mirror of
https://github.com/p2p-ld/numpydantic.git
synced 2024-11-12 17:54:29 +00:00
convert from poetry to pdm, remove linkml parts
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16 changed files with 348 additions and 4135 deletions
1
.gitignore
vendored
1
.gitignore
vendored
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@ -158,3 +158,4 @@ cython_debug/
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# and can be added to the global gitignore or merged into this file. For a more nuclear
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# option (not recommended) you can uncomment the following to ignore the entire idea folder.
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#.idea/
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.pdm-python
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@ -1,10 +0,0 @@
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# linkml
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```{toctree}
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:caption: LinkML
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ndarraygen
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pydanticgen
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template
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```
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@ -1,6 +0,0 @@
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# ndarraygen
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```{eval-rst}
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.. automodule:: numpydantic.linkml.ndarraygen
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:members:
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```
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@ -1,6 +0,0 @@
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# pydanticgen
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```{eval-rst}
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.. automodule:: numpydantic.linkml.pydanticgen
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:members:
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```
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@ -1,6 +0,0 @@
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# template
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```{eval-rst}
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.. automodule:: numpydantic.linkml.template
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:members:
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```
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@ -2,21 +2,9 @@
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Type and shape validation and serialization for numpy arrays in pydantic models
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This package was picked out of [nwb-linkml](https://github.com/p2p-ld/nwb-linkml/), a
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translation of the [NWB](https://www.nwb.org/) schema language and data format to
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linkML and pydantic models. It's in a hurried and limited form to make it
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available for a LinkML hackathon, but will be matured as part of `nwb-linkml` development
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as the primary place this logic exists.
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It does two primary things:
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- **Provide types** - Annotations (based on [npytyping](https://github.com/ramonhagenaars/nptyping))
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for specifying numpy arrays in pydantic models, and
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- **Generate models from LinkML** - extend the LinkML pydantic generator to create models that
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that use the [linkml-arrays](https://github.com/linkml/linkml-arrays) syntax
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```{toctree}
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:maxdepth: 2
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:caption: Contents
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@ -24,7 +12,6 @@ It does two primary things:
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overview
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ndarray
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linkml
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hooks
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todo
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```
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@ -1,8 +0,0 @@
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# ruff: noqa: E402
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# ruff: noqa: F401
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from numpydantic.linkml.ndarraygen import (
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ArrayFormat,
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LinkMLDataArray,
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LinkMLNDArray,
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NWBLinkMLArraylike,
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)
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@ -1,189 +0,0 @@
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"""
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Isolated generator for array classes
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"""
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import warnings
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from abc import ABC, abstractmethod
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from linkml_runtime.linkml_model import ClassDefinition, SlotDefinition
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from numpydantic.maps import flat_to_nptyping
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class ArrayFormat(ABC):
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"""
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Metaclass for different LinkML array source formats
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"""
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@classmethod
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def is_array(cls, cls_: ClassDefinition) -> bool:
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"""Check whether a given class matches one of our subclasses definitions"""
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return any([subcls.check(cls_) for subcls in cls.__subclasses__()])
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@classmethod
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def get(cls, cls_: ClassDefinition) -> type["ArrayFormat"]:
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"""Get matching ArrayFormat subclass"""
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for subcls in cls.__subclasses__():
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if subcls.check(cls_):
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return subcls
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@classmethod
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@abstractmethod
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def check(cls, cls_: ClassDefinition) -> bool:
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"""Method for array format subclasses to check if they match a given source class"""
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@classmethod
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@abstractmethod
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def make(cls, cls_: ClassDefinition) -> str:
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"""
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Make an annotation string from a given array format source class
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"""
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class LinkMLNDArray(ArrayFormat):
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"""
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Tentative linkml-arrays style NDArray
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"""
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@classmethod
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def check(cls, cls_: ClassDefinition) -> bool:
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"""Check if linkml:NDArray in implements"""
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return "linkml:NDArray" in cls_.implements
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@classmethod
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def make(cls, cls_: ClassDefinition) -> str:
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"""Make NDArray"""
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raise NotImplementedError("Havent implemented NDArrays yet!")
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class LinkMLDataArray(ArrayFormat):
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"""
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Tentative linkml-arrays style annotated array with indices
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"""
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@classmethod
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def check(cls, cls_: ClassDefinition) -> bool:
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"""Check if linkml:DataArray in implements"""
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return "linkml:DataArray" in cls_.implements
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@classmethod
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def make(cls, cls_: ClassDefinition) -> str:
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"""Make DataArray"""
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raise NotImplementedError("Havent generated DataArray types yet!")
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class NWBLinkMLArraylike(ArrayFormat):
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"""
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Ye Olde nwb-linkml Arraylike class
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Examples:
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TimeSeries:
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is_a: Arraylike
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attributes:
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num_times:
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name: num_times
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range: AnyType
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required: true
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num_DIM2:
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name: num_DIM2
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range: AnyType
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required: false
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num_DIM3:
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name: num_DIM3
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range: AnyType
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required: false
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num_DIM4:
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name: num_DIM4
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range: AnyType
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required: false
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"""
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@classmethod
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def check(cls, cls_: ClassDefinition) -> bool:
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"""Check if class is Arraylike"""
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return cls_.is_a == "Arraylike"
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@classmethod
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def make(cls, cls_: ClassDefinition) -> str:
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"""Make Arraylike annotation"""
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return cls._array_annotation(cls_)
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@classmethod
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def _array_annotation(cls, cls_: ClassDefinition) -> str:
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"""
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Make an annotation for an NDArray :)
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Args:
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cls_:
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Returns:
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"""
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# if none of the dimensions are optional, we just have one possible array shape
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if all([s.required for s in cls_.attributes.values()]): # pragma: no cover
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return cls._make_npytyping_range(cls_.attributes)
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# otherwise we need to make permutations
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# but not all permutations, because we typically just want to be able to exlude the last possible dimensions
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# the array classes should always be well-defined where the optional dimensions are at the end, so
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requireds = {k: v for k, v in cls_.attributes.items() if v.required}
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optionals = [(k, v) for k, v in cls_.attributes.items() if not v.required]
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annotations = []
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if len(requireds) > 0:
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# first the base case
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annotations.append(cls._make_npytyping_range(requireds))
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# then add back each optional dimension
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for i in range(len(optionals)):
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attrs = {**requireds, **{k: v for k, v in optionals[0 : i + 1]}}
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annotations.append(cls._make_npytyping_range(attrs))
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# now combine with a union:
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union = "Union[\n" + " " * 8
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union += (",\n" + " " * 8).join(annotations)
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union += "\n" + " " * 4 + "]"
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return union
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@classmethod
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def _make_npytyping_range(cls, attrs: dict[str, SlotDefinition]) -> str:
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# slot always starts with...
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prefix = "NDArray["
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# and then we specify the shape:
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shape_prefix = 'Shape["'
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# using the cardinality from the attributes
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dim_pieces = []
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for attr in attrs.values():
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shape_part = (
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str(attr.maximum_cardinality) if attr.maximum_cardinality else "*"
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)
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# do this with the most heinous chain of string replacements rather than regex
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# because i am still figuring out what needs to be subbed lol
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name_part = (
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attr.name.replace(",", "_")
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.replace(" ", "_")
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.replace("__", "_")
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.replace("|", "_")
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.replace("-", "_")
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.replace("+", "plus")
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)
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dim_pieces.append(" ".join([shape_part, name_part]))
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dimension = ", ".join(dim_pieces)
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shape_suffix = '"], '
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# all dimensions should be the same dtype
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try:
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dtype = flat_to_nptyping[list(attrs.values())[0].range]
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except KeyError as e: # pragma: no cover
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warnings.warn(str(e), stacklevel=2)
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range = list(attrs.values())[0].range
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return f"List[{range}] | {range}"
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suffix = "]"
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slot = "".join([prefix, shape_prefix, dimension, shape_suffix, dtype, suffix])
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return slot
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@ -1,652 +0,0 @@
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"""
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Patched subclass of :class:`linkml.generators.PydanticGenerator` to generate NDArrays
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swiped from ``nwb-linkml``.
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Since this is an override of the full generator originally intended for a specific format,
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this is a bit more involved than the isolated ndarray type generator. The most relevant
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parts here are:
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- The :class:`.ArrayCheck` class, which is used to determine when an array needs to be generated -
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Use this to hook into nonstandard array formats that don't match the usual ``implements`` pattern
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"""
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import sys
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from copy import copy
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from dataclasses import dataclass
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from pathlib import Path
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from types import ModuleType
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from jinja2 import Template
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from linkml.generators import PydanticGenerator as BasePydanticGenerator
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from linkml.generators.common.type_designators import (
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get_type_designator_value,
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)
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from linkml.utils.ifabsent_functions import ifabsent_value_declaration
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from linkml_runtime.linkml_model.meta import (
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Annotation,
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ClassDefinition,
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ClassDefinitionName,
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ElementName,
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SchemaDefinition,
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SlotDefinition,
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SlotDefinitionName,
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)
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from linkml_runtime.utils.compile_python import file_text
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from linkml_runtime.utils.formatutils import camelcase, underscore
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from linkml_runtime.utils.schemaview import SchemaView
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# from nwb_linkml.maps import flat_to_nptyping
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from pydantic import BaseModel
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from numpydantic.linkml.ndarraygen import ArrayFormat
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from numpydantic.linkml.template import default_template
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def module_case(name: str) -> str:
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"""
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Returns name that can be used as a python module, used for
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referring to generated pydantic and linkml models.
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Replaces with underscores:
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- -
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- .
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"""
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return name.replace("-", "_").replace(".", "_").replace("/", ".").lower()
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def version_module_case(name: str) -> str:
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"""
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:func:`.module_case` except ensure that it starts with "v"
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"""
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name = module_case(name)
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if not name.startswith("v"):
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name = "v" + name
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return name
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class LinkML_Meta(BaseModel):
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"""Extra LinkML Metadata stored as a class attribute"""
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tree_root: bool = False
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def linkml_classvar(cls: ClassDefinition) -> SlotDefinition:
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"""A class variable that holds additional linkml attrs"""
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slot = SlotDefinition(name="linkml_meta")
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slot.annotations["python_range"] = Annotation(
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"python_range", "ClassVar[LinkML_Meta]"
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)
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meta_fields = {k: getattr(cls, k, None) for k in LinkML_Meta.model_fields}
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meta_field_strings = [f"{k}={v}" for k, v in meta_fields.items() if v is not None]
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meta_field_string = ", ".join(meta_field_strings)
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slot.annotations["fixed_field"] = Annotation(
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"fixed_field", f"Field(LinkML_Meta({meta_field_string}), frozen=True)"
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)
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return slot
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@dataclass
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class PydanticGenerator(BasePydanticGenerator):
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SKIP_ENUM: tuple[str] = ("FlatDType",)
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# SKIP_SLOTS=('VectorData',)
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SKIP_SLOTS: tuple[str] = ("",)
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SKIP_CLASSES: tuple[str] = ("",)
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INJECTED_FIELDS: tuple[str] = (
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'hdf5_path: Optional[str] = Field(None, description="The absolute path that this object is stored in an NWB file")',
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'object_id: Optional[str] = Field(None, description="Unique UUID for each object")',
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)
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# SKIP_CLASSES=('VectorData','VectorIndex')
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split: bool = True
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schema_map: dict[str, SchemaDefinition] | None = None
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versions: dict = None
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"""See :meth:`.LinkMLProvider.build` for usage - a list of specific versions to import from"""
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pydantic_version = "2"
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def _locate_imports(
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self, needed_classes: list[str], sv: SchemaView
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) -> dict[str, list[str]]:
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"""
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Given a list of class names, find the python modules that need to be imported
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"""
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imports = {}
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# These classes are not generated by pydantic!
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skips = ("AnyType",)
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for cls in needed_classes:
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if cls in skips: # pragma: no cover
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continue
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# Find module that contains class
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module_name = sv.element_by_schema_map()[ElementName(cls)]
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# Don't get classes that are defined in this schema!
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if module_name == self.schema.name:
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continue
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schema_name = module_name.split(".")[0]
|
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if (
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self.versions
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and schema_name != self.schema.name.split(".")[0]
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and schema_name in self.versions
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):
|
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version = version_module_case(self.versions[schema_name])
|
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if self.split:
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local_mod_name = (
|
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"..."
|
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+ module_case(schema_name)
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+ "."
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+ version
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+ "."
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+ module_case(module_name)
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)
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else: # pragma: no cover
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local_mod_name = (
|
||||
"..."
|
||||
+ module_case(schema_name)
|
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+ "."
|
||||
+ version
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||||
+ "."
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||||
+ "namespace"
|
||||
)
|
||||
|
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else:
|
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local_mod_name = "." + module_case(module_name)
|
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if local_mod_name not in imports:
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imports[local_mod_name] = [camelcase(cls)]
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else:
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imports[local_mod_name].append(camelcase(cls))
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return imports
|
||||
|
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def _get_namespace_imports(self, sv: SchemaView) -> dict[str, list[str]]:
|
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"""
|
||||
Get imports for namespace packages. For these we import all
|
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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":
|
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needed_classes.append(clsname)
|
||||
|
||||
imports = self._locate_imports(needed_classes, sv)
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return imports
|
||||
|
||||
def _get_class_imports(
|
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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)
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||||
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)
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||||
)
|
||||
|
||||
# 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, "<string>", "exec")
|
||||
module = ModuleType(module_name)
|
||||
|
||||
exec(spec, module.__dict__)
|
||||
sys.modules[module_name] = module
|
||||
return module
|
||||
|
|
@ -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(', ')}})
|
||||
{%- else -%}
|
||||
(ConfiguredBaseModel)
|
||||
{%- endif -%}
|
||||
:
|
||||
{% if c.description -%}
|
||||
\"\"\"
|
||||
{{ c.description }}
|
||||
\"\"\"
|
||||
{%- endif %}
|
||||
{% for attr in c.attributes.values() if c.attributes -%}
|
||||
{{attr.name}}:{{ ' ' }}{%- if attr.equals_string -%}
|
||||
Literal[{{ predefined_slot_values[c.name][attr.name] }}]
|
||||
{%- else -%}
|
||||
{{ attr.annotations['python_range'].value }}
|
||||
{%- endif -%}
|
||||
{%- if attr.annotations['fixed_field'] -%}
|
||||
{{ ' ' }}= {{ attr.annotations['fixed_field'].value }}
|
||||
{%- else -%}
|
||||
{{ ' ' }}= Field(
|
||||
{%- if predefined_slot_values[c.name][attr.name] is string -%}
|
||||
{{ predefined_slot_values[c.name][attr.name] }}
|
||||
{%- elif attr.required -%}
|
||||
...
|
||||
{%- else -%}
|
||||
None
|
||||
{%- endif -%}
|
||||
{%- if attr.title != None %}, title="{{attr.title}}"{% endif -%}
|
||||
{%- if attr.description %}, description=\"\"\"{{attr.description}}\"\"\"{% endif -%}
|
||||
{%- if attr.minimum_value != None %}, ge={{attr.minimum_value}}{% endif -%}
|
||||
{%- if attr.maximum_value != None %}, le={{attr.maximum_value}}{% endif -%}
|
||||
)
|
||||
{%- endif %}
|
||||
{% else -%}
|
||||
None
|
||||
{% endfor %}
|
||||
{% endfor %}
|
||||
"""
|
||||
### FWD REFS / REBUILD MODEL ###
|
||||
if pydantic_ver == "1": # pragma: no cover
|
||||
template += """
|
||||
# Update forward refs
|
||||
# see https://pydantic-docs.helpmanual.io/usage/postponed_annotations/
|
||||
{% for c in schema.classes.values() -%}
|
||||
{{ c.name }}.update_forward_refs()
|
||||
{% endfor %}
|
||||
"""
|
||||
else:
|
||||
template += """
|
||||
# Model rebuild
|
||||
# see https://pydantic-docs.helpmanual.io/usage/models/#rebuilding-a-model
|
||||
{% for c in schema.classes.values() -%}
|
||||
{{ c.name }}.model_rebuild()
|
||||
{% endfor %}
|
||||
"""
|
||||
return template
|
||||
304
pdm.lock
Normal file
304
pdm.lock
Normal file
|
|
@ -0,0 +1,304 @@
|
|||
# This file is @generated by PDM.
|
||||
# It is not intended for manual editing.
|
||||
|
||||
[metadata]
|
||||
groups = ["default"]
|
||||
strategy = ["cross_platform", "inherit_metadata"]
|
||||
lock_version = "4.4.1"
|
||||
content_hash = "sha256:761d4dccd4e594b9e441dddefdb5677d22a4a94c129183e0bb8c88d9acbea1b9"
|
||||
|
||||
[[package]]
|
||||
name = "annotated-types"
|
||||
version = "0.6.0"
|
||||
requires_python = ">=3.8"
|
||||
summary = "Reusable constraint types to use with typing.Annotated"
|
||||
groups = ["default"]
|
||||
files = [
|
||||
{file = "annotated_types-0.6.0-py3-none-any.whl", hash = "sha256:0641064de18ba7a25dee8f96403ebc39113d0cb953a01429249d5c7564666a43"},
|
||||
{file = "annotated_types-0.6.0.tar.gz", hash = "sha256:563339e807e53ffd9c267e99fc6d9ea23eb8443c08f112651963e24e22f84a5d"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "blosc2"
|
||||
version = "2.5.1"
|
||||
requires_python = "<4,>=3.8"
|
||||
summary = "Python wrapper for the C-Blosc2 library"
|
||||
groups = ["default"]
|
||||
dependencies = [
|
||||
"msgpack",
|
||||
"ndindex>=1.4",
|
||||
"numpy>=1.20.3",
|
||||
"py-cpuinfo",
|
||||
]
|
||||
files = [
|
||||
{file = "blosc2-2.5.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:c861262b7fe317c1614a9b59b6c9edf409532b4a6aaf5b2f4ad0d79c6f800b57"},
|
||||
{file = "blosc2-2.5.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8f35b5d69a7a41e9d5054297d2540c25f8af5ea3c62e4a80ca7359292d783c04"},
|
||||
{file = "blosc2-2.5.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:546fa39f397dd54b13d7c42a4f890afaf16c70fe478712070942d464c440ce03"},
|
||||
{file = "blosc2-2.5.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:5455af77e7e94159bb4966cae554f232ca2d52bb80cd3f878ecef39cf569da2a"},
|
||||
{file = "blosc2-2.5.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:b4dc4f595bf95c350c50bb77a8749cdd08a5dc2bdf3bdb18983d49a52d60b595"},
|
||||
{file = "blosc2-2.5.1-cp310-cp310-win32.whl", hash = "sha256:873483bd5c6afb8d139039180ee57b74373232e87b032cb80389fd8bb883ea8e"},
|
||||
{file = "blosc2-2.5.1-cp310-cp310-win_amd64.whl", hash = "sha256:d5a7ef00b82fbca069e949335f9c92ce7cbe2039a9fa2e2bd4f5f418043d6262"},
|
||||
{file = "blosc2-2.5.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:da826d42d616f8a939f27e1501b40e764fded66bc80177eeaefcebdbf3b3afb8"},
|
||||
{file = "blosc2-2.5.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:ae2e0c5dc8561a6b17842ee4320b49621434c20e622c9e9f5c67c9c6eb3b06a3"},
|
||||
{file = "blosc2-2.5.1-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:af3cab9c12a4364c643266ee7d9583b526c0f484a291d72ec6efb09ea7ffbbf9"},
|
||||
{file = "blosc2-2.5.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:22f03a723130cf07e4309fe34b1360c868f4376e862f8ff664eb40d019fdd3f6"},
