Module airbyte_agent_sdk.connectors.zendesk_support

Zendesk-Support connector for Airbyte SDK.

Auto-generated from OpenAPI specification.

Sub-modules

airbyte_agent_sdk.connectors.zendesk_support.connector
airbyte_agent_sdk.connectors.zendesk_support.connector_model
airbyte_agent_sdk.connectors.zendesk_support.models
airbyte_agent_sdk.connectors.zendesk_support.types

Classes

AirbyteAuthConfig(**data: Any) : Authentication configuration for Airbyte hosted mode execution.

Pass this to the connector's auth_config parameter to use hosted mode, where API credentials are stored securely in Airbyte Cloud.

For hosted mode execution, provide client credentials with either:

connector_id: Direct connector/source ID (skips lookup)
workspace_name: Workspace name for connector lookup

Attributes: workspace_name: Workspace name for hosted mode connector lookup organization_id: Optional Airbyte organization ID for multi-org selection airbyte_client_id: Airbyte OAuth client ID (required for hosted mode) airbyte_client_secret: Airbyte OAuth client secret (required for hosted mode) connector_id: Specific connector/source ID (skips lookup if provided)

Examples:

Hosted mode with connector_id (no lookup needed)

connector = GongConnector( auth_config=AirbyteAuthConfig( airbyte_client_id="client_abc123", airbyte_client_secret="secret_xyz789", connector_id="existing-source-uuid" ) )

Hosted mode with workspace_name (lookup by workspace)

connector = GongConnector( auth_config=AirbyteAuthConfig( workspace_name="user-123", organization_id="00000000-0000-0000-0000-000000000123", airbyte_client_id="client_abc123", airbyte_client_secret="secret_xyz789" ) )

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

pydantic.main.BaseModel

Class variables

airbyte_client_id: str | None : The type of the None singleton.

airbyte_client_secret: str | None : The type of the None singleton.

connector_id: str | None : The type of the None singleton.

model_config : The type of the None singleton.

organization_id: str | None : The type of the None singleton.

workspace_name: str | None : The type of the None singleton.

AirbyteSearchMeta(**data: Any) : Pagination metadata for search responses.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

pydantic.main.BaseModel

Class variables

cursor: str | None : Cursor for fetching the next page of results.

has_more: bool : Whether more results are available.

model_config : The type of the None singleton.

took_ms: int | None : Time taken to execute the search in milliseconds.

AirbyteSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

pydantic.main.BaseModel
typing.Generic

Descendants

airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult[ArticleAttachmentsSearchData]
airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult[ArticlesSearchData]
airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult[AutomationsSearchData]
airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult[BrandsSearchData]
airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult[DeletedTicketsSearchData]
airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult[GroupMembershipsSearchData]
airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult[GroupsSearchData]
airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult[MacrosSearchData]
airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult[OrganizationMembershipsSearchData]
airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult[OrganizationsSearchData]
airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult[SatisfactionRatingsSearchData]
airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult[SlaPoliciesSearchData]
airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult[TagsSearchData]
airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult[TicketAuditsSearchData]
airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult[TicketCommentsSearchData]
airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult[TicketFieldsSearchData]
airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult[TicketFormsSearchData]
airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult[TicketMetricsSearchData]
airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult[TicketsSearchData]
airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult[TriggersSearchData]
airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult[UsersSearchData]

Class variables

data: list[~D] : List of matching records.

meta: airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchMeta : Pagination metadata.

model_config : The type of the None singleton.

ArticleAttachmentsSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

ArticlesSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

AutomationsSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

BrandsSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

DeletedTicketsSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

GroupMembershipsSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

GroupsSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

MacrosSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

OrganizationMembershipsSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

OrganizationsSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

SatisfactionRatingsSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

SlaPoliciesSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

TagsSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

TicketAuditsSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

TicketCommentsSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

TicketFieldsSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

TicketFormsSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

TicketMetricsSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

TicketsSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

TriggersSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

UsersSearchResult(**data: Any) : Result from Airbyte cache search operations with typed records.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

airbyte_agent_sdk.connectors.zendesk_support.models.AirbyteSearchResult
pydantic.main.BaseModel
typing.Generic

