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100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,49 +1,50 @@ [tool.poetry] name = "linkml-arrays" -version = "0.0.0" +version = "0.1.0" description = "linkml-arrays" -authors = ["Ryan Ly "] +authors = [ + "Ryan Ly ", + "Chris Mungall ", +] license = "BSD-3" readme = "README.md" [tool.poetry.dependencies] python = "^3.9" -linkml-runtime = ">=1.7.0" +linkml-runtime = ">=1.8.0" numpy = ">=1.24.3" h5py = ">=3.9.0" zarr = ">=2.16.1" -nptyping = ">=2.5.0" xarray = "^2024.1.1" -tox = "^3.25.1" # TODO move out of main deps +ruamel-yaml = "^0.18.6" +importlib_metadata = "*" [tool.poetry.dev-dependencies] -pytest = "^7.1.2" -sphinx = {version = "^5.3.0", extras = ["docs"]} -sphinx-rtd-theme = {version = "^1.0.0", extras = ["docs"]} -# sphinx-autodoc-typehints = {version = "^1.19.4", extras = ["docs"]} -sphinx-click = {version = "^4.3.0", extras = ["docs"]} -myst-parser = {version = "^0.18.1", extras = ["docs"]} -jupyter = {version = "*", extras = ["jupyter"]} - -[tool.poetry.scripts] -linkml-arrays = "linkml_arrays.cli:main" +pytest = "*" +tox = "*" +# sphinx = {version = "*", extras = ["docs"]} +# sphinx-rtd-theme = {version = "^1.0.0", extras = ["docs"]} +# # sphinx-autodoc-typehints = {version = "^1.19.4", extras = ["docs"]} +# sphinx-click = {version = "^4.3.0", extras = ["docs"]} +# myst-parser = {version = "*", extras = ["docs"]} +# jupyter = {version = "*", extras = ["jupyter"]} -[tool.poetry.extras] -docs = [ - "sphinx", - "sphinx-rtd-theme", - # "sphinx-autodoc-typehints", - "sphinx-click", - "myst-parser" -] -jupyter = [ - "jupyter" -] +# [tool.poetry.extras] +# docs = [ +# "sphinx", +# "sphinx-rtd-theme", +# "sphinx-autodoc-typehints", +# "sphinx-click", +# "myst-parser" +# ] +# jupyter = [ +# "jupyter" +# ] -[tool.poetry.group.dev.dependencies] -black = "^24.1.1" -pytest = "^7.1.2" -mypy = "^1.8.0" +# [tool.poetry.group.dev.dependencies] +# black = "^24.1.1" +# pytest = "^7.1.2" +# mypy = "^1.8.0" [tool.poetry-dynamic-versioning] enable = true @@ -52,7 +53,6 @@ style = "pep440" [tool.black] line-length = 100 -target-version = ["py38", "py39", "py310"] [tool.isort] profile = "black" diff --git a/src/linkml_arrays/cli.py b/src/linkml_arrays/cli.py deleted file mode 100644 index 04278f2..0000000 --- a/src/linkml_arrays/cli.py +++ /dev/null @@ -1,44 +0,0 @@ -"""Command line interface for linkml-arrays.""" - -import logging - -import click - -from linkml_arrays import __version__ -from linkml_arrays.main import demo - -__all__ = [ - "main", -] - -logger = logging.getLogger(__name__) - - -@click.group() -@click.option("-v", "--verbose", count=True) -@click.option("-q", "--quiet") -@click.version_option(__version__) -def main(verbose: int, quiet: bool): - """CLI for linkml-arrays. - - :param verbose: Verbosity while running. - :param quiet: Boolean to be quiet or verbose. - """ - if verbose >= 2: - logger.setLevel(level=logging.DEBUG) - elif verbose == 1: - logger.setLevel(level=logging.INFO) - else: - logger.setLevel(level=logging.WARNING) - if quiet: - logger.setLevel(level=logging.ERROR) - - -@main.command() -def run(): - """Run the linkml-arrays's demo command.""" - demo() - - -if __name__ == "__main__": - main() diff --git a/src/linkml_arrays/dumpers/hdf5_dumper.py b/src/linkml_arrays/dumpers/hdf5_dumper.py index 28e8bf0..eb50a03 100644 --- a/src/linkml_arrays/dumpers/hdf5_dumper.py +++ b/src/linkml_arrays/dumpers/hdf5_dumper.py @@ -1,5 +1,6 @@ """Class for dumping a LinkML model to an HDF5 file.""" +from pathlib import Path from typing import Union import h5py @@ -14,7 +15,7 @@ def _iterate_element( ): """Recursively iterate through the elements of a LinkML model and save them. - Writes Pydantic BaseModel objects as groups, slots that implement "linkml:elements" + Write Pydantic BaseModel objects as groups, slots with the "array" element as datasets, and other slots as attributes. """ # get the type of the element @@ -22,7 +23,7 @@ def _iterate_element( for k, v in vars(element).items(): found_slot = schemaview.induced_slot(k, element_type) - if "linkml:elements" in found_slot.implements: + if found_slot.array: # save the numpy array to an hdf5 dataset group.create_dataset(found_slot.name, data=v) else: @@ -39,16 +40,13 @@ class Hdf5Dumper(Dumper): """Dumper class for LinkML models to HDF5 files.""" # TODO is this the right method to overwrite? it does not dump a string - def dumps(self, element: Union[YAMLRoot, BaseModel], schemaview: SchemaView, **kwargs): - """Dump the element to an HDF5 file. - - Raises: - ValueError: If the class requires an identifier and it is not provided. - """ - id_slot = schemaview.get_identifier_slot(element.__class__.__name__) - if id_slot is None: - raise ValueError("The class requires an identifier.") - id_value = getattr(element, id_slot.name) - output_file_path = f"{id_value}.h5" + def dumps( + self, + element: Union[YAMLRoot, BaseModel], + schemaview: SchemaView, + output_file_path: Union[str, Path], + **kwargs, + ): + """Dump the element to an HDF5 file.""" with h5py.File(output_file_path, "w") as f: _iterate_element(element, schemaview, f) diff --git a/src/linkml_arrays/dumpers/yaml_array_file_dumper.py b/src/linkml_arrays/dumpers/yaml_array_file_dumper.py new file mode 100644 index 0000000..18f9807 --- /dev/null +++ b/src/linkml_arrays/dumpers/yaml_array_file_dumper.py @@ -0,0 +1,123 @@ +"""Base class for dumping a LinkML model to YAML with paths to files containing arrays.""" + +import os +from abc import ABCMeta, abstractmethod +from collections.abc import Callable +from pathlib import Path +from typing import List, Optional, Union + +import numpy as np +import yaml +from linkml_runtime import SchemaView +from linkml_runtime.dumpers.dumper_root import Dumper +from linkml_runtime.utils.yamlutils import YAMLRoot +from pydantic import BaseModel + + +def _iterate_element( + element: Union[YAMLRoot, BaseModel], + schemaview: SchemaView, + output_dir: Path, + write_array: Callable, + format: str, + parent_identifier=None, + inlined_name=None, +): + """Recursively iterate through the elements of a LinkML model and save them. + + Return a dictionary with the same structure as the input element, but where the slots + with the "array" element are written to an array file and the paths to these + files are returned in the dictionary. The paths are relative to the output directory. + + Raises: + ValueError: If the class requires an identifier and it is not provided. + """ + # get the type of the element + element_type = type(element).__name__ + + # ask schemaview whether it has a class by this name + found_class = schemaview.get_class(element_type) + + id_slot = schemaview.get_identifier_slot(found_class.name) + if id_slot is not None: + id_value = getattr(element, id_slot.name) + else: + id_value = None + + ret_dict = dict() + for k, v in vars(element).items(): + found_slot = schemaview.induced_slot(k, element_type) + if found_slot.array: + if id_slot is None and parent_identifier is None: + raise ValueError("The class requires an identifier.") + + # determine the output file name without the suffix + if id_slot is not None: + output_file_name = f"{id_value}.{found_slot.name}" + elif inlined_name is not None: + output_file_name = f"{parent_identifier}.{inlined_name}.{found_slot.name}" + elif parent_identifier is not None: + output_file_name = f"{parent_identifier}.