Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

Fix mypy errors around numpy functions not being strictly type hinted #252

Merged
merged 2 commits into from
Oct 11, 2024
Merged

Fix mypy errors around numpy functions not being strictly type hinted #252

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
17d3689
fix mypy errors around numpy functions not being strictly type hinted
TomNicholas Oct 11, 2024
885a9b9
Merge branch 'main' into fix_mypy_errors
TomNicholas Oct 11, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
21 changes: 14 additions & 7 deletions virtualizarr/manifests/array_api.py
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
from typing import TYPE_CHECKING, Callable, Iterable
from typing import TYPE_CHECKING, Any, Callable, Iterable, cast

import numpy as np

Expand Down Expand Up @@ -217,9 +217,12 @@ def stack(
new_shape.insert(axis, length_along_new_stacked_axis)

# do stacking of entries in manifest
stacked_paths = np.stack(
[arr.manifest._paths for arr in arrays],
axis=axis,
stacked_paths = cast( # `np.stack` apparently is type hinted as if the output could have Any dtype
np.ndarray[Any, np.dtypes.StringDType],
np.stack(
[arr.manifest._paths for arr in arrays],
axis=axis,
),
)
stacked_offsets = np.stack(
[arr.manifest._offsets for arr in arrays],
Expand Down Expand Up @@ -296,10 +299,14 @@ def broadcast_to(x: "ManifestArray", /, shape: tuple[int, ...]) -> "ManifestArra
)

# do broadcasting of entries in manifest
broadcasted_paths = np.broadcast_to(
x.manifest._paths,
shape=new_chunk_grid_shape,
broadcasted_paths = cast( # `np.broadcast_to` apparently is type hinted as if the output could have Any dtype
np.ndarray[Any, np.dtypes.StringDType],
np.broadcast_to(
x.manifest._paths,
shape=new_chunk_grid_shape,
),
)

broadcasted_offsets = np.broadcast_to(
x.manifest._offsets,
shape=new_chunk_grid_shape,
Expand Down
9 changes: 6 additions & 3 deletions virtualizarr/manifests/manifest.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -84,7 +84,7 @@ class ChunkManifest:
so it's not possible to have a ChunkManifest object that does not represent a valid grid of chunks.
"""

_paths: np.ndarray[Any, np.dtypes.StringDType] # type: ignore[name-defined]
_paths: np.ndarray[Any, np.dtypes.StringDType]
_offsets: np.ndarray[Any, np.dtype[np.uint64]]
_lengths: np.ndarray[Any, np.dtype[np.uint64]]

Expand Down Expand Up @@ -113,7 +113,10 @@ def __init__(self, entries: dict) -> None:
shape = get_chunk_grid_shape(entries.keys())

# Initializing to empty implies that entries with path='' are treated as missing chunks
paths = np.empty(shape=shape, dtype=np.dtypes.StringDType()) # type: ignore[attr-defined]
paths = cast( # `np.empty` apparently is type hinted as if the output could have Any dtype
np.ndarray[Any, np.dtypes.StringDType],
np.empty(shape=shape, dtype=np.dtypes.StringDType()),
)
offsets = np.empty(shape=shape, dtype=np.dtype("uint64"))
lengths = np.empty(shape=shape, dtype=np.dtype("uint64"))

Expand Down Expand Up @@ -141,7 +144,7 @@ def __init__(self, entries: dict) -> None:
@classmethod
def from_arrays(
cls,
paths: np.ndarray[Any, np.dtype[np.dtypes.StringDType]], # type: ignore[name-defined]
paths: np.ndarray[Any, np.dtypes.StringDType],
offsets: np.ndarray[Any, np.dtype[np.uint64]],
lengths: np.ndarray[Any, np.dtype[np.uint64]],
) -> "ChunkManifest":
Expand Down
Loading