Update APIv3 to Schema v3.1.0

.changeset/five-eggs-cheer.md

@@ -0,0 +1,5 @@
+---
+"fingerprint-pro-server-api-python-sdk": minor
+---
+
+Add `ml_score` field to the `VirtualMachine` signal

.changeset/tough-cherries-try.md

@@ -0,0 +1,5 @@
+---
+"fingerprint-pro-server-api-python-sdk": minor
+---
+
+Add `confidence` and `ml_score` fields to the `Tampering` signal

.github/workflows/functional_tests.yml

@@ -23,7 +23,7 @@ jobs:
       fail-fast: false
       max-parallel: 1
       matrix:
-        python-version: [ "3.9", "3.10", "3.11", "3.12", "3.13", "pypy3.9", "pypy3.10" ]
+        python-version: [ "3.9", "3.10", "3.11", "3.12", "3.13", "pypy3.11" ]
 
     steps:
       - uses: actions/checkout@v4

.github/workflows/test.yml

@@ -13,7 +13,7 @@ jobs:
 
     strategy:
       matrix:
-        python-version: [ "3.9", "3.10", "3.11", "3.12", "3.13", "pypy3.9", "pypy3.10" ]
+        python-version: [ "3.9", "3.10", "3.11", "3.12", "3.13", "pypy3.11" ]
 
     steps:
       - uses: actions/checkout@v4

.schema-version

@@ -1 +1 @@
-v2.12.0
+v3.1.0

docs/Tampering.md

@@ -4,7 +4,9 @@
 Name | Type | Description | Notes
 ------------ | ------------- | ------------- | -------------
 **result** | **bool** | Indicates if an identification request from a browser or an Android SDK has been tampered with. Not supported in the iOS SDK, is always `false` for iOS requests.   * `true` - If the request meets either of the following conditions:     * Contains anomalous browser or device attributes that could not have been legitimately produced by the JavaScript agent or the Android SDK (see `anomalyScore`).     * Originated from an anti-detect browser like Incognition (see `antiDetectBrowser`).   * `false` - If the request is considered genuine or was generated by the iOS SDK.  | 
+**confidence** | **str** | Confidence level of the tampering detection. If a tampering is not detected, confidence is \"high\". If it's detected, can be \"low\", \"medium\", or \"high\".  | 
 **anomaly_score** | **float** | A score that indicates the extent of anomalous data in the request. This field applies to requests originating from **both** browsers and Android SDKs.    * Values above `0.5` indicate that the request has been tampered with.   * Values below `0.5` indicate that the request is genuine.  | 
+**ml_score** | **float** | A score that indicates the models calculated probability that an event is coming from an anti detect browser.   * Values above `0.8` indicate that the request is an anti detect browser based on the ml model   * Values below `0.8` indicate that the request is not an anti detect browser based on the ml model  | 
 **anti_detect_browser** | **bool** | Anti-detect browsers try to evade identification by masking or manipulating their fingerprint to imitate legitimate browser configurations. This field does not apply to requests originating from mobile SDKs.   * `true` - The browser resembles a known anti-detect browser, for example, Incognition.   * `false` - The browser does not resemble an anti-detect browser or the request originates from a mobile SDK.  | 
 
 [[Back to Model list]](../README.md#documentation-for-models) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to README]](../README.md)

docs/VirtualMachine.md

@@ -4,6 +4,7 @@
 Name | Type | Description | Notes
 ------------ | ------------- | ------------- | -------------
 **result** | **bool** | `true` if the request came from a browser running inside a virtual machine (e.g. VMWare), `false` otherwise.  | 
+**ml_score** | **float** | Machine learning-based virtual machine score,  represented as a floating-point value between 0 and 1 (inclusive), with up to three decimal places of precision. A higher score means a higher confidence in the positive `virtual_machine` detection result      | [optional] 
 
 [[Back to Model list]](../README.md#documentation-for-models) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to README]](../README.md)
 

docs/WebhookJailbroken.md

@@ -3,7 +3,7 @@
 ## Properties
 Name | Type | Description | Notes
 ------------ | ------------- | ------------- | -------------
-**result** | **bool** | iOS specific jailbreak detection. There are 2 values:    * `true` - Jailbreak detected.   * `false` - No signs of jailbreak or the client is not iOS.  | [optional] 
+**result** | **bool** | iOS specific jailbreak detection. There are 2 values:   * `true` - Jailbreak detected.   * `false` - No signs of jailbreak or the client is not iOS.  | [optional] 
 