|
||||
{file = "blosc2-2.5.1-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:0fd109eef815ea1e50fde4f676388aa2f3bb5543502d125fb63f16ec7a014464"},
|
||||
{file = "blosc2-2.5.1-cp311-cp311-win32.whl", hash = "sha256:1a3edc3256bad04d3db30c9de7eac3a820f96e741fc754cdabb6a9991e5c37e8"},
|
||||
{file = "blosc2-2.5.1-cp311-cp311-win_amd64.whl", hash = "sha256:e7499e277c13334d54f84e74f429f32341f99f7b978deaf9a7c2e963904cb48c"},
|
||||
{file = "blosc2-2.5.1-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:ab849d3adaeb035f2f16cf495cff1792b28d58dfb3de21b9459ee355c6bb8df3"},
|
||||
{file = "blosc2-2.5.1-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:dd66e60dafcc93d4c1f815d726d76f9fb067ecc9106a6c661010e709135c79ce"},
|
||||
{file = "blosc2-2.5.1-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:eb5fcd1775b3884d9825aa51fb45253f45cfa21c77f4135fad5dc5db710c2a34"},
|
||||
{file = "blosc2-2.5.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:19f79071a336fcf1eda01cd0171291a4ab82b16cf9a15d2b4d26c010146f13b5"},
|
||||
{file = "blosc2-2.5.1-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:956a63231f1b448803e9b4bc3e704ea424c89fc14418d99093472c74f19c19e1"},
|
||||
{file = "blosc2-2.5.1-cp312-cp312-win32.whl", hash = "sha256:5856e57e0e81f9018f1a12e803b9f768fa5533175092d72d165ac60069c7d2ab"},
|
||||
{file = "blosc2-2.5.1-cp312-cp312-win_amd64.whl", hash = "sha256:585d780c5e85f251dec72b75a47666e4a261dbfe1d228769bca545e9fe07f480"},
|
||||
{file = "blosc2-2.5.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:0cb9a6ac1abc466c12bdc90052f17545512de8f854e672a1ea4d2b40292323f5"},
|
||||
{file = "blosc2-2.5.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:3def4650faa1db43143d821228ef58797108cc95d6698c4b1581909cc2b149ca"},
|
||||
{file = "blosc2-2.5.1-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:cf6efecc1a22da26c73ff5c60d0dc086db1e7edcceb6b360dd193cda893bef28"},
|
||||
{file = "blosc2-2.5.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b473472b977b770aab3bf20d0feeee84ecd5bb8b15a675287e090ce818c1cd40"},
|
||||
{file = "blosc2-2.5.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:7afe59d35d93bf8da7db8de43f4d8aef277514de43953c1e5e416ca839b9023a"},
|
||||
{file = "blosc2-2.5.1-cp39-cp39-win32.whl", hash = "sha256:4315ae8d467fe91efa0dbe22004e967008f5fe021ebb3945518f5213d7c4511f"},
|
||||
{file = "blosc2-2.5.1-cp39-cp39-win_amd64.whl", hash = "sha256:73eb5e569a91fbe67f7dd78efe6a1ca9a54afff2c847db5dfa675bfd6a424f60"},
|
||||
{file = "blosc2-2.5.1.tar.gz", hash = "sha256:47d5df50e7286edf81e629ece35f87f13f55c13c5e8545832188c420c75d1659"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "msgpack"
|
||||
version = "1.0.8"
|
||||
requires_python = ">=3.8"
|
||||
summary = "MessagePack serializer"
|
||||
groups = ["default"]
|
||||
files = [
|
||||
{file = "msgpack-1.0.8-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:505fe3d03856ac7d215dbe005414bc28505d26f0c128906037e66d98c4e95868"},
|
||||
{file = "msgpack-1.0.8-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:e6b7842518a63a9f17107eb176320960ec095a8ee3b4420b5f688e24bf50c53c"},
|
||||
{file = "msgpack-1.0.8-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:376081f471a2ef24828b83a641a02c575d6103a3ad7fd7dade5486cad10ea659"},
|
||||
{file = "msgpack-1.0.8-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5e390971d082dba073c05dbd56322427d3280b7cc8b53484c9377adfbae67dc2"},
|
||||
{file = "msgpack-1.0.8-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:00e073efcba9ea99db5acef3959efa45b52bc67b61b00823d2a1a6944bf45982"},
|
||||
{file = "msgpack-1.0.8-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:82d92c773fbc6942a7a8b520d22c11cfc8fd83bba86116bfcf962c2f5c2ecdaa"},
|
||||
{file = "msgpack-1.0.8-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:9ee32dcb8e531adae1f1ca568822e9b3a738369b3b686d1477cbc643c4a9c128"},
|
||||
