# coding: utf-8 """ Event Detection API Event detection occurs when ThousandEyes identifies that error signals related to a component (proxy, network node, AS, server etc) have deviated from the baselines established by events. * To determine this, ThousandEyes takes the test results from all accounts groups within an organization, and analyzes that data. * Noisy test results (those that have too many errors in a short window) are removed until they stabilize, and the rest of the results are tagged with the components associated with that test result (for example, proxy, network, or server). * Next, any increase in failures from the test results and each component helps in determining the problem domain and which component may be at fault. * When this failure rate increases beyond a pre-defined threshold (set by the algorithm), an event is triggered and an email notification is sent to the user (if they've enabled email alerts). With the Events API, you can perform the following tasks on the ThousandEyes platform: * **Retrieve Events**: Obtain a list of events and detailed information for each event. For more information about events, see [Event Detection](https://docs.thousandeyes.com/product-documentation/event-detection). 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 datetime import datetime from pydantic import BaseModel, ConfigDict, Field, StrictStr from typing import Any, ClassVar, Dict, List, Optional from thousandeyes_sdk.event_detection.models.affected_count import AffectedCount from thousandeyes_sdk.event_detection.models.event_alert_severity import EventAlertSeverity from thousandeyes_sdk.event_detection.models.event_state import EventState from thousandeyes_sdk.event_detection.models.event_type import EventType from thousandeyes_sdk.event_detection.models.self_links import SelfLinks from typing import Optional, Set from typing_extensions import Self class Event(BaseModel): """ Event """ # noqa: E501 id: Optional[StrictStr] = Field(default=None, description="A unique ID for each event.") type_name: Optional[StrictStr] = Field(default=None, description="Event type name. Examples include, Local Agent Issue, Network Path Issue, Network Outage, DNS Issue, Server Issue, and Proxy Issue.", alias="typeName") state: Optional[EventState] = None start_date: Optional[datetime] = Field(default=None, description="The start date and time (in UTC, ISO 8601 format) when the event was first detected.", alias="startDate") end_date: Optional[datetime] = Field(default=None, description="The end date and time (in UTC, ISO 8601 format) when the event was resolved (due to timeout). This value is populated for \"ongoing\" events.", alias="endDate") severity: Optional[EventAlertSeverity] = None title: Optional[StrictStr] = Field(default=None, description="Event title") type: Optional[EventType] = None affected_tests: Optional[AffectedCount] = Field(default=None, alias="affectedTests") affected_targets: Optional[AffectedCount] = Field(default=None, alias="affectedTargets") affected_agents: Optional[AffectedCount] = Field(default=None, alias="affectedAgents") links: Optional[SelfLinks] = Field(default=None, alias="_links") __properties: ClassVar[List[str]] = ["id", "typeName", "state", "startDate", "endDate", "severity", "title", "type", "affectedTests", "affectedTargets", "affectedAgents", "_links"] 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 Event 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. * OpenAPI `readOnly` fields are excluded. * OpenAPI `readOnly` fields are excluded. * OpenAPI `readOnly` fields are excluded. * OpenAPI `readOnly` fields are excluded. * OpenAPI `readOnly` fields are excluded. """ excluded_fields: Set[str] = set([ "id", "type_name", "start_date", "end_date", "title", ]) _dict = self.model_dump( by_alias=True, exclude=excluded_fields, exclude_none=True, ) # override the default output from pydantic by calling `to_dict()` of affected_tests if self.affected_tests: _dict['affectedTests'] = self.affected_tests.to_dict() # override the default output from pydantic by calling `to_dict()` of affected_targets if self.affected_targets: _dict['affectedTargets'] = self.affected_targets.to_dict() # override the default output from pydantic by calling `to_dict()` of affected_agents if self.affected_agents: _dict['affectedAgents'] = self.affected_agents.to_dict() # override the default output from pydantic by calling `to_dict()` of links if self.links: _dict['_links'] = self.links.to_dict() # set to None if end_date (nullable) is None # and model_fields_set contains the field if self.end_date is None and "end_date" in self.model_fields_set: _dict['endDate'] = None return _dict @classmethod def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]: """Create an instance of Event from a dict""" if obj is None: return None if not isinstance(obj, dict): return cls.model_validate(obj) _obj = cls.model_validate({ "id": obj.get("id"), "typeName": obj.get("typeName"), "state": obj.get("state"), "startDate": obj.get("startDate"), "endDate": obj.get("endDate"), "severity": obj.get("severity"), "title": obj.get("title"), "type": obj.get("type"), "affectedTests": AffectedCount.from_dict(obj["affectedTests"]) if obj.get("affectedTests") is not None else None, "affectedTargets": AffectedCount.from_dict(obj["affectedTargets"]) if obj.get("affectedTargets") is not None else None, "affectedAgents": AffectedCount.from_dict(obj["affectedAgents"]) if obj.get("affectedAgents") is not None else None, "_links": SelfLinks.from_dict(obj["_links"]) if obj.get("_links") is not None else None }) return _obj