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dosangyoon
2021-10-14 23:29:20 +09:00
parent 972d014ca7
commit b5232af02f
3 changed files with 503 additions and 504 deletions
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hts/HTS.py
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@@ -1,14 +1,11 @@
#import win32com.client
import win32com.client
import time
import os
from datetime import datetime, timedelta
import pandas as pd
from enum import Enum
import plotly.graph_objects as go
from stockpredictor.analysis.Common import Common
from stockpredictor.analysis.Stochastic import Stochastic
from stockpredictor.analysis.RSI import RSI
from BS import BS
# enum 주문 상태 세팅용
class EorderBS(Enum):
@@ -33,16 +30,11 @@ class HTS:
objCpCybos = None
objCpCodeMgr = None
common = None
stochastic = None
rsi = None
bs = None
def __init__(self):
self.common = Common()
self.stochastic = Stochastic()
self.rsi = RSI()
self.bs = BS()
#self.connect()
return
@@ -530,492 +522,54 @@ class HTS:
return
def getCSV(self, fileName, given_day, result):
data = pd.read_csv(fileName)
days = data.날짜
time = data.시간
open = data.시가
close = data.종가
high = data.고가
low = data.저가
vol = data.거래량
start_time = datetime.strptime(given_day + " 090000", '%Y%m%d %H%M%S')
for i in range(len(data)):
temp = datetime.strptime(str(days[i]) + " " + str(time[i]).zfill(4)+"00", '%Y%m%d %H%M%S')
if temp < start_time:
continue
if temp not in result["check"]:
result["check"].add(temp)
result["time"].append(temp)
result["open"].append(open[i])
result["close"].append(close[i])
result["high"].append(high[i])
result["low"].append(low[i])
result["vol"].append(vol[i])
return
def analyze(self, result):
df = pd.DataFrame(result["close"])
max20 = df.rolling(window=10).mean()
stddev20 = df.rolling(window=10).std()
upper_df = max20 + (stddev20 * 2) # 상단 볼린저 밴드
lower_df = max20 - (stddev20 * 2) # 하단 볼린저 밴드
window = 5
open = result["open"]
close = result["close"]
high = result["high"]
low = result["low"]
vol = result["vol"]
close_df = pd.DataFrame(close)
avg1_list = close_df.rolling(window=1).mean().fillna(close[0]).values.tolist()
avg1 = [item[0] for item in avg1_list]
avg2_list = close_df.rolling(window=2).mean().fillna(close[0]).values.tolist()
avg2 = [item[0] for item in avg2_list]
avg5_list = close_df.rolling(window=5).mean().fillna(close[0]).values.tolist()
avg5 = [item[0] for item in avg5_list]
avg10_list = close_df.rolling(window=10).mean().fillna(close[0]).values.tolist()
avg10 = [item[0] for item in avg10_list]
avg20_list = close_df.rolling(window=20).mean().fillna(close[0]).values.tolist()
avg20 = [item[0] for item in avg20_list]
avg30_list = close_df.rolling(window=30).mean().fillna(close[0]).values.tolist()
avg30 = [item[0] for item in avg30_list]
avg40_list = close_df.rolling(window=40).mean().fillna(close[0]).values.tolist()
avg40 = [item[0] for item in avg40_list]
avg50_list = close_df.rolling(window=50).mean().fillna(close[0]).values.tolist()
avg50 = [item[0] for item in avg50_list]
avg60_list = close_df.rolling(window=60).mean().fillna(close[0]).values.tolist()
avg60 = [item[0] for item in avg60_list]
upper, lower = [], []
for i in range(len(upper_df)):
if i < window:
upper.append(upper_df.values[window - 1][0])
lower.append(lower_df.values[window - 1][0])
else:
upper.append(upper_df.values[i][0])
lower.append(lower_df.values[i][0])
point_temp = result["time"]
STOCK = []
for i in range(len(result["open"])):
STOCK.append({'volume': vol[i], 'close': close[i], 'open': open[i],
'high': high[i], 'low': low[i], 'avg5': avg2[i],
'avg20': avg5[i], 'avg60': avg10[i], 'avg120': avg20[i],
'avg240': avg30[i]})
# stochastic 계산
stochastic_df = self.stochastic.apply(pd.DataFrame(STOCK))
stochastic_df = stochastic_df.fillna(0)
fast_k = stochastic_df['fast_k'].values.tolist()
slow_k = stochastic_df['slow_k'].values.tolist()
slow_d = stochastic_df['slow_d'].values.tolist()
# rsi 계산
rsi_df = self.rsi.apply(pd.DataFrame(STOCK))
rsi_df = rsi_df.fillna(0)
rsi = rsi_df['rsi'].values.tolist()
rsis = rsi_df['rsis'].values.tolist()
temp = {"Date": point_temp,
"Open": open, "High": high, "Low": low, "Close": close, "Volume": vol,
"avg1": avg1, "avg2": avg2, "avg5": avg5, "avg10": avg10, "avg20": avg20, "avg30": avg30, "avg40": avg40, "avg50": avg50, "avg60": avg60,
"fast_k": fast_k, "slow_k": slow_k, "slow_d": slow_d,
"rsi": rsi, "rsis": rsis}
data = pd.DataFrame(temp)
df_final_time = pd.DatetimeIndex(point_temp)
data.index = df_final_time
return data, upper, lower
def draw(self, stock_code, given_day, data, upper, lower, bsLine):
buy_line = bsLine['buy']
sell_line = bsLine['sell']
