new dual linked dictionary and usage as feature map

src/delta_barth/constants.py

@@ -1,7 +1,7 @@
 import enum
 from typing import Final
 
-from delta_barth.types import HttpContentHeaders
+from delta_barth.types import DualDict, HttpContentHeaders
 
 # ** error handling
 DEFAULT_INTERNAL_ERR_CODE: Final[int] = 100
@@ -20,13 +20,14 @@ class KnownDelBarApiErrorCodes(enum.Enum):
 
 # ** API response parsing
 # ** column mapping [API-Response --> Target-Features]
-COL_MAP_SALES_PROGNOSIS: Final[dict[str, str]] = {
-    "artikelId": "artikel_refid",
-    "firmaId": "firma_refid",
-    "betrag": "betrag",
-    "menge": "menge",
-    "buchungsDatum": "buchungs_datum",
-}
+COL_MAP_SALES_PROGNOSIS: Final[DualDict[str, str]] = DualDict(
+    artikelId="artikel_refid",
+    firmaId="firma_refid",
+    betrag="betrag",
+    menge="menge",
+    buchungsDatum="buchungs_datum",
+)
+
 FEATURES_SALES_PROGNOSIS: Final[frozenset[str]] = frozenset(
     (
         "firma_refid",
@@ -34,3 +35,5 @@ FEATURES_SALES_PROGNOSIS: Final[frozenset[str]] = frozenset(
         "buchungs_datum",
     )
 )
+
+MIN_NUMBER_DATAPOINTS: Final[int] = 100

src/delta_barth/types.py

@@ -2,13 +2,51 @@ from __future__ import annotations
 
 import enum
 import typing as t
+from collections.abc import Iterator, MutableMapping
 from dataclasses import dataclass, field
 
 import pandas as pd
 from pydantic import BaseModel, ConfigDict, SkipValidation
 
+# ** Data Structures
+K = t.TypeVar("K")
+V = t.TypeVar("V")
+
+
+class DualDict(MutableMapping[K, V]):
+    def __init__(self, **kwargs: V):
+        self._store: dict[K, V] = dict(**kwargs)
+        self._inverted = self._calc_inverted()
+
+    @property
+    def inverted(self) -> dict[V, K]:
+        return self._inverted
+
+    def _calc_inverted(self) -> dict[V, K]:
+        return {val: key for key, val in self.items()}
+
+    def __setitem__(self, key: K, value: V) -> None:
+        self._store[key] = value
+        self._inverted[value] = key
+
+    def __getitem__(self, key: K) -> V:
+        return self._store[key]
+
+    def __delitem__(self, key: K) -> None:
+        value = self._store[key]
+        del self._store[key]
+        del self._inverted[value]
+
+    def __iter__(self) -> Iterator[K]:
+        return iter(self._store)
+
+    def __len__(self) -> int:
+        return len(self._store)
+
+
 # ** Pipeline state management
 StatusDescription: t.TypeAlias = tuple[str, int, str]
+R = t.TypeVar("R", bound="ExportResponse")
 
 
 class IError(t.Protocol):
@@ -24,6 +62,15 @@ class Status(BaseModel):
     api_server_error: SkipValidation[DelBarApiError | None] = None
 
 
+class ResponseType(BaseModel):
+    pass
+
+
+class ExportResponse(BaseModel):
+    response: ResponseType
+    status: Status
+
+
 @dataclass(slots=True)
 class DataPipeStates:
     SUCCESS: Status
@@ -32,9 +79,35 @@ class DataPipeStates:
 
 
 @dataclass(slots=True)
-class PipeResult:
-    status: Status
+class PipeResult(t.Generic[R]):
     data: pd.DataFrame | None
+    status: Status
+    results: R | None = None
+
+    def success(
+        self,
+        data: pd.DataFrame,
+        status: Status,
+    ) -> None:
+        self.data = data
+        self.status = status
+        self.results = None
+
+    def fail(
+        self,
+        status: Status,
+    ) -> None:
+        self.data = None
+        self.status = status
+        self.results = None
+
+    def export(
+        self,
+        response: R,
+    ) -> None:
+        self.data = None
+        self.status = response.status
+        self.results = response
 
 
 # ** API