diff --git a/.gitignore b/.gitignore index 68bc17f..6769ec3 100644 --- a/.gitignore +++ b/.gitignore @@ -158,3 +158,4 @@ cython_debug/ # and can be added to the global gitignore or merged into this file. For a more nuclear # option (not recommended) you can uncomment the following to ignore the entire idea folder. #.idea/ +.pdm-python \ No newline at end of file diff --git a/docs/api/linkml/index.md b/docs/api/linkml/index.md deleted file mode 100644 index 7034541..0000000 --- a/docs/api/linkml/index.md +++ /dev/null @@ -1,10 +0,0 @@ -# linkml - -```{toctree} -:caption: LinkML - -ndarraygen -pydanticgen -template -``` - diff --git a/docs/api/linkml/ndarraygen.md b/docs/api/linkml/ndarraygen.md deleted file mode 100644 index 8212088..0000000 --- a/docs/api/linkml/ndarraygen.md +++ /dev/null @@ -1,6 +0,0 @@ -# ndarraygen - -```{eval-rst} -.. automodule:: numpydantic.linkml.ndarraygen - :members: -``` \ No newline at end of file diff --git a/docs/api/linkml/pydanticgen.md b/docs/api/linkml/pydanticgen.md deleted file mode 100644 index 4f7e77e..0000000 --- a/docs/api/linkml/pydanticgen.md +++ /dev/null @@ -1,6 +0,0 @@ -# pydanticgen - -```{eval-rst} -.. automodule:: numpydantic.linkml.pydanticgen - :members: -``` \ No newline at end of file diff --git a/docs/api/linkml/template.md b/docs/api/linkml/template.md deleted file mode 100644 index d54db25..0000000 --- a/docs/api/linkml/template.md +++ /dev/null @@ -1,6 +0,0 @@ -# template - -```{eval-rst} -.. automodule:: numpydantic.linkml.template - :members: -``` \ No newline at end of file diff --git a/docs/index.md b/docs/index.md index 7b03f5a..3d6bca0 100644 --- a/docs/index.md +++ b/docs/index.md @@ -2,21 +2,9 @@ Type and shape validation and serialization for numpy arrays in pydantic models -This package was picked out of [nwb-linkml](https://github.com/p2p-ld/nwb-linkml/), a -translation of the [NWB](https://www.nwb.org/) schema language and data format to -linkML and pydantic models. It's in a hurried and limited form to make it -available for a LinkML hackathon, but will be matured as part of `nwb-linkml` development -as the primary place this logic exists. - -It does two primary things: - **Provide types** - Annotations (based on [npytyping](https://github.com/ramonhagenaars/nptyping)) for specifying numpy arrays in pydantic models, and -- **Generate models from LinkML** - extend the LinkML pydantic generator to create models that - that use the [linkml-arrays](https://github.com/linkml/linkml-arrays) syntax - - - ```{toctree} :maxdepth: 2 :caption: Contents @@ -24,7 +12,6 @@ It does two primary things: overview ndarray -linkml hooks todo ``` diff --git a/numpydantic/linkml/__init__.py b/numpydantic/linkml/__init__.py deleted file mode 100644 index 750dcbc..0000000 --- a/numpydantic/linkml/__init__.py +++ /dev/null @@ -1,8 +0,0 @@ -# ruff: noqa: E402 -# ruff: noqa: F401 -from numpydantic.linkml.ndarraygen import ( - ArrayFormat, - LinkMLDataArray, - LinkMLNDArray, - NWBLinkMLArraylike, -) diff --git a/numpydantic/linkml/ndarraygen.py b/numpydantic/linkml/ndarraygen.py deleted file mode 100644 index 0d7e590..0000000 --- a/numpydantic/linkml/ndarraygen.py +++ /dev/null @@ -1,189 +0,0 @@ -""" -Isolated generator for array classes -""" - -import warnings -from abc import ABC, abstractmethod - -from linkml_runtime.linkml_model import ClassDefinition, SlotDefinition - -from numpydantic.maps import flat_to_nptyping - - -class ArrayFormat(ABC): - """ - Metaclass for different LinkML array source formats - """ - - @classmethod - def is_array(cls, cls_: ClassDefinition) -> bool: - """Check whether a given class matches one of our subclasses definitions""" - return any([subcls.check(cls_) for subcls in cls.__subclasses__()]) - - @classmethod - def get(cls, cls_: ClassDefinition) -> type["ArrayFormat"]: - """Get matching ArrayFormat subclass""" - for subcls in cls.__subclasses__(): - if subcls.check(cls_): - return subcls - - @classmethod - @abstractmethod - def check(cls, cls_: ClassDefinition) -> bool: - """Method for array format subclasses to check if they match a given source class""" - - @classmethod - @abstractmethod - def make(cls, cls_: ClassDefinition) -> str: - """ - Make an annotation string from a given array format source class - """ - - -class LinkMLNDArray(ArrayFormat): - """ - Tentative linkml-arrays style NDArray - """ - - @classmethod - def check(cls, cls_: ClassDefinition) -> bool: - """Check if linkml:NDArray in implements""" - return "linkml:NDArray" in cls_.implements - - @classmethod - def make(cls, cls_: ClassDefinition) -> str: - """Make NDArray""" - raise NotImplementedError("Havent implemented NDArrays yet!") - - -class LinkMLDataArray(ArrayFormat): - """ - Tentative linkml-arrays style annotated array with indices - """ - - @classmethod - def check(cls, cls_: ClassDefinition) -> bool: - """Check if linkml:DataArray in implements""" - return "linkml:DataArray" in cls_.implements - - @classmethod - def make(cls, cls_: ClassDefinition) -> str: - """Make DataArray""" - raise NotImplementedError("Havent generated DataArray types yet!") - - -class NWBLinkMLArraylike(ArrayFormat): - """ - Ye Olde nwb-linkml Arraylike class - - Examples: - - TimeSeries: - is_a: Arraylike - attributes: - num_times: - name: num_times - range: AnyType - required: true - num_DIM2: - name: num_DIM2 - range: AnyType - required: false - num_DIM3: - name: num_DIM3 - range: AnyType - required: false - num_DIM4: - name: num_DIM4 - range: AnyType - required: false - """ - - @classmethod - def check(cls, cls_: ClassDefinition) -> bool: - """Check if class is Arraylike""" - return cls_.is_a == "Arraylike" - - @classmethod - def make(cls, cls_: ClassDefinition) -> str: - """Make Arraylike annotation""" - return cls._array_annotation(cls_) - - @classmethod - def _array_annotation(cls, cls_: ClassDefinition) -> str: - """ - Make an annotation for an NDArray :) - - Args: - cls_: - - Returns: - - """ - # if none of the dimensions are optional, we just have one possible array shape - if all([s.required for s in cls_.attributes.values()]): # pragma: no cover - return cls._make_npytyping_range(cls_.attributes) - # otherwise we need to make permutations - # but not all permutations, because we typically just want to be able to exlude the last possible dimensions - # the array classes should always be well-defined where the optional dimensions are at the end, so - requireds = {k: v for k, v in cls_.attributes.items() if v.required} - optionals = [(k, v) for k, v in cls_.attributes.items() if not v.required] - - annotations = [] - if len(requireds) > 0: - # first the base case - annotations.append(cls._make_npytyping_range(requireds)) - # then add back each optional dimension - for i in range(len(optionals)): - attrs = {**requireds, **{k: v for k, v in optionals[0 : i + 1]}} - annotations.append(cls._make_npytyping_range(attrs)) - - # now combine with a union: - union = "Union[\n" + " " * 8 - union += (",\n" + " " * 8).join(annotations) - union += "\n" + " " * 4 + "]" - return union - - @classmethod - def _make_npytyping_range(cls, attrs: dict[str, SlotDefinition]) -> str: - # slot always starts with... - prefix = "NDArray[" - - # and then we specify the shape: - shape_prefix = 'Shape["' - - # using the cardinality from the attributes - dim_pieces = [] - for attr in attrs.values(): - shape_part = ( - str(attr.maximum_cardinality) if attr.maximum_cardinality else "*" - ) - - # do this with the most heinous chain of string replacements rather than regex - # because i am still figuring out what needs to be subbed lol - name_part = ( - attr.name.replace(",", "_") - .replace(" ", "_") - .replace("__", "_") - .replace("|", "_") - .replace("-", "_") - .replace("+", "plus") - ) - - dim_pieces.append(" ".join([shape_part, name_part])) - - dimension = ", ".join(dim_pieces) - - shape_suffix = '"], ' - - # all dimensions should be the same dtype - try: - dtype = flat_to_nptyping[list(attrs.values())[0].range] - except KeyError as e: # pragma: no cover - warnings.warn(str(e), stacklevel=2) - range = list(attrs.values())[0].range - return f"List[{range}] | {range}" - suffix = "]" - - slot = "".join([prefix, shape_prefix, dimension, shape_suffix, dtype, suffix]) - return slot diff --git a/numpydantic/linkml/pydanticgen.py b/numpydantic/linkml/pydanticgen.py deleted file mode 100644 index ec24d80..0000000 --- a/numpydantic/linkml/pydanticgen.py +++ /dev/null @@ -1,652 +0,0 @@ -""" -Patched subclass of :class:`linkml.generators.PydanticGenerator` to generate NDArrays -swiped from ``nwb-linkml``. - -Since this is an override of the full generator originally intended for a specific format, -this is a bit more involved than the isolated ndarray type generator. The most relevant -parts here are: -- The :class:`.ArrayCheck` class, which is used to determine when an array needs to be generated - - Use this to hook into nonstandard array formats that don't match the usual ``implements`` pattern - - -""" -import sys -from copy import copy -from dataclasses import dataclass -from pathlib import Path -from types import ModuleType - -from jinja2 import Template -from linkml.generators import PydanticGenerator as BasePydanticGenerator -from linkml.generators.common.type_designators import ( - get_type_designator_value, -) -from linkml.utils.ifabsent_functions import ifabsent_value_declaration -from linkml_runtime.linkml_model.meta import ( - Annotation, - ClassDefinition, - ClassDefinitionName, - ElementName, - SchemaDefinition, - SlotDefinition, - SlotDefinitionName, -) -from linkml_runtime.utils.compile_python import file_text -from linkml_runtime.utils.formatutils import camelcase, underscore -from linkml_runtime.utils.schemaview import SchemaView - -# from nwb_linkml.maps import flat_to_nptyping -from pydantic import BaseModel - -from numpydantic.linkml.ndarraygen import ArrayFormat -from numpydantic.linkml.template import default_template - - -def module_case(name: str) -> str: - """ - Returns name that can be used as a python module, used for - referring to generated pydantic and linkml models. - - Replaces with underscores: - - - - - . - """ - return name.replace("-", "_").replace(".", "_").replace("/", ".").lower() - - -def version_module_case(name: str) -> str: - """ - :func:`.module_case` except ensure that it starts with "v" - """ - name = module_case(name) - if not name.startswith("v"): - name = "v" + name - return name - - -class LinkML_Meta(BaseModel): - """Extra LinkML Metadata stored as a class attribute""" - - tree_root: bool = False - - -def linkml_classvar(cls: ClassDefinition) -> SlotDefinition: - """A class variable that holds additional linkml attrs""" - slot = SlotDefinition(name="linkml_meta") - slot.annotations["python_range"] = Annotation( - "python_range", "ClassVar[LinkML_Meta]" - ) - meta_fields = {k: getattr(cls, k, None) for k in LinkML_Meta.model_fields} - meta_field_strings = [f"{k}={v}" for k, v in meta_fields.items() if v is not None] - meta_field_string = ", ".join(meta_field_strings) - slot.annotations["fixed_field"] = Annotation( - "fixed_field", f"Field(LinkML_Meta({meta_field_string}), frozen=True)" - ) - - return slot - - -@dataclass -class PydanticGenerator(BasePydanticGenerator): - SKIP_ENUM: tuple[str] = ("FlatDType",) - # SKIP_SLOTS=('VectorData',) - SKIP_SLOTS: tuple[str] = ("",) - SKIP_CLASSES: tuple[str] = ("",) - INJECTED_FIELDS: tuple[str] = ( - 'hdf5_path: Optional[str] = Field(None, description="The absolute path that this object is stored in an NWB file")', - 'object_id: Optional[str] = Field(None, description="Unique UUID for each object")', - ) - # SKIP_CLASSES=('VectorData','VectorIndex') - split: bool = True - schema_map: dict[str, SchemaDefinition] | None = None - versions: dict = None - """See :meth:`.LinkMLProvider.build` for usage - a list of specific versions to import from""" - pydantic_version = "2" - - def _locate_imports( - self, needed_classes: list[str], sv: SchemaView - ) -> dict[str, list[str]]: - """ - Given a list of class names, find the python modules that need to be imported - """ - imports = {} - - # These classes are not generated by pydantic! - skips = ("AnyType",) - - for cls in needed_classes: - if cls in skips: # pragma: no cover - continue - # Find module that contains class - module_name = sv.element_by_schema_map()[ElementName(cls)] - # Don't get classes that are defined in this schema! - if module_name == self.schema.name: - continue - schema_name = module_name.split(".")[0] - if ( - self.versions - and schema_name != self.schema.name.split(".")[0] - and schema_name in self.versions - ): - version = version_module_case(self.versions[schema_name]) - if self.split: - local_mod_name = ( - "..." - + module_case(schema_name) - + "." - + version - + "." - + module_case(module_name) - ) - else: # pragma: no cover - local_mod_name = ( - "..." - + module_case(schema_name) - + "." - + version - + "." - + "namespace" - ) - - else: - local_mod_name = "." + module_case(module_name) - if local_mod_name not in imports: - imports[local_mod_name] = [camelcase(cls)] - else: - imports[local_mod_name].append(camelcase(cls)) - return imports - - def _get_namespace_imports(self, sv: SchemaView) -> dict[str, list[str]]: - """ - Get imports for namespace packages. For these we import all - the tree_root classes, ie. all the classes that are top-level classes - rather than nested classes - """ - all_classes = sv.all_classes(imports=True) - needed_classes = [] - for clsname, cls in all_classes.items(): - if cls.is_a != "Arraylike": - needed_classes.append(clsname) - - imports = self._locate_imports(needed_classes, sv) - return imports - - def _get_class_imports( - self, - cls: ClassDefinition, - sv: SchemaView, - all_classes: dict[ClassDefinitionName, ClassDefinition], - class_slots: dict[str, list[SlotDefinition]], - ) -> list[str]: - """Get the imports needed for a single class""" - needed_classes = [] - needed_classes.append(cls.is_a) - # get needed classes used as ranges in class attributes - for slot in class_slots[cls.name]: - if slot.name in self.SKIP_SLOTS: # pragma: no cover - continue - if slot.range in all_classes: - needed_classes.append(slot.range) - # handle when a range is a union of classes - if slot.any_of: - for any_slot_range in slot.any_of: - if any_slot_range.range in all_classes: - needed_classes.append(any_slot_range.range) - - return needed_classes - - def _get_imports( - self, - sv: SchemaView, - local_classes: list[ClassDefinition], - class_slots: dict[str, list[SlotDefinition]], - ) -> dict[str, list[str]]: - # import from local references, rather than serializing every class in every file - if not self.split: - # we are compiling this whole thing in one big file so we don't import anything - return {} - if "is_namespace" in sv.schema.annotations and sv.schema.annotations[ - "is_namespace" - ]["value"] in ("True", True): - return self._get_namespace_imports(sv) - - all_classes = sv.all_classes(imports=True) - # local_classes = sv.all_classes(imports=False) - needed_classes = [] - # find needed classes - is_a and slot ranges - - for cls in local_classes: - # get imports for this class - needed_classes.extend( - self._get_class_imports(cls, sv, all_classes, class_slots) - ) - - # remove duplicates and arraylikes - needed_classes = [ - cls for cls in set(needed_classes) if cls is not None and cls != "Arraylike" - ] - needed_classes = [ - cls for cls in needed_classes if sv.get_class(cls).is_a != "Arraylike" - ] - - imports = self._locate_imports(needed_classes, sv) - - return imports - - def _get_classes(self, sv: SchemaView) -> list[ClassDefinition]: - if self.split: - classes = sv.all_classes(imports=False).values() - else: - classes = sv.all_classes(imports=True).values() - - # Don't want to generate classes when class_uri is linkml:Any, will - # just swap in typing.Any instead down below - classes = [ - c - for c in list(classes) - if c.is_a != "Arraylike" and c.class_uri != "linkml:Any" - ] - - return classes - - def _get_class_slots( - self, sv: SchemaView, cls: ClassDefinition - ) -> list[SlotDefinition]: - slots = [] - for slot_name in sv.class_slots(cls.name): - if slot_name in self.SKIP_SLOTS: - continue - slots.append(sv.induced_slot(slot_name, cls.name)) - return slots - - def _build_class(self, class_original: ClassDefinition) -> ClassDefinition: - class_def: ClassDefinition - class_def = copy(class_original) - class_def.name = camelcase(class_original.name) - if class_def.is_a: - class_def.is_a = camelcase(class_def.is_a) - class_def.mixins = [camelcase(p) for p in class_def.mixins] - if class_def.description: - class_def.description = class_def.description.replace('"', '\\"') - return class_def - - def _check_anyof( - self, s: SlotDefinition, sn: SlotDefinitionName, sv: SchemaView - ) -> None: # pragma: no cover - # Confirm that the original slot range (ignoring the default that comes in from - # induced_slot) isn't in addition to setting any_of - if len(s.any_of) > 0 and sv.get_slot(sn).range is not None: - base_range_subsumes_any_of = False - base_range = sv.get_slot(sn).range - base_range_cls = sv.get_class(base_range, strict=False) - if base_range_cls is not None and base_range_cls.class_uri == "linkml:Any": - base_range_subsumes_any_of = True - if not base_range_subsumes_any_of: - raise ValueError("Slot cannot have both range and any_of defined") - - def sort_classes( - self, clist: list[ClassDefinition], imports: dict[str, list[str]] - ) -> list[ClassDefinition]: - """ - sort classes such that if C is a child of P then C appears after P in the list - - Overridden method include mixin classes - - Modified from original to allow for imported classes - """ - # unnest imports - imported_classes = [] - for i in imports.values(): - imported_classes.extend(i) - - clist = list(clist) - clist = [c for c in clist if c.name not in self.SKIP_CLASSES] - slist = [] # type: list[ClassDefinition] - while len(clist) > 0: - can_add = False - for i in range(len(clist)): - candidate = clist[i] - can_add = False - if candidate.is_a: - candidates = [candidate.is_a] + candidate.mixins - else: - candidates = candidate.mixins - if not candidates: - can_add = True - - else: - if set(candidates) <= set( - [p.name for p in slist] + imported_classes - ): - can_add = True - - if can_add: - slist = slist + [candidate] - del clist[i] - break - if not can_add: # pragma: no cover - raise ValueError( - f"could not find suitable element in {clist} that does not ref {slist}" - ) - - self.sorted_class_names = [camelcase(cname) for cname in imported_classes] - self.sorted_class_names += [camelcase(c.name) for c in slist] - return slist - - def get_class_slot_range( - self, slot_range: str, inlined: bool, inlined_as_list: bool - ) -> str: - """ - Monkeypatch to convert Array typed slots and classes into npytyped hints - """ - sv = self.schemaview - range_cls = sv.get_class(slot_range) - if ArrayFormat.is_array(range_cls): - return ArrayFormat.get(range_cls).make(range_cls) - else: - return self._get_class_slot_range_origin( - slot_range, inlined, inlined_as_list - ) - - def _get_class_slot_range_origin( - self, slot_range: str, inlined: bool, inlined_as_list: bool - ) -> str: - """ - Parent class get class range - - Overriding to not use strings in the type hint when a class has an identifier value - - Not testing this method except for what we changed - """ - sv = self.schemaview - range_cls = sv.get_class(slot_range) - - # Hardcoded handling for Any - if range_cls.class_uri == "linkml:Any": # pragma: no cover - return "Any" - - # Inline the class itself only if the class is defined as inline, or if the class has no - # identifier slot and also isn't a mixin. - if ( - inlined - or inlined_as_list - or ( - # sv.get_identifier_slot(range_cls.name, use_key=True) is None and - not sv.is_mixin(range_cls.name) - ) - ): - if ( - len( - [x for x in sv.class_induced_slots(slot_range) if x.designates_type] - ) - > 0 - and len(sv.class_descendants(slot_range)) > 1 - ): # pragma: no cover - return ( - "Union[" - + ",".join([camelcase(c) for c in sv.class_descendants(slot_range)]) - + "]" - ) - else: - return f"{camelcase(slot_range)}" - - # For the more difficult cases, set string as the default and attempt to improve it - range_cls_identifier_slot_range = "str" # pragma: no cover - - # For mixins, try to use the identifier slot of descendant classes - if ( - self.gen_mixin_inheritance - and sv.is_mixin(range_cls.name) - and sv.get_identifier_slot(range_cls.name) - ): # pragma: no cover - range_cls_identifier_slot_range = self.get_mixin_identifier_range(range_cls) - - return range_cls_identifier_slot_range # pragma: no cover - - def get_class_isa_plus_mixins( - self, classes: list[ClassDefinition] | None = None - ) -> dict[str, list[str]]: - """ - Generate the inheritance list for each class from is_a plus mixins - - Patched to only get local classes - - :return: - """ - sv = self.schemaview - if classes is None: # pragma: no cover - classes = sv.all_classes(imports=False).values() - - parents = {} - for class_def in classes: - class_parents = [] - if class_def.is_a: - class_parents.append(camelcase(class_def.is_a)) - if self.gen_mixin_inheritance and class_def.mixins: # pragma: no cover - class_parents.extend([camelcase(mixin) for mixin in class_def.mixins]) - if len(class_parents) > 0: - # Use the sorted list of classes to order the parent classes, but reversed to match MRO needs - class_parents.sort(key=lambda x: self.sorted_class_names.index(x)) - class_parents.reverse() - parents[camelcase(class_def.name)] = class_parents - return parents - - def get_predefined_slot_value( - self, slot: SlotDefinition, class_def: ClassDefinition - ) -> str | None: - """ - Modified from base pydantic generator to use already grabbed induced_slot from - already-grabbed and modified classes rather than doing a fresh iteration to - save time and respect changes already made elsewhere in the serialization routine - - :return: Dictionary of dictionaries with predefined slot values for each class - """ - sv = self.schemaview - slot_value: str | None = None - # for class_def in sv.all_classes().values(): - # for slot_name in sv.class_slots(class_def.name): - # slot = sv.induced_slot(slot_name, class_def.name) - if slot.designates_type: # pragma: no cover - target_value = get_type_designator_value(sv, slot, class_def) - slot_value = f'"{target_value}"' - if slot.multivalued: - slot_value = "[" + slot_value + "]" - elif slot.ifabsent is not None: - value = ifabsent_value_declaration(slot.ifabsent, sv, class_def, slot) - slot_value = value - # Multivalued slots that are either not inlined (just an identifier) or are - # inlined as lists should get default_factory list, if they're inlined but - # not as a list, that means a dictionary - elif slot.multivalued: - # this is slow, needs to do additional induced slot calls - # has_identifier_slot = self.range_class_has_identifier_slot(slot) - - if slot.inlined and not slot.inlined_as_list: # and has_identifier_slot: - slot_value = "default_factory=dict" - else: # pragma: no cover - slot_value = "default_factory=list" - - return slot_value - - def serialize(self) -> str: - """Generate LinkML models from schema!""" - predefined_slot_values = {} - """splitting up parent class :meth:`.get_predefined_slot_values`""" - - if self.template_file is not None: # pragma: no cover - with open(self.template_file) as template_file: - template_obj = Template(template_file.read()) - else: - template_obj = Template( - default_template(self.pydantic_version, extra_classes=[LinkML_Meta]) - ) - - sv: SchemaView - sv = self.schemaview - if self.schema_map is not None: # pragma: no cover - sv.schema_map = self.schema_map - schema = sv.schema - pyschema = SchemaDefinition( - id=schema.id, - name=schema.name, - description=schema.description.replace('"', '\\"') - if schema.description - else None, - ) - # test caching if import closure - enums = self.generate_enums(sv.all_enums()) - # filter skipped enums - enums = {k: v for k, v in enums.items() if k not in self.SKIP_ENUM} - - classes = self._get_classes(sv) - # just induce slots once because that turns out to be expensive - class_slots = {} # type: Dict[str, List[SlotDefinition]] - for aclass in classes: - class_slots[aclass.name] = self._get_class_slots(sv, aclass) - - # figure out what classes we need to imports - imports = self._get_imports(sv, classes, class_slots) - - sorted_classes = self.sort_classes(classes, imports) - - for class_original in sorted_classes: - # Generate class definition - class_def = self._build_class(class_original) - - if class_def.is_a != "Arraylike": - # skip actually generating arraylike classes, just use them to generate - # the npytyping annotations - pyschema.classes[class_def.name] = class_def - else: # pragma: no cover - continue - - # Not sure why this happens - for attribute in list(class_def.attributes.keys()): - del class_def.attributes[attribute] - - # make class attr that stores extra linkml attrs - class_def.attributes["linkml_meta"] = linkml_classvar(class_def) - - class_name = class_original.name - predefined_slot_values[camelcase(class_name)] = {} - for s in class_slots[class_name]: - sn = SlotDefinitionName(s.name) - predefined_slot_value = self.get_predefined_slot_value(s, class_def) - if predefined_slot_value is not None: - predefined_slot_values[camelcase(class_name)][ - s.name - ] = predefined_slot_value - # logging.error(f'Induced slot {class_name}.{sn} == {s.name} {s.range}') - s.name = underscore(s.name) - if s.description: - s.description = s.description.replace('"', '\\"') - class_def.attributes[s.name] = s - - slot_ranges: list[str] = [] - - self._check_anyof(s, sn, sv) - - if s.any_of is not None and len(s.any_of) > 0: - # list comprehension here is pulling ranges from within AnonymousSlotExpression - slot_ranges.extend([r.range for r in s.any_of]) - else: - slot_ranges.append(s.range) - - pyranges = [ - self.generate_python_range(slot_range, s, class_def) - for slot_range in slot_ranges - ] - # -------------------------------------------------- - # Special Case - since we get abstract classes from - # potentially multiple versions (which are then different) - # model classes, we allow container classes to also - # be generic descendants of BaseModel - # -------------------------------------------------- - if "DynamicTable" in pyranges: # pragma: no cover - pyranges.append("BaseModel") - - pyranges = list(set(pyranges)) # remove duplicates - pyranges.sort() - - if len(pyranges) == 1: - pyrange = pyranges[0] - elif len(pyranges) > 1: - pyrange = f"Union[{', '.join(pyranges)}]" - else: # pragma: no cover - raise Exception( - f"Could not generate python range for {class_name}.{s.name}" - ) - - if s.multivalued: - if s.inlined or s.inlined_as_list: - collection_key = self.generate_collection_key( - slot_ranges, s, class_def - ) - else: # pragma: no cover - collection_key = None - if ( - s.inlined is False - or collection_key is None - or s.inlined_as_list is True - ): # pragma: no cover - pyrange = f"List[{pyrange}] | {pyrange}" - else: - pyrange = f"Dict[{collection_key}, {pyrange}]" - if not s.required and not s.designates_type: - pyrange = f"Optional[{pyrange}]" - ann = Annotation("python_range", pyrange) - s.annotations[ann.tag] = ann - - code = template_obj.render( - imports=imports, - schema=pyschema, - underscore=underscore, - enums=enums, - predefined_slot_values=predefined_slot_values, - allow_extra=self.allow_extra, - metamodel_version=self.schema.metamodel_version, - version=self.schema.version, - class_isa_plus_mixins=self.get_class_isa_plus_mixins(sorted_classes), - injected_fields=self.INJECTED_FIELDS, - ) - return code - - def compile_module( - self, module_path: Path = None, module_name: str = "test" - ) -> ModuleType: # pragma: no cover - replaced with provider - """ - Compiles generated python code to a module - :return: - """ - pycode = self.serialize() - if module_path is not None: - module_path = Path(module_path) - init_file = module_path / "__init__.py" - with open(init_file, "w") as ifile: - ifile.write(" ") - - try: - return compile_python(pycode, module_path, module_name) - except NameError as e: - raise e - - -def compile_python( - text_or_fn: str, package_path: Path = None, module_name: str = "test" -) -> ModuleType: - """ - Compile the text or file and return the resulting module - @param text_or_fn: Python text or file name that references python file - @param package_path: Root package path. If omitted and we've got a python file, the package is the containing - directory - @return: Compiled module - """ - python_txt = file_text(text_or_fn) - if package_path is None and python_txt != text_or_fn: - package_path = Path(text_or_fn) - spec = compile(python_txt, "", "exec") - module = ModuleType(module_name) - - exec(spec, module.__dict__) - sys.modules[module_name] = module - return module diff --git a/numpydantic/linkml/template.py b/numpydantic/linkml/template.py deleted file mode 100644 index 68a7240..0000000 --- a/numpydantic/linkml/template.py +++ /dev/null @@ -1,183 +0,0 @@ -import inspect - -from pydantic import BaseModel - - -def default_template( - pydantic_ver: str = "2", extra_classes: list[type[BaseModel]] | None = None -) -> str: - """Constructs a default template for pydantic classes based on the version of pydantic""" - ### HEADER ### - template = """ -{#- - - Jinja2 Template for a pydantic classes --#} -from __future__ import annotations -from datetime import datetime, date -from enum import Enum -from typing import Dict, Optional, Any, Union, ClassVar, Annotated, TypeVar, List, TYPE_CHECKING -from pydantic import BaseModel as BaseModel, Field""" - if pydantic_ver == "2": - template += """ -from pydantic import ConfigDict, BeforeValidator - """ - template += """ -from nptyping import Shape, Float, Float32, Double, Float64, LongLong, Int64, Int, Int32, Int16, Short, Int8, UInt, UInt32, UInt16, UInt8, UInt64, Number, String, Unicode, Unicode, Unicode, String, Bool, Datetime64 -from nwb_linkml.types import NDArray -import sys -if sys.version_info >= (3, 8): - from typing import Literal -else: - from typing_extensions import Literal -if TYPE_CHECKING: - import numpy as np - -{% for import_module, import_classes in imports.items() %} -from {{ import_module }} import ( - {{ import_classes | join(',\n ') }} -) -{% endfor %} - -metamodel_version = "{{metamodel_version}}" -version = "{{version if version else None}}" -""" - ### BASE MODEL ### - if pydantic_ver == "1": # pragma: no cover - template += """ -List = BaseList - -class WeakRefShimBaseModel(BaseModel): - __slots__ = '__weakref__' - -class ConfiguredBaseModel(WeakRefShimBaseModel, - validate_assignment = False, - validate_all = True, - underscore_attrs_are_private = True, - extra = {% if allow_extra %}'allow'{% else %}'forbid'{% endif %}, - arbitrary_types_allowed = True, - use_enum_values = True): -""" - else: - template += """ -class ConfiguredBaseModel(BaseModel): - model_config = ConfigDict( - validate_assignment = True, - validate_default = True, - extra = {% if allow_extra %}'allow'{% else %}'forbid'{% endif %}, - arbitrary_types_allowed = True, - use_enum_values = True - ) -""" - ### Injected Fields - template += """ -{%- if injected_fields != None -%} - {% for field in injected_fields %} - {{ field }} - {% endfor %} -{%- else -%} - pass -{%- endif -%} - """ - ### Getitem - template += """ - - def __getitem__(self, i: slice|int) -> 'np.ndarray': - if hasattr(self, 'array'): - return self.array[i] - else: - return super().__getitem__(i) - - def __setitem__(self, i: slice|int, value: Any): - if hasattr(self, 'array'): - self.array[i] = value - else: - super().__setitem__(i, value) - """ - - ### Extra classes - if extra_classes is not None: - template += """{{ '\n\n' }}""" - for cls in extra_classes: - template += inspect.getsource(cls) + "\n\n" - ### ENUMS ### - template += """ -{% for e in enums.values() %} -class {{ e.name }}(str, Enum): - {% if e.description -%} - \"\"\" - {{ e.description }} - \"\"\" - {%- endif %} - {% for _, pv in e['values'].items() -%} - {% if pv.description -%} - # {{pv.description}} - {%- endif %} - {{pv.label}} = "{{pv.value}}" - {% endfor %} - {% if not e['values'] -%} - dummy = "dummy" - {% endif %} -{% endfor %} -""" - ### CLASSES ### - template += """ -{%- for c in schema.classes.values() %} -class {{ c.name }} - {%- if class_isa_plus_mixins[c.name] -%} - ({{class_isa_plus_mixins[c.name]|join(', ')}}) 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-[metadata] -lock-version = "2.0" -python-versions = "^3.11" -content-hash = "705fc6a0bad3bc916dc36da3554f46fc0f0d750af32cd32ee95637f491170116" diff --git a/pyproject.toml b/pyproject.toml index 537eb48..0979e59 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,62 +1,59 @@ -[tool.poetry] +[project] name = "numpydantic" version = "0.0.0" description = "Type and shape validation and serialization for numpy arrays in pydantic models" -authors = ["sneakers-the-rat "] -license = "MIT" +authors = [ + {name = "sneakers-the-rat", email = "sneakers-the-rat@protonmail.com"}, +] +dependencies = [ + "pydantic>=2.3.0", + "nptyping>=2.5.0", + "blosc2<3.0.0,>=2.5.1", +] +requires-python = "<4.0,>=3.9" readme = "README.md" +license = {text = "MIT"} -[tool.poetry.dependencies] -python = "^3.11" -pydantic = ">=2.3.0" -nptyping = ">=2.5.0" -blosc2 = "^2.5.1" -dask = { version=">=2024.1.1", extras=["array"]} -h5py = ">=3.10.0" -pytest = { version=">=7.4.0", optional = true} -pytest-depends = {version="^1.0.1", optional = true} -coverage = {version = ">=6.1.1", optional = true} -pytest-cov = {version = "^4.1.0", optional = true} -coveralls = {version = "^3.3.1", optional = true} -sphinx = {version = "^7.2.6", optional = true} -furo = {version = ">=2024.1.29", optional = true} -myst-parser = {version = "^2.0.0", optional = true} -autodoc-pydantic = {version = "^2.0.1", optional = true} -sphinx-autobuild = {version = ">=2021.3.14", optional = true} -sphinx-design = {version = "^0.5.0", optional = true} -black = {version = "^24.1.1", optional = true} -ruff = {version = "^0.2.0", optional = true} -linkml = {version = ">=1.7.0", optional = true} -linkml-runtime = {version = ">=1.7.0", optional = true} -[tool.poetry.extras] -#proxy = [ -# "dask", "h5py" -#] -linkml = [ - "linkml", "linkml-runtime" +[project.optional-dependencies] +dask = [ + "dask[array]>=2024.1.1" +] +hdf5 = [ + "h5py>=3.10.0" +] +arrays = [ + "numpydantic[dask,hdf5]" ] tests = [ - "pytest", "pytest-depends", "coverage", "pytest-cov", "coveralls" + "numpydantic[arrays]", + "pytest>=7.4.0", + "pytest-depends<2.0.0,>=1.0.1", + "coverage>=6.1.1", + "pytest-cov<5.0.0,>=4.1.0", + "coveralls<4.0.0,>=3.3.1" ] docs = [ - "sphinx", "furo", "myst-parser", "autodoc-pydantic", "sphinx-design" -] + "sphinx<8.0.0,>=7.2.6", + "furo>=2024.1.29", + "myst-parser<3.0.0,>=2.0.0", + "autodoc-pydantic<3.0.0,>=2.0.1", + "sphinx-design<1.0.0,>=0.5.0"] dev = [ - "sphinx-autobuild", "black", "ruff", - # proxy - # "dask", "h5py", - # linkml - "linkml", "linkml-runtime", - # tests - "pytest", "pytest-depends", "coverage", "pytest-cov", "coveralls", - # docs - "sphinx", "furo", "myst-parser", "autodoc-pydantic", "sphinx-design" + "numpydantic[tests,docs]", + "sphinx-autobuild>=2021.3.14", + "black<25.0.0,>=24.1.1", + "ruff<1.0.0,>=0.2.0" ] +[tool.pdm] +distribution = true + +[tool.pdm.build] +includes = [] [build-system] -requires = ["poetry-core"] -build-backend = "poetry.core.masonry.api" +requires = ["pdm-backend"] +build-backend = "pdm.backend" [tool.pytest.ini_options] addopts = [ @@ -109,4 +106,4 @@ fixable = ["ALL"] [tool.mypy] plugins = [ "pydantic.mypy" -] +] \ No newline at end of file diff --git a/src/numpydantic/__init__.py b/src/numpydantic/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/tests/__init__.py b/tests/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/tests/test_linkml/test_ndarraygen.py b/tests/test_linkml/test_ndarraygen.py deleted file mode 100644 index ba1e554..0000000 --- a/tests/test_linkml/test_ndarraygen.py +++ /dev/null @@ -1,14 +0,0 @@ -import pytest - -from numpydantic.linkml import ArrayFormat, NWBLinkMLArraylike - -from ..fixtures import nwb_linkml_array - - -def test_nwb_linkml_array(nwb_linkml_array): - classdef, generated = nwb_linkml_array - - assert ArrayFormat.is_array(classdef) - assert NWBLinkMLArraylike.check(classdef) - assert ArrayFormat.get(classdef) is NWBLinkMLArraylike - assert generated == NWBLinkMLArraylike.make(classdef)