Update models for pydantic v2 migration

src/pytmv1/core.py

@@ -283,7 +283,7 @@ def _parse_data(raw_response: Response, class_: Type[R]) -> R:
                 etag=raw_response.headers.get("ETag", ""),
             )
         if class_ == BaseTaskResp:
-            resp_class = task_action(raw_response.json()["action"]).resp_class
+            resp_class = task_action(raw_response.json()["action"]).class_
             class_ = resp_class if resp_class else class_
         return class_(**raw_response.json())
     if "application" in content_type and class_ == BytesResp:

src/pytmv1/model/commons.py

@@ -3,8 +3,9 @@
 from typing import Any, Dict, List, Optional, Tuple, Union
 
 from pydantic import BaseModel as PydanticBaseModel
-from pydantic import Field
+from pydantic import ConfigDict, Field
 from pydantic import RootModel as PydanticRootModel
+from pydantic import model_validator
 from pydantic.alias_generators import to_camel
 
 from .enums import (
@@ -25,37 +26,19 @@
     Status,
 )
 
+CFG = ConfigDict(alias_generator=to_camel, populate_by_name=True)
 
-class BaseModel(PydanticBaseModel):
-    def __init__(self, **data: Any):
-        super().__init__(**data)
 
-    class Config:
-        alias_generator = to_camel
-        populate_by_name = True
+class BaseModel(PydanticBaseModel):
+    model_config = CFG
 
 
 class RootModel(PydanticRootModel[List[int]]):
-    class Config:
-        alias_generator = to_camel
-        populate_by_name = True
+    model_config = CFG
 
 
 class BaseConsumable(BaseModel):
-    def __init__(self, **data: Any):
-        super().__init__(**data)
-
-
-def _get_task_id(headers: List[Dict[str, str]]) -> Optional[str]:
-    task_id: str = next(
-        (
-            h.get("value", "")
-            for h in headers
-            if "Operation-Location" == h.get("name", "")
-        ),
-        "",
-    ).split("/")[-1]
-    return task_id if task_id != "" else None
+    ...
 
 
 class Account(BaseModel):
@@ -204,25 +187,18 @@ class Error(BaseModel):
     message: Optional[str] = None
     number: Optional[int] = None
 
-    def __init__(self, **data: Any):
-        super().__init__(**data)
-
 
 class ExceptionObject(BaseConsumable):
     value: str
     type: ObjectType
     last_modified_date_time: str
     description: Optional[str] = None
 
-    def __init__(self, **data: str) -> None:
-        super().__init__(value=self._obj_value(data), **data)
-
-    @staticmethod
-    def _obj_value(args: Dict[str, str]) -> str:
-        obj_value: Optional[str] = args.get(args.get("type", ""))
-        if obj_value is None:
-            raise ValueError("Object value not found")
-        return obj_value
+    @model_validator(mode="before")
+    @classmethod
+    def _map_data(cls, data: Dict[str, str]) -> Dict[str, str]:
+        data["value"] = data[data["type"]]
+        return data
 
 
 class ImpactScope(BaseModel):
@@ -272,35 +248,39 @@ class MsData(BaseModel):
     status: int
     task_id: Optional[str] = None
 
-    def __init__(self, **data: Any):
-        super().__init__(
-            taskId=_get_task_id(data.pop("headers", {})),
-            **data,
-        )
+    @model_validator(mode="before")
+    @classmethod
+    def map_task_id(cls, data: Dict[str, Any]) -> Dict[str, Any]:
+        data["task_id"] = _get_task_id(data)
+        return data
 
 
 class MsDataUrl(MsData):
     url: str
     id: Optional[str] = None
     digest: Optional[Digest] = None
 
-    def __init__(self, **data: Any):
+    @model_validator(mode="before")
+    @classmethod
+    def map_data(cls, data: Dict[str, Any]) -> Dict[str, Any]:
         data.update(data.pop("body", {}))
-        super().__init__(**data)
+        return data
 
 
 class MsError(Error):
     extra: Dict[str, str] = {}
     task_id: Optional[str] = None
 