ArticleAttachmentsSearchData(**data: Any) : Search result data for article_attachments entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

pydantic.main.BaseModel

Class variables

article_id: int | None : The ID of the article this attachment belongs to

content_type: str | None : The MIME type of the attachment

content_url: str | None : The URL to download the attachment

created_at: str | None : The time the attachment was created

file_name: str | None : The name of the attached file

id: int | None : The unique ID of the attachment

inline: bool | None : Whether the attachment is displayed inline

model_config : The type of the None singleton.

size: int | None : The size of the attachment in bytes

updated_at: str | None : The time the attachment was last updated

url: str | None : The API URL of the attachment

ArticlesSearchData(**data: Any) : Search result data for articles entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

pydantic.main.BaseModel

Class variables

author_id: int | None : The ID of the user who created the article

body: str | None : The body content of the article (HTML)

created_at: str | None : The time the article was created

draft: bool | None : Whether the article is a draft

html_url: str | None : The public URL of the article

id: int | None : The unique ID of the article

label_names: list[typing.Any] | None : List of label names associated with the article

locale: str | None : The locale of the article

model_config : The type of the None singleton.

position: int | None : Position of the article in the section

promoted: bool | None : Whether the article is promoted

section_id: int | None : The ID of the section the article belongs to

title: str | None : The title of the article

updated_at: str | None : The time the article was last updated

url: str | None : The API URL of the article

vote_count: int | None : Number of votes

vote_sum: int | None : Sum of upvotes and downvotes

AutomationsSearchData(**data: Any) : Search result data for automations entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

pydantic.main.BaseModel

Class variables

actions: list[typing.Any] | None : An array of actions

active: bool | None : Whether the automation is active

conditions: dict[str, typing.Any] | None : An object that describes the conditions under which the automation will execute

created_at: str | None : The time the automation was created

id: int | None : Automatically assigned when created

model_config : The type of the None singleton.

position: int | None : The position of the automation

raw_title: str | None : The dynamic content placeholder for title

title: str | None : The title of the automation

updated_at: str | None : The time the automation was last updated

BrandsSearchData(**data: Any) : Search result data for brands entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

pydantic.main.BaseModel

Class variables

active: bool | None : Indicates whether the brand is set as active

brand_url: str | None : The public URL of the brand

created_at: str | None : Timestamp when the brand was created

default: bool | None : Indicates whether the brand is the default brand for tickets generated from non-branded channels

has_help_center: bool | None : Indicates whether the brand has a Help Center enabled

help_center_state: str | None : The state of the Help Center, with allowed values of enabled, disabled, or restricted

host_mapping: str | None : The host mapping configuration for the brand, visible only to administrators

id: int | None : Unique identifier automatically assigned when the brand is created

is_deleted: bool | None : Indicates whether the brand has been deleted

logo: str | None : Brand logo image file represented as an Attachment object

model_config : The type of the None singleton.

name: str | None : The name of the brand

signature_template: str | None : The signature template used for the brand

subdomain: str | None : The subdomain associated with the brand

ticket_form_ids: list[typing.Any] | None : Array of ticket form IDs that are available for use by this brand

updated_at: str | None : Timestamp when the brand was last updated

url: str | None : The API URL for accessing this brand resource

DeletedTicketsSearchData(**data: Any) : Search result data for deleted_tickets entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

pydantic.main.BaseModel

Class variables

actor: dict[str, typing.Any] | None : The user who performed the deletion action

deleted_at: str | None : The timestamp when the ticket was deleted

description: str | None : Additional details or comments about the deleted ticket

id: int | None : The unique identifier of the deleted ticket

model_config : The type of the None singleton.

previous_state: str | None : The state of the ticket before it was deleted

subject: str | None : The subject or title of the deleted ticket

GroupMembershipsSearchData(**data: Any) : Search result data for group_memberships entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

pydantic.main.BaseModel

Class variables

created_at: str | None : When the group membership was created

default: bool | None : If true, tickets assigned directly to the agent will assume this membership's group

group_id: int | None : The id of a group

id: int | None : Automatically assigned upon creation

model_config : The type of the None singleton.

updated_at: str | None : When the group membership was last updated

url: str | None : The API url of this record

user_id: int | None : The id of an agent

GroupsSearchData(**data: Any) : Search result data for groups entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

pydantic.main.BaseModel

Class variables

created_at: str | None : Timestamp indicating when the group was created

default: bool | None : Indicates if the group is the default one for the account

deleted: bool | None : Indicates whether the group has been deleted

description: str | None : The description of the group

id: int | None : Unique identifier automatically assigned when creating groups

is_public: bool | None : Indicates if the group is public (true) or private (false)

model_config : The type of the None singleton.

