def kline():
if request.method == "POST":
data = json.loads(request.get_data(as_text=True))
elif request.method == "GET":
data = request.args
else:
raise ValueError
ts_code = data.get('ts_code')
freq = data.get('freq')
k = get_kline(symbol=ts_code, freq=freq, k_count=5000)
if czsc.__version__ < "0.5":
ka = KlineAnalyze(k, bi_mode="new", xd_mode='strict')
k = pd.DataFrame(ka.kline_new)
else:
ka = KlineAnalyze(k, min_bi_k=5, verbose=False)
k = ka.to_df(ma_params=(5, 20), use_macd=True, max_count=5000)
k = k.fillna("")
kline.loc[:, "dt"] = kline.dt.apply(str)
columns = ["dt", "open", "close", "low", "high", "vol", 'fx_mark', 'fx', 'bi', 'xd']
res = make_response(jsonify({'kdata': k[columns].values.tolist()}))
res.headers['Access-Control-Allow-Origin'] = '*'
res.headers['Access-Control-Allow-Method'] = '*'
res.headers['Access-Control-Allow-Headers'] = '*'
return res
def get(self):
ts_code = self.get_argument('ts_code')
freq = self.get_argument('freq')
asset = self.get_argument('asset', "E")
trade_date = self.get_argument('trade_date')
if trade_date == 'null':
trade_date = datetime.now().date().__str__().replace("-", "")
kline = get_kline(ts_code=ts_code,
end_date=trade_date,
freq=freq,
asset=asset)
kline.loc[:, "dt"] = pd.to_datetime(kline.dt)
if czsc.__version__ < "0.5":
ka = KlineAnalyze(kline, bi_mode="new")
kline = pd.DataFrame(ka.kline_new)
else:
ka = KlineAnalyze(kline, verbose=False)
kline = ka.to_df(ma_params=(5, 20), use_macd=True, max_count=5000)
kline = kline.fillna("")
kline.loc[:, "dt"] = kline.dt.apply(str)
columns = [
"dt", "open", "close", "low", "high", "vol", 'fx_mark', 'fx', 'bi',
'xd'
]
self.finish({'kdata': kline[columns].values.tolist()})
def get(self):
ts_code = self.get_argument('ts_code')
freq = self.get_argument('freq')
trade_date = self.get_argument('trade_date')
if trade_date == 'null':
trade_date = datetime.now().date().__str__().replace("-", "")
kline = get_gm_kline(symbol=ts_code,
end_date=trade_date,
freq=freq,
k_count=3000)
ka = KlineAnalyze(kline,
bi_mode="new",
verbose=False,
use_xd=True,
max_count=5000)
kline = ka.to_df(ma_params=(5, 20),
use_macd=True,
max_count=5000,
mode='new')
kline = kline.fillna("")
kline.loc[:, "dt"] = kline.dt.apply(str)
columns = [
"dt", "open", "close", "low", "high", "vol", 'fx_mark', 'fx', 'bi',
'xd'
]
self.finish({'kdata': kline[columns].values.tolist()})
def get(self):
ts_code = self.get_argument('ts_code')
freq = self.get_argument('freq')
trade_date = self.get_argument('trade_date')
if trade_date == 'null':
trade_date = datetime.now().date()
else:
trade_date = datetime.strptime(trade_date, "%Y%m%d")
kline = get_kline(symbol=ts_code,
end_date=trade_date,
freq=freq,
count=5000)
kline.loc[:, "dt"] = pd.to_datetime(kline.dt)
# kline.loc[:, "is_end"] = True
if czsc.__version__ < "0.5":
ka = KlineAnalyze(kline, bi_mode="new", xd_mode='strict')
kline = pd.DataFrame(ka.kline_new)
else:
ka = KlineAnalyze(kline, bi_mode="new", verbose=False)
kline = ka.to_df(ma_params=(5, 20), use_macd=True, max_count=5000)
kline = kline.fillna("")
kline.loc[:, "dt"] = kline.dt.apply(str)
columns = [
"dt", "open", "close", "low", "high", "vol", 'fx_mark', 'fx', 'bi',
'xd'
]
self.finish({'kdata': kline[columns].values.tolist()})