From 4b9f7ce7b96c532e1b70c12e21f68adc32b3705d Mon Sep 17 00:00:00 2001 From: Davis Vann Bennett Date: Tue, 27 Feb 2024 21:36:56 -0500 Subject: [PATCH] better docstrings, better docs --- docs/api/v2.md | 1 + docs/api/v3.md | 1 + docs/usage_zarr_v2.md | 4 +- mkdocs.yaml | 13 +- poetry.lock | 1073 +++++++++++++++++++------------------ src/pydantic_zarr/core.py | 10 +- src/pydantic_zarr/v2.py | 498 +++++++++++------ src/pydantic_zarr/v3.py | 7 +- tests/test_v2.py | 42 +- 9 files changed, 949 insertions(+), 700 deletions(-) create mode 100644 docs/api/v2.md create mode 100644 docs/api/v3.md diff --git a/docs/api/v2.md b/docs/api/v2.md new file mode 100644 index 0000000..63ef8fb --- /dev/null +++ b/docs/api/v2.md @@ -0,0 +1 @@ +::: pydantic_zarr.v2 \ No newline at end of file diff --git a/docs/api/v3.md b/docs/api/v3.md new file mode 100644 index 0000000..4934fa4 --- /dev/null +++ b/docs/api/v3.md @@ -0,0 +1 @@ +::: pydantic_zarr.v3 \ No newline at end of file diff --git a/docs/usage_zarr_v2.md b/docs/usage_zarr_v2.md index 0ece84e..dc783db 100644 --- a/docs/usage_zarr_v2.md +++ b/docs/usage_zarr_v2.md @@ -132,7 +132,7 @@ except ValidationError as exc: 1 validation error for GroupSpec[GroupAttrs, ~TItem] attributes.b Input should be a valid integer, unable to parse string as an integer [type=int_parsing, input_value='foo', input_type=str] - For further information visit https://errors.pydantic.dev/2.4/v/int_parsing + For further information visit https://errors.pydantic.dev/2.6/v/int_parsing """ # this passes validation @@ -151,7 +151,7 @@ except ValidationError as exc: 1 validation error for GroupSpec[~TAttr, ArraySpec] members.foo Input should be a valid dictionary or instance of ArraySpec [type=model_type, input_value=GroupSpec(zarr_version=2,...tributes={}, members={}), input_type=GroupSpec] - For further information visit https://errors.pydantic.dev/2.4/v/model_type + For further information visit https://errors.pydantic.dev/2.6/v/model_type """ # 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import annotations -from typing import Any, Dict, Literal, Mapping, Set, TypeAlias, Union +from typing import ( + Any, + Dict, + Literal, + Mapping, + Set, + TypeAlias, + Union, +) from pydantic import BaseModel, ConfigDict IncEx: TypeAlias = Union[Set[int], Set[str], Dict[int, Any], Dict[str, Any], None] diff --git a/src/pydantic_zarr/v2.py b/src/pydantic_zarr/v2.py index 3d9b879..b9f42a4 100644 --- a/src/pydantic_zarr/v2.py +++ b/src/pydantic_zarr/v2.py @@ -8,6 +8,7 @@ Mapping, TypeVar, Union, + cast, overload, ) from typing_extensions import Annotated @@ -34,18 +35,17 @@ def stringify_dtype(value: npt.DTypeLike): """ - Convert a np.dtype object into a string + Convert a `numpy.dtype` object into a `str`. - Paramters + Parameters --------- - - value: DTypeLike + value: `npt.DTypeLike` Some object that can be coerced to a numpy dtype Returns ------- - A numpy dtype string representation of the input. + A numpy dtype string representation of `value`. """ return np.dtype(value).str @@ -53,35 +53,48 @@ def stringify_dtype(value: npt.DTypeLike): DtypeStr = Annotated[str, BeforeValidator(stringify_dtype)] -def dictify_codec(value: Union[dict[str, Any], Codec]) -> dict[str, Any]: +def dictify_codec(value: dict[str, Any] | Codec) -> dict[str, Any]: """ - Ensure that a numcodecs `Codec` is converted to a dict. If the input is not an - insance of `numcodecs.abc.Codec`, then it is assumed to be a dict with string keys + Ensure that a `numcodecs.abc.Codec` is converted to a `dict`. If the input is not an + insance of `numcodecs.abc.Codec`, then it is assumed to be a `dict` with string keys and it is returned unaltered. - Paramters + Parameters --------- - value : Union[dict[str, Any], numcodecs.abc.Codec] + value : dict[str, Any] | numcodecs.abc.Codec The value to be dictified if it is not already a dict. Returns ------- - - If the input was a `Codec`, then the result of calling `get_config()` on that - object is returned. This should be a dict with string keys. All other values pass - through unaltered. + dict[str, Any] + If the input was a `Codec`, then the result of calling `get_config()` on that + object is returned. This should be a dict with string keys. All other values pass + through unaltered. """ if isinstance(value, Codec): - result = value.get_config() - else: - result = value - return result + return value.get_config() + return value def parse_dimension_separator(data: Any) -> Literal["/", "."]: + """ + Parse the dimension_separator metadata as per the Zarr version 2 specification. + If the input is `None`, this returns ".". + If the input is either "." or "/", this returns it. + Otherwise, raises a ValueError. + + Parameters + ---------- + data: Any + The input data to parse. + + Returns + ------- + Literal["/", "."] + """ if data is None: - return "/" + return "." if data in ("/", "."): return data raise ValueError(f'Invalid data, expected one of ("/", ".", None), got {data}') @@ -92,7 +105,7 @@ def parse_dimension_separator(data: Any) -> Literal["/", "."]: class NodeSpec(StrictBase): """ - The base class for V2 ArraySpec and GroupSpec. + The base class for V2 `ArraySpec` and `GroupSpec`. Attributes ---------- @@ -106,32 +119,38 @@ class NodeSpec(StrictBase): class ArraySpec(NodeSpec, Generic[TAttr]): """ - A model of a Zarr Version 2 Array. + A model of a Zarr Version 2 Array. The specification for the data structure being modeled by + this class can be found in the + [Zarr specification](https://zarr.readthedocs.io/en/stable/spec/v2.html#arrays). Attributes ---------- - - attributes: TAttr - User-defined metadata associated with this array. - shape: Sequence[int] + attributes: TAttr, default = {} + User-defined metadata associated with this array. Should be JSON-serializable. + shape: tuple[int, ...] The shape of this array. dtype: str The data type of this array. - chunks: Sequence[int] + chunks: Tuple[int, ...] The chunk size for this array. - order: Union["C", "F"] + order: "C" | "F", default = "C" The memory order of this array. Must be either "C", which designates "C order", - or "F", which designates "F order". - fill_value: FillValue + AKA lexicographic ordering or "F", which designates "F order", AKA colexicographic ordering. + The default is "C". + fill_value: FillValue, default = 0 The fill value for this array. The default is 0. - compressor: Optional[CodecDict] - A JSON-serializable representation of a compression codec, or None. - dimension_separator: Union[".", "/"] - The character used for separating chunk keys for this array. Must be either "/" - or ".". The default is "/". + compressor: CodecDict | None + A JSON-serializable representation of a compression codec, or None. The default is None. + filters: List[CodecDict] | None, default = None + A list of JSON-serializable representations of compression codec, or None. + The default is None. + dimension_separator: "." | "/", default = "/" + The character used for partitioning the different dimensions of a chunk key. + Must be either "/" or ".", or absent, in which case it is interpreted as ".". + The default is "/". """ - attributes: TAttr + attributes: TAttr = cast(TAttr, {}) shape: tuple[int, ...] chunks: tuple[int, ...] dtype: DtypeStr @@ -146,7 +165,7 @@ class ArraySpec(NodeSpec, Generic[TAttr]): @model_validator(mode="after") def check_ndim(self): """ - Check that the length of shape and chunks matches. + Check that the `shape` and `chunks` and attributes have the same length. """ if (lshape := len(self.shape)) != (lchunks := len(self.chunks)): msg = ( @@ -159,20 +178,31 @@ def check_ndim(self): @classmethod def from_array(cls, array: npt.NDArray[Any], **kwargs): """ - Create an ArraySpec from a numpy array-like object. + Create an `ArraySpec` from a numpy array-like object. Parameters ---------- - array : object that conforms to the numpy array API. - The shape and dtype of this object will be used to construct an ArraySpec. - If the `chunks` keyword argument is not given, the shape of the array will + array : an array-like object. + Must have `shape` and `dtype` attributes. + The `shape` and `dtype` of this object will be used to construct an `ArraySpec`. + If the `chunks` keyword argument is not given, the `shape` of the array will be used for the chunks. - - **kwargs : keyword arguments to the ArraySpec class constructor. + **kwargs + Keyword arguments passed to the `ArraySpec` constructor. Returns ------- - An instance of ArraySpec with properties derived from the provided array. + ArraySpec + An instance of `ArraySpec` with `shape` and `dtype` attributes derived from `array`. + + Examples + -------- + >>> from pydantic_zarr.v2 import ArraySpec + >>> import numpy as np + >>> x = ArraySpec.from_array(np.arange(10)) + >>> x + ArraySpec(zarr_version=2, attributes={}, shape=(10,), chunks=(10,), dtype='>> import zarr + >>> from pydantic_zarr.v2 import ArraySpec + >>> x = zarr.create((10,10)) + >>> ArraySpec.from_zarr(x) + ArraySpec(zarr_version=2, attributes={}, shape=(10, 10), chunks=(10, 10), dtype=' zarr.Array: """ - Serialize an ArraySpec to a zarr array at a specific path in a zarr store. + Serialize an `ArraySpec` to a Zarr array at a specific path in a Zarr store. This operation + will create metadata documents in the store, but will not write any chunks. Parameters ---------- store : instance of zarr.BaseStore The storage backend that will manifest the array. - path : str The location of the array inside the store. - overwrite : bool Whether to overwrite an existing array or group at the path. If overwrite is - False and an array or group already exists at the path, an exception will be - raised. Defaults to False. + `False` and an array or group already exists at `path`, an exception will be + raised. The default is `False`. Returns ------- - A zarr array that is structurally identical to the ArraySpec. - This operation will create metadata documents in the store. + zarr.Array + A Zarr array that is structurally identical to `self`. """ spec_dict = self.model_dump() attrs = spec_dict.pop("attributes") @@ -254,34 +291,52 @@ def to_zarr( def like( self, other: ArraySpec | zarr.Array, + *, include: IncEx = None, exclude: IncEx = None, ): """ - Compare a GroupSpec to another GroupSpec or a Zarr group, parameterized over the fields - to exclude or include in the comparison. Models are first converted to dict via the - `model_dump` method of pydantic.BaseModel, then compared with the `==` operator. + Compare am `ArraySpec` to another `ArraySpec` or a `zarr.Array`, parameterized over the + fields to exclude or include in the comparison. Models are first converted to `dict` via the + `model_dump` method of `pydantic.BaseModel`, then compared with the `==` operator. Parameters ---------- - other: ArraySpec | zarr.Array - The array (model or actual) to compare with. If other is a zarr.Array, it will be - converted to ArraySpec first. - include: IncEx - A specification of fields to include in the comparison. Default value is `None`, + The array (model or actual) to compare with. If other is a `zarr.Array`, it will be + converted to `ArraySpec` first. + include: IncEx, default = None + A specification of fields to include in the comparison. The default value is `None`, which means that all fields will be included. See the documentation of `pydantic.BaseModel.model_dump` for more details. - exclude: IncEx - A specification of fields to exclude from the comparison. Default value is `None`, + exclude: IncEx, default = None + A specification of fields to exclude from the comparison. The default value is `None`, which means that no fields will be excluded. See the documentation of `pydantic.BaseModel.model_dump` for more details. Returns ------- - bool - `True` if the two models have identical fields, `False` otherwise. + `True` if the two models have identical fields, `False` otherwise, given + the set of fields specified by the `include` and `exclude` keyword arguments. + + Examples + -------- + >>> import zarr + >>> from pydantic_zarr.v2 import ArraySpec + >>> x = zarr.create((10,10)) + >>> x.attrs.put({'foo': 10}) + >>> x_model = ArraySpec.from_zarr(x) + >>> print(x_model.like(x_model)) # it is like itself. + True + >>> print(x_model.like(x)) + True + >>> y = zarr.create((10,10)) + >>> y.attrs.put({'foo': 11}) # x and y are the same, other than their attrs + >>> print(x_model.like(y)) + False + >>> print(x_model.like(y, exclude={'attributes'})) + True """ other_parsed: ArraySpec @@ -297,32 +352,45 @@ def like( class GroupSpec(NodeSpec, Generic[TAttr, TItem]): """ A model of a Zarr Version 2 Group. + The specification for the data structure being modeled