name: str | None : The name of the group

updated_at: str | None : Timestamp indicating when the group was last updated

url: str | None : The API URL of the group

MacrosSearchData(**data: Any) : Search result data for macros entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

pydantic.main.BaseModel

Class variables

actions: list[typing.Any] | None : Actions to perform when macro is applied

active: bool | None : Useful for determining if the macro should be displayed

created_at: str | None : The time the macro was created

description: str | None : The description of the macro

id: int | None : Automatically assigned when the macro is created

model_config : The type of the None singleton.

position: int | None : The position of the macro

raw_title: str | None : The dynamic content placeholder for title

restriction: dict[str, typing.Any] | None : Who may access this macro

title: str | None : The title of the macro

updated_at: str | None : The time the macro was last updated

url: str | None : A URL to access the macro's details

OrganizationMembershipsSearchData(**data: Any) : Search result data for organization_memberships entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

pydantic.main.BaseModel

Class variables

created_at: str | None : When the membership was created

default: bool | None : If true, this is the default organization for the user

id: int | None : Automatically assigned when the membership is created

model_config : The type of the None singleton.

organization_id: int | None : The ID of the organization associated with this user

organization_name: str | None : The name of the organization

updated_at: str | None : When the membership was last updated

url: str | None : The API url of this membership

user_id: int | None : The ID of the user for whom this memberships belongs

view_tickets: bool | None : If true, this user can view tickets from this organization

OrganizationsSearchData(**data: Any) : Search result data for organizations entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

pydantic.main.BaseModel

Class variables

created_at: str | None : Timestamp when the organization was created

deleted_at: str | None : Timestamp when the organization was deleted

details: str | None : Details about the organization, such as the address

domain_names: list[typing.Any] | None : Array of domain names associated with this organization for automatic user assignment

external_id: str | None : Unique external identifier to associate the organization to an external record (case-insensitive)

group_id: int | None : ID of the group where new tickets from users in this organization are automatically assigned

id: int | None : Unique identifier automatically assigned when the organization is created

model_config : The type of the None singleton.

name: str | None : Unique name for the organization (mandatory field)

notes: str | None : Notes about the organization

organization_fields: dict[str, typing.Any] | None : Key-value object for custom organization fields

shared_comments: bool | None : Boolean indicating whether end users in this organization can comment on each other's tickets

shared_tickets: bool | None : Boolean indicating whether end users in this organization can see each other's tickets

tags: list[typing.Any] | None : Array of tags associated with the organization

updated_at: str | None : Timestamp of the last update to the organization

url: str | None : The API URL of this organization

SatisfactionRatingsSearchData(**data: Any) : Search result data for satisfaction_ratings entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

pydantic.main.BaseModel

Class variables

assignee_id: int | None : The identifier of the agent assigned to the ticket at the time the rating was submitted

comment: str | None : Optional comment provided by the requester with the rating

created_at: str | None : Timestamp indicating when the satisfaction rating was created

group_id: int | None : The identifier of the group assigned to the ticket at the time the rating was submitted

id: int | None : Unique identifier for the satisfaction rating, automatically assigned upon creation

model_config : The type of the None singleton.

reason: str | None : Free-text reason for a bad rating provided by the requester in a follow-up question

reason_id: int | None : Identifier for the predefined reason given for a negative rating

requester_id: int | None : The identifier of the ticket requester who submitted the satisfaction rating

score: str | None : The satisfaction rating value: 'offered', 'unoffered', 'good', or 'bad'

ticket_id: int | None : The identifier of the ticket being rated

updated_at: str | None : Timestamp indicating when the satisfaction rating was last updated

url: str | None : The API URL of this satisfaction rating resource

SlaPoliciesSearchData(**data: Any) : Search result data for sla_policies entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

pydantic.main.BaseModel

Class variables

created_at: str | None : When the SLA policy was created

description: str | None : The description of the SLA policy

filter: dict[str, typing.Any] | None : Filter for the SLA policy

id: int | None : Automatically assigned when the SLA policy is created

model_config : The type of the None singleton.

policy_metrics: list[typing.Any] | None : Array of policy metrics

position: int | None : Position of the SLA policy

title: str | None : The title of the SLA policy

updated_at: str | None : When the SLA policy was last updated

url: str | None : URL of the SLA policy

TagsSearchData(**data: Any) : Search result data for tags entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

pydantic.main.BaseModel

Class variables

count: int | None : The number of times this tag has been used across resources

model_config : The type of the None singleton.

