fix: Discriminatory Union types not working after migration to Pydantic v2

phrasetms_client/models/abstract_analyse_settings_dto.py

@@ -1,17 +1,16 @@
 # coding: utf-8
 
 """
-    Phrase TMS API
+Phrase TMS API
 
-    Welcome to Phrase's TMS API documentation.    Please visit our [help center](https://support.phrase.com/hc/en-us/sections/5709662083612) for more information about the APIs.    If you have any questions, please contact [Support](https://support.phrase.com/hc/requests/new).    Please, include the `User-Agent` header with the name of your application or project. It might be a good idea to include some sort of contact information as well, so that we can get in touch if necessary. Examples of excellent `User-Agent` headers:  > User-Agent: Example mobile app (example@phrase.com) <br/> User-Agent: ACME Inc Java 1.8 Client (http://acmeinc.com/contact)  # noqa: E501
+Welcome to Phrase's TMS API documentation.    Please visit our [help center](https://support.phrase.com/hc/en-us/sections/5709662083612) for more information about the APIs.    If you have any questions, please contact [Support](https://support.phrase.com/hc/requests/new).    Please, include the `User-Agent` header with the name of your application or project. It might be a good idea to include some sort of contact information as well, so that we can get in touch if necessary. Examples of excellent `User-Agent` headers:  > User-Agent: Example mobile app (example@phrase.com) <br/> User-Agent: ACME Inc Java 1.8 Client (http://acmeinc.com/contact)  # noqa: E501
 
-    The version of the OpenAPI document: Latest
-    Generated by OpenAPI Generator (https://openapi-generator.tech)
+The version of the OpenAPI document: Latest
+Generated by OpenAPI Generator (https://openapi-generator.tech)
 
-    Do not edit the class manually.
+Do not edit the class manually.
 """
 
-
 from __future__ import annotations
 import pprint
 import re  # noqa: F401
@@ -20,53 +19,95 @@
 
 
 from typing import Optional, Union
-from pydantic import BaseModel, Field, ConfigDict, StrictBool, StrictStr, field_validator
+from pydantic import (
+    BaseModel,
+    Field,
+    ConfigDict,
+    StrictBool,
+    StrictStr,
+    field_validator,
+)
+
 
 class AbstractAnalyseSettingsDto(BaseModel):
     """
     Base analyseSettingsDto
     """
-    type: Optional[StrictStr] = Field(None, description="Response differs based on analyse type")
-    include_confirmed_segments: Optional[StrictBool] = Field(None, alias="includeConfirmedSegments", description="Default: false")
-    include_numbers: Optional[StrictBool] = Field(None, alias="includeNumbers", description="Default: false")
-    include_locked_segments: Optional[StrictBool] = Field(None, alias="includeLockedSegments", description="Default: false")
-    count_source_units: Optional[StrictBool] = Field(None, alias="countSourceUnits", description="Default: false")
-    include_trans_memory: Optional[StrictBool] = Field(None, alias="includeTransMemory", description="Default: false")
-    naming_pattern: Optional[StrictStr] = Field(None, alias="namingPattern")
-    analyze_by_language: Optional[StrictBool] = Field(None, alias="analyzeByLanguage", description="Default: false")
-    analyze_by_provider: Optional[StrictBool] = Field(None, alias="analyzeByProvider", description="Default: false")
-    allow_automatic_post_analysis: Optional[StrictBool] = Field(None, alias="allowAutomaticPostAnalysis", description="If automatic post analysis should be created after update source. Default: false")
-    __properties = ["type", "includeConfirmedSegments", "includeNumbers", "includeLockedSegments", "countSourceUnits", "includeTransMemory", "namingPattern", "analyzeByLanguage", "analyzeByProvider", "allowAutomaticPostAnalysis"]
 
