diff --git a/pdm.lock b/pdm.lock
index d4e7dcf..7bfafcf 100644
--- a/pdm.lock
+++ b/pdm.lock
@@ -5,7 +5,7 @@
 groups = ["default", "dev", "lint", "nb", "tests"]
 strategy = ["inherit_metadata"]
 lock_version = "4.5.0"
-content_hash = "sha256:052435ec6c320b4865368e5fc5bd8dc57dd4bdeb17e5ba811a4304fcc170dd65"
+content_hash = "sha256:750f84cb8e60872ca2b3dc7adf60a9c678e9928a0d6d836d054e2f7b0f0aa902"
 
 [[metadata.targets]]
 requires_python = ">=3.11"
@@ -577,6 +577,20 @@ files = [
     {file = "distlib-0.3.9.tar.gz", hash = "sha256:a60f20dea646b8a33f3e7772f74dc0b2d0772d2837ee1342a00645c81edf9403"},
 ]
 
+[[package]]
+name = "dopt-basics"
+version = "0.1.0"
+requires_python = ">=3.11"
+summary = "basic cross-project tools for Python-based d-opt projects"
+groups = ["default"]
+dependencies = [
+    "tzdata>=2025.1",
+]
+files = [
+    {file = "dopt_basics-0.1.0-py3-none-any.whl", hash = "sha256:edf1105aa2db6ab854f31fc652996f1ee2f61a4dfb196aa61318a70678601c22"},
+    {file = "dopt_basics-0.1.0.tar.gz", hash = "sha256:8bb885109fe3b16d7c6a2264ac361eca0e31ab73f2edbae28a29d81a0cec510f"},
+]
+
 [[package]]
 name = "execnet"
 version = "2.1.1"
diff --git a/pyproject.toml b/pyproject.toml
index 4258a80..efa4397 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -5,7 +5,7 @@ description = "prognosis module"
 authors = [
     {name = "Florian Förster", email = "f.foerster@d-opt.com"},
 ]
-dependencies = ["scikit-learn>=1.6.1", "pandas>=2.2.3", "xgboost>=2.1.4", "joblib>=1.4.2", "typing-extensions>=4.12.2", "requests>=2.32.3", "pydantic>=2.10.6"]
+dependencies = ["scikit-learn>=1.6.1", "pandas>=2.2.3", "xgboost>=2.1.4", "joblib>=1.4.2", "typing-extensions>=4.12.2", "requests>=2.32.3", "pydantic>=2.10.6", "dopt-basics>=0.1.0"]
 requires-python = ">=3.11"
 readme = "README.md"
 license = {text = "LicenseRef-Proprietary"}
diff --git a/src/delta_barth/types.py b/src/delta_barth/types.py
index 3769cb9..4e59571 100644
--- a/src/delta_barth/types.py
+++ b/src/delta_barth/types.py
@@ -2,47 +2,13 @@ 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 dopt_basics.datastructures import DualDict
 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)
-
+__all__ = ["DualDict"]
 
 # ** Pipeline state management
 StatusDescription: t.TypeAlias = tuple[str, int, str]