name: str | None : The tag name string used to label and categorize resources

TicketAuditsSearchData(**data: Any) : Search result data for ticket_audits entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

pydantic.main.BaseModel

Class variables

attachments: list[typing.Any] | None : Files or documents attached to the audit

author_id: int | None : The unique identifier of the user who created the audit

created_at: str | None : Timestamp indicating when the audit was created

events: list[typing.Any] | None : Array of events that occurred in this audit, such as field changes, comments, or tag updates

id: int | None : Unique identifier for the audit record, automatically assigned when the audit is created

metadata: dict[str, typing.Any] | None : Custom and system data associated with the audit

model_config : The type of the None singleton.

ticket_id: int | None : The unique identifier of the ticket associated with this audit

via: dict[str, typing.Any] | None : Describes how the audit was created, providing context about the creation source

TicketCommentsSearchData(**data: Any) : Search result data for ticket_comments entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

pydantic.main.BaseModel

Class variables

attachments: list[typing.Any] | None : List of files or media attached to the comment

audit_id: int | None : Identifier of the audit record associated with this comment event

author_id: int | None : Identifier of the user who created the comment

body: str | None : Content of the comment in its original format

created_at: str | None : Timestamp when the comment was created

event_type: str | None : Specific classification of the event within the ticket event stream

html_body: str | None : HTML-formatted content of the comment

id: int | None : Unique identifier for the comment event

metadata: dict[str, typing.Any] | None : Additional structured information about the comment not covered by standard fields

model_config : The type of the None singleton.

plain_body: str | None : Plain text content of the comment without formatting

public: bool | None : Boolean indicating whether the comment is visible to end users or is an internal note

ticket_id: int | None : Identifier of the ticket to which this comment belongs

timestamp: int | None : Timestamp of when the event occurred in the incremental export stream

type_: str | None : Type of event, typically indicating this is a comment event

uploads: list[typing.Any] | None : Array of upload tokens or identifiers for files being attached to the comment

via: dict[str, typing.Any] | None : Channel or method through which the comment was submitted

via_reference_id: int | None : Reference identifier for the channel through which the comment was created

TicketFieldsSearchData(**data: Any) : Search result data for ticket_fields entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

pydantic.main.BaseModel

Class variables

active: bool | None : Whether this field is currently available for use

agent_description: str | None : A description of the ticket field that only agents can see

collapsed_for_agents: bool | None : If true, the field is shown to agents by default; if false, it is hidden alongside infrequently used fields

created_at: str | None : Timestamp when the custom ticket field was created

custom_field_options: list[typing.Any] | None : Array of option objects for custom ticket fields of type multiselect or tagger

custom_statuses: list[typing.Any] | None : List of customized ticket statuses, only present for system ticket fields of type custom_status

description: str | None : Text describing the purpose of the ticket field to users

editable_in_portal: bool | None : Whether this field is editable by end users in Help Center

id: int | None : Unique identifier for the ticket field, automatically assigned when created

key: str | None : Internal identifier or reference key for the field

model_config : The type of the None singleton.

position: int | None : The relative position of the ticket field on a ticket, controlling display order

raw_description: str | None : The dynamic content placeholder if present, or the description value if not

raw_title: str | None : The dynamic content placeholder if present, or the title value if not

raw_title_in_portal: str | None : The dynamic content placeholder if present, or the title_in_portal value if not

regexp_for_validation: str | None : For regexp fields only, the validation pattern for a field value to be deemed valid

removable: bool | None : If false, this field is a system field that must be present on all tickets

required: bool | None : If true, agents must enter a value in the field to change the ticket status to solved

required_in_portal: bool | None : If true, end users must enter a value in the field to create a request

sub_type_id: int | None : For system ticket fields of type priority and status, controlling available options

system_field_options: list[typing.Any] | None : Array of options for system ticket fields of type tickettype, priority, or status

tag: str | None : For checkbox fields only, a tag added to tickets when the checkbox field is selected

title: str | None : The title of the ticket field displayed to agents

title_in_portal: str | None : The title of the ticket field displayed to end users in Help Center

type_: str | None : Field type such as text, textarea, checkbox, date, integer, decimal, regexp, multiselect, or tagger

updated_at: str | None : Timestamp when the custom ticket field was last updated

url: str | None : The API URL for this ticket field resource

visible_in_portal: bool | None : Whether this field is visible to end users in Help Center