 [[Back to Model list]](../README.md#documentation-for-models) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to README]](../README.md)
 

docs/WebhookTampering.md

@@ -4,7 +4,9 @@
 Name | Type | Description | Notes
 ------------ | ------------- | ------------- | -------------
 **result** | **bool** | Indicates if an identification request from a browser or an Android SDK has been tampered with. Not supported in the iOS SDK, is always `false` for iOS requests.   * `true` - If the request meets either of the following conditions:     * Contains anomalous browser or device attributes that could not have been legitimately produced by the JavaScript agent or the Android SDK (see `anomalyScore`).     * Originated from an anti-detect browser like Incognition (see `antiDetectBrowser`).   * `false` - If the request is considered genuine or was generated by the iOS SDK.  | [optional] 
+**confidence** | **str** | Confidence level of the tampering detection. If a tampering is not detected, confidence is \"high\". If it's detected, can be \"low\", \"medium\", or \"high\".  | [optional] 
 **anomaly_score** | **float** | A score that indicates the extent of anomalous data in the request. This field applies to requests originating from **both** browsers and Android SDKs.    * Values above `0.5` indicate that the request has been tampered with.   * Values below `0.5` indicate that the request is genuine.  | [optional] 
+**ml_score** | **float** | A score that indicates the models calculated probability that an event is coming from an anti detect browser.   * Values above `0.8` indicate that the request is an anti detect browser based on the ml model   * Values below `0.8` indicate that the request is not an anti detect browser based on the ml model  | [optional] 
 **anti_detect_browser** | **bool** | Anti-detect browsers try to evade identification by masking or manipulating their fingerprint to imitate legitimate browser configurations. This field does not apply to requests originating from mobile SDKs.   * `true` - The browser resembles a known anti-detect browser, for example, Incognition.   * `false` - The browser does not resemble an anti-detect browser or the request originates from a mobile SDK.  | [optional] 
 
 [[Back to Model list]](../README.md#documentation-for-models) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to README]](../README.md)

docs/WebhookVirtualMachine.md

@@ -4,6 +4,7 @@
 Name | Type | Description | Notes
 ------------ | ------------- | ------------- | -------------
 **result** | **bool** | `true` if the request came from a browser running inside a virtual machine (e.g. VMWare), `false` otherwise.  | [optional] 
+**ml_score** | **float** | Machine learning–based virtual machine score,  represented as a floating-point value between 0 and 1 (inclusive), with up to three decimal places of precision. A higher score means a higher confidence in the positive `virtual_machine` detection result  | [optional] 
 
 [[Back to Model list]](../README.md#documentation-for-models) [[Back to API list]](../README.md#documentation-for-api-endpoints) [[Back to README]](../README.md)
 

fingerprint_pro_server_api_sdk/models/tampering.py

@@ -29,30 +29,40 @@ class Tampering(BaseModel):
     """
     swagger_types = {
         'result': 'bool',
+        'confidence': 'str',
         'anomaly_score': 'float',
+        'ml_score': 'float',
         'anti_detect_browser': 'bool'
     }
 
     nullable_map = {
         'result': False,
+        'confidence': False,
         'anomaly_score': False,
+        'ml_score': False,
         'anti_detect_browser': False
     }
 
     attribute_map = {
         'result': 'result',
+        'confidence': 'confidence',
         'anomaly_score': 'anomalyScore',
+        'ml_score': 'mlScore',
         'anti_detect_browser': 'antiDetectBrowser'
     }
 
-    def __init__(self, result=None, anomaly_score=None, anti_detect_browser=None):  # noqa: E501
+    def __init__(self, result=None, confidence=None, anomaly_score=None, ml_score=None, anti_detect_browser=None):  # noqa: E501
         """Tampering - a model defined in Swagger"""  # noqa: E501
         self._result = None
+        self._confidence = None
         self._anomaly_score = None
+        self._ml_score = None
         self._anti_detect_browser = None
         self.discriminator = None
         self.result = result
+        self.confidence = confidence
         self.anomaly_score = anomaly_score
+        self.ml_score = ml_score
         self.anti_detect_browser = anti_detect_browser
 
     @property
@@ -78,6 +88,35 @@ def result(self, result: bool):
 
         self._result = result
 
+    @property
+    def confidence(self) -> str:
+        """Gets the confidence of this Tampering.  # noqa: E501
+
+        Confidence level of the tampering detection. If a tampering is not detected, confidence is \"high\". If it's detected, can be \"low\", \"medium\", or \"high\".   # noqa: E501
+
+        :return: The confidence of this Tampering.  # noqa: E501
+        """
+        return self._confidence
+
+    @confidence.setter
+    def confidence(self, confidence: str):
+        """Sets the confidence of this Tampering.
+
+        Confidence level of the tampering detection. If a tampering is not detected, confidence is \"high\". If it's detected, can be \"low\", \"medium\", or \"high\".   # noqa: E501
+
+        :param confidence: The confidence of this Tampering.  # noqa: E501
+        """
+        if confidence is None:
+            raise ValueError("Invalid value for `confidence`, must not be `None`")  # noqa: E501
+        allowed_values = ["low", "medium", "high"]  # noqa: E501
+        if (confidence not in allowed_values):
+            raise ValueError(
+                "Invalid value for `confidence` ({0}), must be one of {1}"  # noqa: E501
+                .format(confidence, allowed_values)
+            )
+
+        self._confidence = confidence
+
     @property
     def anomaly_score(self) -> float:
         """Gets the anomaly_score of this Tampering.  # noqa: E501
@@ -101,6 +140,29 @@ def anomaly_score(self, anomaly_score: float):
 