by this + class can be found in the + [Zarr specification](https://zarr.readthedocs.io/en/stable/spec/v2.html#groups). Attributes ---------- - attributes: TAttr - The user-defined attributes of this group. - members: dict[str, TItem] | None - The members of this group. `members` is a dict with string keys and values that - must inherit from either ArraySpec or GroupSpec. + attributes: TAttr, default = {} + The user-defined attributes of this group. Should be JSON-serializable. + members: dict[str, TItem] | None, default = {} + The members of this group. `members` may be `None`, which models the condition + where the members are unknown, e.g., because they have not been discovered yet. + If `members` is not s`None`, then it must be a dict with string keys and values that + are either `ArraySpec` or `GroupSpec`. """ - attributes: TAttr + attributes: TAttr = cast(TAttr, {}) members: Annotated[dict[str, TItem] | None, AfterValidator(ensure_key_no_path)] = {} @classmethod - def from_zarr(cls, group: zarr.Group, depth: int = -1) -> "GroupSpec[TAttr, TItem]": + def from_zarr( + cls, group: zarr.Group, *, depth: int = -1 + ) -> "GroupSpec[TAttr, TItem]": """ - Create a GroupSpec from a Zarr group. Subgroups and arrays contained in the Zarr - group will be converted to instances of GroupSpec and ArraySpec, respectively, - and these spec instances will be stored in the .items attribute of the parent - GroupSpec. + Create a GroupSpec from an instance of `zarr.Group`. Subgroups and arrays contained in the + Zarr group will be converted to instances of `GroupSpec` and `ArraySpec`, respectively, + and these spec instances will be stored in the `members` attribute of the parent + `GroupSpec`. + + This is a recursive function, and the depth of recursion can be controlled by the `depth` + keyword argument. The default value for `depth` is -1, which directs this function to + traverse the entirety of a `zarr.Group`. This may be slow for large hierarchies, in which + case setting `depth` to a positive integer can limit how deep into the hierarchy the + recursion goes. Parameters ---------- - group : Zarr group - + group : zarr.Group + The Zarr group to model. depth: int An integer which may be no lower than -1. Determines how far into the tree to parse. @@ -365,16 +433,14 @@ def from_zarr(cls, group: zarr.Group, depth: int = -1) -> "GroupSpec[TAttr, TIte def to_zarr(self, store: BaseStore, path: str, **kwargs): """ - Serialize a GroupSpec to a zarr group at a specific path in a zarr store. - + Serialize this `GroupSpec` to a Zarr group at a specific path in a `zarr.BaseStore`. + This operation will create metadata documents in the store. Parameters ---------- - store : instance of zarr.BaseStore + store : zarr.BaseStore The storage backend that will manifest the group and its contents. - path : str The location of the group inside the store. - overwrite : bool Whether to overwrite an existing array or group at the path. If overwrite is False and an array or group already exists at the path, an exception will be @@ -382,8 +448,9 @@ def to_zarr(self, store: BaseStore, path: str, **kwargs): Returns ------- - A zarr group that is structurally identical to the GroupSpec. - This operation will create metadata documents in the store. + zarr.Group + A zarr group that is structurally identical to the GroupSpec. + """ spec_dict = self.model_dump(exclude={"members": True}) attrs = spec_dict.pop("attributes") @@ -395,8 +462,8 @@ def to_zarr(self, store: BaseStore, path: str, **kwargs): "Call to_zarr with overwrite=True to delete the existing group." ) raise ContainsGroupError(msg) - else: - init_group(store=store, overwrite=kwargs["overwrite"], path=path) + else: + init_group(store=store, overwrite=kwargs.get("overwrite", False), path=path) result = zarr.group(store=store, path=path, **kwargs) result.attrs.put(attrs) @@ -414,30 +481,50 @@ def like( exclude: IncEx = None, ): """ - Compare a GroupSpec to another GroupSpec or a Zarr group, parameterized over the fields - to exclude or include in the comparison. Models are first converted to dict via the - `model_dump` method of pydantic.BaseModel, then compared with the `==` operator. + Compare a `GroupSpec` to another `GroupSpec` or a `zarr.Group`, parameterized over the + fields to exclude or include in the comparison. Models are first converted to dict via the + `model_dump` method of `pydantic.BaseModel`, then compared with the `==` operator. Parameters ---------- - other: GroupSpec | zarr.Group - The group (model or actual) to compare with. If other is a zarr.Group, it will be - converted to GroupSpec first. - include: IncEx - A specification of fields to include in the comparison. Default value is `None`, + The group (model or actual) to compare with. If other is a `zarr.Group`, it will be + converted to a `GroupSpec`. + include: IncEx, default = None + A specification of fields to include in the comparison. The default is `None`, which means that all fields will be included. See the documentation of `pydantic.BaseModel.model_dump` for more details. - exclude: IncEx - A specification of fields to exclude from the comparison. Default value is `None`, + exclude: IncEx, default = None + A specification of fields to exclude from the comparison. The default is `None`, which means that no fields will be excluded. See the documentation of `pydantic.BaseModel.model_dump` for more details. Returns ------- - bool `True` if the two models have identical fields, `False` otherwise. + + Examples + -------- + >>> import zarr + >>> from pydantic_zarr.v2 import GroupSpec + >>> import numpy as np + >>> z1 = zarr.group(path='z1') + >>> z1a = z1.array(name='foo', data=np.arange(10)) + >>> z1_model = GroupSpec.from_zarr(z1) + >>> print(z1_model.like(z1_model)) # it is like itself + True + >>> print(z1_model.like(z1)) + True + >>> z2 = zarr.group(path='z2') + >>> z2a = z2.array(name='foo', data=np.arange(10)) + >>> print(z1_model.like(z2)) + True + >>> z2.attrs.put({'foo' : 100}) # now they have different attributes + >>> print(z1_model.like(z2)) + False + >>> print(z1_model.like(z2, exclude={'attributes'})) + True """ other_parsed: GroupSpec @@ -452,8 +539,32 @@ def like( @classmethod def from_flat(cls, data: Dict[str, ArraySpec | GroupSpec]): """ - Create a GroupSpec from a "flat" representation - (a dict mapping string paths to ArraySpec or GroupSpec instances) + Create a `GroupSpec` from a flat hierarchy representation. The flattened hierarchy is a + `dict` with the following constraints. Keys must be valid paths; values must + be `ArraySpec` or `GroupSpec` instances. + + Parameters + ---------- + data: Dict[str, ArraySpec | GroupSpec] + A flattened representation of a Zarr hierarchy. + + Returns + ------- + GroupSpec + A `GroupSpec` representation of the hierarchy. + + Examples + -------- + >>> from pydantic_zarr.v2 import GroupSpec, ArraySpec + >>> import numpy as np + >>> flat = {'': GroupSpec(attributes={'foo': 10}, members=None)} + >>> GroupSpec.from_flat(flat) + GroupSpec(zarr_version=2, attributes={'foo': 10}, members={}) + >>> flat = { + '': GroupSpec(attributes={'foo': 10}, members=None), + '/a': ArraySpec.from_array(np.arange(10))} + >>> GroupSpec.from_flat(flat) + GroupSpec(zarr_version=2, attributes={'foo': 10}, members={'a': ArraySpec(zarr_version=2, attributes={}, shape=(10,), chunks=(10,), dtype=' ArraySpec | GroupSpec: """ - Recursively parse a Zarr group or Zarr array into an untyped ArraySpec or GroupSpec. + Recursively parse a `zarr.Group` or `zarr.Array` into an `ArraySpec` or `GroupSpec`. Parameters - --------- - element : Union[zarr.Array, zarr.Group] + ---------- + element : zarr.Array | zarr.Group + The `zarr.Array` or `zarr.Group` to model. + depth: int, default = -1 + An integer which may be no lower than -1. If `element` is a `zarr.Group`, the `depth` + parameter determines how deeply the hierarchy defined by `element` will be parsed. + This argument has no effect if `element` is a `zarr.Array`. Returns ------- - An instance of GroupSpec or ArraySpec that represents the - structure of the zarr group or array. + ArraySpec | GroupSpec + An instance of `GroupSpec` or `ArraySpec` that models the structure of the input Zarr group + or array. """ if isinstance(element, zarr.Array): @@ -525,29 +642,27 @@ def to_zarr( **kwargs, ) -> zarr.Array | zarr.Group: """ - Serialize a GroupSpec or ArraySpec to a zarr group or array at a specific path in - a zarr