TicketFormsSearchData(**data: Any) : Search result data for ticket_forms entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

pydantic.main.BaseModel

Class variables

active: bool | None : Indicates if the form is set as active

agent_conditions: list[typing.Any] | None : Array of condition sets for agent workspaces

created_at: str | None : Timestamp when the ticket form was created

default: bool | None : Indicates if the form is the default form for this account

display_name: str | None : The name of the form that is displayed to an end user

end_user_conditions: list[typing.Any] | None : Array of condition sets for end user products

end_user_visible: bool | None : Indicates if the form is visible to the end user

id: int | None : Unique identifier for the ticket form, automatically assigned when creating the form

in_all_brands: bool | None : Indicates if the form is available for use in all brands on this account

model_config : The type of the None singleton.

name: str | None : The name of the ticket form

position: int | None : The position of this form among other forms in the account, such as in a dropdown

raw_display_name: str | None : The dynamic content placeholder if present, or the display_name value if not

raw_name: str | None : The dynamic content placeholder if present, or the name value if not

restricted_brand_ids: list[typing.Any] | None : IDs of all brands that this ticket form is restricted to

ticket_field_ids: list[typing.Any] | None : IDs of all ticket fields included in this ticket form

updated_at: str | None : Timestamp of the last update to the ticket form

url: str | None : URL of the ticket form

TicketMetricsSearchData(**data: Any) : Search result data for ticket_metrics entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

pydantic.main.BaseModel

Class variables

agent_wait_time_in_minutes: dict[str, typing.Any] | None : Number of minutes the agent spent waiting during calendar and business hours

assigned_at: str | None : Timestamp when the ticket was assigned

assignee_stations: int | None : Number of assignees the ticket had

assignee_updated_at: str | None : Timestamp when the assignee last updated the ticket

created_at: str | None : Timestamp when the metric record was created

custom_status_updated_at: str | None : Timestamp when the ticket's custom status was last updated

first_resolution_time_in_minutes: dict[str, typing.Any] | None : Number of minutes to the first resolution time during calendar and business hours

full_resolution_time_in_minutes: dict[str, typing.Any] | None : Number of minutes to the full resolution during calendar and business hours

generated_timestamp: int | None : Timestamp of when record was last updated

group_stations: int | None : Number of groups the ticket passed through

id: int | None : Unique identifier for the ticket metric record

initially_assigned_at: str | None : Timestamp when the ticket was initially assigned

instance_id: int | None : ID of the Zendesk instance associated with the ticket

latest_comment_added_at: str | None : Timestamp when the latest comment was added

metric: str | None : Ticket metrics data

model_config : The type of the None singleton.

on_hold_time_in_minutes: dict[str, typing.Any] | None : Number of minutes on hold

reopens: int | None : Total number of times the ticket was reopened

replies: int | None : The number of public replies added to a ticket by an agent

reply_time_in_minutes: dict[str, typing.Any] | None : Number of minutes to the first reply during calendar and business hours

reply_time_in_seconds: dict[str, typing.Any] | None : Number of seconds to the first reply during calendar hours, only available for Messaging tickets

requester_updated_at: str | None : Timestamp when the requester last updated the ticket

requester_wait_time_in_minutes: dict[str, typing.Any] | None : Number of minutes the requester spent waiting during calendar and business hours

solved_at: str | None : Timestamp when the ticket was solved

status: dict[str, typing.Any] | None : The current status of the ticket (open, pending, solved, etc.).

status_updated_at: str | None : Timestamp when the status of the ticket was last updated

ticket_id: int | None : Identifier of the associated ticket

time: str | None : Time related to the ticket

type_: str | None : Type of ticket

updated_at: str | None : Timestamp when the metric record was last updated

url: str | None : The API url of the ticket metric

TicketsSearchData(**data: Any) : Search result data for tickets entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

pydantic.main.BaseModel

Class variables

allow_attachments: bool | None : Boolean indicating whether attachments are allowed on the ticket

allow_channelback: bool | None : Boolean indicating whether agents can reply to the ticket through the original channel

assignee_id: int | None : Unique identifier of the agent currently assigned to the ticket

brand_id: int | None : Unique identifier of the brand associated with the ticket in multi-brand accounts

collaborator_ids: list[typing.Any] | None : Array of user identifiers who are collaborating on the ticket