# 그래프 설정을 위한 변수를 생성한다.
data['Open'] = pd.to_numeric(data['Open'])
data['High'] = pd.to_numeric(data['High'])
data['Low'] = pd.to_numeric(data['Low'])
data['Close'] = pd.to_numeric(data['Close'])
data['Volume'] = pd.to_numeric(data['Volume'])
data['avg1'] = pd.to_numeric(data['avg1'])
data['avg2'] = pd.to_numeric(data['avg2'])
data['avg5'] = pd.to_numeric(data['avg5'])
data['avg10'] = pd.to_numeric(data['avg10'])
data['avg20'] = pd.to_numeric(data['avg20'])
data['avg30'] = pd.to_numeric(data['avg30'])
data['avg40'] = pd.to_numeric(data['avg40'])
data['avg50'] = pd.to_numeric(data['avg50'])
data['avg60'] = pd.to_numeric(data['avg60'])
buy_colors = []
for i in range(len(buy_line)):
if buy_line[i] < 0:
buy_colors.append("#ffffff")
buy_line[i] = lower[0]
else:
buy_colors.append("#ff00ff")
sell_colors = []
for i in range(len(sell_line)):
if sell_line[i] < 0:
sell_colors.append("#ffffff")
sell_line[i] = lower[0]
else:
sell_colors.append("#00ced1")
# 그래프를 설정한다.
buy_check = go.Scatter(x=data['Date'], y=buy_line, mode='markers', name="buy", marker=dict(size=14, color=buy_colors, line_width=0))
sell_check = go.Scatter(x=data['Date'], y=sell_line, mode='markers', name="sell", marker=dict(size=14, color=sell_colors, line_width=0))
bolinger_upper = go.Scatter(x=data['Date'], y=upper, name="upper", line_color='#8B4513')
bolinger_lower = go.Scatter(x=data['Date'], y=lower, name="lower", line_color='#8B4513')
avg1 = go.Scatter(x=data['Date'], y=data['avg1'], name="avg1", line_color='#FF0000')
avg2 = go.Scatter(x=data['Date'], y=data['avg2'], name="avg2", line_color='#A200FF')
avg5 = go.Scatter(x=data['Date'], y=data['avg5'], name="avg5", line_color='#0800FF')
avg10 = go.Scatter(x=data['Date'], y=data['avg10'], name="avg10", line_color='#FF7C00')
avg20 = go.Scatter(x=data['Date'], y=data['avg20'], name="avg20", line_color='#00AAFF')
avg30 = go.Scatter(x=data['Date'], y=data['avg30'], name="avg30", line_color='#FFD100')
avg40 = go.Scatter(x=data['Date'], y=data['avg40'], name="avg40", line_color='#A600FF')
avg50 = go.Scatter(x=data['Date'], y=data['avg50'], name="avg50", line_color='#FF00E0')
avg60 = go.Scatter(x=data['Date'], y=data['avg60'], name="avg60", line_color='#000000')
candle_stick = go.Candlestick(x=data['Date'], open=data['Open'], high=data['High'], low=data['Low'], close=data['Close'], increasing_line_color='red', decreasing_line_color='blue')
