fix(types): annotate the shared _to_price helper for mypy

CI's mypy step failed on the new helper with 8 errors across both clients:
'Missing type parameters for generic type dict' and incompatible argument
types for commodity/value/timestamp.

The errors are real but not new behaviour — the previous Price(**mapped_data)
form passed a dict of kwargs, which mypy cannot check, so the same looseness
was always there and simply invisible. Writing the call out explicitly exposed
it.

Typed the parameter as Dict[str, Any] and cast the three fields pydantic
validates anyway, with a comment saying why the casts are there. Not silenced
with type: ignore — the shape is genuinely Any coming off JSON, and pydantic
raises on anything actually wrong.

mypy on both files: 0 errors.
Full suite still 645 passed. Live smoke re-run after the change:
  5 codes -> 1 request, 5 prices, BRENT_CRUDE_USD $93.60

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01JKAExynd9zoKwt6rYA66EA

Author: karlwaldman

oilpriceapi/async_client.py

@@ -9,7 +9,8 @@
 import asyncio
 import logging
 import os
-from typing import Any, AsyncGenerator, Dict, List, Optional, Union
+from datetime import datetime
+from typing import Any, AsyncGenerator, Dict, List, Optional, Union, cast
 from urllib.parse import urljoin
 
 import httpx
@@ -375,14 +376,18 @@ def __init__(self, client: AsyncOilPriceAPI):
         self.client = client
 
     @staticmethod
-    def _to_price(price_data: dict, fallback_code: Optional[str] = None) -> Price:
-        """Map one API price row onto the Price model."""
+    def _to_price(price_data: Dict[str, Any], fallback_code: Optional[str] = None) -> Price:
+        """Map one API price row onto the Price model.
+
+        Casts are for mypy; pydantic does the real validation. See
+        PricesResource._to_price.
+        """
         return Price(
-            commodity=price_data.get("code", fallback_code),
-            value=price_data.get("price"),
+            commodity=cast(str, price_data.get("code", fallback_code)),
+            value=cast(float, price_data.get("price")),
             currency=price_data.get("currency", "USD"),
-            unit=price_data.get("unit", "barrel"),
-            timestamp=price_data.get("created_at"),
+            unit=cast(str, price_data.get("unit", "barrel")),
+            timestamp=cast(datetime, price_data.get("created_at")),
         )
 
     async def _fetch_batch(self, codes: List[str]) -> List[Price]:

oilpriceapi/resources/prices.py

@@ -7,7 +7,7 @@
 from __future__ import annotations
 
 from datetime import datetime
-from typing import List, Optional, Set, Tuple, Union
+from typing import Any, Dict, List, Optional, Set, Tuple, Union, cast
 
 from .._pagination import validate_page_size
 from ..models import Price
@@ -27,19 +27,24 @@ def __init__(self, client):
         self.client = client
 
     @staticmethod
-    def _to_price(price_data: dict, fallback_code: Optional[str] = None) -> Price:
+    def _to_price(price_data: Dict[str, Any], fallback_code: Optional[str] = None) -> Price:
         """Map one API price row onto the Price model.
 
         Shared by get() and the batched path so the two cannot drift.
+
+        Values are passed to a pydantic model, which does the coercion and
+        raises on anything genuinely wrong. The casts here are for mypy: the
+        JSON payload is Dict[str, Any], and the previous Price(**mapped_data)
+        form simply hid that from the type checker.
         """
         return Price(
-            commodity=price_data.get("code", fallback_code),
-            value=price_data.get("price"),
+            commodity=cast(str, price_data.get("code", fallback_code)),
+            value=cast(float, price_data.get("price")),
             currency=price_data.get("currency"),
             # Retain the established oil-only fallback for legacy minimal
             # responses; any unit actually supplied by the API wins.
-            unit=price_data.get("unit", "barrel"),
-            timestamp=price_data.get("created_at"),
+            unit=cast(str, price_data.get("unit", "barrel")),
+            timestamp=cast(datetime, price_data.get("created_at")),
         )
 
     def _fetch_batch(self, codes: List[str]) -> List[Price]: