Source code for sdmx.util

import logging
import typing
from enum import Enum
from functools import lru_cache
from typing import Any, Mapping, Tuple, TypeVar, Union

import pydantic
from pydantic import Field, ValidationError, validator
from pydantic.class_validators import make_generic_validator
from pydantic.typing import get_origin  # type: ignore [attr-defined]

KT = TypeVar("KT")
VT = TypeVar("VT")

log = logging.getLogger(__name__)

__all__ = [
    "BaseModel",
    "DictLike",
    "Resource",
    "compare",
    "dictlike_field",
    "summarize_dictlike",
    "validate_dictlike",
    "validator",
]


[docs]class Resource(str, Enum): """Enumeration of SDMX REST API endpoints. ====================== ================================================ :class:`Enum` member :mod:`sdmx.model` class ====================== ================================================ ``categoryscheme`` :class:`.CategoryScheme` ``codelist`` :class:`.Codelist` ``conceptscheme`` :class:`.ConceptScheme` ``data`` :class:`.DataSet` ``dataflow`` :class:`.DataflowDefinition` ``datastructure`` :class:`.DataStructureDefinition` ``provisionagreement`` :class:`.ProvisionAgreement` ====================== ================================================ """ # agencyscheme = 'agencyscheme' # attachementconstraint = 'attachementconstraint' # categorisation = 'categorisation' categoryscheme = "categoryscheme" codelist = "codelist" conceptscheme = "conceptscheme" # contentconstraint = 'contentconstraint' data = "data" # dataconsumerscheme = 'dataconsumerscheme' dataflow = "dataflow" # dataproviderscheme = 'dataproviderscheme' datastructure = "datastructure" # hierarchicalcodelist = 'hierarchicalcodelist' # metadata = 'metadata' # metadataflow = 'metadataflow' # metadatastructure = 'metadatastructure' # organisationscheme = 'organisationscheme' # organisationunitscheme = 'organisationunitscheme' # process = 'process' provisionagreement = "provisionagreement" # reportingtaxonomy = 'reportingtaxonomy' # schema = 'schema' # structure = 'structure' # structureset = 'structureset'
[docs] @classmethod def from_obj(cls, obj): """Return an enumeration value based on the class of *obj*.""" clsname = {"DataStructureDefinition": "datastructure"}.get( obj.__class__.__name__, obj.__class__.__name__ ) return cls[clsname.lower()]
@classmethod def describe(cls): return "{" + " ".join(v.name for v in cls._member_map_.values()) + "}"
[docs]class BaseModel(pydantic.BaseModel): """Common settings for :class:`pydantic.BaseModel` in :mod:`sdmx`."""
[docs] class Config: copy_on_model_validation = False validate_assignment = True
[docs]class DictLike(dict, typing.MutableMapping[KT, VT]): """Container with features of a dict & list, plus attribute access.""" __slots__ = ("__dict__", "__field") def __init__(self, *args, **kwargs): super().__init__(*args, **kwargs) # Ensures attribute access to dict items self.__dict__ = self # Reference to the pydantic.field.ModelField for the entries self.__field = None def __getitem__(self, key: Union[KT, int]) -> VT: """:meth:`dict.__getitem__` with integer access.""" try: return super().__getitem__(key) except KeyError: if isinstance(key, int): # int() index access return list(self.values())[key] else: raise def __setitem__(self, key: KT, value: VT) -> None: """:meth:`dict.__setitem` with validation.""" super().__setitem__(*self._validate_entry(key, value)) def __copy__(self): # Construct explicitly to avoid returning the parent class, dict() return DictLike(**self)
[docs] def copy(self): """Return a copy of the DictLike.""" return self.__copy__()
# pydantic compat @classmethod def __get_validators__(cls): yield cls._validate_whole @classmethod def _validate_whole(cls, v, field: pydantic.fields.ModelField): """Validate `v` as an entire DictLike object.""" # Convert anything that can be converted to a dict(). pydantic internals catch # most other invalid types, e.g. set(); no need to handle them here. result = cls(v) # Reference to the pydantic.field.ModelField for the entries result.__field = field return result def _validate_entry(self, key, value): """Validate one `key`/`value` pair.""" try: # Use pydantic's validation machinery v, error = self.__field._validate_mapping_like( ((key, value),), values={}, loc=(), cls=None ) except AttributeError: # .__field is not populated return key, value else: if error: raise ValidationError([error], self.__class__) else: return v.popitem()
[docs] def compare(self, other, strict=True): """Return :obj:`True` if `self` is the same as `other`. Two DictLike instances are identical if they contain the same set of keys, and corresponding values compare equal. Parameters ---------- strict : bool, optional Passed to :func:`compare` for the values. """ if set(self.keys()) != set(other.keys()): log.info(f"Not identical: {sorted(self.keys())} / {sorted(other.keys())}") return False for key, value in self.items(): if not value.compare(other[key], strict): return False return True
# Utility methods for DictLike # # These are defined in separate functions to avoid collisions with keys and the # attribute access namespace, e.g. if the DictLike contains keys "summarize" or # "validate".
[docs]def dictlike_field(): """Shorthand for :class:`pydantic.Field` with :class:`.DictLike` default factory.""" return Field(default_factory=DictLike)
[docs]def summarize_dictlike(dl, maxwidth=72): """Return a string summary of the DictLike contents.""" value_cls = dl[0].__class__.__name__ count = len(dl) keys = " ".join(dl.keys()) result = f"{value_cls} ({count}): {keys}" if len(result) > maxwidth: # Truncate the list of keys result = result[: maxwidth - 3] + "..." return result
[docs]def validate_dictlike(cls): """Adjust `cls` so that its DictLike members are validated. This is necessary because DictLike is a subclass of :class:`dict`, and so :mod:`pydantic` fails to call :meth:`~DictLike.__get_validators__` and register those on BaseModels which include DictLike members. """ # Iterate over annotated members of `cls`; only those which are DictLike for name, anno in filter( lambda item: get_origin(item[1]) is DictLike, cls.__annotations__.items() ): # Add the validator(s) field = cls.__fields__[name] field.post_validators = field.post_validators or [] field.post_validators.extend( make_generic_validator(v) for v in DictLike.__get_validators__() ) return cls
[docs]def compare(attr, a, b, strict: bool) -> bool: """Return :obj:`True` if ``a.attr`` == ``b.attr``. If strict is :obj:`False`, :obj:`None` is permissible as `a` or `b`; otherwise, """ return getattr(a, attr) == getattr(b, attr) or ( not strict and None in (getattr(a, attr), getattr(b, attr)) )
# if not result: # log.info(f"Not identical: {attr}={getattr(a, attr)} / {getattr(b, attr)}") # return result @lru_cache() def direct_fields(cls) -> Mapping[str, pydantic.fields.ModelField]: """Return the :mod:`pydantic` fields defined on `obj` or its class. This is like the ``__fields__`` attribute, but excludes the fields defined on any parent class(es). """ return { name: info for name, info in cls.__fields__.items() if name not in set(cls.mro()[1].__fields__.keys()) } try: from typing import get_args # type: ignore [attr-defined] except ImportError: def get_args(tp) -> Tuple[Any, ...]: """For Python <3.8.""" return tp.__args__