diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml new file mode 100644 index 0000000..04d4084 --- /dev/null +++ b/.github/workflows/test.yml @@ -0,0 +1,24 @@ +name: Linux Testing + +on: + push: + branches: [ main ] + pull_request: + branches: [ main ] + +jobs: + build: + runs-on: ubuntu-latest + strategy: + matrix: + python-version: ['3.10', '3.11', '3.12'] + steps: + - uses: actions/checkout@v4 + - name: Install dependencies + shell: "bash -l {0}" + run: | + pip install poetry + poetry install + - name: Test + run: | + poetry run pytest \ No newline at end of file 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..27532e4 100644 --- a/docs/usage_zarr_v2.md +++ b/docs/usage_zarr_v2.md @@ -100,6 +100,190 @@ print(ArraySpec.from_array(np.arange(10)).model_dump()) } """ ``` +### Flattening and unflattening Zarr hierarchies + +In the previous section we built a model of a Zarr hierarchy by defining `GroupSpec` and `ArraySpec` +instances, then providing those objects as `members` to the constructor of another `GroupSpec`. In +other words, with this approach we create "child nodes" and give those nodes to the "parent node", +recursively. + +Constructing deeply nested hierarchies this way can be tedious. +For this reason, `pydantic-zarr` supports an alternative representation of the Zarr +hierarchy in the form of a dictionary with `str` keys and `ArraySpec` / `GroupSpec` values, and +methods to convert to / from these dictionaries. + +#### Making a `GroupSpec` object from a flat hierarchy + +This example demonstrates how to create a `GroupSpec` from a `dict` representation of a Zarr hierarchy. + +```python +from pydantic_zarr.v2 import GroupSpec, ArraySpec +# other than the key representing the root path "", +# the keys must be valid paths in the Zarr storage hierarchy +# note that the `members` attribute is `None` for the `GroupSpec` instances in this `dict`. +tree = { + "": GroupSpec(members=None, attributes={"root": True}), + "/a": GroupSpec(members=None, attributes={"root": False}), + "/a/b": ArraySpec(shape=(10,10), dtype="uint8", chunks=(1,1)) + } + +print(GroupSpec.from_flat(tree).model_dump()) +""" +{ + 'zarr_version': 2, + 'attributes': {'root': True}, + 'members': { + 'a': { + 'zarr_version': 2, + 'attributes': {'root': False}, + 'members': { + 'b': { + 'zarr_version': 2, + 'attributes': {}, + 'shape': (10, 10), + 'chunks': (1, 1), + 'dtype': '|u1', + 'fill_value': 0, + 'order': 'C', + 'filters': None, + 'dimension_separator': '/', + 'compressor': None, + } + }, + } + }, +} +""" +``` + +#### flattening `GroupSpec` objects + +This is similar to the example above, except that we are working in reverse -- we are making the +flat `dict` from the `GroupSpec` object. + +```python +from pydantic_zarr.v2 import GroupSpec, ArraySpec +# other than the key representing the root path "", +# the keys must be valid paths in the Zarr storage hierarchy +# note that the `members` attribute is `None` for the `GroupSpec` instances in this `dict`. + +a_b = ArraySpec(shape=(10,10), dtype="uint8", chunks=(1,1)) +a = GroupSpec(members={'b': a_b}, attributes={"root": False}) +root = GroupSpec(members={'a': a}, attributes={"root": True}) + +print(root.to_flat()) +""" +{ + '': GroupSpec(zarr_version=2, attributes={'root': True}, members=None), + '/a': GroupSpec(zarr_version=2, attributes={'root': False}, members=None), + '/a/b': ArraySpec( + zarr_version=2, + attributes={}, + shape=(10, 10), + chunks=(1, 1), + dtype='|u1', + fill_value=0, + order='C', + filters=None, + dimension_separator='/', + compressor=None, + ), +} +""" +``` + +#### Implicit groups +`zarr-python` supports creating Zarr arrays or groups deep in the +hierarchy without explicitly creating the intermediate groups first. +`from_flat` models this behavior. For example, `{'/a/b/c': ArraySpec(...)