-    @field_validator('type')
+    type: Optional[StrictStr] = Field(
+        None, description="Response differs based on analyse type"
+    )
+    include_confirmed_segments: Optional[StrictBool] = Field(
+        None, alias="includeConfirmedSegments", description="Default: false"
+    )
+    include_numbers: Optional[StrictBool] = Field(
+        None, alias="includeNumbers", description="Default: false"
+    )
+    include_locked_segments: Optional[StrictBool] = Field(
+        None, alias="includeLockedSegments", description="Default: false"
+    )
+    count_source_units: Optional[StrictBool] = Field(
+        None, alias="countSourceUnits", description="Default: false"
+    )
+    include_trans_memory: Optional[StrictBool] = Field(
+        None, alias="includeTransMemory", description="Default: false"
+    )
+    naming_pattern: Optional[StrictStr] = Field(None, alias="namingPattern")
+    analyze_by_language: Optional[StrictBool] = Field(
+        None, alias="analyzeByLanguage", description="Default: false"
+    )
+    analyze_by_provider: Optional[StrictBool] = Field(
+        None, alias="analyzeByProvider", description="Default: false"
+    )
+    allow_automatic_post_analysis: Optional[StrictBool] = Field(
+        None,
+        alias="allowAutomaticPostAnalysis",
+        description="If automatic post analysis should be created after update source. Default: false",
+    )
+    __properties = [
+        "type",
+        "includeConfirmedSegments",
+        "includeNumbers",
+        "includeLockedSegments",
+        "countSourceUnits",
+        "includeTransMemory",
+        "namingPattern",
+        "analyzeByLanguage",
+        "analyzeByProvider",
+        "allowAutomaticPostAnalysis",
+    ]
+
+    @field_validator("type")
     @classmethod
     def type_validate_enum(cls, value):
         """Validates the enum"""
         if value is None:
             return value
 
-        if value not in ('PreAnalyse', 'PostAnalyse', 'PreAnalyseTarget', 'Compare'):
-            raise ValueError("must be one of enum values ('PreAnalyse', 'PostAnalyse', 'PreAnalyseTarget', 'Compare')")
+        if value not in ("PreAnalyse", "PostAnalyse", "PreAnalyseTarget", "Compare"):
+            raise ValueError(
+                "must be one of enum values ('PreAnalyse', 'PostAnalyse', 'PreAnalyseTarget', 'Compare')"
+            )
         return value
 
     model_config = ConfigDict(populate_by_name=True, validate_assignment=True)
     # JSON field name that stores the object type
-    __discriminator_property_name = 'type'
+    _discriminator_property_name = "type"
 
     # discriminator mappings
-    __discriminator_value_class_map = {
-        'PostAnalyse': 'PostAnalyse',
-        'PreAnalyse': 'PreAnalyse',
-        'PreAnalyseTarget': 'PreAnalyseTargetCompare',
-        'Compare': 'PreAnalyseTargetCompare'
+    _discriminator_value_class_map = {
+        "PostAnalyse": "PostAnalyse",
+        "PreAnalyse": "PreAnalyse",
+        "PreAnalyseTarget": "PreAnalyseTargetCompare",
+        "Compare": "PreAnalyseTargetCompare",
     }
 
     @classmethod
     def get_discriminator_value(cls, obj: dict) -> str:
         """Returns the discriminator value (object type) of the data"""
-        discriminator_value = obj[cls.__discriminator_property_name]
+        discriminator_value = obj[cls._discriminator_property_name.default]
         if discriminator_value:
-            return cls.__discriminator_value_class_map.get(discriminator_value)
+            return cls._discriminator_value_class_map.default.get(discriminator_value)
         else:
             return None
 
@@ -79,28 +120,33 @@ def to_json(self) -> str:
         return json.dumps(self.to_dict())
 
     @classmethod
-    def from_json(cls, json_str: str) -> Union(PostAnalyse, PreAnalyse, PreAnalyseTargetCompare):  # noqa: F821
+    def from_json(
+        cls, json_str: str
+    ) -> Union["PostAnalyse", "PreAnalyse", "PreAnalyseTargetCompare"]:
         """Create an instance of AbstractAnalyseSettingsDto from a JSON string"""
         return cls.from_dict(json.loads(json_str))
 
     def to_dict(self):
         """Returns the dictionary representation of the model using alias"""
-        _dict = self.model_dump(by_alias=True,
-                          exclude={
-                          },
-                          exclude_none=True)
+        _dict = self.model_dump(by_alias=True, exclude={}, exclude_none=True)
         return _dict
 