{file = "msgpack-1.0.8-cp310-cp310-musllinux_1_1_i686.whl", hash = "sha256:e3aa7e51d738e0ec0afbed661261513b38b3014754c9459508399baf14ae0c9d"},
|
||||
{file = "msgpack-1.0.8-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:69284049d07fce531c17404fcba2bb1df472bc2dcdac642ae71a2d079d950653"},
|
||||
{file = "msgpack-1.0.8-cp310-cp310-win32.whl", hash = "sha256:13577ec9e247f8741c84d06b9ece5f654920d8365a4b636ce0e44f15e07ec693"},
|
||||
{file = "msgpack-1.0.8-cp310-cp310-win_amd64.whl", hash = "sha256:e532dbd6ddfe13946de050d7474e3f5fb6ec774fbb1a188aaf469b08cf04189a"},
|
||||
{file = "msgpack-1.0.8-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:9517004e21664f2b5a5fd6333b0731b9cf0817403a941b393d89a2f1dc2bd836"},
|
||||
{file = "msgpack-1.0.8-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:d16a786905034e7e34098634b184a7d81f91d4c3d246edc6bd7aefb2fd8ea6ad"},
|
||||
{file = "msgpack-1.0.8-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:e2872993e209f7ed04d963e4b4fbae72d034844ec66bc4ca403329db2074377b"},
|
||||
{file = "msgpack-1.0.8-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5c330eace3dd100bdb54b5653b966de7f51c26ec4a7d4e87132d9b4f738220ba"},
|
||||
{file = "msgpack-1.0.8-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:83b5c044f3eff2a6534768ccfd50425939e7a8b5cf9a7261c385de1e20dcfc85"},
|
||||
{file = "msgpack-1.0.8-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:1876b0b653a808fcd50123b953af170c535027bf1d053b59790eebb0aeb38950"},
|
||||
{file = "msgpack-1.0.8-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:dfe1f0f0ed5785c187144c46a292b8c34c1295c01da12e10ccddfc16def4448a"},
|
||||
{file = "msgpack-1.0.8-cp311-cp311-musllinux_1_1_i686.whl", hash = "sha256:3528807cbbb7f315bb81959d5961855e7ba52aa60a3097151cb21956fbc7502b"},
|
||||
{file = "msgpack-1.0.8-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:e2f879ab92ce502a1e65fce390eab619774dda6a6ff719718069ac94084098ce"},
|
||||
{file = "msgpack-1.0.8-cp311-cp311-win32.whl", hash = "sha256:26ee97a8261e6e35885c2ecd2fd4a6d38252246f94a2aec23665a4e66d066305"},
|
||||
{file = "msgpack-1.0.8-cp311-cp311-win_amd64.whl", hash = "sha256:eadb9f826c138e6cf3c49d6f8de88225a3c0ab181a9b4ba792e006e5292d150e"},
|
||||
{file = "msgpack-1.0.8-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:114be227f5213ef8b215c22dde19532f5da9652e56e8ce969bf0a26d7c419fee"},
|
||||
{file = "msgpack-1.0.8-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:d661dc4785affa9d0edfdd1e59ec056a58b3dbb9f196fa43587f3ddac654ac7b"},
|
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{file = "pydantic_core-2.16.3-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:2acca2be4bb2f2147ada8cac612f8a98fc09f41c89f87add7256ad27332c2fda"},
|
||||
{file = "pydantic_core-2.16.3-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:1b662180108c55dfbf1280d865b2d116633d436cfc0bba82323554873967b340"},
|
||||
{file = "pydantic_core-2.16.3-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:e7c6ed0dc9d8e65f24f5824291550139fe6f37fac03788d4580da0d33bc00c97"},
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||||
{file = "pydantic_core-2.16.3-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a6b1bb0827f56654b4437955555dc3aeeebeddc47c2d7ed575477f082622c49e"},
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||||
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||||
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||||
{file = "pydantic_core-2.16.3-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:33809aebac276089b78db106ee692bdc9044710e26f24a9a2eaa35a0f9fa70ba"},
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||||
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||||
{file = "pydantic_core-2.16.3-cp311-none-win_amd64.whl", hash = "sha256:d89ca19cdd0dd5f31606a9329e309d4fcbb3df860960acec32630297d61820df"},
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||||
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||||