}` implicitly defines the existence of a groups named `a` and `b` (which is contained in `a`). `from_flat` will create the expected `GroupSpec` object from such `dict` instances. + +```python +from pydantic_zarr.v2 import GroupSpec, ArraySpec +tree = {'/a/b/c': ArraySpec(shape=(1,), dtype='uint8', chunks=(1,))} +print(GroupSpec.from_flat(tree).model_dump()) +""" +{ + 'zarr_version': 2, + 'attributes': {}, + 'members': { + 'a': { + 'zarr_version': 2, + 'attributes': {}, + 'members': { + 'b': { + 'zarr_version': 2, + 'attributes': {}, + 'members': { + 'c': { + 'zarr_version': 2, + 'attributes': {}, + 'shape': (1,), + 'chunks': (1,), + 'dtype': '|u1', + 'fill_value': 0, + 'order': 'C', + 'filters': None, + 'dimension_separator': '/', + 'compressor': None, + } + }, + } + }, + } + }, +} +""" +``` + +## Comparing `GroupSpec` and `ArraySpec` models + +`GroupSpec` and `ArraySpec` both have `like` methods that take another `GroupSpec` or `ArraySpec` as an argument and return `True` (the models are like each other) or `False` (the models are not like each other). + +The `like` method works by converting both input models to `dict` via `pydantic.BaseModel.model_dump`, and comparing the `dict` representation of the models. This means that instances of two different subclasses of `GroupSpec`, which would not be considered equal according to the `==` operator, will be considered `like` if and only if they serialize to identical `dict` instances. + +The `like` method also takes keyword arguments `include` and `exclude`, which results in attributes being explicitly included or excluded from the model comparison. So it's possible to use `like` to check if two `ArraySpec` instances have the same `shape` and `dtype` by calling `array_a.like(array_b, include={'shape', 'dtype'})`. This is useful if you don't care about the compressor or filters and just want to ensure that you can safely write an in-memory array to a Zarr array. + +```python +from pydantic_zarr.v2 import ArraySpec, GroupSpec +import zarr +arr_a = ArraySpec(shape=(1,), dtype='uint8', chunks=(1,)) +arr_b = ArraySpec(shape=(2,), dtype='uint8', chunks=(1,)) # array with different shape + +print(arr_a.like(arr_b)) # False, because of mismatched shape +#> False + +print(arr_a.like(arr_b, exclude={'shape'})) # True, because we exclude shape. +#> True + +# `ArraySpec.like` will convert a zarr.Array to ArraySpec +store = zarr.MemoryStore() +arr_a_stored = arr_a.to_zarr(store, path='arr_a') # this is a zarr.Array + +print(arr_a.like(arr_a_stored)) # arr_a is like the zarr.Array version of itself +#> True + +print(arr_b.like(arr_a_stored)) # False, because of mismatched shape +#> False + +print(arr_b.like(arr_a_stored, exclude={'shape'})) # True, because we exclude shape. +#> True + +# the same thing thing for groups +g_a = GroupSpec(attributes={'foo': 10}, members={'a': arr_a, 'b': arr_b}) +g_b = GroupSpec(attributes={'foo': 11}, members={'a': arr_a, 'b': arr_b}) + +print(g_a.like(g_a)) # g_a is like itself +#> True + +print(g_a.like(g_b)) # False, because of mismatched attributes +#> False + +print(g_a.like(g_b, exclude={'attributes'})) # True, because we ignore attributes +#> True + +print(g_a.like(g_a.to_zarr(store, path='g_a'))) # g_a is like its zarr.Group counterpart +#> True +``` ## Using generic types @@ -132,7 +316,7 @@ 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 +335,7 @@ 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 """ # this passes validation diff --git a/mkdocs.yaml b/mkdocs.yaml index ae469dc..c7be668 100644 --- a/mkdocs.yaml +++ b/mkdocs.yaml @@ -30,14 +30,23 @@ nav: - About: index.md - Usage (Zarr V3): usage_zarr_v3.md - Usage (Zarr V2): usage_zarr_v2.md - - API: api/core.md + - API: + - core: api/core.md + - v2: api/v2.md + - v3: api/v3.md plugins: - mkdocstrings: handlers: python: options: - show_signature_annotations: true + docstring_style: numpy + members_order: source + separate_signature: true + filters: ["!