Coverage for fingerprint_server_sdk/models/bot_info.py: 77%

1""" 

2Server API 

3Fingerprint Server API allows you to get, search, and update Events in a server environment. It can be used for data exports, decision-making, and data analysis scenarios. 

4Server API is intended for server-side usage, it's not intended to be used from the client side, whether it's a browser or a mobile device. 

5The API also supports collection of Automation Intelligence for requests to your server in edge, pre-origin, or middleware contexts. 

6 

7The version of the OpenAPI document: 4 

8Contact: support@fingerprint.com 

9Generated by OpenAPI Generator (https://openapi-generator.tech) 

10 

11Do not edit the class manually. 

12""" # noqa: E501 

13 

14from __future__ import annotations 

15 

16import json 

17import pprint 

18import re # noqa: F401 

19from typing import Any, ClassVar, Optional 

20 

21from pydantic import BaseModel, ConfigDict, Field, StrictStr 

22from typing_extensions import Self 

23 

24 

25class BotInfo(BaseModel): 

26 """ 

27 Extended bot information. 

28 """ 

29 

30 category: StrictStr = Field(description='The type and purpose of the bot. ') 

31 provider: StrictStr = Field(description='The organization or company operating the bot.') 

32 provider_url: Optional[StrictStr] = Field( 

33 default=None, description="The URL of the bot provider's website." 

34 ) 

35 name: StrictStr = Field(description='The specific name or identifier of the bot.') 

36 identity: StrictStr = Field( 

37 description="The verification status of the bot's identity: * `verified` - well-known bot with publicly verifiable identity, directed by the bot provider. * `signed` - bot that signs its platform via Web Bot Auth, directed by the bot provider's customers. * `spoofed` - bot that claims a public identity but fails verification. * `unknown` - bot that does not publish a verifiable identity. " 

38 ) 

39 confidence: StrictStr = Field(description='Confidence level of the bot identification.') 

40 __properties: ClassVar[list[str]] = [ 

41 'category', 

42 'provider', 

43 'provider_url', 

44 'name', 

45 'identity', 

46 'confidence', 

47 ] 

48 

49 model_config = ConfigDict( 

50 populate_by_name=True, 

51 validate_assignment=True, 

52 protected_namespaces=(), 

53 ) 

54 

55 def to_str(self) -> str: 

56 """Returns the string representation of the model using alias""" 

57 return pprint.pformat(self.model_dump(by_alias=True)) 

58 

59 def to_json(self) -> str: 

60 """Returns the JSON representation of the model using alias""" 

61 # TODO: pydantic v2: use .model_dump_json(by_alias=True, exclude_unset=True) instead 

62 return json.dumps(self.to_dict()) 

63 

64 @classmethod 

65 def from_json(cls, json_str: str) -> Optional[Self]: 

66 """Create an instance of BotInfo from a JSON string""" 

67 return cls.from_dict(json.loads(json_str)) 

68 

69 def to_dict(self) -> dict[str, Any]: 

70 """Return the dictionary representation of the model using alias. 

71 

72 This has the following differences from calling pydantic's 

73 `self.model_dump(by_alias=True)`: 

74 

75 * `None` is only added to the output dict for nullable fields that 

76 were set at model initialization. Other fields with value `None` 

77 are ignored. 

78 """ 

79 excluded_fields: set[str] = set([]) 

80 

81 _dict = self.model_dump( 

82 by_alias=True, 

83 exclude=excluded_fields, 

84 exclude_none=True, 

85 ) 

86 return _dict 

87 

88 @classmethod 

89 def from_dict(cls, obj: Optional[dict[str, Any]]) -> Optional[Self]: 

90 """Create an instance of BotInfo from a dict""" 

91 if obj is None: 

92 return None 

93 

94 if not isinstance(obj, dict): 

95 return cls.model_validate(obj) 

96 

97 _obj = cls.model_validate( 

98 { 

99 'category': obj.get('category'), 

100 'provider': obj.get('provider'), 

101 'provider_url': obj.get('provider_url'), 

102 'name': obj.get('name'), 

103 'identity': obj.get('identity'), 

104 'confidence': obj.get('confidence'), 

105 } 

106 ) 

107 return _obj