def todayStock(table='tb_today_stock'):
configger.init()
engine = configger.engine
if (timeUtil.tableNeedUpdate(table) == False):
return pd.read_sql(con=engine, sql='select * from {}'.format(table))
nowtime = datetime.datetime.now()
endDate = nowtime.strftime('%Y%m%d')
createTimeSql = " SELECT CREATE_TIME from information_schema.`TABLES` WHERE `information_schema`.`TABLES`.`TABLE_SCHEMA` = '{}' and `information_schema`.`TABLES`.`TABLE_NAME` = '{}' ".format(
'stock', table)
lastUpdateTime = pd.read_sql(con=engine, sql=createTimeSql).iloc[0, 0]
try:
##排除五点后获取数据
print('needUpdate')
print(needUpdate(lastUpdateTime, nowtime, isWorkDay=True))
if (needUpdate(lastUpdateTime, nowtime)):
stockData = ak.stock_zh_a_spot()
stockData['symbol'] = stockData['symbol'].map(
lambda x: getdotCodeBysymbol(x))
stockData.to_sql(table, con=engine, if_exists='replace')
else:
stockData = pd.read_sql(con=engine,
sql='select * from {}'.format(table))
except:
# traceback.print_exc()
stockData = pd.read_sql(con=engine,
sql='select * from {}'.format(table))
timeUtil.saveOperationTime(table)
return stockData
def all_stock_tick():
"""
描述: A 股数据是从新浪财经获取的数据, 重复运行本函数会被新浪暂时封 IP, 建议增加时间间隔
限量: 单次返回所有 A 股上市公司的实时行情数据
"""
stock_zh_a_spot_df = ak.stock_zh_a_spot()
return stock_zh_a_spot_df
def code(self):
etf = ak.fund_em_etf_fund_daily()
etf = etf[['基金代码', '基金简称', '类型', ]]
etf.columns = ['code','name', 'market']
etf['market'] = 'ETF'
etf['symbol'] = etf['code'].apply(lambda x:'sh' + str(x)[:6] if int(x) > 500000 else 'sz' + str(x)[:6])
etf['tag'] = etf['symbol'].apply(lambda x: 'E_' + str(x))
etf = etf[['name', 'code', 'symbol', 'tag', 'market']]
index = ak.stock_zh_index_spot()
index['code'] = index['symbol'].apply(lambda x:str(x)[2:])
index['tag'] = index['symbol'].apply(lambda x:'I_' + str(x))
index.loc[index['name']=='','name']='TBD'
index['market'] = 'INDEX'
index = index[['name','code','symbol', 'tag','market']]
stock = ak.stock_zh_a_spot()
stock['tag'] = stock['symbol'].apply(lambda x: 'S_' + str(x))
stock.to_csv(self.BASIC + 'stock_spot.csv', encoding='gb18030', index=False)
stock['tag'] = stock['symbol'].apply(lambda x:'S_' + str(x))
stock['market'] = 'STOCK'
stock = stock[['name','code','symbol', 'tag','market']]
df = pd.concat([etf,index,stock],axis=0)
df = df.append({'name':'银证转账', 'code':'817909','symbol':'sh817909','tag':'C_sh817909','market':'TRADE'},ignore_index=True)
df = df.append({'name':'测试账号','code':'817910', 'symbol':'sh817910','tag':'C_sh817910','market':'TRADE'},ignore_index=True)
df['name'] = df['name'].apply(lambda x: x[:-5] if x[-5:] == 'ETF行情' else x)
df['name'] = df['name'].apply(lambda x: x[:-2] if x[-2:] == '行情' else x)
df=df[df['name'].str.contains('ST')==False]
df.to_csv(self.BASIC + 'code_name.csv', encoding='gb18030', index=False)
return
def get_all_stock():
all_stock = ak.stock_zh_a_spot()
print(all_stock)
print(type(all_stock))
stock_list = all_stock['代码'].tolist()
stock_str = json.dumps(stock_list,ensure_ascii=False)
with open('all_china_stocks.txt','w')as f :
f.write(stock_str)
def query_RT_stock():
stock_zh_a_spot_df = ak.stock_zh_a_spot()
for index, stock_data_info in stock_zh_a_spot_df.iterrows():
result = DBUtils.execute(
"INSERT INTO `stock_2020_1218`(`symbol`,`code`,`name`)"
"VALUES('{symbol}','{code}','{name}')".format(
**dict(stock_data_info)))
if result is None or result <= 0:
print(stock_data_info)
def get_stock_code_info(self):
stock_info_df = ak.stock_info_a_code_name() # 获取所有A股code和name
stock_symbol_code = ak.stock_zh_a_spot().get(["symbol", "code"]) # 获取A股所有股票的symbol和code
for _id in range(stock_info_df.shape[0]):
