Coverage for fingerprint_server_sdk/models/identification_confidence.py: 75%

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 Annotated, Any, ClassVar, Optional, Union 

20 

21from pydantic import BaseModel, ConfigDict, Field, StrictStr 

22from typing_extensions import Self 

23 

24 

25class IdentificationConfidence(BaseModel): 

26 """ 

27 The confidence score represents the probability of a false-positive identification. To learn more, visit [Confidence Score](https://docs.fingerprint.com/docs/identification-accuracy-and-confidence#confidence-score). Please note that the confidence score is not yet supported for [High Recall ID](https://docs.fingerprint.com/docs/supplementary-identifiers-highrecall). 

28 """ 

29 

30 score: Union[ 

31 Annotated[float, Field(le=1, strict=True, ge=0)], 

32 Annotated[int, Field(le=1, strict=True, ge=0)], 

33 ] = Field( 

34 description='A floating-point number between 0 and 1 that represents the probability of a false-positive identification. For High Recall ID, this value is 0. ' 

35 ) 

36 version: Optional[StrictStr] = Field( 

37 default=None, 

38 description='The version name of the method used to calculate the confidence score. For High Recall ID, this value is "Not Supported". ', 

39 ) 

40 comment: Optional[StrictStr] = None 

41 __properties: ClassVar[list[str]] = ['score', 'version', 'comment'] 

42 

43 model_config = ConfigDict( 

44 populate_by_name=True, 

45 validate_assignment=True, 

46 protected_namespaces=(), 

47 ) 

48 

49 def to_str(self) -> str: 

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

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

52 

53 def to_json(self) -> str: 

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

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

56 return json.dumps(self.to_dict()) 

57 

58 @classmethod 

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

60 """Create an instance of IdentificationConfidence from a JSON string""" 

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

62 

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

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

65 

66 This has the following differences from calling pydantic's 

67 `self.model_dump(by_alias=True)`: 

68 

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

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

71 are ignored. 

72 """ 

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

74 

75 _dict = self.model_dump( 

76 by_alias=True, 

77 exclude=excluded_fields, 

78 exclude_none=True, 

79 ) 

80 return _dict 

81 

82 @classmethod 

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

84 """Create an instance of IdentificationConfidence from a dict""" 

85 if obj is None: 

86 return None 

87 

88 if not isinstance(obj, dict): 

89 return cls.model_validate(obj) 

90 

91 _obj = cls.model_validate( 

92 { 

93 'score': obj.get('score'), 

94 'version': obj.get('version'), 

95 'comment': obj.get('comment'), 

96 } 

97 ) 

98 return _obj