Zarr

Interface to zarr arrays

class ZarrArrayPath(file: Path | str, path: str | None = None)

Map to an array within a zarr store.

See zarr.open()

file: Path | str

Location of Zarr store file or directory

path: str | None = None

Path to array within hierarchical zarr store

open(**kwargs: dict) → Array

Open the zarr array at the provided path

classmethod from_iterable(spec: Sequence) → ZarrArrayPath

Construct a ZarrArrayPath specifier from an iterable, rather than kwargs

class ZarrJsonDict(*, type: Literal['zarr'], info: dict[str, str], file: str | None = None, path: str | None = None, dtype: str | None = None, value: list | None = None)

Round-trip Json-able version of a Zarr Array

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

to_array_input() → Array | ZarrArrayPath

Construct a ZarrArrayPath if file and path are present, otherwise a ZarrArray

model_config = {}

Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

class ZarrTyping

Static-typing companion for ZarrInterface.

constructors: ClassVar[tuple[ConstructorSpec, ...]] = (ConstructorSpec(fullname='zarr.creation.zeros', shape_arg=0, dtype_arg='dtype', mode='function'), ConstructorSpec(fullname='zarr.creation.ones', shape_arg=0, dtype_arg='dtype', mode='function'), ConstructorSpec(fullname='zarr.creation.empty', shape_arg=0, dtype_arg='dtype', mode='function'), ConstructorSpec(fullname='zarr.creation.full', shape_arg=0, dtype_arg='dtype', mode='function'))

Constructor calls whose return type the mypy plugin should refine.

classmethod emit_imports() → list[str]

import zarr and numpy!

classmethod emit_constructor_source(shape: tuple[int, ...], dtype: str) → str | None

array constructor using zarr.zeros()

class ZarrInterface(shape: tuple[int, ...] | Any = typing.Any, dtype: str | type | Any | generic = typing.Any)

Interface to in-memory or on-disk zarr arrays

return_type

alias of Array

json_model

alias of ZarrJsonDict

typing

alias of ZarrTyping

classmethod enabled() → bool

True if zarr is installed

classmethod check(array: Any) → bool

Check if array is in-memory zarr array, a path to a zarr array, or a ZarrArrayPath

before_validation(array: Array | str | Path | ZarrArrayPath | Sequence) → Array

Ensure that the zarr array is opened

get_dtype(array: Array) → str | type | Any | generic

Override base dtype getter to handle zarr’s string-as-object encoding.

classmethod to_json(array: Array | str | Path | ZarrArrayPath | Sequence, info: SerializationInfo | None = None) → list | ZarrJsonDict

Dump a Zarr Array to JSON

If info.round_trip == False, dump the array as a list of lists. This may be a memory-intensive operation.

Otherwise, dump the metadata for an array from zarr.core.Array.info_items() plus the zarr.core.Array.hexdigest() as a ZarrJsonDict

If either the dump_array value in the context dictionary is True or the zarr array is an in-memory array, dump the array as well (since without a persistent array it would be impossible to roundtrip and dumping to JSON would be meaningless)

Passing `dump_array': True to the serialization context looks like this:

model.model_dump_json(context={'zarr_dump_array': True})