-    def __init__(self, **data: Any):
+    @model_validator(mode="before")
+    @classmethod
+    def map_data(cls, data: Dict[str, Any]) -> Dict[str, Any]:
         data.update(data.pop("body", {}))
         data.update(data.pop("error", {}))
-        super().__init__(
-            extra={"url": data.pop("url", "")},
-            taskId=_get_task_id(data.pop("headers", {})),
-            **data,
-        )
+        url = data.pop("url", None)
+        data["task_id"] = _get_task_id(data)
+        if url:
+            data["extra"] = {"url": url}
+        return data
 
 
 class MsStatus(RootModel):
@@ -328,17 +308,13 @@ class SandboxSuspiciousObject(BaseModel):
     type: ObjectType
     value: str
 
-    def __init__(self, **data: Any):
-        obj: Tuple[str, str] = self._map(data)
-        super().__init__(type=obj[0], value=obj[1], **data)
-
-    @staticmethod
-    def _map(args: Dict[str, str]) -> Tuple[str, str]:
-        return {
-            (k, v)
-            for k, v in args.items()
-            if k in map(lambda ot: ot.value, ObjectType)
-        }.pop()
+    @model_validator(mode="before")
+    @classmethod
+    def map_data(cls, data: Dict[str, str]) -> Dict[str, str]:
+        obj = get_object(data)
+        data["type"] = obj[0]
+        data["value"] = obj[1]
+        return data
 
 
 class Script(BaseConsumable):
@@ -371,3 +347,23 @@ class TiIndicator(Indicator):
     matched_indicator_pattern_ids: List[str]
     first_seen_date_times: List[str]
     last_seen_date_times: List[str]
+
+
+def get_object(data: Dict[str, str]) -> Tuple[str, str]:
+    for k, v in data.items():
+        if k in map(lambda ot: ot.value, ObjectType):
+            return k, v
+    raise ValueError("Could not find ObjectType")
+
+
+def _get_task_id(data: Dict[str, Any]) -> Optional[str]:
+    return next(
+        map(
+            lambda header: header.get("value", "").split("/")[-1],
+            filter(
+                lambda header: "Operation-Location" == header.get("name", ""),
+                data.pop("headers", []),
+            ),
+        ),
+        None,
+    )

src/pytmv1/model/responses.py

@@ -1,19 +1,9 @@
 from __future__ import annotations
 
 from enum import Enum
-from typing import (
-    Any,
-    Dict,
-    Generic,
-    List,
-    Optional,
-    Tuple,
-    Type,
-    TypeVar,
-    Union,
-)
+from typing import Any, Dict, Generic, List, Optional, Type, TypeVar, Union
 
-from pydantic import Field
+from pydantic import Field, model_validator
 
 from .commons import (
     Account,
@@ -32,6 +22,7 @@
     Script,
     SuspiciousObject,
     TiAlert,
+    get_object,
 )
 from .enums import (
     ObjectType,
@@ -71,9 +62,6 @@ class BaseTaskResp(BaseStatusResponse):
     description: Optional[str] = None
     account: Optional[str] = None
 
-    def __init__(self, **data: Any):
-        super().__init__(**data)
-
 
 MR = TypeVar("MR", bound=BaseMultiResponse[Any])
 R = TypeVar("R", bound=BaseResponse)
@@ -103,17 +91,13 @@ class BlockListTaskResp(BaseTaskResp):
     type: ObjectType
     value: str
 
-    def __init__(self, **data: Any):
-        obj: Tuple[str, str] = self._map(data)
-        super().__init__(type=obj[0], value=obj[1], **data)
-
-    @staticmethod
-    def _map(args: Dict[str, str]) -> Tuple[str, str]:
-        return {
-            (k, v)
-            for k, v in args.items()
-            if k in map(lambda ot: ot.value, ObjectType)
-        }.pop()
+    @model_validator(mode="before")
+    @classmethod
+    def map_data(cls, data: Dict[str, str]) -> Dict[str, str]:
+        obj = get_object(data)
+        data["type"] = obj[0]
+        data["value"] = obj[1]
+        return data
 
 
 class BytesResp(BaseResponse):
@@ -286,6 +270,6 @@ class TaskAction(Enum):
     RUN_OS_QUERY = ("runOsquery", None)
     RUN_YARA_RULES = ("runYaraRules", None)
 
