-
Notifications
You must be signed in to change notification settings - Fork 4
Expand file tree
/
Copy pathhttp_health_checks.py
More file actions
97 lines (75 loc) · 3.29 KB
/
Copy pathhttp_health_checks.py
File metadata and controls
97 lines (75 loc) · 3.29 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
# coding: utf-8
"""
STACKIT Network Load Balancer API
This API offers an interface to provision and manage load balancing servers in your STACKIT project. It also has the possibility of pooling target servers for load balancing purposes. For each load balancer provided, two VMs are deployed in your OpenStack project subject to a fee.
The version of the OpenAPI document: 2.0.0
Generated by OpenAPI Generator (https://openapi-generator.tech)
Do not edit the class manually.
""" # noqa: E501
from __future__ import annotations
import json
import pprint
from typing import Any, ClassVar, Dict, List, Optional, Set
from pydantic import BaseModel, ConfigDict, Field, StrictStr
from pydantic_core import to_jsonable_python
from typing_extensions import Self
from stackit.loadbalancer.models.tls_config import TlsConfig
class HttpHealthChecks(BaseModel):
"""
Options for the HTTP health checking.
""" # noqa: E501
ok_statuses: Optional[List[StrictStr]] = Field(
default=None, description="List of HTTP status codes that indicate a healthy response", alias="okStatuses"
)
path: Optional[StrictStr] = Field(default=None, description="Path to send the health check request to")
tls: Optional[TlsConfig] = None
__properties: ClassVar[List[str]] = ["okStatuses", "path", "tls"]
model_config = ConfigDict(
validate_by_name=True,
validate_by_alias=True,
validate_assignment=True,
protected_namespaces=(),
)
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"""
return json.dumps(to_jsonable_python(self.to_dict()))
@classmethod
def from_json(cls, json_str: str) -> Optional[Self]:
"""Create an instance of HttpHealthChecks 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 tls
if self.tls:
_dict["tls"] = self.tls.to_dict()
return _dict
@classmethod
def from_dict(cls, obj: Optional[Dict[str, Any]]) -> Optional[Self]:
"""Create an instance of HttpHealthChecks from a dict"""
if obj is None:
return None
if not isinstance(obj, dict):
return cls.model_validate(obj)
_obj = cls.model_validate(
{
"okStatuses": obj.get("okStatuses"),
"path": obj.get("path"),
"tls": TlsConfig.from_dict(obj["tls"]) if obj.get("tls") is not None else None,
}
)
return _obj