^_"] + docstring_options: + ignore_init_summary: true + merge_init_into_class: true markdown_extensions: - pymdownx.highlight: diff --git a/poetry.lock b/poetry.lock index 1039749..f1cae87 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.7.0 and should not be changed by hand. 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"sha256:d287cb61019c4a0a0f386f76eeaa7f0b1160b1cb90cf96173a4b6cbc135df6e1"}, + {file = "zarr-2.17.0.tar.gz", hash = "sha256:6390a2b8af31babaab4c963efc45bf1da7f9500c9aafac193f84cf019a7c66b0"}, ] [package.dependencies] asciitree = "*" -fasteners = "*" +fasteners = {version = "*", markers = "sys_platform != \"emscripten\""} numcodecs = ">=0.10.0" -numpy = ">=1.20,<1.21.0 || >1.21.0" +numpy = ">=1.21.1" [package.extras] -docs = ["numcodecs[msgpack]", "numpydoc", "pydata-sphinx-theme", "sphinx", "sphinx-copybutton", "sphinx-design", "sphinx-issues", "sphinx-rtd-theme"] +docs = ["numcodecs[msgpack]", "numpydoc", "pydata-sphinx-theme", "sphinx", "sphinx-automodapi", "sphinx-copybutton", "sphinx-design", "sphinx-issues"] jupyter = ["ipytree (>=0.2.2)", "ipywidgets (>=8.0.0)", "notebook"] [[package]] @@ -1503,4 +1514,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p [metadata] lock-version = "2.0" python-versions = "^3.9" -content-hash = "87456c63f23652917476560a826a33a19f57a0ced105777a1d29098f567af5a0" +content-hash = "559a98ae01964c1ad957c1f5b4dbaa4da2e5a0043812a33e6cf9f5e38ad6816e" diff --git a/pyproject.toml b/pyproject.toml index 38bda3b..1f3068f 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "pydantic-zarr" -version = "0.5.1" +version = "0.5.2" description = "pydantic models for zarr" authors = ["Davis Vann Bennett "] readme = "README.md" @@ -17,8 +17,6 @@ pytest = "^7.3.1" pytest-cov = "^4.1.0" mypy = "^1.3.0" pre-commit = "^3.3.3" -black = "23.7.0" -ruff = "0.0.277" [tool.poetry.group.docs.dependencies] mkdocs = "^1.4.3" diff --git a/src/pydantic_zarr/core.py b/src/pydantic_zarr/core.py index 0d4e873..5fec358 100644 --- a/src/pydantic_zarr/core.py +++ b/src/pydantic_zarr/core.py @@ -1,5 +1,56 @@ +from __future__ import annotations +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] + +AccessMode: TypeAlias = Literal["w", "w+", "r", "a"] + class StrictBase(BaseModel): model_config = ConfigDict(frozen=True, extra="forbid") + + +def ensure_member_name(data: Any) -> str: + """ + If the input is a string, then ensure that it is a valid + name for a subnode in a zarr group + """ + if isinstance(data, str): + if "/" in data: + raise ValueError( + f'Strings containing "/" are invalid. Got {data}, which violates this rule.' + ) + if data in ("", ".", ".."): + raise ValueError(f"The string {data} is not a valid member name.") + return data + raise TypeError(f"Exected a str, got {type(data)}.") + + +def ensure_key_no_path(data: Any) -> Any: + if isinstance(data, Mapping): + [ensure_member_name(key) for key in data.keys()] + return data + + +def model_like( + a: BaseModel, b: BaseModel, exclude: IncEx = None, include: IncEx = None +) -> bool: + """ + A similarity check for a pair pydantic.BaseModel, parametrized over included or excluded fields. + + + """ + + a_dict = a.model_dump(exclude=exclude, include=include) + b_dict = b.model_dump(exclude=exclude, include=include) + + return a_dict == b_dict diff --git a/src/pydantic_zarr/v2.py b/src/pydantic_zarr/v2.py index ecdc874..b78e80c 100644 --- a/src/pydantic_zarr/v2.py +++ b/src/pydantic_zarr/v2.py @@ -2,26 +2,32 @@ from typing import ( Any, + Dict, Generic, Literal, Mapping, - Optional, TypeVar, Union, + cast, overload, ) from typing_extensions import Annotated -from pydantic import model_validator +from pydantic import AfterValidator, model_validator from pydantic.functional_validators import BeforeValidator -from zarr.storage import init_group, BaseStore +from zarr.storage import init_group, BaseStore, contains_group, contains_array