# 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, StrictStr
from typing import Any, ClassVar, Dict, List, Optional
from typing_extensions import Annotated
from lance_namespace_urllib3_client.models.identity import Identity
from typing import Optional, Set
from typing_extensions import Self

class CountTableRowsRequest(BaseModel):
    """
    CountTableRowsRequest
    """ # noqa: E501
    identity: Optional[Identity] = None
    context: Optional[Dict[str, StrictStr]] = Field(default=None, description="Arbitrary context for a request as key-value pairs. How to use the context is custom to the specific implementation.  REST NAMESPACE ONLY Context entries are passed via HTTP headers using the naming convention `x-lance-ctx-<key>: <value>`. For example, a context entry `{\"trace_id\": \"abc123\"}` would be sent as the header `x-lance-ctx-trace_id: abc123`. ")
    id: Optional[List[StrictStr]] = None
    version: Optional[Annotated[int, Field(strict=True, ge=0)]] = Field(default=None, description="Version of the table to describe. If not specified, server should resolve it to the latest version. ")
    predicate: Optional[StrictStr] = Field(default=None, description="Optional SQL predicate to filter rows for counting ")
    __properties: ClassVar[List[str]] = ["identity", "context", "id", "version", "predicate"]

    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 CountTableRowsRequest 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 identity
        if self.identity:
            _dict['identity'] = self.identity.to_dict()
        return _dict

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

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

        _obj = cls.model_validate({
            "identity": Identity.from_dict(obj["identity"]) if obj.get("identity") is not None else None,
            "context": obj.get("context"),
            "id": obj.get("id"),
            "version": obj.get("version"),
            "predicate": obj.get("predicate")
        })
        return _obj