# 그래프를 그린다.
fig = go.Figure(data=[candle_stick, bolinger_upper, bolinger_lower, buy_check, sell_check, avg1, avg2, avg5, avg10, avg20, avg30, avg40, avg50, avg60])
fig.update_layout(title=stock_code + "_" + given_day)
fig.show()
return
def checkStatus(self, STOCK, last_index):
status = set()
# 정배열 체크
temp_status = self.common.check_RightArrange(STOCK, last_index)
if temp_status != "":
status.add(temp_status)
# 돌파 체크
temp_status = self.common.check_Dolpa(STOCK, last_index, "5", "20")
if temp_status != "":
status.add(temp_status)
temp_status = self.common.check_Dolpa(STOCK, last_index, "5", "60")
if temp_status != "":
status.add(temp_status)
temp_status = self.common.check_Dolpa(STOCK, last_index, "5", "120")
if temp_status != "":
status.add(temp_status)
temp_status = self.common.check_Dolpa(STOCK, last_index, "5", "240")
if temp_status != "":
status.add(temp_status)
temp_status = self.common.check_Dolpa(STOCK, last_index, "20", "60")
if temp_status != "":
status.add(temp_status)
temp_status = self.common.check_Dolpa(STOCK, last_index, "20", "120")
if temp_status != "":
status.add(temp_status)
temp_status = self.common.check_Dolpa(STOCK, last_index, "20", "240")
if temp_status != "":
status.add(temp_status)
temp_status = self.common.check_Dolpa(STOCK, last_index, "60", "120")
if temp_status != "":
status.add(temp_status)
temp_status = self.common.check_Dolpa(STOCK, last_index, "60", "240")
if temp_status != "":
status.add(temp_status)
temp_status = self.common.check_Dolpa(STOCK, last_index, "120", "240")
if temp_status != "":
status.add(temp_status)
# 20일선 돌파
temp_status = self.common.check_Dolpa_Jiji(STOCK, last_index, '20')
if temp_status != "":
status.add(temp_status)
# 60일선 돌파
temp_status = self.common.check_Dolpa_Jiji(STOCK, last_index, '60')
if temp_status != "":
status.add(temp_status)
# 120일선 돌파
temp_status = self.common.check_Dolpa_Jiji(STOCK, last_index, '120')
if temp_status != "":
status.add(temp_status)
# 240일선 돌파
#temp_status = self.common.check_Dolpa_Jiji(STOCK, last_index, '240')
#if temp_status != "":
# status.add(temp_status)
# 20일선 지지 매수가 추천
temp_status = self.common.check_Dolpa_Jiji_20(STOCK, last_index)
if temp_status != "":
status.add(temp_status)
# 음봉인데 어제보다 종가가 더 높은 경우
# 이 경우 정배열 상태인지도 함께 체크를 한다.
higher_umbong_status = self.common.checkHigherUmbong(STOCK, last_index)
if higher_umbong_status != "":
status.add(temp_status)
# GOLDENCROSS#1은 바로 매수하지 않고, 이 시점 이후로 5일선이 20일선을 하방으로 뚫었다가 다시 20일선을 상방으로 뚫는 순간 매수를 시도한다.
# GOLDENCROSS#2은 바로 매수 가능
# GOLDENCROSS#3은 바로 매수 가능
temp_status = self.common.check_golded_cross(STOCK, last_index)
if temp_status != "":
status.add(temp_status)
# YANGBONG
# 어제 음봉 이후 장대양봉이었다면, 매수
temp_status = self.common.checkLongYangBongAfterUmBong(STOCK, last_index)
if temp_status != "":
status.add(temp_status)
# Doji
# 하락 추세에서 도지가 나오면 매수
temp_status = self.common.checkDoji(STOCK, last_index)
if temp_status != "":
status.add(temp_status)
# Gravestone
# 상승 추세에서 그레이브스톤이 나오면 매도
temp_status = self.common.checkGravestone(STOCK, last_index)
if temp_status != "":
status.add(temp_status)
# Dragonfly
# 하락 추세에서 드레곤플라이가 나오면 매수
temp_status = self.common.checkDragonfly(STOCK, last_index)
if temp_status != "":
status.add(temp_status)
# Hammer
temp_status = self.common.checkHammer(STOCK, last_index)
# 하락 추세에서 해머가 나오면 매수
if temp_status != "":
status.add(temp_status)
# Hangingman
temp_status = self.common.checkHangingman(STOCK, last_index)
