feat: use lru cache decorator for values_df loading

pyproject.toml

@@ -25,6 +25,7 @@ torch = "^1.12.1"
 transformers = "^4.22.2"
 pyarrow = ">=9.0.0,<9.1.0"
 psycopmlutils = ">=0.2.4, <0.3.0"
+frozendict = "^2.3.4"
 
 [tool.poetry.dev-dependencies]
 pytest = ">=7.1.3, <7.1.5"

src/psycop_feature_generation/timeseriesflattener/feature_spec_objects.py

@@ -2,9 +2,11 @@
 
 import itertools
 from collections.abc import Sequence
+from functools import lru_cache
 from typing import Any, Callable, Optional, Union
 
 import pandas as pd
+from frozendict import frozendict
 from pydantic import BaseModel as PydanticBaseModel
 from pydantic import Extra
 
@@ -14,6 +16,11 @@
 from psycop_feature_generation.utils import data_loaders
 
 
+@lru_cache()
+def load_df_with_cache(loader_fn: Callable, kwargs: dict[str, Any]) -> pd.DataFrame:
+    return loader_fn(**kwargs)
+
+
 class BaseModel(PydanticBaseModel):
     """."""
 
@@ -69,7 +76,10 @@ def resolve_values_df(self, data: dict[str, Any]):
                 data["values_loader"] = data_loaders.get(data["values_loader"])
 
             if callable(data["values_loader"]):
-                data["values_df"] = data["values_loader"](**data["loader_kwargs"])
+                data["values_df"] = load_df_with_cache(
+                    loader_fn=data["values_loader"],
+                    kwargs=frozendict(data["loader_kwargs"]),
+                )
             else:
                 raise ValueError("values_loader could not be resolved to a callable")