         self._anomaly_score = anomaly_score
 
+    @property
+    def ml_score(self) -> float:
+        """Gets the ml_score of this Tampering.  # noqa: E501
+
+        A score that indicates the models calculated probability that an event is coming from an anti detect browser.   * Values above `0.8` indicate that the request is an anti detect browser based on the ml model   * Values below `0.8` indicate that the request is not an anti detect browser based on the ml model   # noqa: E501
+
+        :return: The ml_score of this Tampering.  # noqa: E501
+        """
+        return self._ml_score
+
+    @ml_score.setter
+    def ml_score(self, ml_score: float):
+        """Sets the ml_score of this Tampering.
+
+        A score that indicates the models calculated probability that an event is coming from an anti detect browser.   * Values above `0.8` indicate that the request is an anti detect browser based on the ml model   * Values below `0.8` indicate that the request is not an anti detect browser based on the ml model   # noqa: E501
+
+        :param ml_score: The ml_score of this Tampering.  # noqa: E501
+        """
+        if ml_score is None:
+            raise ValueError("Invalid value for `ml_score`, must not be `None`")  # noqa: E501
+
+        self._ml_score = ml_score
+
     @property
     def anti_detect_browser(self) -> bool:
         """Gets the anti_detect_browser of this Tampering.  # noqa: E501

fingerprint_pro_server_api_sdk/models/virtual_machine.py

@@ -28,22 +28,28 @@ class VirtualMachine(BaseModel):
                             and the value is json key in definition.
     """
     swagger_types = {
-        'result': 'bool'
+        'result': 'bool',
+        'ml_score': 'float'
     }
 
     nullable_map = {
-        'result': False
+        'result': False,
+        'ml_score': False
     }
 
     attribute_map = {
-        'result': 'result'
+        'result': 'result',
+        'ml_score': 'mlScore'
     }
 
-    def __init__(self, result=None):  # noqa: E501
+    def __init__(self, result=None, ml_score=None):  # noqa: E501
         """VirtualMachine - a model defined in Swagger"""  # noqa: E501
         self._result = None
+        self._ml_score = None
         self.discriminator = None
         self.result = result
+        if ml_score is not None:
+            self.ml_score = ml_score
 
     @property
     def result(self) -> bool:
@@ -68,3 +74,24 @@ def result(self, result: bool):
 
         self._result = result
 
+    @property
+    def ml_score(self) -> Optional[float]:
+        """Gets the ml_score of this VirtualMachine.  # noqa: E501
+
+        Machine learning-based virtual machine score,  represented as a floating-point value between 0 and 1 (inclusive), with up to three decimal places of precision. A higher score means a higher confidence in the positive `virtual_machine` detection result       # noqa: E501
+
+        :return: The ml_score of this VirtualMachine.  # noqa: E501
+        """
+        return self._ml_score
+
+    @ml_score.setter
+    def ml_score(self, ml_score: Optional[float]):
+        """Sets the ml_score of this VirtualMachine.
+
+        Machine learning-based virtual machine score,  represented as a floating-point value between 0 and 1 (inclusive), with up to three decimal places of precision. A higher score means a higher confidence in the positive `virtual_machine` detection result       # noqa: E501
+
+        :param ml_score: The ml_score of this VirtualMachine.  # noqa: E501
+        """
+
+        self._ml_score = ml_score
+

fingerprint_pro_server_api_sdk/models/webhook_jailbroken.py

@@ -50,7 +50,7 @@ def __init__(self, result=None):  # noqa: E501
     def result(self) -> Optional[bool]:
         """Gets the result of this WebhookJailbroken.  # noqa: E501
 
-        iOS specific jailbreak detection. There are 2 values:    * `true` - Jailbreak detected.   * `false` - No signs of jailbreak or the client is not iOS.   # noqa: E501
+        iOS specific jailbreak detection. There are 2 values:   * `true` - Jailbreak detected.   * `false` - No signs of jailbreak or the client is not iOS.   # noqa: E501
 
         :return: The result of this WebhookJailbroken.  # noqa: E501
         """
@@ -60,7 +60,7 @@ def result(self) -> Optional[bool]:
     def result(self, result: Optional[bool]):
         """Sets the result of this WebhookJailbroken.
 