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||||
{file = "pydantic_core-2.16.3-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:c9bd22a2a639e26171068f8ebb5400ce2c1bc7d17959f60a3b753ae13c632975"},
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||||
{file = "pydantic_core-2.16.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:4204e773b4b408062960e65468d5346bdfe139247ee5f1ca2a378983e11388a2"},
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||||
{file = "pydantic_core-2.16.3-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:f651dd19363c632f4abe3480a7c87a9773be27cfe1341aef06e8759599454120"},
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||||
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||||
{file = "pydantic_core-2.16.3-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:8e47755d8152c1ab5b55928ab422a76e2e7b22b5ed8e90a7d584268dd49e9c6b"},
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||||
{file = "pydantic_core-2.16.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:500960cb3a0543a724a81ba859da816e8cf01b0e6aaeedf2c3775d12ee49cade"},
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||||
{file = "pydantic_core-2.16.3-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:cf6204fe865da605285c34cf1172879d0314ff267b1c35ff59de7154f35fdc2e"},
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||||
{file = "pydantic_core-2.16.3-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:d33dd21f572545649f90c38c227cc8631268ba25c460b5569abebdd0ec5974ca"},
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||||
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||||
{file = "pydantic_core-2.16.3-cp312-none-win32.whl", hash = "sha256:f53aace168a2a10582e570b7736cc5bef12cae9cf21775e3eafac597e8551fbe"},
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||||
{file = "pydantic_core-2.16.3-cp312-none-win_amd64.whl", hash = "sha256:0d32576b1de5a30d9a97f300cc6a3f4694c428d956adbc7e6e2f9cad279e45ed"},
|
||||
{file = "pydantic_core-2.16.3-cp312-none-win_arm64.whl", hash = "sha256:ec08be75bb268473677edb83ba71e7e74b43c008e4a7b1907c6d57e940bf34b6"},
|
||||
{file = "pydantic_core-2.16.3-cp39-cp39-macosx_10_12_x86_64.whl", hash = "sha256:bda1ee3e08252b8d41fa5537413ffdddd58fa73107171a126d3b9ff001b9b820"},
|
||||
{file = "pydantic_core-2.16.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:21b888c973e4f26b7a96491c0965a8a312e13be108022ee510248fe379a5fa23"},
|
||||
{file = "pydantic_core-2.16.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:be0ec334369316fa73448cc8c982c01e5d2a81c95969d58b8f6e272884df0074"},
|
||||
{file = "pydantic_core-2.16.3-cp39-cp39-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:b5b6079cc452a7c53dd378c6f881ac528246b3ac9aae0f8eef98498a75657805"},
|
||||
{file = "pydantic_core-2.16.3-cp39-cp39-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:7ee8d5f878dccb6d499ba4d30d757111847b6849ae07acdd1205fffa1fc1253c"},
|
||||
{file = "pydantic_core-2.16.3-cp39-cp39-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:7233d65d9d651242a68801159763d09e9ec96e8a158dbf118dc090cd77a104c9"},
|
||||
{file = "pydantic_core-2.16.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c6119dc90483a5cb50a1306adb8d52c66e447da88ea44f323e0ae1a5fcb14256"},
|
||||
{file = "pydantic_core-2.16.3-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:578114bc803a4c1ff9946d977c221e4376620a46cf78da267d946397dc9514a8"},
|
||||
{file = "pydantic_core-2.16.3-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:d8f99b147ff3fcf6b3cc60cb0c39ea443884d5559a30b1481e92495f2310ff2b"},
|
||||
{file = "pydantic_core-2.16.3-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:4ac6b4ce1e7283d715c4b729d8f9dab9627586dafce81d9eaa009dd7f25dd972"},
|
||||
{file = "pydantic_core-2.16.3-cp39-none-win32.whl", hash = "sha256:e7774b570e61cb998490c5235740d475413a1f6de823169b4cf94e2fe9e9f6b2"},
|
||||