created_at: str | None : Timestamp indicating when the ticket was created

custom_fields: list[typing.Any] | None : Array of custom field values specific to the account's ticket configuration

custom_status_id: int | None : Unique identifier of the custom status applied to the ticket

deleted_ticket_form_id: int | None : The ID of the ticket form that was previously associated with this ticket but has since been deleted

description: str | None : Initial description or content of the ticket when it was created

due_at: str | None : Timestamp indicating when the ticket is due for completion or resolution

email_cc_ids: list[typing.Any] | None : Array of user identifiers who are CC'd on ticket email notifications

external_id: str | None : External identifier for the ticket, used for integrations with other systems

fields: list[typing.Any] | None : Array of ticket field values including both system and custom fields

follower_ids: list[typing.Any] | None : Array of user identifiers who are following the ticket for updates

followup_ids: list[typing.Any] | None : Array of identifiers for follow-up tickets related to this ticket

forum_topic_id: int | None : Unique identifier linking the ticket to a forum topic if applicable

from_messaging_channel: bool | None : Boolean indicating whether the ticket originated from a messaging channel

generated_timestamp: int | None : Timestamp updated for all ticket updates including system changes, used for incremental export

group_id: int | None : Unique identifier of the agent group assigned to handle the ticket

has_incidents: bool | None : Boolean indicating whether this problem ticket has related incident tickets

id: int | None : Unique identifier for the ticket

is_public: bool | None : Boolean indicating whether the ticket is publicly visible

model_config : The type of the None singleton.

organization_id: int | None : Unique identifier of the organization associated with the ticket

priority: str | None : Priority level assigned to the ticket (e.g., urgent, high, normal, low)

problem_id: int | None : Unique identifier of the problem ticket if this is an incident ticket

raw_subject: str | None : Original unprocessed subject line before any system modifications

recipient: str | None : Email address or identifier of the ticket recipient

requester_id: int | None : Unique identifier of the user who requested or created the ticket

result_type: str | None : The type of the search result (e.g. ticket) when returned from search endpoints

satisfaction_rating: Any : Object containing customer satisfaction rating data for the ticket

sharing_agreement_ids: list[typing.Any] | None : Array of sharing agreement identifiers if the ticket is shared across Zendesk instances

status: str | None : Current status of the ticket (e.g., new, open, pending, solved, closed)

subject: str | None : Subject line of the ticket describing the issue or request

submitter_id: int | None : Unique identifier of the user who submitted the ticket on behalf of the requester

tags: list[typing.Any] | None : Array of tags applied to the ticket for categorization and filtering

ticket_form_id: int | None : Unique identifier of the ticket form used when creating the ticket

type_: str | None : Type of ticket (e.g., problem, incident, question, task)

updated_at: str | None : Timestamp indicating when the ticket was last updated with a ticket event

url: str | None : API URL to access the full ticket resource

via: dict[str, typing.Any] | None : Object describing the channel and method through which the ticket was created

TriggersSearchData(**data: Any) : Search result data for triggers entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

pydantic.main.BaseModel

Class variables

actions: list[typing.Any] | None : An array of actions

active: bool | None : Whether the trigger is active

category_id: str | None : The ID of the category the trigger belongs to

conditions: dict[str, typing.Any] | None : An object that describes the conditions under which the trigger will execute

created_at: str | None : The time the trigger was created

description: str | None : The description of the trigger

id: int | None : Automatically assigned when created

model_config : The type of the None singleton.

position: int | None : Position of the trigger

raw_title: str | None : The dynamic content placeholder for title

title: str | None : The title of the trigger

updated_at: str | None : The time the trigger was last updated

url: str | None : The URL of the trigger

UsersSearchData(**data: Any) : Search result data for users entity.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)

pydantic.main.BaseModel

Class variables

active: bool | None : Indicates if the user account is currently active

alias: str | None : Alternative name or nickname for the user

chat_only: bool | None : Indicates if the user can only interact via chat

created_at: str | None : Timestamp indicating when the user was created

custom_role_id: int | None : Identifier for a custom role assigned to the user

default_group_id: int | None : Identifier of the default group assigned to the user

details: str | None : Additional descriptive information about the user

email: str | None : Email address of the user

external_id: str | None : External system identifier for the user, used for integrations

iana_time_zone: str | None : IANA standard time zone identifier for the user

id: int | None : Unique identifier for the user

last_login_at: str | None : Timestamp of the user's most recent login

locale: str | None : Locale setting determining language and regional format preferences

locale_id: int | None : Identifier for the user's locale preference

model_config : The type of the None singleton.