{found_slot.name}" + else: + output_file_name = f"{found_slot.name}" + + # if output_dir is absolute, make it relative to current working directory + # and create the directory if it does not exist + if output_dir.is_absolute(): + output_dir = Path(os.path.relpath(output_dir, start=os.getcwd())) + output_dir.mkdir(exist_ok=True) + output_file_path_no_suffix = output_dir / output_file_name + + # save the numpy array to file and write the file path to the dictionary + output_file_path = write_array(v, output_file_path_no_suffix) + ret_dict[k] = { + "source": [ + { + "file": f"./{output_file_path}", + "format": format, + } + ] + } + else: + if isinstance(v, BaseModel): + v2 = _iterate_element( + v, + schemaview, + output_dir, + write_array, + format, + id_value, + inlined_name=found_slot.name, + ) + ret_dict[k] = v2 + else: + ret_dict[k] = v + return ret_dict + + +class YamlArrayFileDumper(Dumper, metaclass=ABCMeta): + """Base dumper class for LinkML models to YAML files with paths to array files.""" + + # FORMAT is a class attribute that must be set by subclasses + + def dumps( + self, + element: Union[YAMLRoot, BaseModel], + schemaview: SchemaView, + output_dir: Optional[Union[str, Path]] = None, + **kwargs, + ) -> str: + """Return element formatted as a YAML string.""" + if output_dir is None: + output_dir = "." + input = _iterate_element( + element, schemaview, Path(output_dir), self.write_array, self.FORMAT + ) + + return yaml.dump(input) + + @classmethod + @abstractmethod + def write_array(cls, array: Union[List, np.ndarray], output_file_path: Union[str, Path]): + """Write an array to a file.""" + raise NotImplementedError("Subclasses must implement this method.") diff --git a/src/linkml_arrays/dumpers/yaml_dumper.py b/src/linkml_arrays/dumpers/yaml_dumper.py index b007a15..891c870 100644 --- a/src/linkml_arrays/dumpers/yaml_dumper.py +++ b/src/linkml_arrays/dumpers/yaml_dumper.py @@ -1,4 +1,4 @@ -"""Class for dumpling a LinkML model to a YAML file.""" +"""Class for dumping a LinkML model to YAML.""" from typing import Union @@ -14,8 +14,8 @@ def _iterate_element( ): """Recursively iterate through the elements of a LinkML model and save them. - Returns a dictionary with the same structure as the input element, but with the slots - that implement "linkml:elements" (arrays) are written as lists or lists of lists. + Returns a dictionary with the same structure as the input element, but where the slots + with the "array" element are written as lists of lists in YAML. Raises: ValueError: If the class requires an identifier and it is not provided. @@ -35,10 +35,11 @@ def _iterate_element( ret_dict = dict() for k, v in vars(element).items(): found_slot = schemaview.induced_slot(k, element_type) - if "linkml:elements" in found_slot.implements: + if found_slot.array: if id_slot is None and parent_identifier is None: raise ValueError("The class requires an identifier.") - ret_dict[k] = v.tolist() + assert isinstance(v, list) + ret_dict[k] = v else: if isinstance(v, BaseModel): v2 = _iterate_element(v, schemaview, id_value) diff --git a/src/linkml_arrays/dumpers/yaml_hdf5_dumper.py b/src/linkml_arrays/dumpers/yaml_hdf5_dumper.py index 0d95fe8..95a46c5 100644 --- a/src/linkml_arrays/dumpers/yaml_hdf5_dumper.py +++ b/src/linkml_arrays/dumpers/yaml_hdf5_dumper.py @@ -1,70 +1,35 @@ -"""Class for dumping a LinkML model to a YAML file with paths to HDF5 files.""" +"""Class for dumping a LinkML model to YAML with paths to HDF5 files.""" -from typing import Union +from pathlib import Path +from typing import List, Union import h5py -import yaml -from linkml_runtime import SchemaView -from linkml_runtime.dumpers.dumper_root import Dumper -from linkml_runtime.utils.yamlutils import YAMLRoot -from pydantic import BaseModel +import numpy as np +from .yaml_array_file_dumper import YamlArrayFileDumper -def _iterate_element( - element: Union[YAMLRoot, BaseModel], schemaview: SchemaView, parent_identifier=None -): - """Recursively iterate through the elements of a LinkML model and save them. - Returns a dictionary with the same structure as the input element, but with the slots - that implement "linkml:elements" (arrays) are written to HDF5 files and the paths to these - files are returned in the dictionary. Each array is written to an HDF5 dataset at path - "/data" in a new HDF5 file. +class YamlHdf5Dumper(YamlArrayFileDumper): + """Dumper class for LinkML models to YAML with paths to HDF5 files, one per array. - Raises: - ValueError: If the class requires an identifier and it is not provided. + Each array is written to an HDF5 dataset at path "/data" in a new HDF5 file. """ - # get the type of the element - element_type = type(element).__name__ - # ask schemaview whether it has a class by this name - found_class = schemaview.get_class(element_type) - - id_slot = schemaview.get_identifier_slot(found_class.name) - if id_slot is not None: - id_value = getattr(element, id_slot.name) - else: - id_value = None - - ret_dict = dict() - for k, v in vars(element).items(): - found_slot = schemaview.induced_slot(k, element_type) - if "linkml:elements" in found_slot.implements: - if id_slot is None and parent_identifier is None: - raise ValueError("The class requires an identifier.") - # save the numpy array to file - if parent_identifier is not None: - output_file_path = f"{parent_identifier}.{found_class.name}.{found_slot.name}.h5" - else: - output_file_path = f"{found_class.name}.{found_slot.name}.h5" - with h5py.File( - output_file_path, "w" - ) as f: # TODO do not assume that there is only one by this name - f.create_dataset("data", data=v) - ret_dict[k] = f"file:./{output_file_path}" # TODO make this nicer - else: - if isinstance(v, BaseModel): - v2 = _iterate_element(v, schemaview, id_value) - ret_dict[k] = v2 - else: - ret_dict[k] = v - return ret_dict - - -class YamlHdf5Dumper(Dumper): - """Class for dumping a LinkML model to a YAML file with paths to HDF5 files.""" - - def dumps(self, element: Union[YAMLRoot, BaseModel], schemaview: SchemaView, **kwargs) -> str: - """Return element formatted as a YAML string.""" - input = _iterate_element(element, schemaview) - - return yaml.dump(input) + FILE_SUFFIX = ".h5" # used in parent class + FORMAT = "hdf5" + + @classmethod + def write_array( + cls, array: Union[List, np.ndarray], output_file_path_no_suffix: Union[str, Path] + ): + """Write an array to an HDF5 file.""" + # TODO do not assume that there is only one by this name + # add suffix to the file name + if isinstance(output_file_path_no_suffix, str): + output_file_path_no_suffix = Path(output_file_path_no_suffix) + output_file_path = output_file_path_no_suffix.parent / ( + output_file_path_no_suffix.name + cls.FILE_SUFFIX + ) + with h5py.File(output_file_path, "w") as f: + f.create_dataset("data", data=array) + return output_file_path diff --git a/src/linkml_arrays/dumpers/yaml_numpy_dumper.py b/src/linkml_arrays/dumpers/yaml_numpy_dumper.py index 71433be..62d4b6e 100644 --- a/src/linkml_arrays/dumpers/yaml_numpy_dumper.py +++ b/src/linkml_arrays/dumpers/yaml_numpy_dumper.py @@ -1,67 +1,34 @@ -"""Class for dumpling a LinkML model to a YAML file with paths to NumPy files.""" +"""Class for dumping a LinkML model to YAML with paths to NumPy files.""" -from typing import Union +from pathlib import Path +from typing import List, Union import numpy as np -import yaml -from linkml_runtime import SchemaView -from linkml_runtime.dumpers.dumper_root import Dumper -from linkml_runtime.utils.yamlutils import YAMLRoot -from pydantic import BaseModel +from .yaml_array_file_dumper import YamlArrayFileDumper -def _iterate_element( - element: Union[YAMLRoot, BaseModel], schemaview: SchemaView, parent_identifier=None -): - """Recursively iterate through the elements of a LinkML model and save them. - Returns a dictionary with the same structure as the input element, but with the slots - that implement "linkml:elements" (arrays) are written to HDF5 files and the paths to these - files are returned in the dictionary. Each array is written to an HDF5 dataset at path - "/data" in a new HDF5 file. +class YamlNumpyDumper(YamlArrayFileDumper): + """Dumper class for LinkML models to YAML with paths to .npy files, one per array. - Raises: - ValueError: If the class requires an identifier and it is not provided. + Each array is written to an HDF5 dataset at path "/data" in a new HDF5 file. """ - # get the type of the element - element_type = type(element).