import numcodecs import zarr import os import numpy as np import numpy.typing as npt from numcodecs.abc import Codec - -from pydantic_zarr.core import StrictBase +from zarr.errors import ContainsGroupError, ContainsArrayError +from pydantic_zarr.core import ( + IncEx, + StrictBase, + ensure_key_no_path, + model_like, +) TAttr = TypeVar("TAttr", bound=Mapping[str, Any]) TItem = TypeVar("TItem", bound=Union["GroupSpec", "ArraySpec"]) @@ -29,18 +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 @@ -48,38 +53,59 @@ 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 "." + if data in ("/", "."): + return data + raise ValueError(f'Invalid data, expected one of ("/", ".", None), got {data}') CodecDict = Annotated[dict[str, Any], BeforeValidator(dictify_codec)] -class NodeSpecV2(StrictBase): +class NodeSpec(StrictBase): """ - The base class for V2 ArraySpec and GroupSpec. + The base class for V2 `ArraySpec` and `GroupSpec`. Attributes ---------- @@ -91,47 +117,55 @@ class NodeSpecV2(StrictBase): zarr_version: Literal[2] = 2 -class ArraySpec(NodeSpecV2, Generic[TAttr]): +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 - fill_value: Union[None, int, float] = 0 - order: Union[Literal["C"], Literal["F"]] = "C" - filters: Optional[list[CodecDict]] = None - dimension_separator: Union[Literal["/"], Literal["."]] = "/" - compressor: Optional[CodecDict] = None + fill_value: int | float | None = 0 + order: Literal["C", "F"] = "C" + filters: list[CodecDict] | None = None + dimension_separator: Annotated[ + Literal["/", "."], BeforeValidator(parse_dimension_separator) + ] = "/" + compressor: CodecDict | None = None @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 = ( @@ -144,20 +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. - + **kwargs : Any + Additional keyword arguments are passed to `zarr.create`. 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") + overwrite = kwargs.pop("overwrite", False) + if kwargs.get("mode", "r").startswith("w"): + raise ValueError("Mode='w' is not supported yet") if self.compressor is not None: spec_dict["compressor"] = numcodecs.get_codec(spec_dict["compressor"]) if self.filters is not None: spec_dict["filters"] = [ numcodecs.get_codec(f) for f in spec_dict["filters"] ] - result = zarr.create(store=store, path=path, **spec_dict, overwrite=overwrite) + if contains_array(store, path): + extant_array = zarr.open_array(store, path=path, mode="r") + + if not self.like(extant_array): + if not overwrite: + msg = ( + f"An array already exists at path {path}. " + "That array is structurally dissimilar to the array you are trying to " + "store. Call to_zarr with overwrite=True to overwrite that array." + ) + raise ContainsArrayError(msg) + else: + if not overwrite: + # extant_array is read-only, so we make a new array handle that + # takes **kwargs + return zarr.open_array( + store=extant_array.store, path=extant_array.path, **kwargs + ) + result = zarr.create( + store=store, path=path, overwrite=overwrite, **spec_dict, **kwargs + ) result.attrs.put(attrs) return result + def like( + self, + other: ArraySpec | zarr.Array, + *, + include: IncEx = None, + exclude: IncEx = None, + ): + """ + 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, 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, 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, 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 + if isinstance(other, zarr.Array): + other_parsed = ArraySpec.from_zarr(other) + else: + other_parsed = other + + result = model_like(self, other_parsed, include=include, exclude=exclude) + return result + -class GroupSpec(NodeSpecV2, Generic[TAttr, TItem]): +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] - 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 - members: dict[str, TItem] = {} + attributes: TAttr = cast(TAttr, {}) + members: Annotated[dict[str, TItem] | None, AfterValidator(ensure_key_no_path)] = {} @classmethod - def from_zarr(cls, group: zarr.Group) -> "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. This occurs recursively, so the entire zarr hierarchy below a given - group can be represented as a 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. Returns ------- - An instance of GroupSpec that represents the structure of the zarr hierarchy. + An instance of GroupSpec that represents the structure of the Zarr hierarchy. """ result: GroupSpec[TAttr, TItem] - items = {} + attributes = group.attrs.asdict() + members = {} + + if depth < -1: + msg = ( + f"Invalid value for depth. Got {depth}, expected an integer " + "greater than or equal to -1." + ) + raise ValueError(msg) + if depth == 0: + return cls(attributes=attributes, members=None) + new_depth = max(depth - 1, -1) for name, item in group.items(): if isinstance(item, zarr.Array): # convert to dict before the final typed GroupSpec construction - _item = ArraySpec.from_zarr(item).model_dump() + item_out = ArraySpec.from_zarr(item).model_dump() elif isinstance(item, zarr.Group): # convert to dict before the final typed GroupSpec construction - _item = GroupSpec.from_zarr(item).model_dump() + item_out = GroupSpec.from_zarr(item, depth=new_depth).model_dump() else: msg = ( f"Unparseable object encountered: {type(item)}. Expected zarr.Array" @@ -285,48 +446,200 @@ def from_zarr(cls, group: zarr.Group) -> "GroupSpec[TAttr, TItem]": ) raise ValueError(msg) - items[name] = _item + members[name] = item_out - result = cls(attributes=group.attrs.asdict(), members=items) + result = cls(attributes=attributes, members=members) return result - def to_zarr(self, store: BaseStore, path: str, overwrite: bool = False): + 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 - raised. Defaults to False. + **kwargs : Any + Additional keyword arguments that will be passed to `zarr.create` for creating + sub-arrays. 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 `self`. + """ - spec_dict = self.model_dump() - # pop items because it's not a valid kwarg for init_group - spec_dict.pop("members") - # pop attrs because it's not a valid kwarg for init_group + spec_dict = self.model_dump(exclude={"members": True}) attrs = spec_dict.pop("attributes") - # weird that we have to call init_group before creating the group - init_group(store, overwrite=overwrite, path=path) - result = zarr.group(store=store, path=path, **spec_dict, overwrite=overwrite) + overwrite = kwargs.pop("overwrite", False) + if contains_group(store, path): + extant_group = zarr.group(store, path=path) + if not self.like(extant_group): + if not overwrite: + msg = ( + f"A group already exists at path {path}. " + "That group is structurally dissimilar to the group you are trying to store." + "Call to_zarr with overwrite=True to overwrite that group." + ) + raise ContainsGroupError(msg) + else: + if not overwrite: + # if the extant group is structurally identical to self, and overwrite is false, + # then just return the extant group + return extant_group + + elif contains_array(store, path) and not overwrite: + msg = ( + f"An array already exists at path {path}. " + "Call to_zarr with overwrite=True to overwrite the array." + ) + raise ContainsArrayError(msg) + else: + init_group(store=store, overwrite=overwrite, path=path) + + result = zarr.group(store=store, path=path, overwrite=overwrite) result.attrs.put(attrs) - for name, member in self.members.items(): - subpath = os.path.join(path, name) - member.to_zarr(store, subpath, overwrite=overwrite) + # consider raising an exception if a partial GroupSpec is provided + if self.members is not None: + for name, member in self.members.items(): + subpath = os.path.join(path, name) + member.to_zarr(store, subpath, overwrite=overwrite, **kwargs) return result + def like( + self, + other: GroupSpec | zarr.Group, + 