{file = "pydantic_core-2.16.3-cp39-none-win_amd64.whl", hash = "sha256:9091632a25b8b87b9a605ec0e61f241c456e9248bfdcf7abdf344fdb169c81cf"},
|
||||
{file = "pydantic_core-2.16.3-pp310-pypy310_pp73-macosx_10_12_x86_64.whl", hash = "sha256:36fa178aacbc277bc6b62a2c3da95226520da4f4e9e206fdf076484363895d2c"},
|
||||
{file = "pydantic_core-2.16.3-pp310-pypy310_pp73-macosx_11_0_arm64.whl", hash = "sha256:dcca5d2bf65c6fb591fff92da03f94cd4f315972f97c21975398bd4bd046854a"},
|
||||
{file = "pydantic_core-2.16.3-pp310-pypy310_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:2a72fb9963cba4cd5793854fd12f4cfee731e86df140f59ff52a49b3552db241"},
|
||||
{file = "pydantic_core-2.16.3-pp310-pypy310_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b60cc1a081f80a2105a59385b92d82278b15d80ebb3adb200542ae165cd7d183"},
|
||||
{file = "pydantic_core-2.16.3-pp310-pypy310_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:cbcc558401de90a746d02ef330c528f2e668c83350f045833543cd57ecead1ad"},
|
||||
{file = "pydantic_core-2.16.3-pp310-pypy310_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:fee427241c2d9fb7192b658190f9f5fd6dfe41e02f3c1489d2ec1e6a5ab1e04a"},
|
||||
{file = "pydantic_core-2.16.3-pp310-pypy310_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:f4cb85f693044e0f71f394ff76c98ddc1bc0953e48c061725e540396d5c8a2e1"},
|
||||
{file = "pydantic_core-2.16.3-pp310-pypy310_pp73-win_amd64.whl", hash = "sha256:b29eeb887aa931c2fcef5aa515d9d176d25006794610c264ddc114c053bf96fe"},
|
||||
{file = "pydantic_core-2.16.3-pp39-pypy39_pp73-macosx_10_12_x86_64.whl", hash = "sha256:a425479ee40ff021f8216c9d07a6a3b54b31c8267c6e17aa88b70d7ebd0e5e5b"},
|
||||
{file = "pydantic_core-2.16.3-pp39-pypy39_pp73-macosx_11_0_arm64.whl", hash = "sha256:5c5cbc703168d1b7a838668998308018a2718c2130595e8e190220238addc96f"},
|
||||
{file = "pydantic_core-2.16.3-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:99b6add4c0b39a513d323d3b93bc173dac663c27b99860dd5bf491b240d26137"},
|
||||
{file = "pydantic_core-2.16.3-pp39-pypy39_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:75f76ee558751746d6a38f89d60b6228fa174e5172d143886af0f85aa306fd89"},
|
||||
{file = "pydantic_core-2.16.3-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:00ee1c97b5364b84cb0bd82e9bbf645d5e2871fb8c58059d158412fee2d33d8a"},
|
||||
{file = "pydantic_core-2.16.3-pp39-pypy39_pp73-musllinux_1_1_aarch64.whl", hash = "sha256:287073c66748f624be4cef893ef9174e3eb88fe0b8a78dc22e88eca4bc357ca6"},
|
||||
{file = "pydantic_core-2.16.3-pp39-pypy39_pp73-musllinux_1_1_x86_64.whl", hash = "sha256:ed25e1835c00a332cb10c683cd39da96a719ab1dfc08427d476bce41b92531fc"},
|
||||
{file = "pydantic_core-2.16.3-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:86b3d0033580bd6bbe07590152007275bd7af95f98eaa5bd36f3da219dcd93da"},
|
||||
{file = "pydantic_core-2.16.3.tar.gz", hash = "sha256:1cac689f80a3abab2d3c0048b29eea5751114054f032a941a32de4c852c59cad"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "typing-extensions"
|
||||
version = "4.10.0"
|
||||
requires_python = ">=3.8"
|
||||
summary = "Backported and Experimental Type Hints for Python 3.8+"
|
||||
groups = ["default"]
|
||||
files = [
|
||||
{file = "typing_extensions-4.10.0-py3-none-any.whl", hash = "sha256:69b1a937c3a517342112fb4c6df7e72fc39a38e7891a5730ed4985b5214b5475"},
|
||||
{file = "typing_extensions-4.10.0.tar.gz", hash = "sha256:b0abd7c89e8fb96f98db18d86106ff1d90ab692004eb746cf6eda2682f91b3cb"},
|
||||
]
|
||||
3002
poetry.lock
generated
3002
poetry.lock
generated
File diff suppressed because it is too large
Load diff
|
|
@ -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 <sneakers-the-rat@protonmail.com>"]
|
||||
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"
|
||||
]
|
||||
]
|
||||
0
src/numpydantic/__init__.py
Normal file
0
src/numpydantic/__init__.py
Normal file
0
tests/__init__.py
Normal file
0
tests/__init__.py
Normal file
|
|
@ -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)
|
||||
Loading…
Reference in a new issue