_symbol = stock_symbol_code[stock_symbol_code.code == stock_info_df.iloc[_id].code].symbol.values
if len(_symbol) != 0:
_dict = {"symbol": _symbol[0]}
_dict.update(stock_info_df.iloc[_id].to_dict())
self.col_basic_info.insert_one(_dict)
return stock_info_df
def get_realtime_news(self, freq="day"):
while True:
if_updated = input(
"Has the stock price dataset been updated today? (Y/N) \n")
if if_updated == "Y":
self.redis_client.set("is_today_updated", "1")
break
elif if_updated == "N":
self.redis_client.set("is_today_updated", "")
break
self.get_historical_news() # 对所有股票补充数据到最新
while True:
if freq == "day":
time_now = datetime.datetime.now().strftime(
"%Y-%m-%d %H:%M:%S")
if time_now.split(" ")[0] != self.redis_client.get(
"today_date").decode():
self.redis_client.set("today_date", time_now.split(" ")[0])
self.redis_client.set("is_today_updated",
"") # 过了凌晨，该参数设置回空值，表示今天未进行数据更新
if not bool(
self.redis_client.get("is_today_updated").decode()):
update_time = "{} {}".format(
time_now.split(" ")[0], "15:30:00")
if time_now >= update_time:
stock_zh_a_spot_df = ak.stock_zh_a_spot() # 当天的日数据行情下载
for _id, sym in enumerate(
stock_zh_a_spot_df["symbol"]):
_col = self.db_obj.get_collection(
self.database_name, sym)
_tmp_dict = {}
_tmp_dict.update({
"date":
Timestamp("{} 00:00:00".format(
time_now.split(" ")[0]))
})
_tmp_dict.update(
{"open": stock_zh_a_spot_df.iloc[_id].open})
_tmp_dict.update(
{"high": stock_zh_a_spot_df.iloc[_id].high})
_tmp_dict.update(
{"low": stock_zh_a_spot_df.iloc[_id].low})
_tmp_dict.update(
{"close": stock_zh_a_spot_df.iloc[_id].trade})
_tmp_dict.update({
"volume":
stock_zh_a_spot_df.iloc[_id].volume
})
_col.insert_one(_tmp_dict)
self.redis_client.set(sym, time_now.split(" ")[0])
logging.info(
"finished updating {} price data of {} ... ".
format(sym,
time_now.split(" ")[0]))
self.redis_client.set("is_today_updated", "1")
def mainProcess():
engine = create_engine('mysql+pymysql://root:root@localhost:3306/stock')
createTimeSql = " SELECT CREATE_TIME from information_schema.`TABLES` WHERE `information_schema`.`TABLES`.`TABLE_SCHEMA` = 'stock' and `information_schema`.`TABLES`.`TABLE_NAME` = 'todaystock' "
engine = create_engine('mysql+pymysql://root:root@localhost:3306/stock')
createTime = pd.read_sql(con=engine, sql=createTimeSql)
if (datetime.datetime.now().day != createTime.iloc[0, 0].day):
stockData = ak.stock_zh_a_spot()
stockData.to_sql('todaystock', con=engine, if_exists='replace')
else:
stockData = pd.read_sql(con=engine, sql='select * from todayStock')
importData(stockData, engine)
def get_stock_zh_day():
# stock_zh_a_daily_qfq_df = ak.stock_zh_a_daily(symbol="sz000002", start_date="20101103", end_date="20201116",
# adjust="qfq")
stock_zh_a_spot_df = ak.stock_zh_a_spot()
print(stock_zh_a_spot_df)
stock_list= stock_zh_a_spot_df['代码'].tolist()
print(stock_list)
print(type(stock_list))
stock_list_str = json.dumps(stock_list).encode(encoding='utf8')
print(stock_list_str)
print(type(stock_list_str))
with open('./all_cn_stocks','wb') as f :
f.write(stock_list_str)
def indexStocksCN(idx):
print(idx)
index_stock_cons_df = ak.index_stock_cons(index=idx[2:])
# print(index_stock_cons_df)
index_stock_cons_df.drop_duplicates(subset='品种代码',
keep='first',
inplace=True)
index_stock_cons_df.set_index('品种代码', inplace=True)
# 今日全场股票概况（价格、市值等）
df = ak.stock_zh_a_spot()
df.set_index('symbol', inplace=True)
# 按总市值排顺序，只保留指数成份股
df = df.loc[df.index.isin(
[dealSymbol(s) for s in index_stock_cons_df.index])].copy()
df.sort_values(by='mktcap', ascending=True, inplace=True)
df = df.iloc[:int(len(df) / 2) - 1]
# 计算因子值
days = 30
sortedDf = pd.DataFrame()
tqdmRange = tqdm(range(len(df)))
tqdmRange = tqdm([-3, -2, -1])