__name__ - # ask schemaview whether it has a class by this name - found_class = schemaview.get_class(element_type) - - id_slot = schemaview.get_identifier_slot(found_class.name) - if id_slot is not None: - id_value = getattr(element, id_slot.name) - else: - id_value = None - - ret_dict = dict() - for k, v in vars(element).items(): - found_slot = schemaview.induced_slot(k, element_type) - if "linkml:elements" in found_slot.implements: - if id_slot is None and parent_identifier is None: - raise ValueError("The class requires an identifier.") - # save the numpy array to file - if parent_identifier is not None: - output_file_path = f"{parent_identifier}.{found_class.name}.{found_slot.name}.npy" - else: - output_file_path = f"{found_class.name}.{found_slot.name}.npy" - np.save(output_file_path, v) # TODO do not assume that there is only one by this name - ret_dict[k] = f"file:./{output_file_path}" # TODO make this nicer - else: - if isinstance(v, BaseModel): - v2 = _iterate_element(v, schemaview, id_value) - ret_dict[k] = v2 - else: - ret_dict[k] = v - return ret_dict - - -class YamlNumpyDumper(Dumper): - """Dumper class for LinkML models to YAML files with paths to NumPy files.""" - - def dumps(self, element: Union[YAMLRoot, BaseModel], schemaview: SchemaView, **kwargs) -> str: - """Return element formatted as a YAML string.""" - input = _iterate_element(element, schemaview) - - return yaml.dump(input) + FILE_SUFFIX = ".npy" # used in parent class + FORMAT = "numpy" + + @classmethod + def write_array( + cls, array: Union[List, np.ndarray], output_file_path_no_suffix: Union[str, Path] + ): + """Write an array to a NumPy file.""" + # TODO do not assume that there is only one by this name + # add suffix to the file name + if isinstance(output_file_path_no_suffix, str): + output_file_path_no_suffix = Path(output_file_path_no_suffix) + output_file_path = output_file_path_no_suffix.parent / ( + output_file_path_no_suffix.name + cls.FILE_SUFFIX + ) + arr = np.array(array) + np.save(output_file_path, arr) + return output_file_path diff --git a/src/linkml_arrays/dumpers/zarr_directory_store_dumper.py b/src/linkml_arrays/dumpers/zarr_directory_store_dumper.py index 2c899ec..ca4e1d2 100644 --- a/src/linkml_arrays/dumpers/zarr_directory_store_dumper.py +++ b/src/linkml_arrays/dumpers/zarr_directory_store_dumper.py @@ -1,5 +1,6 @@ """Class for dumping a LinkML model to a Zarr directory store.""" +from pathlib import Path from typing import Union import zarr @@ -14,16 +15,16 @@ def _iterate_element( ): """Recursively iterate through the elements of a LinkML model and save them. - Writes Pydantic BaseModel objects as groups, slots that implement "linkml:elements" - as datasets, and other slots as attributes. + Write Pydantic BaseModel objects as groups, slots with the "array" element + as arrays, and other slots as attributes. """ # get the type of the element element_type = type(element).__name__ for k, v in vars(element).items(): found_slot = schemaview.induced_slot(k, element_type) - if "linkml:elements" in found_slot.implements: - # save the numpy array to an hdf5 dataset + if found_slot.array: + # save the numpy array to a zarr array group.create_dataset(found_slot.name, data=v) else: if isinstance(v, BaseModel): @@ -39,17 +40,14 @@ class ZarrDirectoryStoreDumper(Dumper): """Dumper class for LinkML models to Zarr directory stores.""" # TODO is this the right method to overwrite? it does not dump a string - def dumps(self, element: Union[YAMLRoot, BaseModel], schemaview: SchemaView, **kwargs): - """Dump the element to a Zarr directory store. - - Raises: - ValueError: If the class requires an identifier and it is not provided. - """ - id_slot = schemaview.get_identifier_slot(element.__class__.__name__) - if id_slot is None: - raise ValueError("The class requires an identifier.") - id_value = getattr(element, id_slot.name) - output_file_path = f"{id_value}.zarr" + def dumps( + self, + element: Union[YAMLRoot, BaseModel], + schemaview: SchemaView, + output_file_path: Union[str, Path], + **kwargs, + ): + """Dump the element to a Zarr directory store.""" store = zarr.DirectoryStore(output_file_path) root = zarr.group(store=store, overwrite=True) _iterate_element(element, schemaview, root) diff --git a/src/linkml_arrays/loaders/__init__.py b/src/linkml_arrays/loaders/__init__.py index 0778b0d..af71135 100644 --- a/src/linkml_arrays/loaders/__init__.py +++ b/src/linkml_arrays/loaders/__init__.py @@ -1,15 +1,13 @@ """Dumper classes for linkml-arrays.""" from .hdf5_loader import Hdf5Loader -from .yaml_hdf5_loader import YamlHdf5Loader +from .yaml_array_file_loader import YamlArrayFileLoader from .yaml_loader import YamlLoader -from .yaml_numpy_loader import YamlNumpyLoader from .zarr_directory_store_loader import ZarrDirectoryStoreLoader __all__ = [ "Hdf5Loader", - "YamlHdf5Loader", + "YamlArrayFileLoader", "YamlLoader", - "YamlNumpyLoader", "ZarrDirectoryStoreLoader", ] diff --git a/src/linkml_arrays/loaders/hdf5_loader.py b/src/linkml_arrays/loaders/hdf5_loader.py index 92e6bff..e575d68 100644 --- a/src/linkml_arrays/loaders/hdf5_loader.py +++ b/src/linkml_arrays/loaders/hdf5_loader.py @@ -25,7 +25,7 @@ def _iterate_element( found_slot = schemaview.induced_slot( k, element_type.name ) # assumes the slot name has been written as the name which is OK for now. - if "linkml:elements" in found_slot.implements: + if found_slot.array: assert isinstance(v, h5py.Dataset) v = v[()] # read all the values into memory TODO: support lazy loading elif isinstance(v, h5py.Group): # it's a subgroup diff --git a/src/linkml_arrays/loaders/yaml_array_file_loader.py b/src/linkml_arrays/loaders/yaml_array_file_loader.py new file mode 100644 index 0000000..d40b61d --- /dev/null +++ b/src/linkml_arrays/loaders/yaml_array_file_loader.py @@ -0,0 +1,89 @@ +"""Class for loading a LinkML model from a YAML file with arrays at supported file paths.""" + +from typing import Type, Union + +import h5py +import numpy as np +import yaml +from linkml_runtime import SchemaView +from linkml_runtime.linkml_model import ClassDefinition +from linkml_runtime.loaders.loader_root import Loader +from linkml_runtime.utils.yamlutils import YAMLRoot +from pydantic import BaseModel + + +def _iterate_element( + input_dict: dict, element_type: ClassDefinition, schemaview: SchemaView +) -> dict: + """Recursively iterate through the elements of a LinkML model and load them into a dict. + + Datasets are read into memory. + + Raises: + ValueError: If the array slot has no source or format, or if the format is not supported. + """ + ret_dict = dict() + for k, v in input_dict.items(): + found_slot = schemaview.induced_slot(k, element_type.name) + if found_slot.array: + sources = v.get("source", None) + if sources is None: + raise ValueError(f"Array slot {k} has no source.") + for source in sources: + format = source.get("format", None) + if format is None: + raise ValueError(f"Array slot {k}, source {source} has no format.") + if format == "hdf5": + file = source.get("file", None) + if file is None: + raise ValueError( + f"Array slot {k}, source {source}, format {format} has no file." + ) + array_file_path = file + with h5py.File(array_file_path, "r") as f: + # read all the values into memory TODO: support lazy loading + v = f["data"][()] + elif format == "numpy": + file = source.get("file", None) + if file is None: + raise ValueError( + f"Array slot {k}, source {source}, format {format} has no file." + ) + array_file_path = file + # read all the values into memory TODO: support lazy loading + v = np.load(array_file_path) + elif isinstance(v, dict): + found_slot_range = schemaview.get_class(found_slot.range) + v = _iterate_element(v, found_slot_range, schemaview) + # else: do not transform v + ret_dict[k] = v + + return ret_dict + + +class YamlArrayFileLoader(Loader): + """Class for loading a model from a YAML file with arrays at supported file paths.""" + + def load_any(self, source: str, **kwargs): + """Create an instance of the target class from a YAML file with arrays in files.""" + return self.load(source, **kwargs) + + def loads(self, source: str, **kwargs): + """Create an instance of the target class from a YAML file with arrays in files.""" + return self.load(source, **kwargs) + + def load( + self, + source: str, + target_class: Type[Union[YAMLRoot, BaseModel]], + schemaview: SchemaView, + **kwargs, + ): + """Create an instance of the target class from a YAML file with arrays in files.""" + input_dict = yaml.safe_load(source) + + element_type = schemaview.get_class(target_class.