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Implement MDIO Dataset builder to create in-memory instance of schemas.v1.dataset.Dataset #568
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9dd9fbc
schema_v1-dataset_builder-add_dimension
dmitriyrepin f88531e
Merge remote-tracking branch 'upstream/v1' into v1
dmitriyrepin 1358f95
First take on add_dimension(), add_coordinate(), add_variable()
dmitriyrepin e5261cb
Finished add_dimension, add_coordinate, add_variable
dmitriyrepin 95c01d8
Work on build
dmitriyrepin 46f82f0
Generalize _to_dictionary()
dmitriyrepin 0dc7cc8
build
dmitriyrepin 79863ac
Dataset Build - pass one
dmitriyrepin ec480f1
Merge the latest TGSAI/mdio-python:v1 branch
dmitriyrepin fa81ea2
Merge branch 'v1' into v1
tasansal 4b2b163
Revert .container changes
dmitriyrepin c532c3b
PR review: remove DEVELOPER_NOTES.md
dmitriyrepin 08798cd
PR Review: add_coordinate() should accept only data_type: ScalarType
dmitriyrepin e8febe4
PR review: add_variable() data_type remove default
dmitriyrepin 0a4be3f
RE review: do not add dimension variable
dmitriyrepin 7b25d6b
PR Review: get api version from the package version
dmitriyrepin 7ca3ed8
PR Review: remove add_dimension_coordinate
dmitriyrepin 4d1ec9c
PR Review: add_coordinate() remove data_type default value
dmitriyrepin 99fcf43
PR Review: improve unit tests by extracting common functionality in v…
dmitriyrepin 0778fdd
Remove the Dockerfile changes. They are not supposed to be a part of …
dmitriyrepin 7e74567
PR Review: run ruff
dmitriyrepin 0aaa5f6
PR Review: fix pre-commit errors
dmitriyrepin 1904dee
remove some noqa overrides
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"""Builder pattern implementation for MDIO v1 schema models.""" | ||
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from datetime import UTC | ||
from datetime import datetime | ||
from enum import Enum | ||
from enum import auto | ||
from importlib import metadata | ||
from typing import Any | ||
from typing import TypeAlias | ||
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from pydantic import BaseModel | ||
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from mdio.schemas.compressors import ZFP | ||
from mdio.schemas.compressors import Blosc | ||
from mdio.schemas.dimension import NamedDimension | ||
from mdio.schemas.dtype import ScalarType | ||
from mdio.schemas.dtype import StructuredType | ||
from mdio.schemas.metadata import ChunkGridMetadata | ||
from mdio.schemas.metadata import UserAttributes | ||
from mdio.schemas.v1.dataset import Dataset | ||
from mdio.schemas.v1.dataset import DatasetInfo | ||
from mdio.schemas.v1.stats import StatisticsMetadata | ||
from mdio.schemas.v1.units import AllUnits | ||
from mdio.schemas.v1.variable import Coordinate | ||
from mdio.schemas.v1.variable import Variable | ||
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AnyMetadataList: TypeAlias = list[ | ||
AllUnits | UserAttributes | ChunkGridMetadata | StatisticsMetadata | DatasetInfo | ||
] | ||
CoordinateMetadataList: TypeAlias = list[AllUnits | UserAttributes] | ||
VariableMetadataList: TypeAlias = list[ | ||
AllUnits | UserAttributes | ChunkGridMetadata | StatisticsMetadata | ||
] | ||
DatasetMetadataList: TypeAlias = list[DatasetInfo | UserAttributes] | ||
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class _BuilderState(Enum): | ||
"""States for the template builder.""" | ||
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INITIAL = auto() | ||
HAS_DIMENSIONS = auto() | ||
HAS_COORDINATES = auto() | ||
HAS_VARIABLES = auto() | ||
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def _get_named_dimension( | ||
dimensions: list[NamedDimension], name: str, size: int | None = None | ||
) -> NamedDimension | None: | ||
"""Get a dimension by name and optional size from the list[NamedDimension].""" | ||
if dimensions is None: | ||
return False | ||
if not isinstance(name, str): | ||
msg = f"Expected str, got {type(name).__name__}" | ||
raise TypeError(msg) | ||
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nd = next((dim for dim in dimensions if dim.name == name), None) | ||
if nd is None: | ||
return None | ||
if size is not None and nd.size != size: | ||
msg = f"Dimension {name!r} found but size {nd.size} does not match expected size {size}" | ||
raise ValueError(msg) | ||
return nd | ||
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def _to_dictionary(val: BaseModel | dict[str, Any] | AnyMetadataList) -> dict[str, Any]: | ||
"""Convert a dictionary, list or pydantic BaseModel to a dictionary.""" | ||
if val is None: | ||
return None | ||
if isinstance(val, BaseModel): | ||
return val.model_dump(mode="json", by_alias=True) | ||
if isinstance(val, dict): | ||
return val | ||
if isinstance(val, list): | ||
metadata_dict = {} | ||
for md in val: | ||
if md is None: | ||
continue | ||
metadata_dict.update(_to_dictionary(md)) | ||
return metadata_dict | ||
msg = f"Expected BaseModel, dict or list, got {type(val).__name__}" | ||
raise TypeError(msg) | ||
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class MDIODatasetBuilder: | ||
"""Builder for creating MDIO datasets with enforced build order. | ||
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This builder implements the builder pattern to create MDIO datasets with a v1 schema. | ||
It enforces a specific build order to ensure valid dataset construction: | ||
1. Must add dimensions first via add_dimension() | ||