# 상승 추세에서 행잉맨이 나오면 매도
if temp_status != "":
status.add(temp_status)
# 상승장악형 (Engulfing) - 다음 날도 양봉이라면 매수
# 하락 추세에서 상승장악형이 나오면 매수
temp_status = self.common.checkEngulfingHigh(STOCK, last_index)
if temp_status != "":
status.add(temp_status)
# 하락장악형 (Engulfing)
# 상승 추세에서 하락장악형이 나오면 매도
temp_status = self.common.checkEngulfingLow(STOCK, last_index)
if temp_status != "":
status.add(temp_status)
# 상승 포아형 (Harami)
# 하락 추세에서 상승포아형이 나오면 매수
temp_status = self.common.checkHaramiHigh(STOCK, last_index)
if temp_status != "":
status.add(temp_status)
# 하락 포아형 (Harami)
# 상승 추세에서 하락포아형이 나오면 매도
temp_status = self.common.checkHaramiLow(STOCK, last_index)
if temp_status != "":
status.add(temp_status)
# 관통형 (piercing)
# 하락 추세에서 관통형이 나오면 매수
temp_status = self.common.checkPiercing(STOCK, last_index)
if temp_status != "":
status.add(temp_status)
# 흑운형 (Dark-cloud)
# 상승 추세에서 흑운형이 나오면 매도
temp_status = self.common.checkDarkCloud(STOCK, last_index)
if temp_status != "":
status.add(temp_status)
# 샛별 (Morning start)
# 하락 추세에서 샛별형이 나오면 매수
temp_status = self.common.checkMorningstar(STOCK, last_index)
if temp_status != "":
status.add(temp_status)
# 저녁별 (Evening start)
# 상승 추세에서 저녁별형이 나오면 매도
temp_status = self.common.checkEveningstar(STOCK, last_index)
if temp_status != "":
status.add(temp_status)
return status
def checkTransaction_Realtime(self, data, upper, lower):
def checkTransaction(self, data):
size = len(data["Close"])
STOCK = []
for i in range(size):
STOCK.append({'volume': data['Volume'][i], 'close': data["Close"][i], 'open': data["Open"][i], 'high': data["High"][i], 'low': data["Low"][i], 'avg2': data["avg2"][i], 'avg5': data["avg5"][i], 'avg10': data["avg10"][i], 'avg20': data["avg20"][i], 'avg30': data["avg30"], 'avg40': data["avg40"], 'avg50': data["avg50"], 'avg60': data["avg60"][i]})
bsLine = {}
bsLine['buy'] = [-1 for i in range(size)]
bsLine['weight'] = [-1 for i in range(size)]
bsLine['sell'] = [-1 for i in range(size)]
i = size - 1
"""
status = self.checkStatus(STOCK, i)
count_1 = 0
# if "GOLDEN#2_" in status: count_1 += 1
# if "arrange_" in status: count_1 += 1
# if "UMYANG_" in status: count_1 += 1
# if "5-20_" in status: count_1 += 1
if "5_20_" in status: count_1 += 1
if "5_60_" in status: count_1 += 1
if "5_120_" in status: count_1 += 1
if "5_240_" in status: count_1 += 1
if "20_60_" in status: count_1 += 1
if "20_120_" in status: count_1 += 1
if "20_240_" in status: count_1 += 1
if "60_120_" in status: count_1 += 1
if "60_240_" in status: count_1 += 1
if "120_240_" in status: count_1 += 1
if "arrange_" in status and "HIGHERUMBONG_" in status: count_1 += 1
if "20_" in status: count_1 += 1
if "60_" in status: count_1 += 1
if "120_" in status: count_1 += 1
if "240_" in status: count_1 += 1
if "GOLDEN#3_" in status: count_1 += 1
if "DOJI_" in status: count_1 += 1
if "DRAGONEFLY_" in status: count_1 += 1
if "HAMMER_" in status: count_1 += 1
if "ENHIGH_" in status: count_1 += 1
if "HAHIGH_" in status: count_1 += 1
if "PIERCING_" in status: count_1 += 1
if "MORNINGSTAR_" in status: count_1 += 1
count_0 = 0
if "GRAVESTONE_" in status: count_0 += 1
if "HANGINGMAN_" in status: count_0 += 1
if "ENLOW_" in status: count_0 += 1
if "HALOW_" in status: count_0 += 1
if "DARKCLOUD_" in status: count_0 += 1
if "EVENINGSTAR" in status: count_0 += 1
if i > 20:
if data["High"][i] > data["upper"][i]:
bsLine['sell'][i] = data["High"][i]