     @classmethod
-    def from_dict(cls, obj: dict) -> Union(PostAnalyse, PreAnalyse, PreAnalyseTargetCompare):  # noqa: F821
+    def from_dict(
+        cls, obj: dict
+    ) -> Union["PostAnalyse", "PreAnalyse", "PreAnalyseTargetCompare"]:
         """Create an instance of AbstractAnalyseSettingsDto from a dict"""
         # look up the object type based on discriminator mapping
         object_type = cls.get_discriminator_value(obj)
         if object_type:
             klass = getattr(phrasetms_client.models, object_type)
             return klass.from_dict(obj)
         else:
-            raise ValueError("AbstractAnalyseSettingsDto failed to lookup discriminator value from " +
-                             json.dumps(obj) + ". Discriminator property name: " + cls.__discriminator_property_name +
-                             ", mapping: " + json.dumps(cls.__discriminator_value_class_map))
-
+            raise ValueError(
+                "AbstractAnalyseSettingsDto failed to lookup discriminator value from "
+                + json.dumps(obj)
+                + ". Discriminator property name: "
+                + cls._discriminator_property_name.default
+                + ", mapping: "
+                + json.dumps(cls._discriminator_value_class_map.default)
+            )

phrasetms_client/models/abstract_connector_dto.py

@@ -1,17 +1,16 @@
 # coding: utf-8
 
 """
-    Phrase TMS API
+Phrase TMS API
 
-    Welcome to Phrase's TMS API documentation.    Please visit our [help center](https://support.phrase.com/hc/en-us/sections/5709662083612) for more information about the APIs.    If you have any questions, please contact [Support](https://support.phrase.com/hc/requests/new).    Please, include the `User-Agent` header with the name of your application or project. It might be a good idea to include some sort of contact information as well, so that we can get in touch if necessary. Examples of excellent `User-Agent` headers:  > User-Agent: Example mobile app (example@phrase.com) <br/> User-Agent: ACME Inc Java 1.8 Client (http://acmeinc.com/contact)  # noqa: E501
+Welcome to Phrase's TMS API documentation.    Please visit our [help center](https://support.phrase.com/hc/en-us/sections/5709662083612) for more information about the APIs.    If you have any questions, please contact [Support](https://support.phrase.com/hc/requests/new).    Please, include the `User-Agent` header with the name of your application or project. It might be a good idea to include some sort of contact information as well, so that we can get in touch if necessary. Examples of excellent `User-Agent` headers:  > User-Agent: Example mobile app (example@phrase.com) <br/> User-Agent: ACME Inc Java 1.8 Client (http://acmeinc.com/contact)  # noqa: E501
 
-    The version of the OpenAPI document: Latest
-    Generated by OpenAPI Generator (https://openapi-generator.tech)
+The version of the OpenAPI document: Latest
+Generated by OpenAPI Generator (https://openapi-generator.tech)
 
-    Do not edit the class manually.
+Do not edit the class manually.
 """
 
-
 from __future__ import annotations
 import pprint
 import re  # noqa: F401
@@ -21,48 +20,51 @@
 import phrasetms_client.models
 
 
-
 from pydantic import BaseModel, Field, ConfigDict, StrictStr, StringConstraints
 
+
 class AbstractConnectorDto(BaseModel):
     """
     AbstractConnectorDto
     """
-    name: Annotated[str, StringConstraints(strict=True, max_length=255, min_length=0)] = Field(..., description="Name of the connector")
+
+    name: Annotated[
+        str, StringConstraints(strict=True, max_length=255, min_length=0)
+    ] = Field(..., description="Name of the connector")
     type: StrictStr = Field(..., description="Connector type")
     __properties = ["name", "type"]
 
     model_config = ConfigDict(populate_by_name=True, validate_assignment=True)
     # JSON field name that stores the object type
-    __discriminator_property_name = 'type'
+    _discriminator_property_name = "type"
 
     # discriminator mappings
-    __discriminator_value_class_map = {
-        'AdobeExperienceManager': 'AdobeExperienceManager',
-        'AmazonS3': 'AmazonS3',
-        'BitbucketServer': 'BitbucketServer',
-        'Contentstack': 'Contentstack',
-        'Ftp': 'Ftp',
-        'Git': 'Git',
-        'GitLab': 'GitLab',
-        'Joomla': 'Joomla',
-        'Kentico': 'Kentico',
-        'Magento': 'Magento',
-        'Marketo': 'Marketo',
-        'MicrosoftAzure': 'MicrosoftAzure',
-        'Sftp': 'Sftp',
-        'Sitecore': 'Sitecore',
-        'Tridion': 'Tridion',
-        'Typo3': 'Typo3',
-        'Wordpress': 'Wordpress'
+    _discriminator_value_class_map = {
+        "AdobeExperienceManager": "AdobeExperienceManager",
+        "AmazonS3": "AmazonS3",
+        "BitbucketServer": "BitbucketServer",
+        "Contentstack": "Contentstack",
+        "Ftp": "Ftp",
+        "Git": "Git",
+        "GitLab": "GitLab",
+        "Joomla": "Joomla",
+        "Kentico": "Kentico",
+        "Magento": "Magento",
+        "Marketo": "Marketo",
+        "MicrosoftAzure": "MicrosoftAzure",
+        "Sftp": "Sftp",
+        "Sitecore": "Sitecore",
+        "Tridion": "Tridion",
+        "Typo3": "Typo3",
+        "Wordpress": "Wordpress",
     }
 