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. + + Parameters + ---------- + other: GroupSpec | zarr.Group + 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, 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 + if isinstance(other, zarr.Group): + other_parsed = GroupSpec.from_zarr(other) + else: + other_parsed = other + + result = model_like(self, other_parsed, include=include, exclude=exclude) + return result + + def to_flat(self, root_path: str = ""): + """ + Flatten this `GroupSpec`. + This method returns a `dict` with string keys and values that are `GroupSpec` or + `ArraySpec`. + + 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 `node.to_flat` 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 + --------- + root_path: `str`, default = ''. + The root path. The keys in `self.members` will be + made relative to `root_path` when used as keys in the result dictionary. + + Returns + ------- + Dict[str, ArraySpec | GroupSpec] + A flattened representation of the hierarchy. + + Examples + -------- + + >>> from pydantic_zarr.v2 import to_flat, GroupSpec + >>> g1 = GroupSpec(members=None, attributes={'foo': 'bar'}) + >>> to_flat(g1) + {'': GroupSpec(zarr_version=2, attributes={'foo': 'bar'}, members=None)} + >>> to_flat(g1 root_path='baz') + {'baz': GroupSpec(zarr_version=2, attributes={'foo': 'bar'}, members=None)} + >>> to_flat(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)} + """ + return to_flat(self, root_path=root_path) + + @classmethod + def from_flat(cls, data: Dict[str, ArraySpec | GroupSpec]): + """ + 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=' GroupSpec: @@ -338,46 +651,39 @@ def from_zarr(element: zarr.Array) -> ArraySpec: ... -def from_zarr(element: Union[zarr.Array, zarr.Group]) -> Union[ArraySpec, GroupSpec]: +def from_zarr( + element: zarr.Array | zarr.Group, depth: int = -1 +) -> 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): result = ArraySpec.from_zarr(element) + return result elif isinstance(element, zarr.Group): - members = {} - for name, member in element.items(): - if isinstance(member, zarr.Array): - _item = ArraySpec.from_zarr(member) - elif isinstance(member, zarr.Group): - _item = GroupSpec.from_zarr(member) - else: - msg = ( - f"Unparseable object encountered: {type(member)}. Expected " - "zarr.Array or zarr.Group.", - ) - raise ValueError(msg) - members[name] = _item - - result = GroupSpec(attributes=element.attrs.asdict(), members=members) + result = GroupSpec.from_zarr(element, depth=depth) return result - else: - msg = ( - f"Object of type {type(element)} cannot be processed by this function. " - "This function can only parse zarr.Group or zarr.Array" - ) - raise ValueError(msg) - return result + msg = ( + f"Object of type {type(element)} cannot be processed by this function. " + "This function can only parse zarr.Group or zarr.Array" + ) + raise TypeError(msg) @overload @@ -385,7 +691,7 @@ def to_zarr( spec: ArraySpec, store: BaseStore, path: str, - overwrite: bool = False, + **kwargs, ) -> zarr.Array: ... @@ -395,52 +701,232 @@ def to_zarr( spec: GroupSpec, store: BaseStore, path: str, - overwrite: bool = False, + **kwargs, ) -> zarr.Group: ... def to_zarr( - spec: Union[ArraySpec, GroupSpec], + spec: ArraySpec | GroupSpec, store: BaseStore, path: str, - overwrite: bool = False, -) -> Union[zarr.Array, zarr.Group]: + **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): - result = spec.to_zarr(store, path, overwrite=overwrite) + result = spec.to_zarr(store, path, **kwargs) elif isinstance(spec, GroupSpec): - result = spec.to_zarr(store, path, overwrite=overwrite) + 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) return result + + +def to_flat( + node: ArraySpec | GroupSpec, root_path: str = "" +) -> Dict[str, ArraySpec | GroupSpec]: + """ + Flatten a `GroupSpec` or `ArraySpec`. + Converts a `GroupSpec` or `ArraySpec` and a string, into