2. Can optionally add coordinates via add_coordinate() | ||
3. Must add variables via add_variable() | ||
4. Must call build() to create the dataset. | ||
""" | ||
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def __init__(self, name: str, attributes: UserAttributes | None = None): | ||
try: | ||
api_version = metadata.version("multidimio") | ||
except metadata.PackageNotFoundError: | ||
api_version = "unknown" | ||
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self._info = DatasetInfo(name=name, api_version=api_version, created_on=datetime.now(UTC)) | ||
self._attributes = attributes | ||
self._dimensions: list[NamedDimension] = [] | ||
self._coordinates: list[Coordinate] = [] | ||
self._variables: list[Variable] = [] | ||
self._state = _BuilderState.INITIAL | ||
self._unnamed_variable_counter = 0 | ||
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def add_dimension(self, name: str, size: int) -> "MDIODatasetBuilder": | ||
"""Add a dimension. | ||
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This function be called at least once before adding coordinates or variables. | ||
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Args: | ||
name: Name of the dimension | ||
size: Size of the dimension | ||
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Raises: | ||
ValueError: If 'name' is not a non-empty string. | ||
if the dimension is already defined. | ||
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Returns: | ||
self: Returns self for method chaining | ||
""" | ||
if not name: | ||
msg = "'name' must be a non-empty string" | ||
raise ValueError(msg) | ||
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# Validate that the dimension is not already defined | ||
old_var = next((e for e in self._dimensions if e.name == name), None) | ||
if old_var is not None: | ||
msg = "Adding dimension with the same name twice is not allowed" | ||
raise ValueError(msg) | ||
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dim = NamedDimension(name=name, size=size) | ||
self._dimensions.append(dim) | ||
self._state = _BuilderState.HAS_DIMENSIONS | ||
return self | ||
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def add_coordinate( # noqa: PLR0913 | ||
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self, | ||
name: str, | ||
*, | ||
long_name: str = None, | ||
dimensions: list[str], | ||
data_type: ScalarType, | ||
compressor: Blosc | ZFP | None = None, | ||
metadata_info: CoordinateMetadataList | None = None, | ||
) -> "MDIODatasetBuilder": | ||
"""Add a coordinate after adding at least one dimension. | ||
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This function must be called after all required dimensions are added via add_dimension(). | ||
This call will create a coordinate variable. | ||
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Args: | ||
name: Name of the coordinate | ||
long_name: Optional long name for the coordinate | ||
dimensions: List of dimension names that the coordinate is associated with | ||
data_type: Data type for the coordinate (defaults to FLOAT32) | ||
compressor: Compressor used for the variable (defaults to None) | ||
metadata_info: Optional metadata information for the coordinate | ||
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Raises: | ||
ValueError: If no dimensions have been added yet. | ||
If 'name' is not a non-empty string. | ||
If 'dimensions' is not a non-empty list. | ||
If the coordinate is already defined. | ||
If any referenced dimension is not already defined. | ||
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Returns: | ||
self: Returns self for method chaining | ||
""" | ||
if self._state == _BuilderState.INITIAL: | ||
msg = "Must add at least one dimension before adding coordinates" | ||
raise ValueError(msg) | ||
if not name: | ||
msg = "'name' must be a non-empty string" | ||
raise ValueError(msg) | ||
if dimensions is None or not dimensions: | ||
msg = "'dimensions' must be a non-empty list" | ||
raise ValueError(msg) | ||
old_var = next((e for e in self._coordinates if e.name == name), None) | ||
# Validate that the coordinate is not already defined | ||
if old_var is not None: | ||
msg = "Adding coordinate with the same name twice is not allowed" | ||
raise ValueError(msg) | ||
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# Validate that all referenced dimensions are already defined | ||
named_dimensions = [] | ||
for dim_name in dimensions: | ||
nd = _get_named_dimension(self._dimensions, dim_name) | ||
if nd is None: | ||
msg = f"Pre-existing dimension named {dim_name!r} is not found" | ||
raise ValueError(msg) | ||
named_dimensions.append(nd) | ||
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meta_dict = _to_dictionary(metadata_info) | ||
coord = Coordinate( | ||
name=name, | ||
longName=long_name, | ||
dimensions=named_dimensions, | ||
compressor=compressor, | ||
dataType=data_type, | ||
metadata=meta_dict, | ||
) | ||
self._coordinates.append(coord) | ||
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# Add a coordinate variable to the dataset | ||
self.add_variable( | ||
name=coord.name, | ||
long_name=f"'{coord.name}' coordinate variable", | ||
dimensions=dimensions, # dimension names (list[str]) | ||
data_type=coord.data_type, | ||
compressor=compressor, | ||
coordinates=[name], # Use the coordinate name as a reference | ||
metadata_info=coord.metadata, | ||
) | ||
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self._state = _BuilderState.HAS_COORDINATES | ||
