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106 lines
5.5 KiB
Python
106 lines
5.5 KiB
Python
# coding: utf-8
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"""
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Usage API
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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 Billing` permission to access this endpoint. * This endpoint offers visibility across all account groups within the organization. * Users with `View Billing` permission in multiple organizations should query the endpoint with the `aid` query string parameter (see optional parameters) for each organization. * **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 endpoints for detailed usage instructions and optional parameters.
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The version of the OpenAPI document: 7.0.4
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Generated by OpenAPI Generator (https://openapi-generator.tech)
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Do not edit the class manually.
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""" # noqa: E501
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from __future__ import annotations
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import pprint
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import re # noqa: F401
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import json
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from pydantic import BaseModel, ConfigDict, Field, StrictBool, StrictInt, StrictStr
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from typing import Any, ClassVar, Dict, List, Optional
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from typing import Optional, Set
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from typing_extensions import Self
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class UnitsByTests(BaseModel):
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"""
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UnitsByTests
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""" # noqa: E501
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aid: Optional[StrictStr] = Field(default=None, description="Unique ID of the account group owning the test that is generating units")
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account_group_name: Optional[StrictStr] = Field(default=None, description="Name of the account group which owns the test that is generating the units", alias="accountGroupName")
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enterprise_units_used: Optional[StrictInt] = Field(default=None, description="Units generated by the by the enterprise agents running the test", alias="enterpriseUnitsUsed")
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enterprise_units_projected: Optional[StrictInt] = Field(default=None, description="Enterprise Units projected in the current usage period, based on units consumed to date and configuration of the test", alias="enterpriseUnitsProjected")
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cloud_units_used: Optional[StrictInt] = Field(default=None, description="Units generated by the by the cloud agents running the test", alias="cloudUnitsUsed")
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cloud_units_projected: Optional[StrictInt] = Field(default=None, description="Cloud Units projected in the current usage period, based on units consumed to date and configuration of the test", alias="cloudUnitsProjected")
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test_id: Optional[StrictStr] = Field(default=None, description="Unique ID of the test generating usage", alias="testId")
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test_name: Optional[StrictStr] = Field(default=None, description="Name of the test generating usage", alias="testName")
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test_type: Optional[StrictStr] = Field(default=None, description="Type of test generating usage. Note that this is a friendly testType entry (so it shouldn’t be parsed to discover the correct endpoint to query for configuration details).", alias="testType")
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is_instant_test: Optional[StrictBool] = Field(default=None, description="Indicates whether the test is scheduled or instant", alias="isInstantTest")
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__properties: ClassVar[List[str]] = ["aid", "accountGroupName", "enterpriseUnitsUsed", "enterpriseUnitsProjected", "cloudUnitsUsed", "cloudUnitsProjected", "testId", "testName", "testType", "isInstantTest"]
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model_config = ConfigDict(
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populate_by_name=True,
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validate_assignment=True,
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protected_namespaces=(),
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)
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def to_str(self) -> str:
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"""Returns the string representation of the model using alias"""
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return pprint.pformat(self.model_dump(by_alias=True))
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def to_json(self) -> str:
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"""Returns the JSON representation of the model using alias"""
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# TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead
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return json.dumps(self.to_dict())
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@classmethod
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def from_json(cls, json_str: str) -> Optional[Self]:
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"""Create an instance of UnitsByTests from a JSON string"""
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return cls.from_dict(json.loads(json_str))
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def to_dict(self) -> Dict[str, Any]:
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"""Return the dictionary representation of the model using alias.
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This has the following differences from calling pydantic's
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`self.model_dump(by_alias=True)`:
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* `None` is only added to the output dict for nullable fields that
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were set at model initialization. Other fields with value `None`
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are ignored.
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"""
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excluded_fields: Set[str] = set([
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])
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_dict = self.model_dump(
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by_alias=True,
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exclude=excluded_fields,
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exclude_none=True,
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)
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return _dict
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@classmethod
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def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
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"""Create an instance of UnitsByTests from a dict"""
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if obj is None:
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return None
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if not isinstance(obj, dict):
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return cls.model_validate(obj)
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_obj = cls.model_validate({
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"aid": obj.get("aid"),
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"accountGroupName": obj.get("accountGroupName"),
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"enterpriseUnitsUsed": obj.get("enterpriseUnitsUsed"),
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"enterpriseUnitsProjected": obj.get("enterpriseUnitsProjected"),
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"cloudUnitsUsed": obj.get("cloudUnitsUsed"),
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"cloudUnitsProjected": obj.get("cloudUnitsProjected"),
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"testId": obj.get("testId"),
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"testName": obj.get("testName"),
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"testType": obj.get("testType"),
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"isInstantTest": obj.get("isInstantTest")
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})
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return _obj
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