# coding: utf-8
"""
Amorphic Data Platform
Amorphic Data Platform - API Definition documentation
The version of the OpenAPI document: 1.0
Generated by OpenAPI Generator (https://openapi-generator.tech)
Do not edit the class manually.
""" # noqa: E501
from __future__ import annotations
import pprint
import re # noqa: F401
import json
from pydantic import BaseModel, ConfigDict, Field, StrictStr, field_validator
from typing import Any, ClassVar, Dict, List, Optional
from openapi_client.models.model_data_input_schema import ModelDataInputSchema
from typing import Optional, Set
from typing_extensions import Self
[docs]
class ModelData(BaseModel):
"""
ModelData
""" # noqa: E501
artifacts_location: Optional[StrictStr] = Field(default=None, alias="ArtifactsLocation")
existing_model_resource: Optional[StrictStr] = Field(default=None, alias="ExistingModelResource")
description: StrictStr = Field(alias="Description")
model_name: StrictStr = Field(alias="ModelName")
output_type: StrictStr = Field(alias="OutputType")
algorithm_used: StrictStr = Field(alias="AlgorithmUsed")
supported_file_formats: List[StrictStr] = Field(alias="SupportedFileFormats")
pre_processed_glue_jobs: StrictStr = Field(alias="PreProcessedGlueJobs")
post_processed_glue_jobs: StrictStr = Field(alias="PostProcessedGlueJobs")
keywords: Optional[List[StrictStr]] = Field(default=None, alias="Keywords")
input_schema: Optional[ModelDataInputSchema] = Field(default=None, alias="InputSchema")
output_schema: Optional[ModelDataInputSchema] = Field(default=None, alias="OutputSchema")
__properties: ClassVar[List[str]] = ["ArtifactsLocation", "ExistingModelResource", "Description", "ModelName", "OutputType", "AlgorithmUsed", "SupportedFileFormats", "PreProcessedGlueJobs", "PostProcessedGlueJobs", "Keywords", "InputSchema", "OutputSchema"]
[docs]
@field_validator('output_type')
def output_type_validate_enum(cls, value):
"""Validates the enum"""
if value not in set(['datasetdata', 'metadata']):
raise ValueError("must be one of enum values ('datasetdata', 'metadata')")
return value
model_config = ConfigDict(
populate_by_name=True,
validate_assignment=True,
protected_namespaces=(),
)
[docs]
def to_str(self) -> str:
"""Returns the string representation of the model using alias"""
return pprint.pformat(self.model_dump(by_alias=True))
[docs]
def to_json(self) -> str:
"""Returns the JSON representation of the model using alias"""
# TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
return json.dumps(self.to_dict())
[docs]
@classmethod
def from_json(cls, json_str: str) -> Optional[Self]:
"""Create an instance of ModelData from a JSON string"""
return cls.from_dict(json.loads(json_str))
[docs]
def to_dict(self) -> Dict[str, Any]:
"""Return the dictionary representation of the model using alias.
This has the following differences from calling pydantic's
`self.model_dump(by_alias=True)`:
* `None` is only added to the output dict for nullable fields that
were set at model initialization. Other fields with value `None`
are ignored.
"""
excluded_fields: Set[str] = set([
])
_dict = self.model_dump(
by_alias=True,
exclude=excluded_fields,
exclude_none=True,
)
# override the default output from pydantic by calling `to_dict()` of input_schema
if self.input_schema:
_dict['InputSchema'] = self.input_schema.to_dict()
# override the default output from pydantic by calling `to_dict()` of output_schema
if self.output_schema:
_dict['OutputSchema'] = self.output_schema.to_dict()
return _dict
[docs]
@classmethod
def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
"""Create an instance of ModelData from a dict"""
if obj is None:
return None
if not isinstance(obj, dict):
return cls.model_validate(obj)
_obj = cls.model_validate({
"ArtifactsLocation": obj.get("ArtifactsLocation"),
"ExistingModelResource": obj.get("ExistingModelResource"),
"Description": obj.get("Description"),
"ModelName": obj.get("ModelName"),
"OutputType": obj.get("OutputType"),
"AlgorithmUsed": obj.get("AlgorithmUsed"),
"SupportedFileFormats": obj.get("SupportedFileFormats"),
"PreProcessedGlueJobs": obj.get("PreProcessedGlueJobs"),
"PostProcessedGlueJobs": obj.get("PostProcessedGlueJobs"),
"Keywords": obj.get("Keywords"),
"InputSchema": ModelDataInputSchema.from_dict(obj["InputSchema"]) if obj.get("InputSchema") is not None else None,
"OutputSchema": ModelDataInputSchema.from_dict(obj["OutputSchema"]) if obj.get("OutputSchema") is not None else None
})
return _obj