-    def __init__(self, action: str, resp_class: Optional[Type[T]]):
+    def __init__(self, action: str, class_: Optional[Type[T]]):
         self.action = action
-        self.resp_class = resp_class
+        self.class_ = class_

tests/data.py

@@ -30,7 +30,7 @@ def text(self) -> str:
 
 
 def sae_alert():
-    return SaeAlert.construct(
+    return SaeAlert.model_construct(
         id="1",
         investigationStatus=InvestigationStatus.NEW,
         model="Possible Credential Dumping via Registry",
@@ -40,32 +40,32 @@ def sae_alert():
         description="description",
         workbenchLink="https://THE_WORKBENCH_URL",
         score=64,
-        impactScope=ImpactScope.construct(
+        impactScope=ImpactScope.model_construct(
             desktopCount=1,
             serverCount=0,
             accountCount=1,
             emailAddressCount=0,
             entities=[
-                Entity.construct(
-                    entity_value=HostInfo.construct(
+                Entity.model_construct(
+                    entity_value=HostInfo.model_construct(
                         name="host", ips=["1.1.1.1", "2.2.2.2"]
                     )
                 )
             ],
         ),
         indicators=[
-            Indicator.construct(
+            Indicator.model_construct(
                 provenance=["Alert"],
-                value=HostInfo.construct(
+                value=HostInfo.model_construct(
                     name="host", ips=["1.1.1.1", "2.2.2.2"]
                 ),
             )
         ],
         matchedRules=[
-            MatchedRule.construct(
+            MatchedRule.model_construct(
                 name="Potential Credential Dumping via Registry",
                 matchedFilters=[
-                    MatchedFilter.construct(
+                    MatchedFilter.model_construct(
                         name="Possible Credential Dumping via Registry Hive",
                         mitreTechniqueIds=[
                             "V9.T1003.004",
@@ -80,7 +80,7 @@ def sae_alert():
 
 
 def ti_alert():
-    return TiAlert.construct(
+    return TiAlert.model_construct(
         id="1",
         investigationStatus=InvestigationStatus.NEW,
         model="Threat Intelligence Sweeping",
@@ -94,38 +94,38 @@ def ti_alert():
         reportLink="https://THE_TI_REPORT_URL",
         createdBy="n/a",
         score=42,
-        impactScope=ImpactScope.construct(
+        impactScope=ImpactScope.model_construct(
             desktopCount=1,
             serverCount=0,
             accountCount=1,
             emailAddressCount=0,
             entities=[
-                Entity.construct(
-                    entity_value=HostInfo.construct(
+                Entity.model_construct(
+                    entity_value=HostInfo.model_construct(
                         name="host", ips=["1.1.1.1", "2.2.2.2"]
                     )
                 )
             ],
         ),
         indicators=[
-            Indicator.construct(
+            Indicator.model_construct(
                 provenance=["Alert"],
-                value=HostInfo.construct(
+                value=HostInfo.model_construct(
                     name="host", ips=["1.1.1.1", "2.2.2.2"]
                 ),
             )
         ],
         matchedIndicatorPatterns=[
-            MatchedIndicatorPattern.construct(
+            MatchedIndicatorPattern.model_construct(
                 tags=["STIX2.malicious-activity"],
                 pattern="[file:name = 'goog-phish-proto-1.vlpset']",
             )
         ],
         matchedRules=[
-            MatchedRule.construct(
+            MatchedRule.model_construct(
                 name="Potential Credential Dumping via Registry",
                 matchedFilters=[
-                    MatchedFilter.construct(
+                    MatchedFilter.model_construct(
                         name="Possible Credential Dumping via Registry Hive",
                         mitreTechniqueIds=[
                             "V9.T1003.004",