     @classmethod
     def get_discriminator_value(cls, obj: dict) -> str:
         """Returns the discriminator value (object type) of the data"""
-        discriminator_value = obj[cls.__discriminator_property_name]
+        discriminator_value = obj[cls._discriminator_property_name.default]
         if discriminator_value:
-            return cls.__discriminator_value_class_map.get(discriminator_value)
+            return cls._discriminator_value_class_map.default.get(discriminator_value)
         else:
             return None
 
@@ -75,28 +77,69 @@ def to_json(self) -> str:
         return json.dumps(self.to_dict())
 
     @classmethod
-    def from_json(cls, json_str: str) -> Union(AdobeExperienceManager, AmazonS3, BitbucketServer, Contentstack, Ftp, Git, GitLab, Joomla, Kentico, Magento, Marketo, MicrosoftAzure, Sftp, Sitecore, Tridion, Typo3, Wordpress):  # noqa: F821
+    def from_json(
+        cls, json_str: str
+    ) -> Union[
+        "AdobeExperienceManager",
+        "AmazonS3",
+        "BitbucketServer",
+        "Contentstack",
+        "Ftp",
+        "Git",
+        "GitLab",
+        "Joomla",
+        "Kentico",
+        "Magento",
+        "Marketo",
+        "MicrosoftAzure",
+        "Sftp",
+        "Sitecore",
+        "Tridion",
+        "Typo3",
+        "Wordpress",
+    ]:
         """Create an instance of AbstractConnectorDto from a JSON string"""
         return cls.from_dict(json.loads(json_str))
 
     def to_dict(self):
         """Returns the dictionary representation of the model using alias"""
-        _dict = self.model_dump(by_alias=True,
-                          exclude={
-                          },
-                          exclude_none=True)
+        _dict = self.model_dump(by_alias=True, exclude={}, exclude_none=True)
         return _dict
 
     @classmethod
-    def from_dict(cls, obj: dict) -> Union(AdobeExperienceManager, AmazonS3, BitbucketServer, Contentstack, Ftp, Git, GitLab, Joomla, Kentico, Magento, Marketo, MicrosoftAzure, Sftp, Sitecore, Tridion, Typo3, Wordpress):  # noqa: F821
+    def from_dict(
+        cls, obj: dict
+    ) -> Union[
+        "AdobeExperienceManager",
+        "AmazonS3",
+        "BitbucketServer",
+        "Contentstack",
+        "Ftp",
+        "Git",
+        "GitLab",
+        "Joomla",
+        "Kentico",
+        "Magento",
+        "Marketo",
+        "MicrosoftAzure",
+        "Sftp",
+        "Sitecore",
+        "Tridion",
+        "Typo3",
+        "Wordpress",
+    ]:
         """Create an instance of AbstractConnectorDto from a dict"""
         # look up the object type based on discriminator mapping
         object_type = cls.get_discriminator_value(obj)
         if object_type:
             klass = getattr(phrasetms_client.models, object_type)
             return klass.from_dict(obj)
         else:
-            raise ValueError("AbstractConnectorDto failed to lookup discriminator value from " +
-                             json.dumps(obj) + ". Discriminator property name: " + cls.__discriminator_property_name +
-                             ", mapping: " + json.dumps(cls.__discriminator_value_class_map))
-
+            raise ValueError(
+                "AbstractConnectorDto failed to lookup discriminator value from "
+                + json.dumps(obj)
+                + ". Discriminator property name: "
+                + cls._discriminator_property_name.default
+                + ", mapping: "
+                + json.dumps(cls._discriminator_value_class_map.default)
+            )