# coding: utf-8 """ Alerts API You can manage the following alert functionalities on the ThousandEyes platform using the Alerts API: * **Alerts**: Retrieve alert details. Alerts are assigned to tests through alert rules. * **Alert Rules**: Conditions that you configure in order to highlight or be notified of events of interest in your ThousandEyes tests. When an alert rule’s conditions are met, the associated alert is triggered and the alert becomes active. It remains active until the alert is cleared. Alert rules are reusable across multiple tests.. * **Alert Suppression Windows**: Suppress alerts for tests during periods such as planned maintenance. Windows can be one-time events or recurring events to handle periodic occurrences such as monthly downtime for maintenance. For more information about the alerts, see [Alerts](https://docs.thousandeyes.com/product-documentation/alerts). 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 from typing import Any, ClassVar, Dict, List, Optional from thousandeyes_sdk.alerts.models.link import Link from thousandeyes_sdk.alerts.models.test_self_link import TestSelfLink from typing import Optional, Set from typing_extensions import Self class TestLinks(BaseModel): """ A list of links that can be accessed to get more information """ # noqa: E501 var_self: Optional[TestSelfLink] = Field(default=None, alias="self") test_results: Optional[List[Link]] = Field(default=None, description="Reference to the test results.", alias="testResults") __properties: ClassVar[List[str]] = ["self", "testResults"] 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 TestLinks 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 var_self if self.var_self: _dict['self'] = self.var_self.to_dict() # override the default output from pydantic by calling `to_dict()` of each item in test_results (list) _items = [] if self.test_results: for _item in self.test_results: if _item: _items.append(_item.to_dict()) _dict['testResults'] = _items return _dict @classmethod def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]: """Create an instance of TestLinks from a dict""" if obj is None: return None if not isinstance(obj, dict): return cls.model_validate(obj) _obj = cls.model_validate({ "self": TestSelfLink.from_dict(obj["self"]) if obj.get("self") is not None else None, "testResults": [Link.from_dict(_item) for _item in obj["testResults"]] if obj.get("testResults") is not None else None }) return _obj