# coding: utf-8 """ Usage API These usage endpoints define the following operations: * **Usage**: Retrieve usage data for the specified time period (default is one month). * Users must have the `View organization usage` permission to access this endpoint. * This operation offers visibility across all account groups within the organization. * Users with `View organization usage` permission in multiple organizations should query the operation with the `aid` query string parameter (see optional parameters) for each organization. * The `agentId` field in enterprise agent unit responses may be omitted when not available. * **Quotas**: Obtain organization and account usage quotas. Additionally, users with the appropriate permissions can create, update, or delete these quotas. * Users must have the necessary permissions to perform quota-related actions. Refer to the Usage API operations for detailed usage instructions and optional parameters. 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, StrictStr from typing import Any, ClassVar, Dict, List, Optional from typing import Optional, Set from typing_extensions import Self class EnterpriseAgentUnits(BaseModel): """ EnterpriseAgentUnits """ # noqa: E501 aid: Optional[StrictStr] = Field(default=None, description="Unique identifier of the account group owning the enterprise agent units.") account_group_name: Optional[StrictStr] = Field(default=None, description="Name of the account group which owns the enterprise agent units.", alias="accountGroupName") agent_id: Optional[StrictStr] = Field(default=None, description="Unique identifier of the enterprise agent generating usage. This field may be omitted when not available.", alias="agentId") agent_name: Optional[StrictStr] = Field(default=None, description="Name of the enterprise agent generating usage.", alias="agentName") enterprise_units_used: Optional[StrictInt] = Field(default=None, description="Number of enterprise agent units owned by the specific account group in the usage period.", alias="enterpriseUnitsUsed") enterprise_units_projected: Optional[StrictInt] = Field(default=None, description="Number of enterprise units projected in the current usage period, based on units consumed to date and configuration of enabled tests. This value is updated hourly. Returns non-zero value only for organizations with metered billing.", alias="enterpriseUnitsProjected") __properties: ClassVar[List[str]] = ["aid", "accountGroupName", "agentId", "agentName", "enterpriseUnitsUsed", "enterpriseUnitsProjected"] model_config = ConfigDict( populate_by_name=True, validate_assignment=True, protected_namespaces=(), extra="allow", ) 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 self.model_dump_json(by_alias=True, exclude_unset=True, exclude_none=True) @classmethod def from_json(cls, json_str: str) -> Optional[Self]: """Create an instance of EnterpriseAgentUnits 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, ) return _dict @classmethod def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]: """Create an instance of EnterpriseAgentUnits from a dict""" if obj is None: return None if not isinstance(obj, dict): return cls.model_validate(obj) _obj = cls.model_validate({ "aid": obj.get("aid"), "accountGroupName": obj.get("accountGroupName"), "agentId": obj.get("agentId"), "agentName": obj.get("agentName"), "enterpriseUnitsUsed": obj.get("enterpriseUnitsUsed"), "enterpriseUnitsProjected": obj.get("enterpriseUnitsProjected") }) return _obj