def get_hist_csv(code):
"""
获取个股历史交易数据（包括均线数据），可以通过参数设置获取
日k线、周k线、月k线，以及5分钟、15分钟、30分钟和60分钟k线数据
"""
h5path = './stockdata/data/last3year/' + code + '.csv'
if not os.path.exists(h5path):
df = wt.get_hist_data(code)
if df is not None:
#df.index=pd.to_datetime(df.index)
df = df.sort_index(ascending=True)
df.to_csv(h5path)
else:
df = pd.read_csv(h5path, index_col='date')
tem = str(df.index[-1])[0:10]
if tem != today:
#if datetime.datetime.today().isoweekday() in [1,2,3,4,5]:
t = time.strptime(tem, '%Y-%m-%d')
y, m, d = t[0:3]
tt = datetime.datetime(y, m, d)
bd = tt + datetime.timedelta(days=1)
bday = bd.strftime('%Y-%m-%d')
df1 = wt.get_hist_data(code, start=str(bday), end=str(today))
if df1 is not None:
#df1.index=pd.to_datetime(df.index)
df1 = df1.sort_index(ascending=True)
df = df.append(df1)
df1.to_csv(h5path, mode='a', header=None)
df.index = pd.to_datetime(df.index)
return df
def get_data_last3year_mp(code):
h5path = './testh5df/stockdata_last3year.h5'
if os.path.exists(h5path):
h5 = pd.HDFStore(h5path, 'a', complevel=4, complib='blosc')
else:
h5 = pd.HDFStore(h5path, 'w', complevel=4, complib='blosc')
try:
dff = h5[code]
tem = str(dff.index[-1])[0:10]
if tem < bftoday:
print('\nUpdating data from %s for %s:' % (tem, code))
t = time.strptime(tem, "%Y-%m-%d")
y, m, d = t[0:3]
tt = datetime.datetime(y, m, d)
bd = tt + datetime.timedelta(days=1)
#if bd.weekday()==5:
# bd = bd+datetime.timedelta(days=2)
# print 'It is Sat'
bday = bd.strftime('%Y-%m-%d')
all_data1 = pd.DataFrame()
try:
all_data = wt.get_hist_data(code, start=bday, end=today)
#print all_data
all_data1 = all_data1.append(all_data)
if all_data1.empty == False:
#all_data1.sort_index(ascending=True,inplace=True)
df = dff.append(all_data1)
#print df
h5[code] = df
return df
except Exception as e:
print(e, 'No data for %s to upadate' % code)
return
except Exception as e:
print(e)
print('Getting the data for %s: \n' % code)
df = wt.get_hist_data(code)
#df.sort_index(ascending=True,inplace=True)
h5[code] = df
#h5.close()
return df
def get_hist_hdf5(code):
"""
获取个股历史交易数据（包括均线数据），可以通过参数设置获取日k线、周k线、月k线，以及5分钟、15分钟、30分钟和60分钟k线数据
"""
h5path = './testh5df/stockdata.h5'
if os.path.exists(h5path):
h5 = pd.HDFStore(h5path, 'a', complevel=4, complib='blosc')
else:
h5 = pd.HDFStore(h5path, 'w', complevel=4, complib='blosc')
if code[0] == '0' or code[0] == '3' or code[0] == '2':
label = 'l3y/sz' + code
elif code[0] == '6' or code[0] == '9':
label = 'l3y/ss' + code
try:
dd = h5[label]
tem = str(dd.index[-1])[0:10]
if tem != today:
if datetime.datetime.today().isoweekday() in [1, 2, 3, 4, 5]:
#print 'Updating the data from%s for %s:'%(tem,code)
t = time.strptime(tem, '%Y-%m-%d')
y, m, d = t[0:3]
tt = datetime.datetime(y, m, d)
bd = tt + datetime.timedelta(days=1)
bday = bd.strftime('%Y-%m-%d')
df1 = wt.get_hist_data(code, start=bday, end=today)
df = dd.append(df1)
#df=df.sort_index(ascending=True,inplace=True)
h5.append(label, df, data_columns=df.columns)
except:
df = wt.get_hist_data(code)
#df=df.sort_index(ascending=True,inplace=True)
h5.append(label, df, data_columns=df.columns)
#finally:
# h5.close()
df.index = pd.to_datetime(df.index)
return df
def get_open_hist_hdf5(code, h5):
"""
获取个股历史交易数据（包括均线数据），可以通过参数设置获取日k线、周k线、月k线，以及5分钟、15分钟、30分钟和60分钟k线数据
"""
if code[0] == '0' or code[0] == '3' or code[0] == '2':
label = 'l3y/sz' + code
elif code[0] == '6' or code[0] == '9':
label = 'l3y/ss' + code
try:
df = h5[label]
#print(df)
tem = str(df.index[-1])[0:10]
if tem < today:
#if datetime.datetime.today().isoweekday() in [1,2,3,4,5]:
t = time.strptime(tem, '%Y-%m-%d')
y, m, d = t[0:3]
tt = datetime.datetime(y, m, d)
bd = tt + datetime.timedelta(days=1)
bday = bd.strftime('%Y-%m-%d')
df1 = wt.get_hist_data(code, start=bday, end=today)
#print(df1)
df = df.append(df1)
df.index = pd.to_datetime(df.index)
#df=df.sort_index(ascending=True)
#print(df)
h5[label] = df
except:
df = wt.get_hist_data(code)
#print (df)
if df is not None:
#df.index=pd.to_datetime(df.index)
#df=df.sort_index(ascending=True)
h5[label] = df
finally:
pass
return df