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Module airbyte_agent_sdk.connectors.google_search_console

Google-Search-Console connector for Airbyte SDK.

Auto-generated from OpenAPI specification.

Sub-modules​

  • airbyte_agent_sdk.connectors.google_search_console.connector
  • airbyte_agent_sdk.connectors.google_search_console.connector_model
  • airbyte_agent_sdk.connectors.google_search_console.models
  • airbyte_agent_sdk.connectors.google_search_console.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.google_search_console.models.AirbyteSearchResult[SearchAnalyticsAllFieldsSearchData]
  • airbyte_agent_sdk.connectors.google_search_console.models.AirbyteSearchResult[SearchAnalyticsByCountrySearchData]
  • airbyte_agent_sdk.connectors.google_search_console.models.AirbyteSearchResult[SearchAnalyticsByDateSearchData]
  • airbyte_agent_sdk.connectors.google_search_console.models.AirbyteSearchResult[SearchAnalyticsByDeviceSearchData]
  • airbyte_agent_sdk.connectors.google_search_console.models.AirbyteSearchResult[SearchAnalyticsByPageSearchData]
  • airbyte_agent_sdk.connectors.google_search_console.models.AirbyteSearchResult[SearchAnalyticsByQuerySearchData]
  • airbyte_agent_sdk.connectors.google_search_console.models.AirbyteSearchResult[SitemapsSearchData]
  • airbyte_agent_sdk.connectors.google_search_console.models.AirbyteSearchResult[SitesSearchData]

Class variables​

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

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

model_config : The type of the None singleton.

SearchAnalyticsAllFieldsSearchResult(**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.google_search_console.models.AirbyteSearchResult
  • pydantic.main.BaseModel
  • typing.Generic

SearchAnalyticsByCountrySearchResult(**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.google_search_console.models.AirbyteSearchResult
  • pydantic.main.BaseModel
  • typing.Generic

SearchAnalyticsByDateSearchResult(**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.google_search_console.models.AirbyteSearchResult
  • pydantic.main.BaseModel
  • typing.Generic

SearchAnalyticsByDeviceSearchResult(**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.google_search_console.models.AirbyteSearchResult
  • pydantic.main.BaseModel
  • typing.Generic

SearchAnalyticsByPageSearchResult(**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.google_search_console.models.AirbyteSearchResult
  • pydantic.main.BaseModel
  • typing.Generic

SearchAnalyticsByQuerySearchResult(**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.google_search_console.models.AirbyteSearchResult
  • pydantic.main.BaseModel
  • typing.Generic

SitemapsSearchResult(**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.google_search_console.models.AirbyteSearchResult
  • pydantic.main.BaseModel
  • typing.Generic

SitesSearchResult(**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.google_search_console.models.AirbyteSearchResult
  • pydantic.main.BaseModel
  • typing.Generic

GoogleSearchConsoleAuthConfig(**data: Any) : OAuth2 Authentication

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​

client_id: str : The client ID of your Google Search Console developer application.

client_secret: str : The client secret of your Google Search Console developer application.

model_config : The type of the None singleton.

refresh_token: str : The refresh token for obtaining new access tokens.

GoogleSearchConsoleConnector(auth_config: GoogleSearchConsoleAuthConfig | AirbyteAuthConfig | BaseModel | None = None, on_token_refresh: Any | None = None) : Type-safe Google-Search-Console API connector.

Auto-generated from OpenAPI specification with full type safety.

Initialize a new google-search-console connector instance.

Supports both local and hosted execution modes:

  • Local mode: Provide connector-specific auth config (e.g., GoogleSearchConsoleAuthConfig)
  • 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) Examples:

Local mode (direct API calls)

connector = GoogleSearchConsoleConnector(auth_config=GoogleSearchConsoleAuthConfig(client_id="...", client_secret="...", refresh_token="..."))

Hosted mode with explicit connector_id (no lookup needed)

connector = GoogleSearchConsoleConnector( 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 = GoogleSearchConsoleConnector( 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​

create(*, airbyte_config: AirbyteAuthConfig, auth_config: "'GoogleSearchConsoleAuthConfig' | None" = None, server_side_oauth_secret_id: str | None = None, name: str | None = None, replication_config: "'GoogleSearchConsoleReplicationConfig' | None" = None, source_template_id: str | None = None) : Create a new hosted connector on Airbyte Cloud.

