# coding: utf-8

"""
    Mender API

    Combined API specification for the features of the different Mender backend services, suitable for code generation applications 

    The version of the OpenAPI document: 1
    Contact: support@mender.io
    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
from typing import Any, ClassVar, Dict, List, Optional
from mender_client.models.statistics import Statistics
from typing import Optional, Set
from typing_extensions import Self

class DeploymentStatistics(BaseModel):
    """
    DeploymentStatistics
    """ # noqa: E501
    status: Optional[Statistics] = None
    total_size: Optional[StrictInt] = Field(default=None, description="Sum of sizes (in bytes) of all artifacts assigned to all device deployments, which are part of this deployment. If the same artifact is assigned to multiple device deployments, its size will be counted multiple times. ")
    __properties: ClassVar[List[str]] = ["status", "total_size"]

    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 DeploymentStatistics 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 status
        if self.status:
            _dict['status'] = self.status.to_dict()
        return _dict

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

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

        _obj = cls.model_validate({
            "status": Statistics.from_dict(obj["status"]) if obj.get("status") is not None else None,
            "total_size": obj.get("total_size")
        })
        return _obj