a `dict` with string keys and + values that are `GroupSpec` or `ArraySpec`. + + 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. + root_path: `str`, default = ''. + The root path. If `node` is a `GroupSpec`, then the keys in `node.members` will be + made relative to `root_path` when used as keys in the result dictionary. + + Returns + ------- + 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'}) + >>> to_flat(g1) + {'': GroupSpec(zarr_version=2, attributes={'foo': 'bar'}, members=None)} + >>> to_flat(g1 root_path='baz') + {'baz': GroupSpec(zarr_version=2, attributes={'foo': 'bar'}, members=None)} + >>> to_flat(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: 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(to_flat(value, "/".join([root_path, name]))) + + result[root_path] = model_copy + # sort by increasing key length + result_sorted_keys = dict(sorted(result.items(), key=lambda v: len(v[0]))) + return result_sorted_keys + + +def from_flat(data: Dict[str, ArraySpec | GroupSpec]) -> ArraySpec | GroupSpec: + """ + Wraps `from_flat_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 from_flat, GroupSpec, ArraySpec + >>> import numpy as np + >>> tree = {'': ArraySpec.from_array(np.arange(10))} + >>> from_flat(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))} + >>> from_flat(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 from_flat_group(data) + + +def from_flat_group(data: Dict[str, ArraySpec | GroupSpec]) -> GroupSpec: + """ + 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 from_flat_group, GroupSpec, ArraySpec + >>> import numpy as np + >>> tree = {'/foo': ArraySpec.from_array(np.arange(10))} + >>> from_flat_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[TAttr, TItem]": + def from_zarr(cls, group: zarr.Group) -> 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, @@ -318,7 +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_core.py b/tests/test_core.py new file mode 100644 index 0000000..193634c --- /dev/null +++ b/tests/test_core.py @@ -0,0 +1,9 @@ +import pytest + +from pydantic_zarr.core import ensure_member_name + + +@pytest.mark.parametrize("data", ["/", "///", "a/b/", "a/b/vc"]) +def test_parse_str_no_path(data) -> None: + with pytest.raises(ValueError, match='Strings containing "/" are invalid.'): + ensure_member_name(data) diff --git a/tests/test_v2.py b/tests/test_v2.py index 40ebc7c..cf52cc3 100644 --- a/tests/test_v2.py +++ b/tests/test_v2.py @@ -1,11 +1,18 @@ from pydantic import ValidationError import pytest import zarr -from zarr.errors import ContainsGroupError +from zarr.errors import ContainsGroupError, ContainsArrayError from typing import Any, Literal, Union, Optional import numcodecs from numcodecs.abc import Codec -from pydantic_zarr.v2 import ArraySpec, GroupSpec, to_zarr, from_zarr +from pydantic_zarr.v2 import ( + ArraySpec, + GroupSpec, + to_flat, + to_zarr, + from_zarr, + from_flat, +) import numpy as np import numpy.typing as npt import sys @@ -55,7 +62,8 @@ def test_array_spec( compressor=compressor, filters=_filters, ) - array.attrs.put({"foo": [100, 200, 300], "bar": "hello"}) + attributes = {"foo": [100, 200, 300], "bar": "hello"} + array.attrs.put(attributes) spec = ArraySpec.from_zarr(array) assert spec.zarr_version == array._version @@ -101,6 +109,35 @@ def test_array_spec( assert spec.shape == array2.shape assert spec.fill_value == array2.fill_value + # test serialization + store = zarr.MemoryStore() + stored = spec.to_zarr(store, path="foo") + assert ArraySpec.from_zarr(stored) == spec + + # test that to_zarr is idempotent + assert spec.to_zarr(store, path="foo") == stored + + # test that to_zarr raises if the extant array is different + spec_2 = spec.model_copy(update={"attributes": {"baz": 10}}) + with pytest.raises(ContainsArrayError): + spec_2.to_zarr(store, path="foo") + + # test that we can overwrite the dissimilar array + stored_2 = spec_2.to_zarr(store, path="foo", overwrite=True) + assert ArraySpec.from_zarr(stored_2) == spec_2 + + # test that mode and write_empty_chunks get passed through + assert spec_2.to_zarr(store, path="foo", mode="a").read_only is False + assert spec_2.to_zarr(store, path="foo", mode="r").read_only is True + assert ( + spec_2.to_zarr(store, path="foo", write_empty_chunks=False)._write_empty_chunks + is False + ) + assert ( + spec_2.to_zarr(store, path="foo", write_empty_chunks=True)._write_empty_chunks + is True + ) + @pytest.mark.parametrize("array", (np.arange(10), np.zeros((10, 10), dtype="uint8"))) def test_array_spec_from_array(array: npt.NDArray[Any]): @@ -201,9 +238,18 @@ class ArrayAttrs(TypedDict): observed = from_zarr(group) assert observed == spec - # check that we can't overwrite the original group + # assert that we get the same group twice + assert to_zarr(spec, store, "/group_a") == group + + # check that we can't call to_zarr targeting the original group with a different spec + spec_2 = spec.model_copy(update={"attributes": RootAttrs(foo=99, bar=[0, 1, 2])}) with pytest.raises(ContainsGroupError): - group = to_zarr(spec, store, "/group_a") + _ = to_zarr(spec_2, store, "/group_a") + + # check that we can't call to_zarr with the original spec if the group has changed + group.attrs.put({"foo": 100}) + with pytest.raises(ContainsGroupError): + _ = to_zarr(spec, store, "/group_a") # materialize again with overwrite group2 = to_zarr(spec, store, "/group_a", overwrite=True) @@ -288,6 +334,7 @@ class ArrayAttrsB(TypedDict): GroupA.from_zarr(groupAMat) GroupB.from_zarr(groupBMat) + ArrayA.from_zarr(groupAMat["a"]) ArrayB.from_zarr(groupBMat["a"]) @@ -320,3 +367,126 @@ def test_from_array(shape, dtype): spec2 = ArraySpec.from_array(template, chunks=chunks, attributes=attrs) assert spec2.chunks == chunks assert spec2.attributes == attrs + + +@pytest.mark.parametrize("data", ["/", "a/b/c"]) +def test_member_name(data: str): + with pytest.raises(ValidationError, match='Strings containing "/" are invalid.'): + GroupSpec(attributes={}, members={data: GroupSpec(attributes={}, members={})}) + + +@pytest.mark.parametrize( + ("data, expected"), + [ + ( + ArraySpec.from_array(np.arange(10)), + {"": ArraySpec.from_array(np.arange(10))}, + ), + ( + GroupSpec( + attributes={"foo": 10}, + members={ + "a": ArraySpec.from_array(np.arange(5), attributes={"foo": 100}) + }, + ), + { + "": GroupSpec(attributes={"foo": 10}, members=None), + "/a": ArraySpec.from_array(np.arange(5), attributes={"foo": 100}), + }, + ), + ( + GroupSpec( + attributes={}, + members={ + "a": GroupSpec( + attributes={"foo": 10}, + members={ + "a": ArraySpec.from_array( + np.arange(5), attributes={"foo": 100} + ) + }, + ), + "b": ArraySpec.from_array(np.arange(2), attributes={"foo": 3}), + }, + ), + { + "": 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}), + }, + ), + ], +) +def test_flatten_unflatten(data, expected) -> None: + flattened = to_flat(data) + assert flattened == expected + assert from_flat(flattened) == data + + +# todo: parametrize +def test_array_like() -> None: + a = ArraySpec.from_array(np.arange(10)) + assert a.like(a) + + b = a.model_copy(update={"dtype": "uint8"}) + assert not a.like(b) + assert a.like(b, exclude={"dtype"}) + assert a.like(b, include={"shape"}) + + c = a.model_copy(update={"shape": (100, 100)}) + assert not a.like(c) + assert a.like(c, exclude={"shape"}) + assert a.like(c, include={"dtype"}) + + +# todo: parametrize +def test_group_like() -> None: + tree = { + "": 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"}), + } + group = GroupSpec.from_flat(tree) + assert group.like(group) + assert not group.like(group.model_copy(update={"attributes": None})) + assert group.like( + group.model_copy(update={"attributes": None}), exclude={"attributes"} + ) + 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