def read_data(self, needStore = False):
if os.path.exists('i_data.json'):
with open('k_data.json', 'r') as f:
k_data = pd.read_json(f.read(), orient = 'records', lines = True)
k_data.date = k_data.date.dt.strftime('%Y-%m-%d')
with open('d_data.json', 'r') as f:
d_data = pd.read_json(f.read(), orient = 'records', lines = True)
with open('i_data.json', 'r') as f:
i_data = pd.read_json(f.read(), orient = 'records', lines = True)
i_data.date = i_data.date.dt.strftime('%Y-%m-%d')
else:
obj = CStock(self.code, dbinfo = ct.OUT_DB_INFO, redis_host = '127.0.0.1')
k_data = obj.get_k_data()
k_data.date = pd.to_datetime(k_data.date).dt.strftime('%Y-%m-%d')
d_data = obj.get_chip_distribution()
iobj = CIndex(self.index_code, dbinfo = ct.OUT_DB_INFO, redis_host = '127.0.0.1')
i_data = iobj.get_k_data()
cdates = k_data.date.tolist()
i_data = i_data.loc[i_data.date.isin(cdates)]
i_data = i_data.reset_index(drop = True)
k_data = k_data[['date', 'open', 'high', 'low', 'close', 'volume', 'amount', 'outstanding', 'totals', 'adj', 'aprice', 'uprice', 'sprice', 'mprice', 'lprice', 'profit']]
k_data = k_data.rename(columns = {"date": "time"})
i_data = i_data[['date', 'open', 'high', 'low', 'close', 'volume', 'amount']]
i_data = i_data.rename(columns = {"date": "time"})
if needStore:
with open('k_data.json', 'w') as f:
f.write(k_data.to_json(orient='records', lines=True))
with open('d_data.json', 'w') as f:
f.write(d_data.to_json(orient='records', lines=True))
with open('i_data.json', 'w') as f:
f.write(i_data.to_json(orient='records', lines=True))
return k_data, d_data, i_data
base_color = '#e6daa6'
name = "shanghai_%s_image" % cdate
i_data = i_data[[
'date', 'open', 'high', 'low', 'close', 'volume', 'amount'
]]
fig, index_ax = plt.subplots(figsize=(16, 10))
fig.subplots_adjust(bottom=0.2)
candlestick2_ochl(index_ax,
i_data['open'],
i_data['close'],
i_data['high'],
i_data['low'],
width=1.0,
colorup='r',
colordown='g')
index_ax.set_ylabel(name)
index_ax.set_xticks(range(0, len(i_data['date']), 10))
plt.plot()
fig.autofmt_xdate()
plt.show()
index_obj = CIndex('000001', dbinfo=ct.OUT_DB_INFO, redis_host='127.0.0.1')
df = index_obj.get_k_data()
cdates = df[(df.pchange > 4) & (df.date > '1999-01-01')].date.tolist()
for mdate in cdates:
start_date = mdate
end_date = get_day_nday_after(start_date, num=40, dformat="%Y-%m-%d")
index_data = index_obj.get_k_data_in_range(start_date, end_date)
plot_index(start_date, index_data)