# real time 에서는 현재 기점에 사고 파는 가격을 표기한다.
if count_0 == 0 and count_1 > 0:
bsLine['buy'][i] = STOCK[i]['close'] - 5
bsLine['sell'][i] = STOCK[i]['close']
if count_0 > 0:
bsLine['buy'][i] = 0
bsLine['sell'][i] = STOCK[i]['close'] + 5
"""
if data["slow_k"][i] <= 36:
if data["Low"][i] < data["lower"][i]:
bsLine['buy'][i] = data["Close"][i] - 5
if data["slow_k"][i] <= 25:
if data["slow_k"][i - 1] < data["slow_d"][i - 1] and data["slow_d"][i] < data["slow_k"][i]:
bsLine['buy'][i] = data["Close"][i] - 5
if STOCK[i]['low'] < lower[i]:
bsLine['buy'][i] = STOCK[i]['close'] - 5
if STOCK[i]['close'] > upper[i]:
bsLine['sell'][i] = STOCK[i]['close'] + 5
return bsLine['buy'][i], bsLine['sell'][i]
# rsi가 rsis 위로 올라오며 15 이하일 경우 10배로 주문함 (14:30 이전)
if data["rsi"][i] < 15 and data["rsis"][i] < 15 and data["rsi"][i - 1] < data["rsis"][i - 1] and data["rsis"][i] < data["rsi"][i]:
bsLine['buy'][i] = data["Close"][i] - 5
bsLine['weight'][i] = 10
if data["slow_k"][i] == 1:
bsLine['weight'][i] = 8
elif data["slow_k"][i] in(2,3):
bsLine['weight'][i] = 7
elif data["slow_k"][i] in(4,5,6):
bsLine['weight'][i] = 6
elif data["slow_k"][i] in(7,8,9,10):
bsLine['weight'][i] = 5
elif data["slow_k"][i] in(11,12,13,14,15):
bsLine['weight'][i] = 4
elif data["slow_k"][i] in(16,17,18,19,20,21):
bsLine['weight'][i] = 3
elif data["slow_k"][i] in(22,23,24,25,26,27,28):
bsLine['weight'][i] = 2
elif data["slow_k"][i] in(29,30,31,32,33,34,35,36):
bsLine['weight'][i] = 1
if data["rsi"][i] < 10:
bsLine['weight'][i] = 8
if i<=20:
bsLine['weight'][i] = 1
def checkTransaction_Simulation(self, data, upper, lower):
size = len(data["Close"])
STOCK = []
for i in range(size):
STOCK.append({'volume': data['Volume'][i], 'close': data["Close"][i], 'open': data["Open"][i], 'high': data["High"][i], 'low': data["Low"][i], 'avg5': data["avg2"][i], 'avg20': data["avg5"][i], 'avg60': data["avg10"][i], 'avg120': data["avg20"][i], 'avg240': data["avg30"][i]})
return bsLine['buy'][i], bsLine['weight'][i], bsLine['sell'][i]
bsLine = {}
bsLine['buy'] = [-1 for i in range(len(lower))]
bsLine['sell'] = [-1 for i in range(len(lower))]
for i in range(5, size-5):
"""
status = self.checkStatus(STOCK, i)
