From f8661c35389b195f72d659775bd4366f85d29ca9 Mon Sep 17 00:00:00 2001
From: Michael Ekstrand <md@ekstrandom.net>
Date: Thu, 9 May 2024 12:57:25 -0400
Subject: [PATCH] fix typecheck errors in sparse matrix & iknn

---
 lenskit/algorithms/item_knn.py | 8 ++++----
 lenskit/data/matrix.py         | 5 ++---
 2 files changed, 6 insertions(+), 7 deletions(-)

diff --git a/lenskit/algorithms/item_knn.py b/lenskit/algorithms/item_knn.py
index e6b9259a3..51b3b1e2a 100644
--- a/lenskit/algorithms/item_knn.py
+++ b/lenskit/algorithms/item_knn.py
@@ -365,7 +365,7 @@ class ItemItem(Predictor):
     AGG_WA = intern("weighted-average")
     RATING_AGGS = [AGG_WA]  # the aggregates that use rating values
 
-    nnbrs: int | None
+    nnbrs: int
     min_nbrs: int
     min_sim: float
     save_nbrs: int | None
@@ -387,7 +387,7 @@ class ItemItem(Predictor):
 
     def __init__(
         self,
-        nnbrs: int | None,
+        nnbrs: int,
         min_nbrs: int = 1,
         min_sim: float = 1.0e-6,
         save_nbrs: int | None = None,
@@ -560,9 +560,9 @@ def predict_for_user(self, user, items, ratings=None):
                 _logger.debug("user %s missing, returning empty predictions", user)
                 return pd.Series(np.nan, index=items)
             upos = self.user_index_.get_loc(user)
-            row = self.rating_matrix_[upos]
+            row = self.rating_matrix_[upos]  # type: ignore
             ratings = pd.Series(
-                row.values(),
+                row.values().numpy(),
                 index=pd.Index(self.item_index_[row.indices()[0]]),
             )
 
diff --git a/lenskit/data/matrix.py b/lenskit/data/matrix.py
index ab0467546..1f5cead93 100644
--- a/lenskit/data/matrix.py
+++ b/lenskit/data/matrix.py
@@ -11,21 +11,20 @@
 from __future__ import annotations
 
 import logging
-from collections import namedtuple
-from typing import Generic, Literal, NamedTuple, TypeVar, overload
 
 import numpy as np
 import pandas as pd
 import scipy.sparse as sps
 import torch as t
 from csr import CSR
+from typing_extensions import Generic, Literal, NamedTuple, TypeVar, overload
 
 _log = logging.getLogger(__name__)
 
 M = TypeVar("M", CSR, sps.csr_matrix, sps.coo_matrix, t.Tensor)
 
 
-class RatingMatrix(NamedTuple):
+class RatingMatrix(NamedTuple, Generic[M]):
     """
     A rating matrix with associated indices.