究环境、行情数据2005年至今、可使用全市场金融数据。

from __future__ import print_function, absolute_import

from gm.api import *

set_token(juejin_token)

im_data = get_history_symbol(symbol='CFFEX.IM2212', start_date='2022-12-12', end_date='2022-12-16', df=True)

import pandas as pd

import datetime





def get_tick(code, start_time, end_time, period='tick'):

    from xtquant import xtdata



    xtdata.download_history_data(code, period=period, start_time=start_time, end_time=end_time)

    data = xtdata.get_local_data(field_list=, stock_code=

, period=period, count=10)

    result_list = data

    df = pd.DataFrame(result_list)



    df['time_str'] = df['time'].apply(lambda x: datetime.datetime.fromtimestamp(x / 1000.0))

    return df





def process_timestamp(df, filename):

    df = df.set_index('time_str')

    result = df.resample('3S').first().ffill()

    result = result[(result.index >= '2022-07-20 09:30') & (result.index <= '2022-07-20 15:00')]

    result = result.reset_index()

    result.to_csv(filename + '.csv')





def dump_single_code_tick():

    # 导出单个转债的tick数据

    code='128022'

    start_date = '20210113'

    end_date = '20210130'



    post_fix = 'SZ' if code.startswith('12') else 'SH'

    code = '{}.{}'.format(code,post_fix)

    filename = '{}'.format(code)

    df = get_tick(code, start_date, end_date)



dump_single_code_tick()

from xtquant import xtdata

data = xtdata.get_market_data(field_list=['time', 'open', 'close', 'high', 'low', 'volume', 'amount'], stock_list=['603000.SH'], period='1d', start_time='20230101')

print(data)

def func(context):

    pos_dict = get_positions()

    for code,pos in pos_dict.items():

        enable_amount = pos.enable_amount

        if enable_amount>0:

            order_target(code, 0)



# 标准

def initialize(context):

    # 初始化策略

    run_daily(context, func, time='9:25')



def handle_data(context, data):

    pass

def func(context):

    pos_dict = get_positions()

    for code,pos in pos_dict.items():

        enable_amount = pos.enable_amount

        if enable_amount>0 and code.startswith(('12','11')): # 只清除转债

            order_target(code, 0)

code_list = ['113578.SS','123014.SZ'] # 股票池，这里可以填几千个股票也没问题的

zz_df_price = get_price(code_list, start_date=None, end_date=None, frequency='1d', fields='close', fq=None, count=1)

yesterday_price_dict = zz_df_price.iloc[0].to_json()

zz_df_price.iloc[0].to_json()

index      113578.SS	123014.SZ

2023-07-14	93.036	 118.36

'{"113578.SS":93.036,"123014.SZ":118.36}'

import datetime



def initialize(context):

    # 初始化策略

    g.already_run = False



def handle_data(context, data):

    pass



def get_available_cash(context):

    # 读取变量protfolio里的可用资金的值

    return context.portfolio.cash



def current_time():

    return datetime.datetime.now().strftime('%H:%M:%S.%f')



def tick_data(context, data):

    log.info('可用资金{}'.format(get_available_cash(context)))

    if not g.already_run:

        g.already_run = True

        # 卖出100手 R-001

        ret = order_tick('131810.SZ', -10, priceGear='1', limit_price=None)



def on_order_response(context, trade_list):

    # 委托回调函数，有委托出现就调用此函数

    log.info('已委托下单 {}'.format(current_time()))

# encoding:gbk

import datetime





ACCOUNT = '你的账户ID'

start = True



def init(ContextInfo):

    ContextInfo.set_account(ACCOUNT)



def current_time():

    return datetime.datetime.now().strftime('%H:%M:%S.%f')





def get_available_cash(ContextInfo):

    acct_info = get_trade_detail_data(ACCOUNT, 'stock', 'account')

    return acct_info[0].m_dAvailable





def deal_callback(ContextInfo, dealInfo):

    print('before')

    print(dealInfo.m_strProductID)

    print(dealInfo.m_nDirection)

    print(dealInfo.m_dTradeAmount)

    print(dealInfo.m_nVolume)

    print(dealInfo.m_dPrice)

    print('call back --- ')

    print(current_time())



def buy_action(ContextInfo):

    opType = 24

    orderType = 1101

    accountID = ACCOUNT

    orderCode = '131810.SZ'

    prType = 11

    price = 1.8

    volume = 10

    quickTrade = 2

    passorder(opType, orderType, accountID, orderCode, prType, price, volume, quickTrade, ContextInfo)



def handlebar(ContextInfo):

    global start

    if ContextInfo.is_last_bar():



        cash = get_available_cash(ContextInfo)

        print('{} 可用资金{}'.format(current_time(),cash))

        if start:

            print('下单逆回购 131810 ')

            buy_action(ContextInfo)

            start = False

# 交易回调

def on_trade_response(context, trade_list):

    # 成交主推

    now = context.blotter.current_dt.strftime("%H:%M:%S")



    for trade_info in trade_list:

        if trade_info['order_id'] == '':

            # 不是本策略跳过

            log.info('非本策略订单')

            continue



        code = trade_info['stock_code']

        code = post_fix_convert(code)

        business_time = trade_info['business_time']

        business_amount = trade_info['business_amount']  # 这个是负数，如果卖出

        business_price = trade_info['business_price']

        g.total_cash -= business_amount # 马上更新资金状态