moderator: bool | None : Indicates if the user has moderator privileges

name: str | None : Display name of the user

notes: str | None : Internal notes about the user, visible only to agents

only_private_comments: bool | None : Indicates if the user can only make private comments on tickets

organization_id: int | None : Identifier of the organization the user belongs to

permanently_deleted: bool | None : Indicates if the user has been permanently deleted from the system

phone: str | None : Phone number of the user

photo: dict[str, typing.Any] | None : Profile photo or avatar of the user

report_csv: bool | None : Indicates if the user receives reports in CSV format

restricted_agent: bool | None : Indicates if the agent has restricted access permissions

role: str | None : Role assigned to the user defining their permissions level

role_type: int | None : Type classification of the user's role

shared: bool | None : Indicates if the user is shared across multiple accounts

shared_agent: bool | None : Indicates if the user is a shared agent across multiple brands or accounts

shared_phone_number: bool | None : Indicates if the phone number is shared with other users

signature: str | None : Email signature text for the user

suspended: bool | None : Indicates if the user account is suspended

tags: list[typing.Any] | None : Labels or tags associated with the user for categorization

ticket_restriction: str | None : Defines which tickets the user can access based on restrictions

time_zone: str | None : Time zone setting for the user

two_factor_auth_enabled: bool | None : Indicates if two-factor authentication is enabled for the user

updated_at: str | None : Timestamp indicating when the user was last updated

url: str | None : API endpoint URL for accessing the user's detailed information

user_fields: dict[str, typing.Any] | None : Custom field values specific to the user, stored as key-value pairs

verified: bool | None : Indicates if the user's identity has been verified

Auto-generated from OpenAPI specification with full type safety.

Initialize a new zendesk-support connector instance.

Supports both local and hosted execution modes:

Local mode: Provide connector-specific auth config (e.g., ZendeskSupportAuthConfig)
Hosted mode: Provide AirbyteAuthConfig with client credentials and either connector_id or workspace_name

Args: auth_config: Either connector-specific auth config for local mode, or AirbyteAuthConfig for hosted mode on_token_refresh: Optional callback for OAuth2 token refresh persistence. Called with new_tokens dict when tokens are refreshed. Can be sync or async. Example: lambda tokens: save_to_database(tokens) subdomain: Your Zendesk subdomain Examples:

Local mode (direct API calls)

connector = ZendeskSupportConnector(auth_config=ZendeskSupportAuthConfig(access_token="...", refresh_token="..."))

Hosted mode with explicit connector_id (no lookup needed)

connector = ZendeskSupportConnector( auth_config=AirbyteAuthConfig( airbyte_client_id="client_abc123", airbyte_client_secret="secret_xyz789", connector_id="existing-source-uuid" ) )

Hosted mode with lookup by workspace_name

connector = ZendeskSupportConnector( auth_config=AirbyteAuthConfig( workspace_name="user-123", organization_id="00000000-0000-0000-0000-000000000123", airbyte_client_id="client_abc123", airbyte_client_secret="secret_xyz789" ) )

Class variables

connector_name : The type of the None singleton.

connector_version : The type of the None singleton.

sdk_version : The type of the None singleton.

Static methods

tool_utils(func: _F | None = None, *, update_docstring: bool = True, max_output_chars: int | None = 100000, framework: FrameworkName | None = None, internal_retries: int = 0, should_internal_retry: Callable[[Exception, tuple[Any, ...], dict[str, Any]], bool] | None = None, exhausted_runtime_failure_message: Callable[[Exception, tuple[Any, ...], dict[str, Any]], str | None] | None = None) ‑> ~_F | Callable[[~_F], ~_F] : Decorator that adds tool utilities like docstring augmentation and output limits.

Composes :func:airbyte_agent_sdk.translation.translate_exceptions for runtime wrapping (sync/async branch + output-size check + framework signal translation + optional internal retry loop), and adds connector-specific docstring augmentation on top of it.

Usage: @mcp.tool() @ZendeskSupportConnector.tool_utils async def execute(entity: str, action: str, params: dict): ...

@mcp.tool() @ZendeskSupportConnector.tool_utils(update_docstring=False, max_output_chars=None) async def execute(entity: str, action: str, params: dict): ...