store. + Serialize a `GroupSpec` or `ArraySpec` to a Zarr group or array at a specific path in + a Zarr store. Parameters ---------- - spec : GroupSpec or ArraySpec - The GroupSpec or ArraySpec that will be serialized to storage. - - store : instance of zarr.BaseStore - The storage backend that will manifest the group or array. - + spec : ArraySpec | GroupSpec + The `GroupSpec` or `ArraySpec` that will be serialized to storage. + store : zarr.BaseStore + The storage backend that will manifest the Zarr group or array modeled by `spec`. path : str - The location of the group or array inside the store. - + The location of the Zarr group or array inside the store. overwrite : bool - Whether to overwrite an existing array or group at the path. If overwrite is - False and an array or group already exists at the path, an exception will be - raised. Defaults to False. + Whether to overwrite an existing array or group at the path. If overwrite is + `False` and a Zarr array or group already exists at `path`, an exception will be + raised. Defaults to `False`. Returns ------- - A zarr Group or Array that is structurally equivalent to the spec object. - This operation will create metadata documents in the store. + zarr.Array | zarr.Group + A `zarr.Group` or `zarr.Array` that is structurally equivalent to `spec`. + This operation will create metadata documents in the store. """ if isinstance(spec, ArraySpec): @@ -556,8 +671,8 @@ def to_zarr( result = spec.to_zarr(store, path, **kwargs) else: msg = ( - "Invalid argument for spec. Expected an instance of GroupSpec or ", - f"ArraySpec, got {type(spec)} instead.", + "Invalid argument for spec. Expected an instance of `GroupSpec` or ", + f"`ArraySpec`, got {type(spec)} instead.", ) raise ValueError(msg) @@ -565,81 +680,145 @@ def to_zarr( def flatten( - node: ArraySpec | GroupSpec, path: str = "/" + node: ArraySpec | GroupSpec, root_path: str = "" ) -> Dict[str, ArraySpec | GroupSpec]: """ Flatten a `GroupSpec` or `ArraySpec`. - Takes a `GroupSpec` or `ArraySpec` and a string, and returns dictionary with string keys and values that are - `GroupSpec` or `ArraySpec`. If the input is an `ArraySpec`, then this function just returns the dict `{path: node}`. - If the input is a `GroupSpec`, then the resulting dictionary will contain a copy of the input with an empty `members` attribute - under the key `path`, as well as copies of the result of calling `flatten_node` on each member of the input, each under a key created by joining `path` with a '/` character - to the name of each member. + Takes a `GroupSpec` or `ArraySpec` and a string, and returns a `dict` with string keys and + values that are `GroupSpec` or `ArraySpec`. - Paramters + If the input is an `ArraySpec`, then this function just returns the dict `{root_path: node}`. + + If the input is a `GroupSpec`, then the resulting `dict` will contain a copy of the input + with a null `members` attribute under the key `root_path`, as well as copies of the result of + calling `flatten_node` on each element of `node.members`, each under a key created by joining + `root_path` with a '/` character to the name of each member, and so on recursively for each + sub-member. + + Parameters --------- node: `GroupSpec` | `ArraySpec` The node to flatten. - path: `str`, default is 'root' + root_path: `str`, default = ''. The root path. If the input is a `GroupSpec`, then the keys in `GroupSpec.members` will be made relative to `path` when used as keys in the result dictionary. Returns ------- - `Dict[str, GroupSpec | ArraySpec]` - + Dict[str, ArraySpec | GroupSpec] + A flattened representation of the hierarchy. + + Examples + -------- + + >>> from pydantic_zarr.v2 import flatten, GroupSpec + >>> g1 = GroupSpec(members=None, attributes={'foo': 'bar'}) + >>> flatten(g1) + {'': GroupSpec(zarr_version=2, attributes={'foo': 'bar'}, members=None)} + >>> flatten(g1 root_path='baz') + {'baz': GroupSpec(zarr_version=2, attributes={'foo': 'bar'}, members=None)} + >>> flatten(GroupSpec(members={'g1': g1}, attributes={'foo': 'bar'})) + {'/g1': GroupSpec(zarr_version=2, attributes={'foo': 'bar'}, members=None), '': GroupSpec(zarr_version=2, attributes={'foo': 'bar'}, members=None)} """ result = {} - model_copy: Union[ArraySpec, GroupSpec] + model_copy: ArraySpec | GroupSpec if isinstance(node, ArraySpec): model_copy = node.model_copy(deep=True) else: model_copy = node.model_copy(deep=True, update={"members": None}) if node.members is not None: for name, value in node.members.items(): - result.update(flatten(value, os.path.join(path, name))) + result.update(flatten(value, "/".join([root_path, name]))) - result[path] = model_copy + result[root_path] = model_copy return result -def unflatten(tree: Dict[str, ArraySpec | GroupSpec]) -> ArraySpec | GroupSpec: +def unflatten(data: Dict[str, ArraySpec | GroupSpec]) -> ArraySpec | GroupSpec: """ - Wraps unflatten_group, handling the special case where a zarr array is defined at the root of - a hierarchy and thus is not contained by a group. + Wraps `unflatten_group`, handling the special case where a Zarr array is defined at the root of + a hierarchy and thus is not contained by a Zarr group. + + Parameters + ---------- + + data: Dict[str, ArraySpec | GroupSpec] + A flat representation of a Zarr hierarchy. This is a `dict` with keys that are strings, + and values that are either `GroupSpec` or `ArraySpec` instances. + + Returns + ------- + ArraySpec | GroupSpec + The `ArraySpec` or `GroupSpec` representation of the input data. + + Examples + -------- + >>> from pydantic_zarr.v2 import unflatten, GroupSpec, ArraySpec + >>> import numpy as np + >>> tree = {'': ArraySpec.from_array(np.arange(10))} + >>> unflatten(tree) # special case of a Zarr array at the root of the hierarchy + ArraySpec(zarr_version=2, attributes={}, shape=(10,), chunks=(10,), dtype='>> tree = {'/foo': ArraySpec.from_array(np.arange(10))} + >>> unflatten(tree) # note that an implicit Group is created + GroupSpec(zarr_version=2, attributes={}, members={'foo': ArraySpec(zarr_version=2, attributes={}, shape=(10,), chunks=(10,), dtype=' 0: + msg = f'Invalid keys {invalid_keys} found in data. Keys may not end with the "/"" character' + raise ValueError(msg) + + if tuple(data.keys()) == ("",) and isinstance(tuple(data.values())[0], ArraySpec): + return tuple(data.values())[0] else: - return unflatten_group(tree) + return unflatten_group(data) def unflatten_group(data: Dict[str, ArraySpec | GroupSpec]) -> GroupSpec: """ - Generate a GroupSpec from a "flat" representation of a hierarchy, i.e. a dictionary with - string keys (paths) and ArraySpec / GroupSpec values (nodes). + Generate a `GroupSpec` from a flat representation of a hierarchy, i.e. a `dict` with + string keys (paths) and `ArraySpec` / `GroupSpec` values (nodes). + + Parameters + ---------- + data: Dict[str, ArraySpec | GroupSpec] + A flat representation of a Zarr hierarchy rooted at a Zarr group. + + Returns + ------- + GroupSpec + A `GroupSpec` that represents the hierarchy described by `data`. + + Examples + -------- + >>> from pydantic_zarr.v2 import unflatten_group, GroupSpec, ArraySpec + >>> import numpy as np + >>> tree = {'/foo': ArraySpec.from_array(np.arange(10))} + >>> unflatten_group(tree) # note that an implicit Group is created + GroupSpec(zarr_version=2, attributes={}, members={'foo': ArraySpec(zarr_version=2, attributes={}, shape=(10,), chunks=(10,), dtype=' GroupSpec: root_node = GroupSpec(attributes={}, members=None) # partition the tree (sans root node) into 2 categories: (arrays, groups + their members). - for key, value in data.items(): + for key, value in data_copy.items(): key_parts = key.split(sep) if key_parts[0] != root_name: - raise ValueError(f'Invalid path: {key} does not start with "{sep}".') + raise ValueError( + f'Invalid path: {key} does not start with "{root_name}{sep}".' + ) subparent_name = key_parts[1] - if len(key_parts) == 2: # this is an array or group that belongs to the group we are ultimately returning if isinstance(value, ArraySpec): @@ -661,7 +841,7 @@ def unflatten_group(data: Dict[str, ArraySpec | GroupSpec]) -> GroupSpec: else: if subparent_name not in submember_by_parent_name: submember_by_parent_name[subparent_name] = {} - submember_by_parent_name[subparent_name][sep] = value + submember_by_parent_name[subparent_name][root_name] = value else: # these are groups or arrays that belong to one of the member groups # not