This factory method:

  1. Creates a source on Airbyte Cloud with the provided credentials
  2. Returns a connector configured with the new connector_id

Supports two authentication modes:

  1. Direct credentials: Provide auth_config with typed credentials
  2. Server-side OAuth: Provide server_side_oauth_secret_id from OAuth flow

Args: airbyte_config: Airbyte hosted auth config with client credentials and workspace_name. Optionally include organization_id for multi-org request routing. auth_config: Typed auth config. Required unless using server_side_oauth_secret_id. server_side_oauth_secret_id: OAuth secret ID from get_consent_url redirect. When provided, auth_config is not required. name: Optional source name (defaults to connector name + workspace_name) replication_config: Typed replication settings. Required for connectors with x-airbyte-replication-config (REPLICATION mode sources). source_template_id: Source template ID. Required when organization has multiple source templates for this connector type.

Returns: A GoogleSearchConsoleConnector instance configured in hosted mode

Raises: ValueError: If neither or both auth_config and server_side_oauth_secret_id provided

Example:

Create a new hosted connector with API key auth

connector = await GoogleSearchConsoleConnector.create( airbyte_config=AirbyteAuthConfig( workspace_name="my-workspace", organization_id="00000000-0000-0000-0000-000000000123", airbyte_client_id="client_abc", airbyte_client_secret="secret_xyz", ), auth_config=GoogleSearchConsoleAuthConfig(client_id="...", client_secret="...", refresh_token="..."), )

With replication config (required for this connector):

connector = await GoogleSearchConsoleConnector.create( airbyte_config=AirbyteAuthConfig( workspace_name="my-workspace", organization_id="00000000-0000-0000-0000-000000000123", airbyte_client_id="client_abc", airbyte_client_secret="secret_xyz", ), auth_config=GoogleSearchConsoleAuthConfig(client_id="...", client_secret="...", refresh_token="..."), replication_config=GoogleSearchConsoleReplicationConfig(site_urls="...", start_date="..."), )

With server-side OAuth:

connector = await GoogleSearchConsoleConnector.create( airbyte_config=AirbyteAuthConfig( workspace_name="my-workspace", organization_id="00000000-0000-0000-0000-000000000123", airbyte_client_id="client_abc", airbyte_client_secret="secret_xyz", ), server_side_oauth_secret_id="airbyte_oauth_...secret...", replication_config=GoogleSearchConsoleReplicationConfig(site_urls="...", start_date="..."), )

Use the connector

result = await connector.execute("entity", "list", {})

get_consent_url(*, airbyte_config: AirbyteAuthConfig, redirect_url: str, name: str | None = None, replication_config: "'GoogleSearchConsoleReplicationConfig' | None" = None, source_template_id: str | None = None) : Initiate server-side OAuth flow with auto-source creation.

Returns a consent URL where the end user should be redirected to grant access. After completing consent, the source is automatically created and the user is redirected to your redirect_url with a connector_id query parameter.

Args: airbyte_config: Airbyte hosted auth config with client credentials and workspace_name. Optionally include organization_id for multi-org request routing. redirect_url: URL where users will be redirected after OAuth consent. After consent, user arrives at: redirect_url?connector_id=... name: Optional name for the source. Defaults to connector name + workspace_name. replication_config: Typed replication settings. Merged with OAuth credentials. source_template_id: Source template ID. Required when organization has multiple source templates for this connector type.

Returns: The OAuth consent URL

Example: consent_url = await GoogleSearchConsoleConnector.get_consent_url( airbyte_config=AirbyteAuthConfig( workspace_name="my-workspace", organization_id="00000000-0000-0000-0000-000000000123", airbyte_client_id="client_abc", airbyte_client_secret="secret_xyz", ), redirect_url="https://myapp.com/oauth/callback", name="My Google-Search-Console Source", replication_config=GoogleSearchConsoleReplicationConfig(site_urls="...", start_date="..."), )

Redirect user to: consent_url

After consent, user arrives at: https://myapp.com/oauth/callback?connector_id=...

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() @GoogleSearchConsoleConnector.tool_utils async def execute(entity: str, action: str, params: dict): ...

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

@mcp.tool() @GoogleSearchConsoleConnector.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.

Example: connector = await GoogleSearchConsoleConnector.create(...) print(f"Created connector: {connector.connector_id}")

Methods​

check(self) ‑> airbyte_agent_sdk.connectors.google_search_console.models.GoogleSearchConsoleCheckResult : 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: GoogleSearchConsoleCheckResult 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', 'get', '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']}")

GoogleSearchConsoleReplicationConfig(**data: Any) : Replication Configuration - Settings for data replication from Google Search Console.

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​

model_config : The type of the None singleton.

site_urls: str : The URLs of the website property attached to your GSC account. Examples: https://example.com/ or sc-domain:example.com

start_date: str | None : UTC date in the format YYYY-MM-DD. Any data before this date will not be replicated.

