Fix minor typos

docs/contributing.md

@@ -255,7 +255,7 @@ print("Hello world")
 
 #### Building documentation without executing code blocks
 
-Sometimes, you may want the documentation to build quicker. You can disable code block execution by commenting out the [markdown-exec](https://github.com/zarr-developers/zarr-python/blob/884a8c91afcc3efe28b3da952be3b85125c453cb/mkdocs.yml#L132 plugin in the mkdocs configuration file). This will make code blocks and cross references render incorrectly (i.e., expect build warnings), but also reduces build time by ~3x. Be sure to undo the commenting out before opening your pull request.
+Sometimes, you may want the documentation to build quicker. You can disable code block execution by commenting out the [markdown-exec plugin](https://github.com/zarr-developers/zarr-python/blob/884a8c91afcc3efe28b3da952be3b85125c453cb/mkdocs.yml#L132) in the mkdocs configuration file. This will make code blocks and cross references render incorrectly (i.e., expect build warnings), but also reduces build time by ~3x. Be sure to undo the commenting out before opening your pull request.
 
 ### Changelog
 

docs/user-guide/arrays.md

@@ -512,7 +512,7 @@ print(np.all(z.oindex[[0, 2], :] == z[[0, 2], :]))
 
 ### Block Indexing
 
-Zarr also support block indexing, which allows selections of whole chunks based on their
+Zarr also supports block indexing, which allows selections of whole chunks based on their
 logical indices along each dimension of an array. For example, this allows selecting
 a subset of chunk aligned rows and/or columns from a 2-dimensional array. E.g.:
 

docs/user-guide/consolidated_metadata.md

@@ -17,7 +17,7 @@ If consolidated metadata is present in a Zarr Group's metadata then it is used
 by default.  The initial read to open the group will need to communicate with
 the store (reading from a file for a [`zarr.storage.LocalStore`][], making a
 network request for a [`zarr.storage.FsspecStore`][]). After that, any subsequent
-metadata reads get child Group or Array nodes will *not* require reads from the store.
+metadata reads to get child Group or Array nodes will *not* require reads from the store.
 
 In Python, the consolidated metadata is available on the `.consolidated_metadata`
 attribute of the `GroupMetadata` object.
@@ -49,7 +49,7 @@ print(result)
 ```
 
 If we open that group, the Group's metadata has a `zarr.core.group.ConsolidatedMetadata`
-that can be used.:
+that can be used:
 
 ```python exec="true" session="consolidated_metadata" source="above" result="ansi"
 from pprint import pprint
@@ -58,19 +58,19 @@ import io
 consolidated = zarr.open_group(store="memory://consolidated-metadata-demo")
 consolidated_metadata = consolidated.metadata.consolidated_metadata.metadata
 
-# Note: pprint can be users without capturing the output regularly
+# Note: pprint can be used without capturing the output regularly
 output = io.StringIO()
 pprint(dict(sorted(consolidated_metadata.items())), stream=output, width=60)
 print(output.getvalue())
 ```
 
-Operations on the group to get children automatically use the consolidated metadata.:
+Operations on the group to get children automatically use the consolidated metadata:
 
 ```python exec="true" session="consolidated_metadata" source="above" result="ansi"
 print(consolidated['a'])  # no read / HTTP request to the Store is required
 ```
 
-With nested groups, the consolidated metadata is available on the children, recursively.:
+With nested groups, the consolidated metadata is available on the children, recursively:
 
 ```python exec="true" session="consolidated_metadata" source="above" result="ansi"
 child = group.create_group('child', attributes={'kind': 'child'})

docs/user-guide/data_types.md

@@ -262,7 +262,7 @@ here, it's possible to create it yourself: see [Adding New Data Types](#adding-n
 
 ### Example Usage
 
-This section will demonstrates the basic usage of Zarr data types.
+This section will demonstrate the basic usage of Zarr data types.
 
 Create a `ZDType` from a native data type:
 

docs/user-guide/experimental.md

@@ -4,7 +4,7 @@ This section contains documentation for experimental Zarr Python features. The f
 
 ## `CacheStore`
 
-Zarr Python 3.1.4 adds [`zarr.experimental.cache_store.CacheStore`][] provides a dual-store caching implementation
+Zarr Python 3.1.4 adds [`zarr.experimental.cache_store.CacheStore`][], which provides a dual-store caching implementation
 that can be wrapped around any Zarr store to improve performance for repeated data access.
 This is particularly useful when working with remote stores (e.g., S3, HTTP) where network
 latency can significantly impact data access speed.

docs/user-guide/extending.md

@@ -78,11 +78,11 @@ Coming soon.
 