great that we repeat this conditional dict initialization diff --git a/src/pydantic_zarr/v3.py b/src/pydantic_zarr/v3.py index bc21680..9081b4c 100644 --- a/src/pydantic_zarr/v3.py +++ b/src/pydantic_zarr/v3.py @@ -11,6 +11,7 @@ Tuple, TypeVar, Union, + cast, overload, ) from zarr.storage import BaseStore @@ -107,7 +108,7 @@ class ArraySpec(NodeSpec, Generic[TAttr]): """ node_type: Literal["array"] = "array" - attributes: TAttr = {} + attributes: TAttr = cast(TAttr, {}) shape: Sequence[int] data_type: DtypeStr chunk_grid: NamedConfig # todo: validate this against shape @@ -205,7 +206,7 @@ class GroupSpec(NodeSpec, Generic[TAttr, TItem]): """ node_type: Literal["group"] = "group" - attributes: TAttr = {} + attributes: TAttr = cast(TAttr, {}) members: dict[str, TItem] = {} @classmethod @@ -317,7 +318,7 @@ def to_zarr( path : str The location of the group or array inside the store. overwrite : bool - Whether to overwrite an existing array or group at the path. If overwrite is + Whether to overwrite an existing array or group at the path. If overwrite is False and an array or group already exists at the path, an exception will be raised. Defaults to False. diff --git a/tests/test_v2.py b/tests/test_v2.py index d397acb..c1cc006 100644 --- a/tests/test_v2.py +++ b/tests/test_v2.py @@ -295,6 +295,7 @@ class ArrayAttrsB(TypedDict): GroupA.from_zarr(groupAMat) GroupB.from_zarr(groupBMat) + ArrayA.from_zarr(groupAMat["a"]) ArrayB.from_zarr(groupBMat["a"]) @@ -340,7 +341,7 @@ def test_member_name(data: str): [ ( ArraySpec.from_array(np.arange(10)), - {"/": ArraySpec.from_array(np.arange(10))}, + {"": ArraySpec.from_array(np.arange(10))}, ), ( GroupSpec( @@ -350,7 +351,7 @@ def test_member_name(data: str): }, ), { - "/": GroupSpec(attributes={"foo": 10}, members=None), + "": GroupSpec(attributes={"foo": 10}, members=None), "/a": ArraySpec.from_array(np.arange(5), attributes={"foo": 100}), }, ), @@ -370,7 +371,7 @@ def test_member_name(data: str): }, ), { - "/": GroupSpec(attributes={}, members=None), + "": GroupSpec(attributes={}, members=None), "/a": GroupSpec(attributes={"foo": 10}, members=None), "/a/a": ArraySpec.from_array(np.arange(5), attributes={"foo": 100}), "/b": ArraySpec.from_array(np.arange(2), attributes={"foo": 3}), @@ -403,7 +404,7 @@ def test_array_like() -> None: # todo: parametrize def test_group_like() -> None: tree = { - "/": GroupSpec(attributes={"path": "/"}, members=None), + "": GroupSpec(attributes={"path": ""}, members=None), "/a": GroupSpec(attributes={"path": "/a"}, members=None), "/b": ArraySpec.from_array(np.arange(10), attributes={"path": "/b"}), "/a/b": ArraySpec.from_array(np.arange(10), attributes={"path": "/a/b"}), @@ -417,3 +418,36 @@ def test_group_like() -> None: assert group.like( group.model_copy(update={"attributes": None}), include={"members"} ) + + +# todo: parametrize +def test_from_zarr_depth(): + tree = { + "": GroupSpec(members=None, attributes={"level": 0, "type": "group"}), + "/1": GroupSpec(members=None, attributes={"level": 1, "type": "group"}), + "/1/2": GroupSpec(members=None, attributes={"level": 2, "type": "group"}), + "/1/2/1": GroupSpec(members=None, attributes={"level": 3, "type": "group"}), + "/1/2/2": ArraySpec.from_array( + np.arange(20), attributes={"level": 3, "type": "array"} + ), + } + + store = zarr.MemoryStore() + group_out = GroupSpec.from_flat(tree).to_zarr(store, path="test") + group_in_0 = GroupSpec.from_zarr(group_out, depth=0) + assert group_in_0 == tree[""] + + group_in_1 = GroupSpec.from_zarr(group_out, depth=1) + assert group_in_1.attributes == tree[""].attributes + assert group_in_1.members["1"] == tree["/1"] + + group_in_2 = GroupSpec.from_zarr(group_out, depth=2) + assert group_in_2.members["1"].members["2"] == tree["/1/2"] + assert group_in_2.attributes == tree[""].attributes + assert group_in_2.members["1"].attributes == tree["/1"].attributes + + group_in_3 = GroupSpec.from_zarr(group_out, depth=3) + assert group_in_3.members["1"].members["2"].members["1"] == tree["/1/2/1"] + assert group_in_3.attributes == tree[""].attributes + assert group_in_3.members["1"].attributes == tree["/1"].attributes + assert group_in_3.members["1"].members["2"].attributes == tree["/1/2"].attributes