misc type-check fixes

apis/python/src/tiledbsoma/_dataframe.py

@@ -33,7 +33,9 @@
 from ._soma_array import SOMAArray
 from ._tdb_handles import DataFrameWrapper
 from ._types import (
+    NPFInfo,
     NPFloating,
+    NPIInfo,
     NPInteger,
     OpenTimestamp,
     StatusAndReason,
@@ -925,7 +927,7 @@ def _fill_out_slot_soma_domain(
         if is_max_domain:
             # Core max domain is immutable. If unspecified, it should be as big
             # as possible since it can never be resized.
-            iinfo = np.iinfo(cast(NPInteger, dtype))
+            iinfo: NPIInfo = np.iinfo(cast(NPInteger, dtype))
             slot_domain = iinfo.min, iinfo.max - 1
             # Here the slot_domain isn't specified by the user; we're setting it.
             # The SOMA spec disallows negative soma_joinid.
@@ -943,7 +945,7 @@ def _fill_out_slot_soma_domain(
             slot_domain = 0, 0
     elif np.issubdtype(dtype, NPFloating):
         if is_max_domain:
-            finfo = np.finfo(cast(NPFloating, dtype))
+            finfo: NPFInfo = np.finfo(cast(NPFloating, dtype))
             slot_domain = finfo.min, finfo.max
             saturated_range = True
         else:

apis/python/src/tiledbsoma/_fast_csr.py

@@ -158,7 +158,7 @@ def append(
         )
         row_ind = rows_future.result()
         col_ind = cols_future.result()
-        self.coo_chunks.append((row_ind, col_ind, data.to_numpy()))  # type: ignore[arg-type]
+        self.coo_chunks.append((row_ind, col_ind, data.to_numpy()))
         _accum_row_length(self.row_length, row_ind)
 
     def finalize(self) -> AccumulatedCSR:
@@ -214,7 +214,7 @@ def finalize(self) -> AccumulatedCSR:
 
 
 @typeguard_ignore  # type: ignore[misc]
-@numba.jit(nopython=True, nogil=True)  # type: ignore[attr-defined,misc]
+@numba.jit(nopython=True, nogil=True)  # type: ignore[misc]
 def _accum_row_length(
     row_length: npt.NDArray[np.int64], row_ind: npt.NDArray[np.int64]
 ) -> None:
@@ -223,7 +223,7 @@ def _accum_row_length(
 
 
 @typeguard_ignore  # type: ignore[misc]
-@numba.jit(nopython=True, nogil=True)  # type: ignore[attr-defined,misc]
+@numba.jit(nopython=True, nogil=True)  # type: ignore[misc]
 def _copy_chunk_range(
     row_ind_chunk: npt.NDArray[np.signedinteger[npt.NBitBase]],
     col_ind_chunk: npt.NDArray[np.signedinteger[npt.NBitBase]],
@@ -245,7 +245,7 @@ def _copy_chunk_range(
 
 
 @typeguard_ignore  # type: ignore[misc]
-@numba.jit(nopython=True, nogil=True)  # type: ignore[attr-defined,misc]
+@numba.jit(nopython=True, nogil=True)  # type: ignore[misc]
 def _copy_chunklist_range(
     chunk_list: numba.typed.List,
     data: NPNDArray,
@@ -271,7 +271,7 @@ def _copy_chunklist_range(
 
 
 @typeguard_ignore  # type: ignore[misc]
-@numba.jit(nopython=True, nogil=True)  # type: ignore[attr-defined,misc]
+@numba.jit(nopython=True, nogil=True)  # type: ignore[misc]
 def _finalize_indptr(indptr: npt.NDArray[np.signedinteger[npt.NBitBase]]) -> None:
     prev = 0
     for r in range(len(indptr)):