-        iOS specific jailbreak detection. There are 2 values:    * `true` - Jailbreak detected.   * `false` - No signs of jailbreak or the client is not iOS.   # noqa: E501
+        iOS specific jailbreak detection. There are 2 values:   * `true` - Jailbreak detected.   * `false` - No signs of jailbreak or the client is not iOS.   # noqa: E501
 
         :param result: The result of this WebhookJailbroken.  # noqa: E501
         """

fingerprint_pro_server_api_sdk/models/webhook_tampering.py

@@ -29,32 +29,44 @@ class WebhookTampering(BaseModel):
     """
     swagger_types = {
         'result': 'bool',
+        'confidence': 'str',
         'anomaly_score': 'float',
+        'ml_score': 'float',
         'anti_detect_browser': 'bool'
     }
 
     nullable_map = {
         'result': False,
+        'confidence': False,
         'anomaly_score': False,
+        'ml_score': False,
         'anti_detect_browser': False
     }
 
     attribute_map = {
         'result': 'result',
+        'confidence': 'confidence',
         'anomaly_score': 'anomalyScore',
+        'ml_score': 'mlScore',
         'anti_detect_browser': 'antiDetectBrowser'
     }
 
-    def __init__(self, result=None, anomaly_score=None, anti_detect_browser=None):  # noqa: E501
+    def __init__(self, result=None, confidence=None, anomaly_score=None, ml_score=None, anti_detect_browser=None):  # noqa: E501
         """WebhookTampering - a model defined in Swagger"""  # noqa: E501
         self._result = None
+        self._confidence = None
         self._anomaly_score = None
+        self._ml_score = None
         self._anti_detect_browser = None
         self.discriminator = None
         if result is not None:
             self.result = result
+        if confidence is not None:
+            self.confidence = confidence
         if anomaly_score is not None:
             self.anomaly_score = anomaly_score
+        if ml_score is not None:
+            self.ml_score = ml_score
         if anti_detect_browser is not None:
             self.anti_detect_browser = anti_detect_browser
 
@@ -79,6 +91,33 @@ def result(self, result: Optional[bool]):
 
         self._result = result
 
+    @property
+    def confidence(self) -> Optional[str]:
+        """Gets the confidence of this WebhookTampering.  # noqa: E501
+
+        Confidence level of the tampering detection. If a tampering is not detected, confidence is \"high\". If it's detected, can be \"low\", \"medium\", or \"high\".   # noqa: E501
+
+        :return: The confidence of this WebhookTampering.  # noqa: E501
+        """
+        return self._confidence
+
+    @confidence.setter
+    def confidence(self, confidence: Optional[str]):
+        """Sets the confidence of this WebhookTampering.
+
+        Confidence level of the tampering detection. If a tampering is not detected, confidence is \"high\". If it's detected, can be \"low\", \"medium\", or \"high\".   # noqa: E501
+
+        :param confidence: The confidence of this WebhookTampering.  # noqa: E501
+        """
+        allowed_values = ["low", "medium", "high"]  # noqa: E501
+        if (confidence not in allowed_values):
+            raise ValueError(
+                "Invalid value for `confidence` ({0}), must be one of {1}"  # noqa: E501
+                .format(confidence, allowed_values)
+            )
+
+        self._confidence = confidence
+
     @property
     def anomaly_score(self) -> Optional[float]:
         """Gets the anomaly_score of this WebhookTampering.  # noqa: E501
@@ -100,6 +139,27 @@ def anomaly_score(self, anomaly_score: Optional[float]):
 
         self._anomaly_score = anomaly_score
 
+    @property
+    def ml_score(self) -> Optional[float]:
+        """Gets the ml_score of this WebhookTampering.  # noqa: E501
+
+        A score that indicates the models calculated probability that an event is coming from an anti detect browser.   * Values above `0.8` indicate that the request is an anti detect browser based on the ml model   * Values below `0.8` indicate that the request is not an anti detect browser based on the ml model   # noqa: E501
+
+        :return: The ml_score of this WebhookTampering.  # noqa: E501
+        """
+        return self._ml_score
+
+    @ml_score.setter
+    def ml_score(self, ml_score: Optional[float]):
+        """Sets the ml_score of this WebhookTampering.
+
+        A score that indicates the models calculated probability that an event is coming from an anti detect browser.   * Values above `0.8` indicate that the request is an anti detect browser based on the ml model   * Values below `0.8` indicate that the request is not an anti detect browser based on the ml model   # noqa: E501
+
+        :param ml_score: The ml_score of this WebhookTampering.  # noqa: E501
+        """
+
+        self._ml_score = ml_score
+
     @property
     def anti_detect_browser(self) -> Optional[bool]:
         """Gets the anti_detect_browser of this WebhookTampering.  # noqa: E501