__name__) + element = _iterate_element(input_dict, element_type, schemaview) + obj = target_class(**element) + + return obj diff --git a/src/linkml_arrays/loaders/yaml_hdf5_loader.py b/src/linkml_arrays/loaders/yaml_hdf5_loader.py deleted file mode 100644 index 771600f..0000000 --- a/src/linkml_arrays/loaders/yaml_hdf5_loader.py +++ /dev/null @@ -1,62 +0,0 @@ -"""Class for loading a LinkML model from a YAML file with HDF5 file paths.""" - -from typing import Type, Union - -import h5py -import yaml -from linkml_runtime import SchemaView -from linkml_runtime.linkml_model import ClassDefinition -from linkml_runtime.loaders.loader_root import Loader -from linkml_runtime.utils.yamlutils import YAMLRoot -from pydantic import BaseModel - - -def _iterate_element( - input_dict: dict, element_type: ClassDefinition, schemaview: SchemaView -) -> dict: - """Recursively iterate through the elements of a LinkML model and load them into a dict. - - Datasets are read into memory. - """ - ret_dict = dict() - for k, v in input_dict.items(): - found_slot = schemaview.induced_slot(k, element_type.name) - if "linkml:elements" in found_slot.implements: - array_file_path = v.replace("file:./", "") - with h5py.File(array_file_path, "r") as f: - v = f["data"][()] # read all the values into memory TODO: support lazy loading - elif isinstance(v, dict): - found_slot_range = schemaview.get_class(found_slot.range) - v = _iterate_element(v, found_slot_range, schemaview) - # else: do not transform v - ret_dict[k] = v - - return ret_dict - - -class YamlHdf5Loader(Loader): - """Class for loading a LinkML model from a YAML file with HDF5 file paths.""" - - def load_any(self, source: str, **kwargs): - """Create an instance of the target class from a YAML file with HDF5 file paths.""" - return self.load(source, **kwargs) - - def loads(self, source: str, **kwargs): - """Create an instance of the target class from a YAML file with HDF5 file paths.""" - return self.load(source, **kwargs) - - def load( - self, - source: str, - target_class: Type[Union[YAMLRoot, BaseModel]], - schemaview: SchemaView, - **kwargs, - ): - """Create an instance of the target class from a YAML file with HDF5 file paths.""" - input_dict = yaml.safe_load(source) - - element_type = schemaview.get_class(target_class.__name__) - element = _iterate_element(input_dict, element_type, schemaview) - obj = target_class(**element) - - return obj diff --git a/src/linkml_arrays/loaders/yaml_loader.py b/src/linkml_arrays/loaders/yaml_loader.py index 6211ea8..3c691f9 100644 --- a/src/linkml_arrays/loaders/yaml_loader.py +++ b/src/linkml_arrays/loaders/yaml_loader.py @@ -2,7 +2,6 @@ from typing import Type, Union -import numpy as np import yaml from linkml_runtime import SchemaView from linkml_runtime.linkml_model import ClassDefinition @@ -14,16 +13,11 @@ def _iterate_element( input_dict: dict, element_type: ClassDefinition, schemaview: SchemaView ) -> dict: - """Recursively iterate through the elements of a LinkML model and load them into a dict. - - Datasets are loaded into NumPy arrays. - """ + """Recursively iterate through the elements of a LinkML model and load them into a dict.""" ret_dict = dict() for k, v in input_dict.items(): found_slot = schemaview.induced_slot(k, element_type.name) - if "linkml:elements" in found_slot.implements: - v = np.asarray(v) - elif isinstance(v, dict): + if isinstance(v, dict): found_slot_range = schemaview.get_class(found_slot.range) v = _iterate_element(v, found_slot_range, schemaview) # else: do not transform v diff --git a/src/linkml_arrays/loaders/yaml_numpy_loader.py b/src/linkml_arrays/loaders/yaml_numpy_loader.py deleted file mode 100644 index 5b2bd63..0000000 --- a/src/linkml_arrays/loaders/yaml_numpy_loader.py +++ /dev/null @@ -1,61 +0,0 @@ -"""Class for loading a LinkML model from a YAML file with NumPy file paths.""" - -from typing import Type, Union - -import numpy as np -import yaml -from linkml_runtime import SchemaView -from linkml_runtime.linkml_model import ClassDefinition -from linkml_runtime.loaders.loader_root import Loader -from linkml_runtime.utils.yamlutils import YAMLRoot -from pydantic import BaseModel - - -def _iterate_element( - input_dict: dict, element_type: ClassDefinition, schemaview: SchemaView -) -> dict: - """Recursively iterate through the elements of a LinkML model and load them into a dict. - - Datasets are read into memory. - """ - ret_dict = dict() - for k, v in input_dict.items(): - found_slot = schemaview.induced_slot(k, element_type.name) - if "linkml:elements" in found_slot.implements: - array_file_path = v.replace("file:./", "") - v = np.load(array_file_path) # TODO: support lazy loading - elif isinstance(v, dict): - found_slot_range = schemaview.get_class(found_slot.range) - v = _iterate_element(v, found_slot_range, schemaview) - # else: do not transform v - ret_dict[k] = v - - return ret_dict - - -class YamlNumpyLoader(Loader): - """Class for loading a LinkML model from a YAML file with NumPy file paths.""" - - def load_any(self, source: str, **kwargs): - """Create an instance of the target class from a YAML file with NumPy file paths.""" - return self.load(source, **kwargs) - - def loads(self, source: str, **kwargs): - """Create an instance of the target class from a YAML file with NumPy file paths.""" - return self.load(source, **kwargs) - - def load( - self, - source: str, - target_class: Type[Union[YAMLRoot, BaseModel]], - schemaview: SchemaView, - **kwargs, - ): - """Create an instance of the target class from a YAML file with NumPy file paths.""" - input_dict = yaml.safe_load(source) - - element_type = schemaview.get_class(target_class.__name__) - element = _iterate_element(input_dict, element_type, schemaview) - obj = target_class(**element) - - return obj diff --git a/src/linkml_arrays/loaders/zarr_directory_store_loader.py b/src/linkml_arrays/loaders/zarr_directory_store_loader.py index 29707d5..fdd6e09 100644 --- a/src/linkml_arrays/loaders/zarr_directory_store_loader.py +++ b/src/linkml_arrays/loaders/zarr_directory_store_loader.py @@ -25,7 +25,7 @@ def _iterate_element( found_slot = schemaview.induced_slot( k, element_type.name ) # assumes the slot name has been written as the name which is OK for now. - if "linkml:elements" in found_slot.implements: + if found_slot.array: assert isinstance(v, zarr.Array) v = v[()] # read all the values into memory # TODO support lazy loading elif isinstance(v, zarr.hierarchy.Group): # it's a subgroup diff --git a/src/linkml_arrays/main.py b/src/linkml_arrays/main.py deleted file mode 100644 index 5a05fe2..0000000 --- a/src/linkml_arrays/main.py +++ /dev/null @@ -1,10 +0,0 @@ -"""Main python file.""" - - -def demo(): - """Define API.""" - print("Hello, World!") - - -if __name__ == "__main__": - demo() diff --git a/tests/array_classes_lol.py b/tests/array_classes_lol.py new file mode 100644 index 0000000..4b2cb4c --- /dev/null +++ b/tests/array_classes_lol.py @@ -0,0 +1,344 @@ +from __future__ import annotations + +import re +import sys +from datetime import date, datetime +from decimal import Decimal +from enum import Enum +from typing import Any, ClassVar, Dict, List, Literal, Optional, Union + +from pydantic.version import VERSION as PYDANTIC_VERSION + +if int(PYDANTIC_VERSION[0]) >= 2: + from pydantic import BaseModel, ConfigDict, Field, RootModel, field_validator +else: + from pydantic import BaseModel, Field, validator + +from pydantic import conlist + +metamodel_version = "None" +version = "None" + + +class ConfiguredBaseModel(BaseModel): + model_config = ConfigDict( + validate_assignment=True, + validate_default=True, + extra="forbid", + arbitrary_types_allowed=True, + use_enum_values=True, + strict=False, + ) + pass + + +class LinkMLMeta(RootModel): + root: Dict[str, Any] = {} + model_config = ConfigDict(frozen=True) + + def __getattr__(self, key: str): + return getattr(self.root, key) + + def __getitem__(self, key: str): + return self.root[key] + + def __setitem__(self, key: str, value): + self.root[key] = value + + +linkml_meta = LinkMLMeta( + { + "default_prefix": "https://example.org/arrays/", + "description": "Example LinkML schema to demonstrate a 3D DataArray of " + "temperature values with labeled axes\n" + "using classes containing arrays for the axes and data instead " + "of using array slots/attributes.