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99 lines
4.0 KiB
Python
99 lines
4.0 KiB
Python
# coding: utf-8
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"""
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Administrative API
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Manage users, accounts, and account groups in the ThousandEyes platform using the Administrative API. This API provides the following endpoints that define the operations to manage your organization: * `/account-groups`: Account groups are used to divide an organization into different sections. These endpoints can be used to create, retrieve, update and delete account groups. * `/users`: Create, retrieve, update and delete users within an organization. * `/roles`: Create, retrieve and update roles for the current user. * `/permissions`: Retrieve all assignable permissions. Used in the context of modifying roles. * `/audit-user-events`: Retrieve all activity log events. For more information about the administrative models, see [Account Management](https://docs.thousandeyes.com/product-documentation/user-management).
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The version of the OpenAPI document: 7.0.12
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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, 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 AgentBase(BaseModel):
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"""
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AgentBase
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""" # noqa: E501
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ip_addresses: Optional[List[StrictStr]] = Field(default=None, description="Array of private IP addresses.", alias="ipAddresses")
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public_ip_addresses: Optional[List[StrictStr]] = Field(default=None, description="Array of public IP addresses.", alias="publicIpAddresses")
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network: Optional[StrictStr] = Field(default=None, description="Network (including ASN) of agent’s public IP.")
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__properties: ClassVar[List[str]] = ["ipAddresses", "publicIpAddresses", "network"]
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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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extra="allow",
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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 self.model_dump_json(by_alias=True, exclude_unset=True, exclude_none=True)
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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 AgentBase 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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* OpenAPI `readOnly` fields are excluded.
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* OpenAPI `readOnly` fields are excluded.
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* OpenAPI `readOnly` fields are excluded.
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"""
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excluded_fields: Set[str] = set([
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"ip_addresses",
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"public_ip_addresses",
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"network",
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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 AgentBase 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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"ipAddresses": obj.get("ipAddresses"),
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"publicIpAddresses": obj.get("publicIpAddresses"),
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"network": obj.get("network")
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})
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return _obj
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