count_1 = 0
#if "GOLDEN#2_" in status: count_1 += 1
#if "arrange_" in status: count_1 += 1
#if "UMYANG_" in status: count_1 += 1
#if "5-20_" in status: count_1 += 1
if "5_20_" in status: count_1 += 1
if "5_60_" in status: count_1 += 1
if "5_120_" in status: count_1 += 1
if "5_240_" in status: count_1 += 1
if "20_60_" in status: count_1 += 1
if "20_120_" in status: count_1 += 1
if "20_240_" in status: count_1 += 1
if "60_120_" in status: count_1 += 1
if "60_240_" in status: count_1 += 1
if "120_240_" in status: count_1 += 1
if "arrange_" in status and "HIGHERUMBONG_" in status: count_1 += 1
if "20_" in status: count_1 += 1
if "60_" in status: count_1 += 1
if "120_" in status: count_1 += 1
if "240_" in status: count_1 += 1
if "GOLDEN#3_" in status: count_1 += 1
if "DOJI_" in status: count_1 += 1
if "DRAGONEFLY_" in status: count_1 += 1
if "HAMMER_" in status: count_1 += 1
if "ENHIGH_" in status: count_1 += 1
if "HAHIGH_" in status: count_1 += 1
if "PIERCING_" in status: count_1 += 1
if "MORNINGSTAR_" in status: count_1 += 1
count_0 = 0
if "GRAVESTONE_" in status: count_0 += 1
if "HANGINGMAN_" in status: count_0 += 1
if "ENLOW_" in status: count_0 += 1
if "HALOW_" in status: count_0 += 1
if "DARKCLOUD_" in status: count_0 += 1
if "EVENINGSTAR" in status: count_0 += 1
# 시뮬레이션은 이번에 사고 파는 것으로 판단했기 때문에, 다음 봉에서 사고 판 위치를 표시한다.
if count_0 == 0 and count_1 > 0:
bsLine['buy'][i + 1] = STOCK[i]['close'] - 5
#bsLine['sell'][i + 2] = STOCK[i]['close']
#if count_0 > 0:
# bsLine['sell'][i + 2] = STOCK[i]['close'] + 5
if data["avg60"][i - 1] > data["avg60"][i]:
bsLine['sell'][i] = STOCK[i]['close']
"""
if STOCK[i]['low'] < lower[i]:
bsLine['buy'][i] = STOCK[i]['close'] - 5
if STOCK[i]['close'] > upper[i]:
bsLine['sell'][i] = STOCK[i]['close'] + 5
return bsLine
def simulate(self, stock_code, given_day):
#timecheckList = pd.read_csv("timecheck.csv").values.tolist()
#timecheck = {datetime.strptime(given_day + " " + str(second).zfill(6), '%Y%m%d %H%M%S'): False for second, check in timecheckList}
result = {"check": set(),
"time": [],
"open": [],
"close": [],
"high": [],
"low": [],
"vol": []}
# 데이터를 가지고 온다.
self.getCSV("./data/"+stock_code+"_"+given_day+".csv", given_day, result)
# 분석을 통해서 볼린저밴드 상/하단을 계산한다.
data, upper, lower = self.analyze(result)
# 사야 할 시점과 팔아야 할 시점을 체크한다.
bsLine = self.checkTransaction_Simulation(data, upper, lower)
# 그래프를 그린다.
self.draw(stock_code, given_day, data, upper, lower, bsLine)
# 가져온 만큼 데이터를 누적해서 파일로 작성한다.
# self.write(given_day, result)
return
def getSellingPrice(self, final_price):
# 만약 잔고가 있으면 장부가보다 5원 높게 매도한다.
@@ -1071,9 +625,9 @@ class HTS:
self.getRealTime(stock_code, given_day, result)
# 분석을 통해서 볼린저밴드 상/하단을 계산한다.
data, upper, lower = self.analyze(result)
data = self.bs.analyze(result)
# 사야 할 시점/가격과 팔아야 할 시점/가격을 체크한다.
bs_buy_price, bs_sell_price = self.checkTransaction_Realtime(data, upper, lower)
bs_buy_price, bs_weight, bs_sell_price = self.checkTransaction(data)
final_price = data["Close"][len(data["Close"])-1]
if bs_buy_price > 0:
@@ -1131,23 +685,10 @@ if __name__ == "__main__":
PROJECT_HOME = os.path.join(os.path.dirname(os.path.join(os.path.dirname(__file__))))
RESOURCE_DIR = PROJECT_HOME + "/resources/analysis/"+today.strftime("%Y%m%d")
stock_codes = ["252670", "122630"]
given_days = ['20210901','20210902','20210903','20210906','20210907','20210908','20210909','20210910','20210913','20210914','20210915','20210916','20210917','20210923','20210924','20210927','20210928','20210929','20210930','20211001', '20211005']
given_days = ['20210901']
hts = HTS()
#hts.all_stocks()
#hts.getChartData(stock_codes)
#hts.currentStock(stock_codes)
#for given_day in given_days:
#hts.writeStockData(stock_codes, given_day)
#for stock_code in stock_codes:
#hts.simulate(stock_code, given_day)
#given_day = datetime.today().strftime('%Y%m%d')
stock_codes = ["252670", "122630"]
given_day = datetime.today().strftime('%Y%m%d')
#hts.writeStockData(stock_codes, given_day)
hts.simulate(stock_codes[0], given_days[0])
#hts.buyRealTime(stock_codes[0], given_day)
hts.buyRealTime(stock_codes[0], given_day)
print ("done...")