Yield curves for #9 and #10

example.py

@@ -131,3 +131,14 @@ def bonds_dataframe():
 
 CURRENCIES
 # %%
+
+from finec.yield_curve import YieldCurve, get_yields_from_cbr
+
+y = YieldCurve("2022-09-28")
+r1 = y.rate(t=1)
+# 830.2383903307176
+
+rs = get_yields_from_cbr("2022-09-28")
+# {'0.25': 8.2, '0.50': 8.19, '0.75': 8.23, '1.00': 8.3, '2.00': 8.74, '3.00': 9.22, '5.00': 9.91, '7.00': 10.27, '10.00': 10.5, '15.00': 10.69, '20.00': 10.8, '30.00': 10.9}
+
+# %%

finec/__init__.py

@@ -1,2 +0,0 @@
-def start():
-    return 1

finec/yield_curve.py

@@ -7,34 +7,34 @@
 from dataclasses import dataclass
 import numpy as np
 from finec.moex import Endpoint
-
+from typing import Dict, Optional
 
 #%%
 a1 = 0
 a2 = 0.6
 k = 1.6
 
 
-def a(n: int):
+def fa(n: int):
     if n == 1:
         return a1
     if n == 2:
         return a2
-    return a(n - 1) + a(2) * k ** (n - 2)
+    return fa(n - 1) + fa(2) * k ** (n - 2)
 
 
-def b(n: int):
+def fb(n: int):
     if n == 1:
-        return a(2)
+        return fa(2)
     else:
-        return b(n - 1) * k
+        return fb(n - 1) * k
 
 
 def s(t, params):
     res = 0
     for i in range(1, 9 + 1):
         g = params[f"g{i}"]
-        res += g * np.exp(-((t - a(i)) ** 2) / b(i) ** 2)
+        res += g * np.exp(-((t - fa(i)) ** 2) / fb(i) ** 2)
     return res
 
 
@@ -65,3 +65,41 @@ def yield_curve(date: str, t: float):
     params = yield_curve_parameters(date)[-1]
     return Y(t, params)
 
+
+@dataclass
+class YieldCurve:
+    iso_date: str
+    params: Optional[Dict] = None
+
+    def __post_init__(self):
+        self.params = yield_curve_parameters(self.iso_date)
+
+    @property
+    def last(self):
+        return self.params[-1]
+
+    def rate(self, t: float):
+        return Y(t, self.last)
+
+
+#%%
+import pandas as pd
+from datetime import datetime
+
+
+def make_date(iso_date: str):
+    return datetime.strptime(iso_date, "%Y-%m-%d").strftime("%d.%m.%Y")
+
+
+def make_url(iso_date: str):
+    return "https://www.cbr.ru/hd_base/zcyc_params/zcyc/?DateTo={}".format(
+        make_date(iso_date)
+    )
+
+
+def get_yields_from_cbr(iso_date: str) -> Dict[str, float]:
+    df = pd.read_html(make_url(iso_date))[0]
+    return df.iloc[:, 1:].T.to_dict()[0]
+
+
+# %%