# 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: 0.81.1
    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 mixpeek.models.logical_operator_input import LogicalOperatorInput
from typing import Optional, Set
from typing_extensions import Self

class TriggerCollectionRequest(BaseModel):
    """
    Request to trigger (re)processing through a collection.  **For bucket-sourced collections (tier 0):** Discovers objects from source bucket(s) and creates a batch for processing. Use `include_buckets` to limit which source buckets to process from.  **For collection-sourced collections (tier N):** Processes existing documents from upstream collection(s). Use `include_collections` to limit which source collections to process from.  Use `source_filters` for field-level filtering on objects or documents.  **Document Overwrite Behavior:** - If source bucket has `unique_key` configured: Documents are UPSERTED (overwrites existing) - If source bucket has NO `unique_key`: New documents are CREATED (may cause duplicates)  To enable idempotent re-processing, configure `unique_key` on the source bucket.
    """ # noqa: E501
    include_buckets: Optional[List[StrictStr]] = Field(default=None, description="Limit processing to objects from these specific buckets (IDs or names). Only applies to bucket-sourced collections. If not provided, all configured source buckets are used.")
    include_collections: Optional[List[StrictStr]] = Field(default=None, description="Limit processing to documents from these specific collections (IDs or names). Only applies to collection-sourced collections. If not provided, all configured source collections are used.")
    source_filters: Optional[LogicalOperatorInput] = Field(default=None, description="Field-level filters for objects (bucket-sourced) or documents (collection-sourced). Uses LogicalOperator format (AND/OR/NOT). Use this to filter by metadata fields, status, or any other object/document properties.")
    __properties: ClassVar[List[str]] = ["include_buckets", "include_collections", "source_filters"]

    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 TriggerCollectionRequest 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 source_filters
        if self.source_filters:
            _dict['source_filters'] = self.source_filters.to_dict()
        return _dict

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

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

        _obj = cls.model_validate({
            "include_buckets": obj.get("include_buckets"),
            "include_collections": obj.get("include_collections"),
            "source_filters": LogicalOperatorInput.from_dict(obj["source_filters"]) if obj.get("source_filters") is not None else None
        })
        return _obj