 ## Custom array buffers
 
-Zarr-python provides control over where and how arrays stored in memory through
+Zarr-python provides control over where and how arrays are stored in memory through
 [`zarr.abc.buffer.Buffer`][]. Currently both CPU (the default) and GPU implementations are
 provided (see [Using GPUs with Zarr](gpu.md) for more information). You can implement your own buffer
 classes by implementing the interface defined in [`zarr.abc.buffer.BufferPrototype`][].
 
 ## Other extensions
 
-In the future, Zarr will support writing custom custom data types and chunk grids.
+In the future, Zarr will support writing custom data types and chunk grids.

docs/user-guide/gpu.md

@@ -7,7 +7,7 @@ Zarr can use GPUs to accelerate your workload by running `zarr.Config.enable_gpu
     memory as the final stage of the codec pipeline. Data will still be read into
     or copied to host (CPU) memory for encoding and decoding.
 
-    In the future, codecs will be available compressing and decompressing data on
+    In the future, codecs will be available for compressing and decompressing data on
     the GPU, avoiding the need to move data between the host and device for
     compression and decompression.
 

docs/user-guide/groups.md

@@ -69,7 +69,7 @@ For more information on groups see the [`zarr.Group` API docs](../api/zarr/group
 ## Batch Group Creation
 
 You can also create multiple groups concurrently with a single function call. [`zarr.create_hierarchy`][] takes
-a [`zarr Storage instance`](../api/zarr/storage.md) instance and a dict of `key : metadata` pairs, parses that dict, and
+a [`zarr Storage`](../api/zarr/storage.md) instance and a dict of `key : metadata` pairs, parses that dict, and
 writes metadata documents to storage:
 
 ```python exec="true" session="groups" source="above" result="ansi"

docs/user-guide/performance.md

@@ -296,7 +296,7 @@ Zarr arrays and groups can be pickled, as long as the underlying store object ca
 pickled. With the exception of the `zarr.storage.MemoryStore`, any of the
 storage classes provided in the `zarr.storage` module can be pickled.
 
-If an array or group is backed by a persistent store such as the a `zarr.storage.LocalStore`,
+If an array or group is backed by a persistent store such as a `zarr.storage.LocalStore`,
 `zarr.storage.ZipStore` or `zarr.storage.FsspecStore` then the store data
 **are not** pickled. The only thing that is pickled is the necessary parameters to allow the store
 to re-open any underlying files or databases upon being unpickled.

docs/user-guide/storage.md

@@ -119,7 +119,7 @@ print(array)
 
 ### Remote Store
 
-The [`zarr.storage.FsspecStore`][] stores the contents of a Zarr hierarchy in following the same
+The [`zarr.storage.FsspecStore`][] stores the contents of a Zarr hierarchy following the same
 logical layout as the [`LocalStore`][zarr.storage.LocalStore], except the store is assumed to be on a remote storage system
 such as cloud object storage (e.g. AWS S3, Google Cloud Storage, Azure Blob Store). The
 [`zarr.storage.FsspecStore`][] is backed by [fsspec](https://filesystem-spec.readthedocs.io) and can support any backend
@@ -154,7 +154,7 @@ print(store)
 
 ### Memory Store
 
-The [`zarr.storage.MemoryStore`][] an in-memory store that allows for serialization of
+The [`zarr.storage.MemoryStore`][] is an in-memory store that allows for serialization of
 Zarr data (metadata and chunks) to a dictionary:
 
 ```python exec="true" session="storage" source="above" result="ansi"

docs/user-guide/v3_migration.md

@@ -126,7 +126,7 @@ The following sections provide details on breaking changes in Zarr-Python 3.
 
 ### The Store class
 
-The Store API has changed significant in Zarr-Python 3.
+The Store API has changed significantly in Zarr-Python 3.
 
 #### The base store class
 

src/zarr/api/asynchronous.py

@@ -933,10 +933,9 @@ async def create(
         and these values must be instances of [`zarr.abc.codec.ArrayArrayCodec`][], or a
         dict representations of [`zarr.abc.codec.ArrayArrayCodec`][].
 
-        For Zarr format 2, a "filter" can be any numcodecs codec; you should ensure that the
-        the order if your filters is consistent with the behavior of each filter.
+        For Zarr format 2, a "filter" can be any numcodecs codec; you should ensure that the order of your filters is consistent with the behavior of each filter.
 
-        The default value of ``"auto"`` instructs Zarr to use a default used based on the data
+        The default value of ``"auto"`` instructs Zarr to use a default based on the data
         type of the array and the Zarr format specified. For all data types in Zarr V3, and most
         data types in Zarr V2, the default filters are empty. The only cases where default filters
         are not empty is when the Zarr format is 2, and the data type is a variable-length data type like

src/zarr/core/array.py

@@ -181,7 +181,7 @@ class DefaultFillValue:
     A string like ``"auto"`` is ambiguous because such a string is a valid fill value for an array
     with a string data type.
     An instance of this class lies outside the space of valid fill values, which means it can
-    umambiguously express that the default fill value should be used.
+    unambiguously express that the default fill value should be used.
     """
 
 
@@ -1339,7 +1339,7 @@ def _iter_shard_keys(
         ------
         key: str
             The storage key of each shard in the selection or in case of no shard
-            present of each chunk although the latter case as technically incorrect.
+            present of each chunk although the latter case is technically incorrect.
         """
         # Iterate over the coordinates of chunks in chunk grid space.
         return _iter_shard_keys(
@@ -4079,7 +4079,7 @@ async def from_array(
         dict representations of [`zarr.abc.codec.ArrayArrayCodec`][].
 