SearchAnalyticsAllFieldsSearchData(**data: Any) : Search result data for search_analytics_all_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​

clicks: int | None : The number of times users clicked on the search result for a specific query

country: str | None : The country from which the search query originated

ctr: float | None : Click-through rate, calculated as clicks divided by impressions

date: str | None : The date when the search query occurred

device: str | None : The type of device used by the user (e.g., desktop, mobile)

impressions: int | None : The number of times a search result appeared in response to a query

model_config : The type of the None singleton.

page: str | None : The page URL that appeared in the search results

position: float | None : The average position of the search result on the search engine results page

query: str | None : The search query entered by the user

search_type: str | None : The type of search (e.g., web, image, video) that triggered the search result

site_url: str | None : The URL of the site from which the data originates

SearchAnalyticsByCountrySearchData(**data: Any) : Search result data for search_analytics_by_country 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​

clicks: int | None : The number of times users clicked on the search result for a specific country

country: str | None : The country for which the search analytics data is being reported

ctr: float | None : The click-through rate for a specific country

date: str | None : The date for which the search analytics data is being reported

impressions: int | None : The total number of times a search result was shown for a specific country

model_config : The type of the None singleton.

position: float | None : The average position at which the site's search result appeared for a specific country

search_type: str | None : The type of search for which the data is being reported

site_url: str | None : The URL of the site for which the search analytics data is being reported

SearchAnalyticsByDateSearchData(**data: Any) : Search result data for search_analytics_by_date 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​

clicks: int | None : The total number of clicks on the specific date

ctr: float | None : The click-through rate for the specific date

date: str | None : The date for which the search analytics data is being reported

impressions: int | None : The number of impressions on the specific date

model_config : The type of the None singleton.

position: float | None : The average position in search results for the specific date

search_type: str | None : The type of search query that generated the data

site_url: str | None : The URL of the site for which the search analytics data is being reported

SearchAnalyticsByDeviceSearchData(**data: Any) : Search result data for search_analytics_by_device 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​

clicks: int | None : The total number of clicks by device type

ctr: float | None : Click-through rate by device type

date: str | None : The date for which the search analytics data is provided

device: str | None : The type of device used by the user (e.g., desktop, mobile)

impressions: int | None : The total number of impressions by device type

model_config : The type of the None singleton.

position: float | None : The average position in search results by device type

search_type: str | None : The type of search performed

site_url: str | None : The URL of the site for which search analytics data is being provided

SearchAnalyticsByPageSearchData(**data: Any) : Search result data for search_analytics_by_page 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​

clicks: int | None : The number of clicks for a specific page

ctr: float | None : Click-through rate for the page

date: str | None : The date for which the search analytics data is reported

impressions: int | None : The number of impressions for the page

model_config : The type of the None singleton.

page: str | None : The URL of the specific page being analyzed

position: float | None : The average position at which the page appeared in search results

search_type: str | None : The type of search query that led to the page being displayed

site_url: str | None : The URL of the site for which the search analytics data is being reported

SearchAnalyticsByQuerySearchData(**data: Any) : Search result data for search_analytics_by_query 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​

clicks: int | None : The number of clicks for the specific query

ctr: float | None : The click-through rate for the specific query

date: str | None : The date for which the search analytics data is recorded

impressions: int | None : The number of impressions for the specific query

model_config : The type of the None singleton.

position: float | None : The average position for the specific query

query: str | None : The search query for which the data is recorded

search_type: str | None : The type of search result for the specific query

site_url: str | None : The URL of the site for which the search analytics data is captured

SitemapsSearchData(**data: Any) : Search result data for sitemaps 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​

contents: list[typing.Any] | None : Data related to the sitemap contents

errors: str | None : Errors encountered while processing the sitemaps

is_pending: bool | None : Flag indicating if the sitemap is pending for processing

is_sitemaps_index: bool | None : Flag indicating if the data represents a sitemap index

last_downloaded: str | None : Timestamp when the sitemap was last downloaded

last_submitted: str | None : Timestamp when the sitemap was last submitted

model_config : The type of the None singleton.

path: str | None : Path to the sitemap file

type_: str | None : Type of the sitemap

warnings: str | None : Warnings encountered while processing the sitemaps

SitesSearchData(**data: Any) : Search result data for sites 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​

model_config : The type of the None singleton.

permission_level: str | None : The user's permission level for the site (owner, full, restricted, etc.)

site_url: str | None : The URL of the site data being fetched

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