# coding: utf-8

"""
    Lance Namespace Specification

    This OpenAPI specification is a part of the Lance namespace specification. It contains 2 parts:  The `components/schemas`, `components/responses`, `components/examples`, `tags` sections define the request and response shape for each operation in a Lance Namespace across all implementations. See https://lance.org/format/namespace/operations for more details.  The `servers`, `security`, `paths`, `components/parameters` sections are for the Lance REST Namespace implementation, which defines a complete REST server that can work with Lance datasets. See https://lance.org/format/namespace/rest for more details. 

    The version of the OpenAPI document: 1.0.0
    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, StrictInt, StrictStr
from typing import Any, ClassVar, Dict, List, Optional
from lance_namespace_urllib3_client.models.json_arrow_data_type import JsonArrowDataType
from lance_namespace_urllib3_client.models.partition_transform import PartitionTransform
from typing import Optional, Set
from typing_extensions import Self

class PartitionField(BaseModel):
    """
    Partition field definition
    """ # noqa: E501
    field_id: StrictStr = Field(description="Unique identifier for this partition field (must not be renamed)")
    source_ids: List[StrictInt] = Field(description="Field IDs of the source columns in the schema")
    transform: Optional[PartitionTransform] = Field(default=None, description="Well-known partition transform. Exactly one of transform or expression must be specified.")
    expression: Optional[StrictStr] = Field(default=None, description="DataFusion SQL expression using col0, col1, ... as column references. Exactly one of transform or expression must be specified.")
    result_type: JsonArrowDataType = Field(description="The output type of the partition value (JsonArrowDataType format)")
    __properties: ClassVar[List[str]] = ["field_id", "source_ids", "transform", "expression", "result_type"]

    model_config = ConfigDict(
        populate_by_name=True,
        validate_assignment=True,
        protected_namespaces=(),
    )


    def to_str(self) -> str:
        """Returns the string representation of the model using alias"""
        return pprint.pformat(self.model_dump(by_alias=True))

    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())

    @classmethod
    def from_json(cls, json_str: str) -> Optional[Self]:
        """Create an instance of PartitionField from a JSON string"""
        return cls.from_dict(json.loads(json_str))

    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 transform
        if self.transform:
            _dict['transform'] = self.transform.to_dict()
        # override the default output from pydantic by calling `to_dict()` of result_type
        if self.result_type:
            _dict['result_type'] = self.result_type.to_dict()
        return _dict

    @classmethod
    def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
        """Create an instance of PartitionField from a dict"""
        if obj is None:
            return None

        if not isinstance(obj, dict):
            return cls.model_validate(obj)

        _obj = cls.model_validate({
            "field_id": obj.get("field_id"),
            "source_ids": obj.get("source_ids"),
            "transform": PartitionTransform.from_dict(obj["transform"]) if obj.get("transform") is not None else None,
            "expression": obj.get("expression"),
            "result_type": JsonArrowDataType.from_dict(obj["result_type"]) if obj.get("result_type") is not None else None
        })
        return _obj


