Bump the actions group across 1 directory with 2 updates

.github/workflows/ci.yml

@@ -25,7 +25,7 @@ jobs:
       - uses: actions/setup-python@v5
         with:
           python-version: "3.x"
-      - uses: pre-commit/action@v3.0.0
+      - uses: pre-commit/action@v3.0.1
         with:
           extra_args: --hook-stage manual --all-files
       - name: Run PyLint
@@ -66,4 +66,4 @@ jobs:
           --durations=20
 
       - name: Upload coverage report
-        uses: codecov/codecov-action@v3.1.4
+        uses: codecov/codecov-action@v4.5.0

src/n5py/__init__.py

@@ -18,16 +18,21 @@
 import os
 import struct
 import sys
-from typing import Any, Dict, Optional, cast
 import warnings
+from typing import Any, Optional, cast
 
 import numpy as np
 from numcodecs.abc import Codec
 from numcodecs.compat import ndarray_copy
 from numcodecs.registry import get_codec, register_codec
-
 from zarr.meta import ZARR_FORMAT, json_dumps, json_loads
-from zarr.storage import FSStore, NestedDirectoryStore, _prog_ckey, _prog_number, normalize_storage_path
+from zarr.storage import (
+    FSStore,
+    NestedDirectoryStore,
+    _prog_ckey,
+    _prog_number,
+    normalize_storage_path,
+)
 from zarr.storage import array_meta_key as zarr_array_meta_key
 from zarr.storage import attrs_key as zarr_attrs_key
 from zarr.storage import group_meta_key as zarr_group_meta_key
@@ -94,7 +99,9 @@ def __getitem__(self, key: str) -> bytes:
         elif key.endswith(zarr_array_meta_key):
             key_new = key.replace(zarr_array_meta_key, n5_attrs_key)
             top_level = key == zarr_array_meta_key
-            value = array_metadata_to_zarr(self._load_n5_attrs(key_new), top_level=top_level)
+            value = array_metadata_to_zarr(
+                self._load_n5_attrs(key_new), top_level=top_level
+            )
             return json_dumps(value)
 
         elif key.endswith(zarr_attrs_key):
@@ -127,7 +134,9 @@ def __setitem__(self, key: str, value: Any):
             key_new = key.replace(zarr_array_meta_key, n5_attrs_key)
             top_level = key == zarr_array_meta_key
             n5_attrs = self._load_n5_attrs(key_new)
-            n5_attrs.update(**array_metadata_to_n5(json_loads(value), top_level=top_level))
+            n5_attrs.update(
+                **array_metadata_to_n5(json_loads(value), top_level=top_level)
+            )
             value = json_dumps(n5_attrs)
 
         elif key.endswith(zarr_attrs_key):
@@ -138,7 +147,9 @@ def __setitem__(self, key: str, value: Any):
 
             for k in n5_keywords:
                 if k in zarr_attrs:
-                    warnings.warn(f"Attribute {k} is a reserved N5 keyword", UserWarning)
+                    warnings.warn(
+                        f"Attribute {k} is a reserved N5 keyword", UserWarning
+                    )
 
             # remove previous user attributes
             for k in list(n5_attrs.keys()):
@@ -245,7 +256,7 @@ def listdir(self, path: Optional[str] = None):
         else:
             return children
 
-    def _load_n5_attrs(self, path: str) -> Dict[str, Any]:
+    def _load_n5_attrs(self, path: str) -> dict[str, Any]:
         try:
             s = super().__getitem__(path)
             return json_loads(s)
@@ -379,7 +390,9 @@ def __getitem__(self, key: str) -> bytes:
         elif key.endswith(zarr_array_meta_key):
             key_new = key.replace(zarr_array_meta_key, self._array_meta_key)
             top_level = key == zarr_array_meta_key
-            value = array_metadata_to_zarr(self._load_n5_attrs(key_new), top_level=top_level)
+            value = array_metadata_to_zarr(
+                self._load_n5_attrs(key_new), top_level=top_level
+            )
             return json_dumps(value)
 
         elif key.endswith(zarr_attrs_key):
@@ -412,7 +425,9 @@ def __setitem__(self, key: str, value: Any):
             key_new = key.replace(zarr_array_meta_key, self._array_meta_key)
             top_level = key == zarr_array_meta_key
             n5_attrs = self._load_n5_attrs(key_new)
-            n5_attrs.update(**array_metadata_to_n5(json_loads(value), top_level=top_level))
+            n5_attrs.update(
+                **array_metadata_to_n5(json_loads(value), top_level=top_level)
+            )
 
             value = json_dumps(n5_attrs)
 