         For Zarr format 2, a "filter" can be any numcodecs codec; you should ensure that the
-        the order if your filters is consistent with the behavior of each filter.
+        order of your filters is consistent with the behavior of each filter.
 
         The default value of ``"keep"`` instructs Zarr to infer ``filters`` from ``data``.
         If that inference is not possible, Zarr will fall back to the behavior specified by ``"auto"``,
@@ -4096,7 +4096,7 @@ async def from_array(
         filters are applied (if any are specified) and the data is serialized into bytes.
 
         For Zarr format 3, a "compressor" is a codec that takes a bytestream, and
-        returns another bytestream. Multiple compressors my be provided for Zarr format 3.
+        returns another bytestream. Multiple compressors may be provided for Zarr format 3.
 
         For Zarr format 2, a "compressor" can be any numcodecs codec. Only a single compressor may
         be provided for Zarr format 2.
@@ -4124,7 +4124,7 @@ async def from_array(
         Fill value for the array.
         If not specified, defaults to the fill value of the data array.
     order : {"C", "F"}, optional
-        The memory of the array (default is "C").
+        The memory order of the array (default is "C").
         For Zarr format 2, this parameter sets the memory order of the array.
         For Zarr format 3, this parameter is deprecated, because memory order
         is a runtime parameter for Zarr format 3 arrays. The recommended way to specify the memory
@@ -4326,9 +4326,9 @@ async def init_array(
         dict representations of [`zarr.abc.codec.ArrayArrayCodec`][].
 
         For Zarr format 2, a "filter" can be any numcodecs codec; you should ensure that the
-        the order if your filters is consistent with the behavior of each filter.
+        order of your filters is consistent with the behavior of each filter.
 
-        The default value of ``"auto"`` instructs Zarr to use a default used based on the data
+        The default value of ``"auto"`` instructs Zarr to use a default based on the data
         type of the array and the Zarr format specified. For all data types in Zarr V3, and most
         data types in Zarr V2, the default filters are empty. The only cases where default filters
         are not empty is when the Zarr format is 2, and the data type is a variable-length data type like
@@ -4354,7 +4354,7 @@ async def init_array(
     fill_value : Any, optional
         Fill value for the array.
     order : {"C", "F"}, optional
-        The memory of the array (default is "C").
+        The memory order of the array (default is "C").
         For Zarr format 2, this parameter sets the memory order of the array.
         For Zarr format 3, this parameter is deprecated, because memory order
         is a runtime parameter for Zarr format 3 arrays. The recommended way to specify the memory
@@ -4576,9 +4576,9 @@ async def create_array(
         dict representations of [`zarr.abc.codec.ArrayArrayCodec`][].
 
         For Zarr format 2, a "filter" can be any numcodecs codec; you should ensure that the
-        the order if your filters is consistent with the behavior of each filter.
+        order of your filters is consistent with the behavior of each filter.
 
-        The default value of ``"auto"`` instructs Zarr to use a default used based on the data
+        The default value of ``"auto"`` instructs Zarr to use a default based on the data
         type of the array and the Zarr format specified. For all data types in Zarr V3, and most
         data types in Zarr V2, the default filters are empty. The only cases where default filters
         are not empty is when the Zarr format is 2, and the data type is a variable-length data type like
@@ -4591,7 +4591,7 @@ async def create_array(
         filters are applied (if any are specified) and the data is serialized into bytes.
 
         For Zarr format 3, a "compressor" is a codec that takes a bytestream, and
-        returns another bytestream. Multiple compressors my be provided for Zarr format 3.
+        returns another bytestream. Multiple compressors may be provided for Zarr format 3.
         If no ``compressors`` are provided, a default set of compressors will be used.
         These defaults can be changed by modifying the value of ``array.v3_default_compressors``
         in [`zarr.config`][zarr.config].
@@ -4611,7 +4611,7 @@ async def create_array(
     fill_value : Any, optional
         Fill value for the array.
     order : {"C", "F"}, optional
-        The memory of the array (default is "C").
+        The memory order of the array (default is "C").
         For Zarr format 2, this parameter sets the memory order of the array.
         For Zarr format 3, this parameter is deprecated, because memory order
         is a runtime parameter for Zarr format 3 arrays. The recommended way to specify the memory