for i in tqdmRange:
symbol = dealSymbol(df.index[i])
tqdmRange.set_description("cauculating factor value for %s" % symbol)
factorVaule_1 = []
factorVaule_2 = []
stockK = ak.stock_zh_index_daily_tx(symbol=symbol)
stockK['symbol'] = symbol
for j in range(0, len(stockK)):
if j < days:
factorVaule_1.append(None)
factorVaule_2.append(None)
continue
factorVaule_1.append(factor_1(stockK.iloc[j - days:j]))
factorVaule_2.append(factor_1(stockK.iloc[j - days:j]))
stockK['factor_1'] = factorVaule_1
stockK['factor_2'] = factorVaule_2
stockK.to_csv('Quotation/' + symbol + '.csv')
stockK = stockK[['symbol', 'factor_1', 'factor_2']].copy()
stockK.reset_index(inplace=True)
sortedDf = sortedDf.append(stockK)
sortedDf.sort_values(by=['date', 'factor_1'], ascending=True, inplace=True)
sortedDf.dropna(subset=['factor_1'], inplace=True)
sortedDf.to_csv(idx + 'factor.csv')
sortedDf['date'] = pd.to_datetime(sortedDf['date']).date
return sortedDf
def get_stock_price(stock_code):
global stock_zh_a_spot_df
global stock_hk_spot_df
if stock_zh_a_spot_df.empty:
print("get A stock information")
stock_zh_a_spot_df = ak.stock_zh_a_spot()
if stock_hk_spot_df.empty:
print("get HK stock information")
stock_hk_spot_df = ak.stock_hk_spot()
if stock_code[:2] == "hk":
return float(
stock_hk_spot_df.set_index('symbol').at[stock_code[2:],
'lasttrade'])
elif stock_code == '689009':
return 64.0
else:
return float(
stock_zh_a_spot_df.set_index('code').at[stock_code, 'trade'])
def importTodayStock():
stockData = ak.stock_zh_a_spot()
engine = create_engine('mysql+pymysql://root:root@localhost:3306/stock')
stockData.to_sql('todaystock',con=engine,if_exists='replace')
def getZhASpot(request):
zh_a_spot = akshare.stock_zh_a_spot()
return HttpResponse(zh_a_spot)
df = df[[code, value]]
return df
# Fund
open_df = ak.fund_em_open_fund_daily()
open_df = select_today_price(open_df, '基金代码', open_df.columns[2], fundlist)
#open_df.to_csv(csv_file)
qdii_df = ak.fund_em_open_fund_daily()
qdii_df = select_today_price(qdii_df, '基金代码', qdii_df.columns[4],
overseefundlist)
# Stock
etf_df = select_today_price(ak.fund_em_etf_fund_daily(), '基金代码', '市价', etflist)
sz162411_df = ak.fund_etf_hist_sina(symbol=sz162411_code)
sz162411_df = select_today_close_price(sz162411_df, sz162411_code)
a_stock_df = select_today_price(ak.stock_zh_a_spot(), 'code', 'trade',
a_stockList)
# US Stock
#voo_df = ak.stock_us_daily(symbol=voo_code, adjust="")
#voo_df = select_today_close_price(voo_df,voo_code)
#us_stock_df = select_today_price(ak.stock_us_spot(),'symbol','price',us_stockList)
#toCS
open_df.append(qdii_df).append(etf_df).append(sz162411_df).append(
a_stock_df).to_csv(csv_file)
import akshare as ak
stock_zh_a_spot_df = ak.stock_zh_a_spot()
# print(stock_zh_a_spot_df)
stock_zh_a_spot_df.to_csv('test.csv')
# coding: utf-8
import akshare as ak
import os
import datetime
import time
import pytz
localtime = datetime.datetime.now(
tz=pytz.timezone('Asia/Shanghai')).strftime("%Y-%m-%d")
if not os.path.exists(localtime):
os.mkdir(localtime)
try:
df_Stock = ak.stock_zh_a_spot()
df_Stock.to_excel(localtime + '/A_data.xlsx')
except:
pass
time.sleep(10)
try:
dce_text = ak.match_main_contract(exchange="dce")
czce_text = ak.match_main_contract(exchange="czce")
shfe_text = ak.match_main_contract(exchange="shfe")
df_Future_C = ak.futures_zh_spot(subscribe_list=",".join(
[dce_text, czce_text, shfe_text]),
adjust=False,
market="CF")
df_Future_C.to_excel(localtime + '/Future_C_data.xlsx')
except:
pass
def stock_zh_a_spot(self):
stock_zh_a_spot_df = ak.stock_zh_a_spot()
return stock_zh_a_spot_df
def get_CurrentQuoteS(self):
response = ak.stock_zh_a_spot()
return response
