def test_rt_predict():
p = xa.RTPredict("SH512500", t0dict="SH000905")
p.get_t0_rate()
p = xa.QDIIPredict(c, fetch=True, save=True, positions=True)
try:
data["t1"].append(round(p.get_t1(return_date=False), 4))
data["t1rate"].append(round(p.get_t1_rate(return_date=False), 2))
try:
data["t0"].append(round(p.get_t0(return_date=False), 4))
data["t0rate"].append(round(p.get_t0_rate(return_date=False), 2))
except ValueError:
data["t0"].append("-")
data["t0rate"].append("-")
data["position"].append(round(p.get_position(return_date=False), 3))
data["now"].append(xa.get_rt(c)["current"])
data["code"].append(c)
data["name"].append(xa.get_rt(c)["name"])
except xa.exceptions.NonAccurate as e:
print("%s cannot be predicted exactly now" % c)
print(e.reason)
for c in nonqdiis:
p = xa.RTPredict(c)
data["t1"].append(xa.get_rt("F" + c[2:])["current"])
data["t1rate"].append("-")
data["t0"].append(round(p.get_t0(return_date=False), 4))
data["t0rate"].append(round(p.get_t0_rate(return_date=False), 2))
data["position"].append("-")
data["now"].append(xa.get_rt(c)["current"])
data["code"].append(c)
data["name"].append(xa.get_rt(c)["name"])
df = pd.DataFrame(data)
with open("demo.html", "w") as f:
df.to_html(f)
