ready for numpy 2.0

dedupeio · Jun 21, 2024 · 139291b · 139291b
1 parent 85fc7e7
commit 139291b
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Showing 3 changed files with 10 additions and 10 deletions.
diff --git a/dedupe/_typing.py b/dedupe/_typing.py
@@ -47,10 +47,10 @@
 BlocksStr = Iterator[BlockStr]
 Blocks = Union[BlocksInt, BlocksStr]
 ClusterInt = Tuple[
-    Tuple[int, ...], Union[numpy.typing.NDArray[numpy.float_], Tuple[float, ...]]
+    Tuple[int, ...], Union[numpy.typing.NDArray[numpy.float64], Tuple[float, ...]]
 ]
 ClusterStr = Tuple[
-    Tuple[str, ...], Union[numpy.typing.NDArray[numpy.float_], Tuple[float, ...]]
+    Tuple[str, ...], Union[numpy.typing.NDArray[numpy.float64], Tuple[float, ...]]
 ]
 ClustersInt = Iterable[ClusterInt]
 ClustersStr = Iterable[ClusterStr]
@@ -107,18 +107,18 @@ class TrainingData(TypedDict):
 
 # Takes pairs of records and generates a (n_samples X n_features) array
 FeaturizerFunction = Callable[
-    [Sequence[RecordDictPair]], numpy.typing.NDArray[numpy.float_]
+    [Sequence[RecordDictPair]], numpy.typing.NDArray[numpy.float64]
 ]
 
 
 class Classifier(Protocol):
     """Takes an array of pairwise distances and computes the likelihood they are a pair."""
 
-    def fit(self, X: numpy.typing.NDArray[numpy.float_], y: LabelsLike) -> None: ...
+    def fit(self, X: numpy.typing.NDArray[numpy.float64], y: LabelsLike) -> None: ...
 
     def predict_proba(
-        self, X: numpy.typing.NDArray[numpy.float_]
-    ) -> numpy.typing.NDArray[numpy.float_]: ...
+        self, X: numpy.typing.NDArray[numpy.float64]
+    ) -> numpy.typing.NDArray[numpy.float64]: ...
 
 
 class ClosableJoinable(Protocol):

diff --git a/dedupe/convenience.py b/dedupe/convenience.py
@@ -43,18 +43,18 @@ def randomPairs(n_records: int, sample_size: int) -> IndicesIterator:
     else:
         try:
             random_pairs = numpy.array(
-                random.sample(range(n), sample_size), dtype=numpy.uint
+                random.sample(range(n), sample_size), dtype=numpy.uint64
             )
         except OverflowError:
             return randomPairsWithReplacement(n_records, sample_size)
 
     b: int = 1 - 2 * n_records
 
     i = (-b - 2 * numpy.sqrt(2 * (n - random_pairs) + 0.25)) // 2
-    i = i.astype(numpy.uint)
+    i = i.astype(numpy.int64)
 
     j = random_pairs + i * (b + i + 2) // 2 + 1
-    j = j.astype(numpy.uint)
+    j = j.astype(numpy.uint64)
 
     return zip(i, j)
 

diff --git a/pyproject.toml b/pyproject.toml
@@ -28,7 +28,7 @@ dependencies = [
     "scikit-learn",
     "affinegap>=1.3",
     "categorical-distance>=1.9",
-    "numpy>=1.20,<2.0",
+    "numpy>=1.20",
     "doublemetaphone",
     "highered>=0.2.0",
     "simplecosine>=1.2",