@mcp.tool() @ZendeskSupportConnector.tool_utils(framework="pydantic_ai", internal_retries=2) async def execute(entity: str, action: str, params: dict): ...

Args: update_docstring: When True, append connector capabilities to doc. max_output_chars: Max serialized output size before raising. Use None to disable. framework: One of "pydantic_ai" | "langchain" | "openai_agents" | "mcp". Defaults to None → auto-detect by attempting each framework's canonical import in order. Explicit always wins. internal_retries: How many transient runtime failures (429/5xx, network, timeout) to retry silently before surfacing. Default 0. Forwarded to :func:airbyte_agent_sdk.translation.translate_exceptions. should_internal_retry: Optional predicate (error, args, kwargs) -> bool further restricting which retryable errors are safe for this specific tool. Forwarded to :func:airbyte_agent_sdk.translation.translate_exceptions. exhausted_runtime_failure_message: Optional callback (error, args, kwargs) -> str | None. Invoked after internal retries are exhausted OR were skipped via should_internal_retry returning False. Forwarded to :func:airbyte_agent_sdk.translation.translate_exceptions.

Instance variables

connector_id: str | None : Get the connector/source ID (only available in hosted mode).

Returns: The connector ID if in hosted mode, None if in local mode.

Methods

check(self) ‑> airbyte_agent_sdk.connectors.zendesk_support.models.ZendeskSupportCheckResult : Perform a health check to verify connectivity and credentials.

Executes a lightweight list operation (limit=1) to validate that the connector can communicate with the API and credentials are valid.

Returns: ZendeskSupportCheckResult with status ("healthy" or "unhealthy") and optional error message

Example: result = await connector.check() if result.status == "healthy": print("Connection verified!") else: print(f"Check failed: {result.error}")

close(self) : Close the connector and release resources.

entity_schema(self, entity: str) ‑> dict[str, typing.Any] | None : Get the JSON schema for an entity.

Args: entity: Entity name (e.g., "contacts", "companies")

Returns: JSON schema dict describing the entity structure, or None if not found.

Example: schema = connector.entity_schema("contacts") if schema: print(f"Contact properties: {list(schema.get('properties', {}).keys())}")

execute(self, entity: str, action: "Literal['list', 'create', 'get', 'update', 'download', 'context_store_search']", params: Mapping[str, Any] | None = None) ‑> Any : Execute an entity operation with full type safety.

This is the recommended interface for blessed connectors as it:

Uses the same signature as non-blessed connectors
Provides full IDE autocomplete for entity/action/params
Makes migration from generic to blessed connectors seamless

Args: entity: Entity name (e.g., "customers") action: Operation action (e.g., "create", "get", "list") params: Operation parameters (typed based on entity+action)

Returns: Typed response based on the operation

Example: customer = await connector.execute( entity="customers", action="get", params={"id": "cus_123"} )

list_entities(self) ‑> list[dict[str, typing.Any]] : Get structured data about available entities, actions, and parameters.

Returns a list of entity descriptions with:

entity_name: Name of the entity (e.g., "contacts", "deals")
description: Entity description from the first endpoint
available_actions: List of actions (e.g., ["list", "get", "create"])
parameters: Dict mapping action -> list of parameter dicts

Example: entities = connector.list_entities() for entity in entities: print(f"{entity['entity_name']}: {entity['available_actions']}")

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Hosted mode with explicit connector_id (no lookup needed)

Hosted mode with lookup by workspace_name

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Ancestors (in MRO)

Ancestors (in MRO)

Ancestors (in MRO)

Class variables

Ancestors (in MRO)

Class variables

Ancestors (in MRO)

Class variables

Ancestors (in MRO)

Class variables

Ancestors (in MRO)

Class variables

Ancestors (in MRO)

Class variables

Ancestors (in MRO)

Class variables

Ancestors (in MRO)

Class variables

Ancestors (in MRO)

Class variables

Ancestors (in MRO)

Class variables

Ancestors (in MRO)

Class variables

Ancestors (in MRO)

Class variables

Ancestors (in MRO)

Class variables

Ancestors (in MRO)

Class variables

Ancestors (in MRO)

Class variables

Ancestors (in MRO)

Class variables

Ancestors (in MRO)

Class variables

Ancestors (in MRO)

Class variables

Ancestors (in MRO)

Class variables

Ancestors (in MRO)

Class variables

Ancestors (in MRO)

Class variables

Class variables

Static methods

Instance variables

Methods