@@ -424,7 +439,9 @@ def __setitem__(self, key: str, value: Any):
 
             for k in n5_keywords:
                 if k in zarr_attrs.keys():
-                    warnings.warn(f"Attribute {k} is a reserved N5 keyword", UserWarning)
+                    warnings.warn(
+                        f"Attribute {k} is a reserved N5 keyword", UserWarning
+                    )
 
             # replace previous user attributes
             for k in list(n5_attrs.keys()):
@@ -583,23 +600,25 @@ def invert_chunk_coords(key: str):
     return key
 
 
-def group_metadata_to_n5(group_metadata: Dict[str, Any]) -> Dict[str, Any]:
+def group_metadata_to_n5(group_metadata: dict[str, Any]) -> dict[str, Any]:
     """Convert group metadata from zarr to N5 format."""
     del group_metadata["zarr_format"]
     # TODO: This should only exist at the top-level
     group_metadata["n5"] = N5_FORMAT
     return group_metadata
 
 
-def group_metadata_to_zarr(group_metadata: Dict[str, Any]) -> Dict[str, Any]:
+def group_metadata_to_zarr(group_metadata: dict[str, Any]) -> dict[str, Any]:
     """Convert group metadata from N5 to zarr format."""
     # This only exists at the top level
     group_metadata.pop("n5", None)
     group_metadata["zarr_format"] = ZARR_FORMAT
     return group_metadata
 
 
-def array_metadata_to_n5(array_metadata: Dict[str, Any], top_level=False) -> Dict[str, Any]:
+def array_metadata_to_n5(
+    array_metadata: dict[str, Any], top_level=False
+) -> dict[str, Any]:
     """Convert array metadata from zarr to N5 format. If the `top_level` keyword argument is True,
     then the `N5` : N5_FORMAT key : value pair will be inserted into the metadata."""
 
@@ -611,14 +630,19 @@ def array_metadata_to_n5(array_metadata: Dict[str, Any], top_level=False) -> Dic
     try:
         dtype = np.dtype(array_metadata["dataType"])
     except TypeError:
-        raise TypeError(f"Data type {array_metadata['dataType']} is not supported by N5")
+        raise TypeError(
+            f"Data type {array_metadata['dataType']} is not supported by N5"
+        )
 
     array_metadata["dataType"] = dtype.name
     array_metadata["dimensions"] = array_metadata["dimensions"][::-1]
     array_metadata["blockSize"] = array_metadata["blockSize"][::-1]
 
     if "fill_value" in array_metadata:
-        if array_metadata["fill_value"] != 0 and array_metadata["fill_value"] is not None:
+        if (
+            array_metadata["fill_value"] != 0
+            and array_metadata["fill_value"] is not None
+        ):
             raise ValueError(
                 f"""Received fill_value = {array_metadata['fill_value']},
                 but N5 only supports fill_value = 0"""
@@ -634,7 +658,9 @@ def array_metadata_to_n5(array_metadata: Dict[str, Any], top_level=False) -> Dic
 
     if "filters" in array_metadata:
         if array_metadata["filters"] != [] and array_metadata["filters"] is not None:
-            raise ValueError("Received filters, but N5 storage does not support zarr filters")
+            raise ValueError(
+                "Received filters, but N5 storage does not support zarr filters"
+            )
         del array_metadata["filters"]
 
     assert "compression" in array_metadata
@@ -649,8 +675,8 @@ def array_metadata_to_n5(array_metadata: Dict[str, Any], top_level=False) -> Dic
 
 
 def array_metadata_to_zarr(
-    array_metadata: Dict[str, Any], top_level: bool = False
-) -> Dict[str, Any]:
+    array_metadata: dict[str, Any], top_level: bool = False
+) -> dict[str, Any]:
     """Convert array metadata from N5 to zarr format.
     If the `top_level` keyword argument is True, then the `N5` key will be removed from metadata"""
     for t, f in zarr_to_n5_keys:
@@ -679,7 +705,7 @@ def array_metadata_to_zarr(
     return array_metadata
 
