
"""
ARL Infrastructure API

OpenAPI specification for ARL (Agentic RL) Infrastructure custom resources. This SDK provides models for WarmPool, Sandbox, and Task Kubernetes custom resources.

The version of the OpenAPI document: v1alpha1
Generated by OpenAPI Generator (https://openapi-generator.tech)

Do not edit the class manually.
"""

from __future__ import annotations

import json
import pprint
import re  # noqa: F401
from datetime import datetime
from typing import Any, ClassVar

from pydantic import BaseModel, ConfigDict, Field, StrictStr
from typing_extensions import Self

from .condition import Condition


class SandboxStatus(BaseModel):
    """
    SandboxStatus
    """

    conditions: list[Condition] | None = None
    last_task_time: datetime | None = Field(default=None, alias="lastTaskTime")
    phase: StrictStr | None = None
    pod_ip: StrictStr | None = Field(default=None, alias="podIP")
    pod_name: StrictStr | None = Field(default=None, alias="podName")
    work_dir: StrictStr | None = Field(default=None, alias="workDir")
    __properties: ClassVar[list[str]] = [
        "conditions",
        "lastTaskTime",
        "phase",
        "podIP",
        "podName",
        "workDir",
    ]

    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) -> Self | None:
        """Create an instance of SandboxStatus 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 each item in conditions (list)
        _items = []
        if self.conditions:
            for _item_conditions in self.conditions:
                if _item_conditions:
                    _items.append(_item_conditions.to_dict())
            _dict["conditions"] = _items
        return _dict

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

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

        _obj = cls.model_validate(
            {
                "conditions": [Condition.from_dict(_item) for _item in obj["conditions"]]
                if obj.get("conditions") is not None
                else None,
                "lastTaskTime": obj.get("lastTaskTime"),
                "phase": obj.get("phase"),
                "podIP": obj.get("podIP"),
                "podName": obj.get("podName"),
                "workDir": obj.get("workDir"),
            }
        )
        return _obj