\n" + "Creating separate types for the array slots enables reuse and " + "extension.", + "id": "https://example.org/arrays", + "name": "arrays-temperature-example-2", + } +) + + +class Container(ConfiguredBaseModel): + """ + A container for a temperature dataset + """ + + linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta( + {"from_schema": "https://example.org/arrays", "tree_root": True} + ) + + name: str = Field( + ..., + json_schema_extra={ + "linkml_meta": { + "alias": "name", + "domain_of": [ + "Container", + "TemperatureDataset", + "LatitudeInDegSeries", + "LongitudeInDegSeries", + ], + } + }, + ) + temperature_dataset: TemperatureDataset = Field( + ..., + json_schema_extra={ + "linkml_meta": {"alias": "temperature_dataset", "domain_of": ["Container"]} + }, + ) + latitude_series: LatitudeInDegSeries = Field( + ..., + json_schema_extra={"linkml_meta": {"alias": "latitude_series", "domain_of": ["Container"]}}, + ) + longitude_series: LongitudeInDegSeries = Field( + ..., + json_schema_extra={ + "linkml_meta": {"alias": "longitude_series", "domain_of": ["Container"]} + }, + ) + + +class TemperatureDataset(ConfiguredBaseModel): + linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta( + { + "from_schema": "https://example.org/arrays", + "implements": ["linkml:DataArray"], + "tree_root": True, + } + ) + + name: str = Field( + ..., + json_schema_extra={ + "linkml_meta": { + "alias": "name", + "domain_of": [ + "Container", + "TemperatureDataset", + "LatitudeInDegSeries", + "LongitudeInDegSeries", + ], + } + }, + ) + latitude_in_deg: str = Field( + ..., + json_schema_extra={ + "linkml_meta": {"alias": "latitude_in_deg", "domain_of": ["TemperatureDataset"]} + }, + ) + longitude_in_deg: str = Field( + ..., + json_schema_extra={ + "linkml_meta": {"alias": "longitude_in_deg", "domain_of": ["TemperatureDataset"]} + }, + ) + date: DateSeries = Field( + ..., + json_schema_extra={"linkml_meta": {"alias": "date", "domain_of": ["TemperatureDataset"]}}, + ) + day_in_d: Optional[DaysInDSinceSeries] = Field( + None, + json_schema_extra={ + "linkml_meta": {"alias": "day_in_d", "domain_of": ["TemperatureDataset"]} + }, + ) + temperatures_in_K: TemperaturesInKMatrix = Field( + ..., + json_schema_extra={ + "linkml_meta": {"alias": "temperatures_in_K", "domain_of": ["TemperatureDataset"]} + }, + ) + + +class LatitudeInDegSeries(ConfiguredBaseModel): + """ + A 2D array whose values represent latitude + """ + + linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "https://example.org/arrays"}) + + name: str = Field( + ..., + json_schema_extra={ + "linkml_meta": { + "alias": "name", + "domain_of": [ + "Container", + "TemperatureDataset", + "LatitudeInDegSeries", + "LongitudeInDegSeries", + ], + } + }, + ) + values: List[List[float]] = Field( + default_factory=list, + json_schema_extra={ + "linkml_meta": { + "alias": "values", + "array": {"exact_number_dimensions": 2}, + "domain_of": [ + "LatitudeInDegSeries", + "LongitudeInDegSeries", + "DateSeries", + "DaysInDSinceSeries", + "TemperaturesInKMatrix", + ], + "unit": {"ucum_code": "deg"}, + } + }, + ) + + +class LongitudeInDegSeries(ConfiguredBaseModel): + """ + A 2D array whose values represent longitude + """ + + linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "https://example.org/arrays"}) + + name: str = Field( + ..., + json_schema_extra={ + "linkml_meta": { + "alias": "name", + "domain_of": [ + "Container", + "TemperatureDataset", + "LatitudeInDegSeries", + "LongitudeInDegSeries", + ], + } + }, + ) + values: List[List[float]] = Field( + default_factory=list, + json_schema_extra={ + "linkml_meta": { + "alias": "values", + "array": {"exact_number_dimensions": 2}, + "domain_of": [ + "LatitudeInDegSeries", + "LongitudeInDegSeries", + "DateSeries", + "DaysInDSinceSeries", + "TemperaturesInKMatrix", + ], + "unit": {"ucum_code": "deg"}, + } + }, + ) + + +class DateSeries(ConfiguredBaseModel): + """ + A 1D series of dates + """ + + linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "https://example.org/arrays"}) + + values: List[str] = Field( + default_factory=list, + json_schema_extra={ + "linkml_meta": { + "alias": "values", + "array": {"exact_number_dimensions": 1}, + "domain_of": [ + "LatitudeInDegSeries", + "LongitudeInDegSeries", + "DateSeries", + "DaysInDSinceSeries", + "TemperaturesInKMatrix", + ], + } + }, + ) + + +class DaysInDSinceSeries(ConfiguredBaseModel): + """ + A 1D series whose values represent the number of days since a reference date + """ + + linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "https://example.org/arrays"}) + + values: List[int] = Field( + default_factory=list, + json_schema_extra={ + "linkml_meta": { + "alias": "values", + "array": {"exact_number_dimensions": 1}, + "domain_of": [ + "LatitudeInDegSeries", + "LongitudeInDegSeries", + "DateSeries", + "DaysInDSinceSeries", + "TemperaturesInKMatrix", + ], + "unit": {"ucum_code": "d"}, + } + }, + ) + reference_date: str = Field( + ..., + description="""The reference date for the `day_in_d` values""", + json_schema_extra={ + "linkml_meta": {"alias": "reference_date", "domain_of": ["DaysInDSinceSeries"]} + }, + ) + + +class TemperaturesInKMatrix(ConfiguredBaseModel): + """ + A 3D array of temperatures + """ + + linkml_meta: ClassVar[LinkMLMeta] = LinkMLMeta({"from_schema": "https://example.org/arrays"}) + + conversion_factor: Optional[float] = Field( + None, + description="""A conversion factor to apply to the temperature values""", + json_schema_extra={ + "linkml_meta": { + "alias": "conversion_factor", + "domain_of": ["TemperaturesInKMatrix"], + "unit": {"ucum_code": "K"}, + } + }, + ) + values: List[List[List[float]]] = Field( + default_factory=list, + json_schema_extra={ + "linkml_meta": { + "alias": "values", + "array": { + "dimensions": [{"alias": "x"}, {"alias": "y"}, {"alias": "date"}], + "exact_number_dimensions": 3, + }, + "domain_of": [ + "LatitudeInDegSeries", + "LongitudeInDegSeries", + "DateSeries", + "DaysInDSinceSeries", + "TemperaturesInKMatrix", + ], + "unit": {"ucum_code": "K"}, + } + }, + ) + + +# Model rebuild +# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model +Container.model_rebuild() +TemperatureDataset.model_rebuild() +LatitudeInDegSeries.model_rebuild() +LongitudeInDegSeries.model_rebuild() +DateSeries.model_rebuild() +DaysInDSinceSeries.model_rebuild() +TemperaturesInKMatrix.model_rebuild() diff --git a/tests/demo_test.py b/tests/demo_test.py deleted file mode 100644 index 1eaf64b..0000000 --- a/tests/demo_test.py +++ /dev/null @@ -1,13 +0,0 @@ -"""Demo version test.""" - -import unittest - -from linkml_arrays import __version__ - - -class TestVersion(unittest.TestCase): - """Test version.""" - - def test_version_type(self): - """Demo test.""" - self.assertIsInstance(__version__, str) diff --git a/tests/input/container_yaml.yaml b/tests/input/container_yaml.yaml new file mode 100644 index 0000000..8c1c32c --- /dev/null +++ b/tests/input/container_yaml.yaml @@ -0,0 +1,39 @@ +name: my_container +latitude_series: + name: my_latitude + values: + - - 1 + - 2 + - - 3 + - 4 +longitude_series: + name: my_longitude + values: + - - 5 + - 6 + - - 7 + - 8 +temperature_dataset: + name: my_temperature + latitude_in_deg: my_latitude + longitude_in_deg: my_longitude + temperatures_in_K: + conversion_factor: 1000 + values: + - - - 0 + - 1 + - - 2 + - 3 + - - - 4 + - 5 + - - 6 + - 7 + date: + values: + - "2020-01-01" + - "2020-01-02" + day_in_d: + values: + - 0 + - 1 + reference_date: "2020-01-01" diff --git a/tests/input/container_yaml_hdf5.yaml b/tests/input/container_yaml_hdf5.yaml new file mode 100644 index 0000000..b2e8d1a --- /dev/null +++ b/tests/input/container_yaml_hdf5.yaml @@ -0,0 +1,34 @@ +name: my_container +latitude_series: + name: my_latitude + values: + source: + - file: ./out/my_latitude.values.h5 + format: hdf5 +longitude_series: + name: my_longitude + values: + source: + - file: ./out/my_longitude.values.h5 + format: hdf5 +temperature_dataset: + date: + values: + source: + - file: ./out/my_temperature.date.values.h5 + format: hdf5 + day_in_d: + reference_date: '2020-01-01' + values: + source: + - file: ./out/my_temperature.day_in_d.values.h5 + format: hdf5 + latitude_in_deg: my_latitude + longitude_in_deg: my_longitude + name: my_temperature + temperatures_in_K: + conversion_factor: 1000.0 + values: + source: + - file: ./out/my_temperature.temperatures_in_K.values.h5 + format: hdf5 diff --git a/tests/input/container_yaml_numpy.yaml b/tests/input/container_yaml_numpy.yaml new file mode 100644 index 0000000..1e8d765 --- /dev/null +++ b/tests/input/container_yaml_numpy.yaml @@ -0,0 +1,34 @@ +name: my_container +latitude_series: + name: my_latitude + values: + source: + - file: "./out/my_latitude.values.npy" + format: numpy +longitude_series: + name: my_longitude + values: + source: + - file: "./out/my_longitude.values.npy" + format: numpy +temperature_dataset: + date: + values: + source: + - file: "./out/my_temperature.date.values.npy" + format: numpy + day_in_d: + reference_date: '2020-01-01' + values: + source: + - file: "./out/my_temperature.day_in_d.values.npy" + format: numpy + latitude_in_deg: my_latitude + longitude_in_deg: my_longitude + name: my_temperature + temperatures_in_K: + conversion_factor: 1000.0 + values: + source: + - file: "./out/my_temperature.temperatures_in_K.values.npy" + format: numpy diff --git a/tests/input/my_temperature.h5 b/tests/input/my_container.h5 similarity index 60% rename from tests/input/my_temperature.h5 rename to tests/input/my_container.h5 index b23a807..1938a66 100644 Binary files a/tests/input/my_temperature.h5 and b/tests/input/my_container.h5 differ diff --git a/tests/input/my_container.zarr/.zattrs b/tests/input/my_container.zarr/.zattrs new file mode 100644 index 0000000..060eade --- /dev/null +++ b/tests/input/my_container.zarr/.zattrs @@ -0,0 +1,3 @@ +{ + "name": "my_container" +} \ No newline at end of file diff --git a/tests/input/my_temperature.zarr/.zgroup b/tests/input/my_container.zarr/.zgroup similarity index 100% rename from tests/input/my_temperature.zarr/.zgroup rename to tests/input/my_container.zarr/.zgroup diff --git a/tests/input/my_container.zarr/latitude_series/.zattrs b/tests/input/my_container.zarr/latitude_series/.zattrs new file mode 100644 index 0000000..6b698b1 --- /dev/null +++ b/tests/input/my_container.zarr/latitude_series/.zattrs @@ -0,0 +1,3 @@ +{ + "name": "my_latitude" +} \ No newline at end of file diff --git a/tests/input/my_temperature.zarr/latitude_in_deg/.zgroup b/tests/input/my_container.zarr/latitude_series/.zgroup similarity index 100% rename from tests/input/my_temperature.zarr/latitude_in_deg/.zgroup rename to tests/input/my_container.zarr/latitude_series/.zgroup diff --git a/tests/input/my_temperature.zarr/temperatures_in_K/values/.zarray b/tests/input/my_container.zarr/latitude_series/values/.zarray similarity index 81% rename from tests/input/my_temperature.zarr/temperatures_in_K/values/.zarray rename to tests/input/my_container.zarr/latitude_series/values/.zarray index 4d53b4f..fe4bc83 100644 --- a/tests/input/my_temperature.zarr/temperatures_in_K/values/.zarray +++ b/tests/input/my_container.zarr/latitude_series/values/.zarray @@ -1,8 +1,7 @@ { "chunks": [ - 3, - 3, - 3 + 2, + 2 ], "compressor": { "blocksize": 0, @@ -16,9 +15,8 @@ "filters": null, "order": "C", "shape": [ - 3, - 3, - 3 + 2, + 2 ], "zarr_format": 2 } \ No newline at end of file diff --git a/tests/input/my_container.zarr/latitude_series/values/0.0 b/tests/input/my_container.zarr/latitude_series/values/0.0 new file mode 100644 index 0000000..29cf010 Binary files /dev/null and b/tests/input/my_container.zarr/latitude_series/values/0.0 differ diff --git a/tests/input/my_container.zarr/longitude_series/.zattrs b/tests/input/my_container.zarr/longitude_series/.zattrs new file mode 100644 index 0000000..2670cd2 --- /dev/null +++ b/tests/input/my_container.zarr/longitude_series/.zattrs @@ -0,0 +1,3 @@ +{ + "name": "my_longitude" +} \ No newline at end of file diff --git a/tests/input/my_temperature.zarr/longitude_in_deg/.zgroup b/tests/input/my_container.zarr/longitude_series/.zgroup similarity index 100% rename from tests/input/my_temperature.zarr/longitude_in_deg/.zgroup rename to tests/input/my_container.zarr/longitude_series/.zgroup diff --git a/tests/input/my_temperature.zarr/time_in_d/values/.zarray b/tests/input/my_container.zarr/longitude_series/values/.zarray similarity index 74% rename from tests/input/my_temperature.zarr/time_in_d/values/.zarray rename to tests/input/my_container.zarr/longitude_series/values/.zarray index 82cf922..fe4bc83 100644 --- a/tests/input/my_temperature.zarr/time_in_d/values/.zarray +++ b/tests/input/my_container.zarr/longitude_series/values/.zarray @@ -1,6 +1,7 @@ { "chunks": [ - 3 + 2, + 2 ], "compressor": { "blocksize": 0, @@ -9,12 +10,13 @@ "id": "blosc", "shuffle": 1 }, - "dtype": " Container: + latitude_in_deg = LatitudeInDegSeries(name="my_latitude", values=[[1, 2], [3, 4]]) + longitude_in_deg = LongitudeInDegSeries(name="my_longitude", values=[[5, 6], [7, 8]]) + date = DateSeries(values=["2020-01-01", "2020-01-02"]) + days_in_d_since = DaysInDSinceSeries(values=[0, 1], reference_date="2020-01-01") + temperatures_in_K = TemperaturesInKMatrix( + conversion_factor=1000.0, + values=[[[0, 1], [2, 3]], [[4, 5], [6, 7]]], + ) + # NOTE: currently no way to pass in the actual LatitudeInDegSeries object + temperature_dataset = TemperatureDataset( + name="my_temperature", + latitude_in_deg="my_latitude", + longitude_in_deg="my_longitude", + date=date, + day_in_d=days_in_d_since, + temperatures_in_K=temperatures_in_K, + ) + container = Container( + name="my_container", + latitude_series=latitude_in_deg, + longitude_series=longitude_in_deg, + temperature_dataset=temperature_dataset, + ) + + return container + + +def test_yaml_dumper(): + """Test YamlDumper dumping to a YAML file.""" + container = _create_container() + + schemaview = SchemaView(INPUT_DIR / "temperature_schema.yaml") + ret = YamlDumper().dumps(container, schemaview=schemaview) + + # read and compare with the expected YAML file ignoring order of keys + expected_yaml_file = INPUT_DIR / "container_yaml.yaml" + yaml = YAML(typ="safe") + with open(expected_yaml_file) as f: + expected = yaml.load(f) # load yaml into dictionary + actual = yaml.load(ret) + assert actual == expected + + +def test_yaml_numpy_dumper(): + """Test YamlNumpyDumper dumping to a YAML file and NumPy .npy files in a directory.""" + container = _create_container() + + schemaview = SchemaView(INPUT_DIR / "temperature_schema.yaml") + ret = YamlNumpyDumper().dumps(container, schemaview=schemaview, output_dir="./out") + + # read and compare with the expected YAML file ignoring order of keys + expected_yaml_file = INPUT_DIR / "container_yaml_numpy.yaml" + yaml = YAML(typ="safe") + with open(expected_yaml_file) as f: + expected = yaml.load(f) # load yaml into dictionary + actual = yaml.load(ret) + assert actual == expected + + +def test_yaml_hdf5_dumper(): + """Test YamlNumpyDumper dumping to a YAML file and HDF5 datasets in a directory.""" + container = _create_container() + + schemaview = SchemaView(INPUT_DIR / "temperature_schema.yaml") + ret = YamlHdf5Dumper().dumps(container, schemaview=schemaview, output_dir="./out") + + # read and compare with the expected YAML file ignoring order of keys + expected_yaml_file = INPUT_DIR / "container_yaml_hdf5.yaml" + yaml = YAML(typ="safe") + with open(expected_yaml_file) as f: + expected = yaml.load(f) # load yaml into dictionary + actual = yaml.load(ret) + assert actual == expected + + +def test_hdf5_dumper(tmp_path): + """Test Hdf5Dumper dumping to an HDF5 file.""" + container = _create_container() + + schemaview = SchemaView(INPUT_DIR / "temperature_schema.yaml") + output_file_path = tmp_path / "my_container.h5" + Hdf5Dumper().dumps(container, schemaview=schemaview, output_file_path=output_file_path) + + assert os.path.exists(output_file_path) + with h5py.File(output_file_path, "r") as f: + assert f.attrs["name"] == "my_container" + assert set(f["latitude_series"].keys()) == set(["values"]) + np.testing.assert_array_equal(f["latitude_series/values"][:], [[1, 2], [3, 4]]) + assert set(f["longitude_series"].keys()) == set(["values"]) + np.testing.assert_array_equal(f["longitude_series/values"][:], [[5, 6], [7, 8]]) + assert set(f["temperature_dataset"]) == set(["date", "day_in_d", "temperatures_in_K"]) + assert set(f["temperature_dataset/date"].keys()) == set(["values"]) + np.testing.assert_array_equal( + f["temperature_dataset/date/values"].asstr()[:], np.array(["2020-01-01", "2020-01-02"]) ) - temperature = TemperatureDataset( - name="my_temperature", - latitude_in_deg=latitude_in_deg, - longitude_in_deg=longitude_in_deg, - time_in_d=time_in_d, - temperatures_in_K=temperatures_in_K, + assert set(f["temperature_dataset/day_in_d"].keys()) == set(["values"]) + assert f["temperature_dataset/day_in_d"].attrs["reference_date"] == "2020-01-01" + np.testing.assert_array_equal(f["temperature_dataset/day_in_d/values"][:], [0, 1]) + assert set(f["temperature_dataset/temperatures_in_K"].keys()) == set(["values"]) + np.testing.assert_array_equal( + f["temperature_dataset/temperatures_in_K/values"][:], + [[[0, 1], [2, 3]], [[4, 5], [6, 7]]], ) - schemaview = SchemaView(Path(__file__) / "../../input/temperature_dataset.yaml") - ZarrDirectoryStoreDumper().dumps(temperature, schemaview=schemaview) - - assert os.path.exists("my_temperature.zarr") - # TODO use Zarr to assert that the data is correct +def test_zarr_directory_store_dumper(tmp_path): + """Test ZarrDumper dumping to an HDF5 file.""" + container = _create_container() + + schemaview = SchemaView(INPUT_DIR / "temperature_schema.yaml") + output_file_path = tmp_path / "my_container.zarr" + ZarrDirectoryStoreDumper().dumps( + container, schemaview=schemaview, output_file_path=output_file_path + ) + + assert os.path.exists(output_file_path) + + root = zarr.group(store=output_file_path) + # NOTE this is pretty much the same code as test_hdf5_dumper + assert root.attrs["name"] == "my_container" + assert set(root["latitude_series"].keys()) == set(["values"]) + np.testing.assert_array_equal(root["latitude_series/values"][:], [[1, 2], [3, 4]]) + assert set(root["longitude_series"].keys()) == set(["values"]) + np.testing.assert_array_equal(root["longitude_series/values"][:], [[5, 6], [7, 8]]) + assert set(root["temperature_dataset"]) == set(["date", "day_in_d", "temperatures_in_K"]) + assert set(root["temperature_dataset/date"].keys()) == set(["values"]) + np.testing.assert_array_equal( + root["temperature_dataset/date/values"][:], np.array(["2020-01-01", "2020-01-02"]) + ) + assert set(root["temperature_dataset/day_in_d"].keys()) == set(["values"]) + assert root["temperature_dataset/day_in_d"].attrs["reference_date"] == "2020-01-01" + np.testing.assert_array_equal(root["temperature_dataset/day_in_d/values"][:], [0, 1]) + assert set(root["temperature_dataset/temperatures_in_K"].keys()) == set(["values"]) + np.testing.assert_array_equal( + root["temperature_dataset/temperatures_in_K/values"][:], + [[[0, 1], [2, 3]], [[4, 5], [6, 7]]], + ) diff --git a/tests/test_loaders/test_loaders.py b/tests/test_loaders/test_loaders.py index 6ce15f6..ca6e481 100644 --- a/tests/test_loaders/test_loaders.py +++ b/tests/test_loaders/test_loaders.py @@ -1,160 +1,104 @@ -"""Test loading data from various file formats into LinkML models.""" +"""Test loading data from various file formats into pydantic models with arrays as LoLs.""" -import unittest from pathlib import Path -import numpy as np from hbreader import hbread from linkml_runtime import SchemaView from linkml_arrays.loaders import ( Hdf5Loader, - YamlHdf5Loader, + YamlArrayFileLoader, YamlLoader, - YamlNumpyLoader, ZarrDirectoryStoreLoader, ) -from tests.test_dumpers.array_classes import ( - DaySeries, - LatitudeSeries, - LongitudeSeries, +from tests.array_classes_lol import ( + Container, + DateSeries, + DaysInDSinceSeries, + LatitudeInDegSeries, + LongitudeInDegSeries, TemperatureDataset, - TemperatureMatrix, + TemperaturesInKMatrix, ) -class YamlLoadersTestCase(unittest.TestCase): - """Test loading of pydantic-style classes from YAML arrays.""" +def _check_container(container: Container): + assert isinstance(container, Container) + assert container.name == "my_container" - def test_load_pydantic_arrays(self): - """Test loading of pydantic-style classes from YAML arrays.""" - read_yaml = hbread( - "temperature_dataset_yaml.yaml", base_path=str(Path(__file__) / "../../input") - ) - schemaview = SchemaView(Path(__file__) / "../../input/temperature_dataset.yaml") - ret = YamlLoader().loads(read_yaml, target_class=TemperatureDataset, schemaview=schemaview) + assert isinstance(container.latitude_series, LatitudeInDegSeries) + assert container.latitude_series.name == "my_latitude" + assert container.latitude_series.values == [[1, 2], [3, 4]] - assert isinstance(ret, TemperatureDataset) - assert ret.name == "my_temperature" + assert isinstance(container.longitude_series, LongitudeInDegSeries) + assert container.longitude_series.name == "my_longitude" + assert container.longitude_series.values == [[5, 6], [7, 8]] - assert isinstance(ret.latitude_in_deg, LatitudeSeries) - np.testing.assert_array_equal(ret.latitude_in_deg.values, np.array([1, 2])) + assert isinstance(container.temperature_dataset, TemperatureDataset) + assert container.temperature_dataset.name == "my_temperature" + assert container.temperature_dataset.latitude_in_deg == "my_latitude" + # currently no way to get the actual LatitudeInDegSeries object from the + # TemperatureDataset object because the TemperatureDataset Pydantic object + # expects a string for the latitude_in_deg field + # to be isomorphic with the json schema / yaml representation - assert isinstance(ret.longitude_in_deg, LongitudeSeries) - np.testing.assert_array_equal(ret.longitude_in_deg.values, np.array([4, 5])) + assert container.temperature_dataset.longitude_in_deg == "my_longitude" - assert isinstance(ret.time_in_d, DaySeries) - np.testing.assert_array_equal(ret.time_in_d.values, np.array([7, 8])) + assert isinstance(container.temperature_dataset.date, DateSeries) + assert container.temperature_dataset.date.values == ["2020-01-01", "2020-01-02"] - assert isinstance(ret.temperatures_in_K, TemperatureMatrix) - np.testing.assert_array_equal(ret.temperatures_in_K.values, np.arange(8).reshape((2, 2, 2))) + assert isinstance(container.temperature_dataset.day_in_d, DaysInDSinceSeries) + assert container.temperature_dataset.day_in_d.values == [0, 1] + assert container.temperature_dataset.day_in_d.reference_date == "2020-01-01" + assert isinstance(container.temperature_dataset.temperatures_in_K, TemperaturesInKMatrix) + assert container.temperature_dataset.temperatures_in_K.values == [ + [[0, 1], [2, 3]], + [[4, 5], [6, 7]], + ] -class YamlNumpyLoadersTestCase(unittest.TestCase): - """Test loading of pydantic-style classes from YAML + Numpy arrays.""" - - def test_load_pydantic_arrays(self): - """Test loading of pydantic-style classes from YAML + Numpy arrays.""" - read_yaml = hbread( - "temperature_dataset_npy_dumped.yaml", base_path=str(Path(__file__) / "../../input") - ) - schemaview = SchemaView(Path(__file__) / "../../input/temperature_dataset.yaml") - ret = YamlNumpyLoader().loads( - read_yaml, target_class=TemperatureDataset, schemaview=schemaview - ) - - assert isinstance(ret, TemperatureDataset) - assert ret.name == "my_temperature" - - assert isinstance(ret.latitude_in_deg, LatitudeSeries) - np.testing.assert_array_equal(ret.latitude_in_deg.values, np.array([1, 2, 3])) - - assert isinstance(ret.longitude_in_deg, LongitudeSeries) - np.testing.assert_array_equal(ret.longitude_in_deg.values, np.array([4, 5, 6])) - - assert isinstance(ret.time_in_d, DaySeries) - np.testing.assert_array_equal(ret.time_in_d.values, np.array([7, 8, 9])) - - assert isinstance(ret.temperatures_in_K, TemperatureMatrix) - np.testing.assert_array_equal(ret.temperatures_in_K.values, np.ones((3, 3, 3))) - - -class YamlHdf5LoadersTestCase(unittest.TestCase): - """Test loading of pydantic-style classes from YAML + HDF5 datasets.""" - - def test_load_pydantic_arrays(self): - """Test loading of pydantic-style classes from YAML + HDF5 datasets.""" - read_yaml = hbread( - "temperature_dataset_hdf5_dumped.yaml", base_path=str(Path(__file__) / "../../input") - ) - schemaview = SchemaView(Path(__file__) / "../../input/temperature_dataset.yaml") - ret = YamlHdf5Loader().loads( - read_yaml, target_class=TemperatureDataset, schemaview=schemaview - ) - - assert isinstance(ret, TemperatureDataset) - assert ret.name == "my_temperature" - - assert isinstance(ret.latitude_in_deg, LatitudeSeries) - np.testing.assert_array_equal(ret.latitude_in_deg.values, np.array([1, 2, 3])) - - assert isinstance(ret.longitude_in_deg, LongitudeSeries) - np.testing.assert_array_equal(ret.longitude_in_deg.values, np.array([4, 5, 6])) - - assert isinstance(ret.time_in_d, DaySeries) - np.testing.assert_array_equal(ret.time_in_d.values, np.array([7, 8, 9])) - - assert isinstance(ret.temperatures_in_K, TemperatureMatrix) - np.testing.assert_array_equal(ret.temperatures_in_K.values, np.ones((3, 3, 3))) +def test_yaml_loader(): + """Test YamlLoader loading pydantic classes from YAML arrays.""" + data_yaml = hbread("container_yaml.yaml", base_path=str(Path(__file__) / "../../input")) + schemaview = SchemaView(Path(__file__) / "../../input/temperature_schema.yaml") + container = YamlLoader().loads(data_yaml, target_class=Container, schemaview=schemaview) + _check_container(container) -class Hdf5LoadersTestCase(unittest.TestCase): - """Test loading of pydantic-style classes from an HDF5 file.""" - def test_load_pydantic_arrays(self): - """Test loading of pydantic-style classes from an HDF5 file.""" - file_path = str(Path(__file__).parent.parent / "input" / "my_temperature.h5") - schemaview = SchemaView(Path(__file__) / "../../input/temperature_dataset.yaml") - ret = Hdf5Loader().loads(file_path, target_class=TemperatureDataset, schemaview=schemaview) - - assert isinstance(ret, TemperatureDataset) - assert ret.name == "my_temperature" - - assert isinstance(ret.latitude_in_deg, LatitudeSeries) - np.testing.assert_array_equal(ret.latitude_in_deg.values, np.array([1, 2, 3])) - - assert isinstance(ret.longitude_in_deg, LongitudeSeries) - np.testing.assert_array_equal(ret.longitude_in_deg.values, np.array([4, 5, 6])) - - assert isinstance(ret.time_in_d, DaySeries) - np.testing.assert_array_equal(ret.time_in_d.values, np.array([7, 8, 9])) - - assert isinstance(ret.temperatures_in_K, TemperatureMatrix) - np.testing.assert_array_equal(ret.temperatures_in_K.values, np.ones((3, 3, 3))) - - -class ZarrDirectoryStoreLoadersTestCase(unittest.TestCase): - """Test loading of pydantic-style classes from a Zarr directory store.""" - - def test_load_pydantic_arrays(self): - """Test loading of pydantic-style classes from a Zarr directory store.""" - file_path = str(Path(__file__).parent.parent / "input" / "my_temperature.zarr") - schemaview = SchemaView(Path(__file__) / "../../input/temperature_dataset.yaml") - ret = ZarrDirectoryStoreLoader().loads( - file_path, target_class=TemperatureDataset, schemaview=schemaview - ) - - assert isinstance(ret, TemperatureDataset) - assert ret.name == "my_temperature" - - assert isinstance(ret.latitude_in_deg, LatitudeSeries) - np.testing.assert_array_equal(ret.latitude_in_deg.values, np.array([1, 2, 3])) - - assert isinstance(ret.longitude_in_deg, LongitudeSeries) - np.testing.assert_array_equal(ret.longitude_in_deg.values, np.array([4, 5, 6])) - - assert isinstance(ret.time_in_d, DaySeries) - np.testing.assert_array_equal(ret.time_in_d.values, np.array([7, 8, 9])) - - assert isinstance(ret.temperatures_in_K, TemperatureMatrix) - np.testing.assert_array_equal(ret.temperatures_in_K.values, np.ones((3, 3, 3))) +def test_yaml_array_file_loader_numpy(): + """Test loading of pydantic-style classes from YAML + Numpy arrays.""" + read_yaml = hbread("container_yaml_numpy.yaml", base_path=str(Path(__file__) / "../../input")) + schemaview = SchemaView(Path(__file__) / "../../input/temperature_schema.yaml") + container = YamlArrayFileLoader().loads( + read_yaml, target_class=Container, schemaview=schemaview + ) + _check_container(container) + + +def test_yaml_array_file_loader_hdf5(): + """Test loading of pydantic-style classes from YAML + HDF5 arrays.""" + read_yaml = hbread("container_yaml_hdf5.yaml", base_path=str(Path(__file__) / "../../input")) + schemaview = SchemaView(Path(__file__) / "../../input/temperature_schema.yaml") + container = YamlArrayFileLoader().loads( + read_yaml, target_class=Container, schemaview=schemaview + ) + _check_container(container) + + +def test_hdf5_loader(): + """Test loading of pydantic-style classes from HDF5 datasets.""" + file_path = str(Path(__file__).parent.parent / "input" / "my_container.h5") + schemaview = SchemaView(Path(__file__) / "../../input/temperature_schema.yaml") + container = Hdf5Loader().loads(file_path, target_class=Container, schemaview=schemaview) + _check_container(container) + + +def test_zarr_directory_store_loader(): + """Test loading of pydantic-style classes from Zarr arrays.""" + file_path = str(Path(__file__).parent.parent / "input" / "my_container.zarr") + schemaview = SchemaView(Path(__file__) / "../../input/temperature_schema.yaml") + container = ZarrDirectoryStoreLoader().loads( + file_path, target_class=Container, schemaview=schemaview + ) + _check_container(container) diff --git a/tox.ini b/tox.ini index 19869bd..10382d4 100644 --- a/tox.ini +++ b/tox.ini @@ -15,11 +15,11 @@ envlist = lint flake8 mypy - docstr-coverage + ; docstr-coverage py [testenv] -whitelist_externals = +allowlist_externals = poetry commands = poetry run pytest @@ -53,7 +53,7 @@ description = Run documentation linters. skip_install = true deps = darglint - flake8<5.0.0 + flake8 flake8-black flake8-bandit flake8-bugbear @@ -73,14 +73,20 @@ description = Run the flake8 tool with several plugins (bandit, docstrings, impo [flake8] max-line-length = 100 ignore = - DAR101 # Missing parameter(s) in Docstring: - with_git_hash - DAR201 # Missing "Returns" in Docstring: - return - DAR301 # Missing "Yields" in Docstring: - yield - E111 # indentation is not a multiple of 4 - T201 # print found. - S101 # Use of assert detected. + DAR101 + DAR201 + DAR301 + E111 + T201 + S101 + ; DAR101 # Missing parameter(s) in Docstring: - with_git_hash + ; DAR201 # Missing "Returns" in Docstring: - return + ; DAR301 # Missing "Yields" in Docstring: - yield + ; E111 # indentation is not a multiple of 4 + ; T201 # print found. + ; S101 # Use of assert detected. exclude = - tests/test_dumpers/array_classes.py + tests/array_classes_lol.py [testenv:mypy] deps = mypy @@ -94,4 +100,4 @@ deps = docstr-coverage commands = docstr-coverage src/ tests/ --skip-private --skip-magic -description = Run the docstr-coverage tool to check documentation coverage \ No newline at end of file +description = Run the docstr-coverage tool to check documentation coverage