thousandeyes-sdk-python/thousandeyes-sdk-event-detection/src/thousandeyes_sdk/event_detection/models/self_links.py
Shahid Hussain Khan 09e9385636
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Add Event detection API (#43)
* [GitHub Bot] Generated python SDK

* Updated README

---------

Co-authored-by: API Team <api-team@thousandeyes.com>
Co-authored-by: Miguel Pragosa <mpragosa@thousandeyes.com>
2024-08-11 10:21:46 +01:00

92 lines
3.9 KiB
Python

# 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 pydantic import BaseModel, ConfigDict, Field
from typing import Any, ClassVar, Dict, List, Optional
from thousandeyes_sdk.event_detection.models.link import Link
from typing import Optional, Set
from typing_extensions import Self
class SelfLinks(BaseModel):
"""
A links object containing the self link.
""" # noqa: E501
var_self: Optional[Link] = Field(default=None, alias="self")
__properties: ClassVar[List[str]] = ["self"]
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 SelfLinks 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()
return _dict
@classmethod
def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
"""Create an instance of SelfLinks from a dict"""
if obj is None:
return None
if not isinstance(obj, dict):
return cls.model_validate(obj)
_obj = cls.model_validate({
"self": Link.from_dict(obj["self"]) if obj.get("self") is not None else None
})
return _obj