 
-def attrs_to_zarr(attrs: Dict[str, Any]) -> Dict[str, Any]:
+def attrs_to_zarr(attrs: dict[str, Any]) -> dict[str, Any]:
     """Get all zarr attributes from an N5 attributes dictionary (i.e.,
     all non-keyword attributes)."""
 
@@ -691,7 +717,9 @@ def attrs_to_zarr(attrs: Dict[str, Any]) -> Dict[str, Any]:
     return attrs
 
 
-def compressor_config_to_n5(compressor_config: Optional[Dict[str, Any]]) -> Dict[str, Any]:
+def compressor_config_to_n5(
+    compressor_config: Optional[dict[str, Any]],
+) -> dict[str, Any]:
     if compressor_config is None:
         return {"type": "raw"}
     else:
@@ -751,7 +779,9 @@ def compressor_config_to_n5(compressor_config: Optional[Dict[str, Any]]) -> Dict
     return n5_config
 
 
-def compressor_config_to_zarr(compressor_config: Dict[str, Any]) -> Optional[Dict[str, Any]]:
+def compressor_config_to_zarr(
+    compressor_config: dict[str, Any],
+) -> Optional[dict[str, Any]]:
     codec_id = compressor_config["type"]
     zarr_config = {"id": codec_id}
 
@@ -808,10 +838,16 @@ def __init__(self, dtype, chunk_shape, compressor_config=None, compressor=None):
 
         if compressor:
             if compressor_config is not None:
-                raise ValueError("Only one of compressor_config or compressor should be given.")
+                raise ValueError(
+                    "Only one of compressor_config or compressor should be given."
+                )
             compressor_config = compressor.get_config()
 
-        if compressor_config is None and compressor is None or compressor_config["id"] == "raw":
+        if (
+            compressor_config is None
+            and compressor is None
+            or compressor_config["id"] == "raw"
+        ):
             self.compressor_config = None
             self._compressor = None
         else:
@@ -884,7 +920,8 @@ def _create_header(chunk):
     def _read_header(chunk):
         num_dims = struct.unpack(">H", chunk[2:4])[0]
         shape = tuple(
-            struct.unpack(">I", chunk[i : i + 4])[0] for i in range(4, num_dims * 4 + 4, 4)
+            struct.unpack(">I", chunk[i : i + 4])[0]
+            for i in range(4, num_dims * 4 + 4, 4)
         )[::-1]
 
         len_header = 4 + num_dims * 4
@@ -908,4 +945,4 @@ def _from_big_endian(self, data):
         return a.astype(self.dtype)
 
 
-register_codec(N5ChunkWrapper, N5ChunkWrapper.codec_id)
+register_codec(N5ChunkWrapper, N5ChunkWrapper.codec_id)

tests/test_n5.py

@@ -23,10 +23,12 @@ def test_make_n5_chunk_wrapper():
             dtype,
             chunk_shape=chunk_shape,
             compressor_config=codec.get_config(),
-            compressor=codec
+            compressor=codec,
         )
 
-    wrapper_a = N5ChunkWrapper(dtype, chunk_shape=chunk_shape, compressor_config=codec.get_config())
+    wrapper_a = N5ChunkWrapper(
+        dtype, chunk_shape=chunk_shape, compressor_config=codec.get_config()
+    )
     wrapper_b = N5ChunkWrapper(dtype, chunk_shape=chunk_shape, compressor=codec)
     assert wrapper_a == wrapper_b