apis/python/src/tiledbsoma/_fastercsx.py

@@ -176,7 +176,7 @@ def to_scipy(
             indptr = (self.indptr[idx_start : idx_end + 1]).copy()
             indices = self.indices[indptr[0] : indptr[-1]].copy()
             data = self.data[indptr[0] : indptr[-1]].copy()
-            indptr -= indptr[0]  # type: ignore[misc]
+            indptr -= indptr[0]
 
         shape = (
             (n_major, self.shape[1])

apis/python/src/tiledbsoma/_indexer.py

@@ -79,7 +79,7 @@ def get_indexer(self, target: IndexerDataType) -> npt.NDArray[np.intp]:
         Args:
             target: Data to return re-index data for.
         """
-        return (  # type: ignore[no-any-return]
+        return (
             self._reindexer.get_indexer_pyarrow(target)
             if isinstance(target, (pa.Array, pa.ChunkedArray))
             else self._reindexer.get_indexer_general(target)

apis/python/src/tiledbsoma/_query.py

@@ -147,7 +147,7 @@ def by_var(self, coords: Numpyable) -> npt.NDArray[np.intp]:
 def _to_numpy(it: Numpyable) -> npt.NDArray[np.int64]:
     if isinstance(it, np.ndarray):
         return it
-    return it.to_numpy()  # type: ignore[no-any-return]
+    return it.to_numpy()
 
 
 @attrs.define(frozen=True)

apis/python/src/tiledbsoma/_types.py

@@ -28,6 +28,8 @@
     NPFloating = np.floating[npt.NBitBase]
     NPNDArray = npt.NDArray[np.number[npt.NBitBase]]
     NPIntArray = npt.NDArray[np.integer[npt.NBitBase]]
+    NPIInfo = np.iinfo[NPInteger]
+    NPFInfo = np.finfo[NPFloating]
 else:
     # When not-type-checking, but running with `pandas>=2`, the "missing" type-params don't affect anything.
     PDSeries = pd.Series
@@ -40,6 +42,8 @@
     NPFloating = np.floating
     NPNDArray = np.ndarray
     NPIntArray = np.ndarray
+    NPIInfo = np.iinfo
+    NPFInfo = np.finfo
 
 
 Path = Union[str, pathlib.Path]

apis/python/src/tiledbsoma/_util.py

@@ -533,12 +533,12 @@ def _set_coord(dim_idx: int, sarr: clib.SOMAArray, coord: object) -> None:
         ts_dom = pa.array(dom, type=dim.type).cast(pa.int64())
 
         if coord.start is not None:
-            istart = coord.start.astype("int64")
+            istart = int(coord.start.astype("int64"))
         else:
             istart = ts_dom[0].as_py()
 
         if coord.stop is not None:
-            istop = coord.stop.astype("int64")
+            istop = int(coord.stop.astype("int64"))
         else:
             istop = ts_dom[1].as_py()
 

apis/python/src/tiledbsoma/experimental/_xarray_backend.py

@@ -79,7 +79,7 @@ def update_slice_index(index: slice, dim_size: int) -> slice:
 
         # Read the data from SOMA, convert to numpy, and reshape.
         result = self._array.read(key).to_numpy()
-        return result.reshape(output_shape)  # type: ignore
+        return result.reshape(output_shape)
 
     @property
     def ndim(self) -> int:

apis/python/src/tiledbsoma/experimental/ingest.py

@@ -729,11 +729,11 @@ def _write_visium_spots(
     if additional_metadata is None:
         additional_metadata = {
             "soma_geometry_type": "radius",
-            "soma_geometry": 0.5 * np.double(spot_diameter),  # type: ignore
+            "soma_geometry": 0.5 * np.double(spot_diameter),
         }
     else:
         additional_metadata["soma_geometry_type"] = "radius"
-        additional_metadata["soma_geometry"] = 0.5 * np.double(spot_diameter)  # type: ignore
+        additional_metadata["soma_geometry"] = 0.5 * np.double(spot_diameter)
     if ingestion_params.write_schema_no_data:
         add_metadata(soma_point_cloud, additional_metadata)
         return soma_point_cloud