# coding: utf-8

"""
    Mixpeek API

    This is the Mixpeek API, providing access to various endpoints for data processing and retrieval.

    The version of the OpenAPI document: 0.82
    Contact: info@mixpeek.com
    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
from typing import Any, ClassVar, Dict, List, Optional
from typing import Optional, Set
from typing_extensions import Self

class PatchTaxonomyRequest(BaseModel):
    """
    Request to update a taxonomy's metadata.  **IMPORTANT: Partial Updates with Controlled Mutability**  This endpoint allows updating ONLY metadata fields. Core taxonomy logic is immutable to ensure consistency for join history and dependent resources.  **✅ Fields You CAN Update (Metadata Only):** - `taxonomy_name`: Rename the taxonomy - `description`: Update documentation - `metadata`: Update custom metadata fields  **❌ Fields You CANNOT Update (Immutable Core Logic):** - `config`: Taxonomy configuration (retriever_id, input_mappings, collections, hierarchy) - `taxonomy_type`: Type (flat vs hierarchical) - `retriever_id`: Associated retriever - `input_mappings`: Field mappings - `enrichment_fields`: Enrichment configuration  **Need to Modify Core Logic?** Use POST /taxonomies/{taxonomy_id}/clone instead. Cloning creates a new taxonomy with a new ID, allowing you to: - Change retriever or input mappings - Modify enrichment fields - Update collection configuration - Change taxonomy hierarchy  **Behavior:** - All fields are OPTIONAL - provide only what you want to update - Empty updates (no fields provided) will be rejected with 400 error - Original taxonomy remains unchanged (no destructive operations)  **Why This Design?** - Join history is tied to specific taxonomy configuration - Changing retriever would invalidate previous joins - Version tracking enables auditing and rollback
    """ # noqa: E501
    taxonomy_name: Optional[StrictStr] = Field(default=None, description="Updated name for the taxonomy")
    description: Optional[StrictStr] = Field(default=None, description="Updated description for the taxonomy")
    metadata: Optional[Dict[str, Any]] = Field(default=None, description="Updated metadata for the taxonomy")
    __properties: ClassVar[List[str]] = ["taxonomy_name", "description", "metadata"]

    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 PatchTaxonomyRequest 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,
        )
        return _dict

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

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

        _obj = cls.model_validate({
            "taxonomy_name": obj.get("taxonomy_name"),
            "description": obj.get("description"),
            "metadata": obj.get("metadata")
        })
        return _obj