return self | ||
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def add_variable( # noqa: PLR0913 | ||
self, | ||
name: str, | ||
*, | ||
long_name: str = None, | ||
dimensions: list[str], | ||
data_type: ScalarType | StructuredType, | ||
compressor: Blosc | ZFP | None = None, | ||
coordinates: list[str] | None = None, | ||
metadata_info: VariableMetadataList | None = None, | ||
) -> "MDIODatasetBuilder": | ||
"""Add a variable after adding at least one dimension and, optionally, coordinate. | ||
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This function must be called after all required dimensions are added via add_dimension() | ||
This function must be called after all required coordinates are added via add_coordinate(). | ||
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If this function is called with a single dimension name that matches the variable name, | ||
it will create a dimension variable. Dimension variables are special variables that | ||
represent sampling along a dimension. | ||
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Args: | ||
name: Name of the variable | ||
long_name: Optional long name for the variable | ||
dimensions: List of dimension names that the variable is associated with | ||
data_type: Data type for the variable (defaults to FLOAT32) | ||
compressor: Compressor used for the variable (defaults to None) | ||
coordinates: List of coordinate names that the variable is associated with | ||
(defaults to None, meaning no coordinates) | ||
metadata_info: Optional metadata information for the variable | ||
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Raises: | ||
ValueError: If no dimensions have been added yet. | ||
If 'name' is not a non-empty string. | ||
If 'dimensions' is not a non-empty list. | ||
If the variable is already defined. | ||
If any referenced dimension is not already defined. | ||
If any referenced coordinate is not already defined. | ||
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Returns: | ||
self: Returns self for method chaining. | ||
""" | ||
if self._state == _BuilderState.INITIAL: | ||
msg = "Must add at least one dimension before adding variables" | ||
raise ValueError(msg) | ||
if not name: | ||
msg = "'name' must be a non-empty string" | ||
raise ValueError(msg) | ||
if dimensions is None or not dimensions: | ||
msg = "'dimensions' must be a non-empty list" | ||
raise ValueError(msg) | ||
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# Validate that the variable is not already defined | ||
old_var = next((e for e in self._variables if e.name == name), None) | ||
if old_var is not None: | ||
msg = "Adding variable with the same name twice is not allowed" | ||
raise ValueError(msg) | ||
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# Validate that all referenced dimensions are already defined | ||
named_dimensions = [] | ||
for dim_name in dimensions: | ||
nd = _get_named_dimension(self._dimensions, dim_name) | ||
if nd is None: | ||
msg = f"Pre-existing dimension named {dim_name!r} is not found" | ||
raise ValueError(msg) | ||
named_dimensions.append(nd) | ||
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coordinate_objs: list[Coordinate] = [] | ||
# Validate that all referenced coordinates are already defined | ||
if coordinates is not None: | ||
for coord in coordinates: | ||
c: Coordinate = next((c for c in self._coordinates if c.name == coord), None) | ||
if c is not None: | ||
coordinate_objs.append(c) | ||
else: | ||
msg = f"Pre-existing coordinate named {coord!r} is not found" | ||
raise ValueError(msg) | ||
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# If this is a dimension coordinate variable, embed the Coordinate into it | ||
if coordinates is not None and len(coordinates) == 1 and coordinates[0] == name: | ||
coordinates = coordinate_objs | ||
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meta_dict = _to_dictionary(metadata_info) | ||
var = Variable( | ||
name=name, | ||
long_name=long_name, | ||
dimensions=named_dimensions, | ||
data_type=data_type, | ||
compressor=compressor, | ||
coordinates=coordinates, | ||
metadata=meta_dict, | ||
) | ||
self._variables.append(var) | ||
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self._state = _BuilderState.HAS_VARIABLES | ||
return self | ||
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def build(self) -> Dataset: | ||
"""Build the final dataset. | ||
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This function must be called after at least one dimension is added via add_dimension(). | ||
It will create a Dataset object with all added dimensions, coordinates, and variables. | ||
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Raises: | ||
ValueError: If no dimensions have been added yet. | ||
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Returns: | ||
Dataset: The built dataset with all added dimensions, coordinates, and variables. | ||
""" | ||
if self._state == _BuilderState.INITIAL: | ||
msg = "Must add at least one dimension before building" | ||
raise ValueError(msg) | ||
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var_meta_dict = _to_dictionary([self._info, self._attributes]) | ||
return Dataset(variables=self._variables, metadata=var_meta_dict) |
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"""Unit tests for parts of the MDIO package related to the v1 schema.""" |
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