# coding: utf-8

"""
    Daytona

    Daytona AI platform API Docs

    The version of the OpenAPI document: 1.0
    Contact: support@daytona.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, StrictFloat, StrictInt
from typing import Any, ClassVar, Dict, List, Union
from pydantic import TypeAdapter
from typing import Optional, Set
from typing_extensions import Self

_JSON_ADAPTER = TypeAdapter(Dict[str, Any])

class RunnerHealthMetrics(BaseModel):
    """
    RunnerHealthMetrics
    """ # noqa: E501
    current_cpu_load_average: Union[StrictFloat, StrictInt] = Field(description="Current CPU load average", serialization_alias="currentCpuLoadAverage")
    current_cpu_usage_percentage: Union[StrictFloat, StrictInt] = Field(description="Current CPU usage percentage", serialization_alias="currentCpuUsagePercentage")
    current_memory_usage_percentage: Union[StrictFloat, StrictInt] = Field(description="Current memory usage percentage", serialization_alias="currentMemoryUsagePercentage")
    current_disk_usage_percentage: Union[StrictFloat, StrictInt] = Field(description="Current disk usage percentage", serialization_alias="currentDiskUsagePercentage")
    current_allocated_cpu: Union[StrictFloat, StrictInt] = Field(description="Currently allocated CPU cores", serialization_alias="currentAllocatedCpu")
    current_allocated_memory_gi_b: Union[StrictFloat, StrictInt] = Field(description="Currently allocated memory in GiB", serialization_alias="currentAllocatedMemoryGiB")
    current_allocated_disk_gi_b: Union[StrictFloat, StrictInt] = Field(description="Currently allocated disk in GiB", serialization_alias="currentAllocatedDiskGiB")
    current_snapshot_count: Union[StrictFloat, StrictInt] = Field(description="Number of snapshots currently stored", serialization_alias="currentSnapshotCount")
    current_started_sandboxes: Union[StrictFloat, StrictInt] = Field(description="Number of started sandboxes", serialization_alias="currentStartedSandboxes")
    cpu: Union[StrictFloat, StrictInt] = Field(description="Total CPU cores on the runner")
    memory_gi_b: Union[StrictFloat, StrictInt] = Field(description="Total RAM in GiB on the runner", serialization_alias="memoryGiB")
    disk_gi_b: Union[StrictFloat, StrictInt] = Field(description="Total disk space in GiB on the runner", serialization_alias="diskGiB")
    additional_properties: Dict[str, Any] = {}
    __properties: ClassVar[List[str]] = ["currentCpuLoadAverage", "currentCpuUsagePercentage", "currentMemoryUsagePercentage", "currentDiskUsagePercentage", "currentAllocatedCpu", "currentAllocatedMemoryGiB", "currentAllocatedDiskGiB", "currentSnapshotCount", "currentStartedSandboxes", "cpu", "memoryGiB", "diskGiB"]

    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"""
        return _JSON_ADAPTER.dump_json(self.to_dict()).decode()

    @classmethod
    def from_json(cls, json_str: str) -> Optional[Self]:
        """Create an instance of RunnerHealthMetrics 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.
        * Fields in `self.additional_properties` are added to the output dict.
        """
        excluded_fields: Set[str] = set([
            "additional_properties",
        ])

        _dict = self.model_dump(
            by_alias=True,
            exclude=excluded_fields,
            exclude_none=True,
        )
        # puts key-value pairs in additional_properties in the top level
        if self.additional_properties is not None:
            for _key, _value in self.additional_properties.items():
                _dict[_key] = _value

        return _dict

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

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

        _obj = cls.model_validate({
            "current_cpu_load_average": obj.get("currentCpuLoadAverage"),
            "current_cpu_usage_percentage": obj.get("currentCpuUsagePercentage"),
            "current_memory_usage_percentage": obj.get("currentMemoryUsagePercentage"),
            "current_disk_usage_percentage": obj.get("currentDiskUsagePercentage"),
            "current_allocated_cpu": obj.get("currentAllocatedCpu"),
            "current_allocated_memory_gi_b": obj.get("currentAllocatedMemoryGiB"),
            "current_allocated_disk_gi_b": obj.get("currentAllocatedDiskGiB"),
            "current_snapshot_count": obj.get("currentSnapshotCount"),
            "current_started_sandboxes": obj.get("currentStartedSandboxes"),
            "cpu": obj.get("cpu"),
            "memory_gi_b": obj.get("memoryGiB"),
            "disk_gi_b": obj.get("diskGiB")
        })
        # store additional fields in additional_properties
        for _key in obj.keys():
            if _key not in cls.__properties:
                _obj.additional_properties[_key] = obj.get(_key)

        return _obj


