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Module airbyte_agent_sdk.connectors.pinterest.connector

Pinterest connector.

Classes​

AdAccountsQuery(connector: PinterestConnector) : Query class for AdAccounts entity operations.

Initialize query with connector reference.

Methods​

context_store_search(self, query: AdAccountsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.pinterest.models.AirbyteSearchResult[AdAccountsSearchData] : Search ad_accounts records from Airbyte cache.

This operation searches cached data from Airbyte syncs. Only available in hosted execution mode.

Available filter fields (AdAccountsSearchFilter):

  • country: Country associated with the ad account
  • created_time: Timestamp when the ad account was created (Unix seconds)
  • currency: Currency used for billing
  • id: Unique identifier for the ad account
  • name: Name of the ad account
  • owner: Owner details of the ad account
  • permissions: Permissions assigned to the ad account
  • updated_time: Timestamp when the ad account was last updated (Unix seconds)

Args: query: Filter and sort conditions. Supports operators like eq, neq, gt, gte, lt, lte, in, like, fuzzy, keyword, not, and, or. Example: {"filter": {"eq": {"status": "active"}}} limit: Maximum results to return (default 1000) cursor: Pagination cursor from previous response's meta.cursor fields: Field paths to include in results. Each path is a list of keys for nested access. Example: [["id"], ["user", "name"]] returns id and user.name fields.

Returns: AdAccountsSearchResult with typed records, pagination metadata, and optional search metadata

Raises: NotImplementedError: If called in local execution mode

get(self, ad_account_id: str, **kwargs) ‑> airbyte_agent_sdk.connectors.pinterest.models.AdAccount : Get an ad account by ID.

Args: ad_account_id: Unique identifier of the ad account. **kwargs: Additional parameters

Returns: AdAccount

list(self, page_size: int | None = None, bookmark: str | None = None, include_shared_accounts: bool | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.pinterest.models.PinterestExecuteResultWithMeta[list[AdAccount], AdAccountsListResultMeta] : Get a list of the ad accounts that the authenticated user has access to.

Args: page_size: Maximum number of items to include in a single page of the response. bookmark: Cursor value for paginating through results. include_shared_accounts: Include shared ad accounts. **kwargs: Additional parameters

Returns: AdAccountsListResult

AdGroupsQuery(connector: PinterestConnector) : Query class for AdGroups entity operations.

Initialize query with connector reference.

Methods​

context_store_search(self, query: AdGroupsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.pinterest.models.AirbyteSearchResult[AdGroupsSearchData] : Search ad_groups records from Airbyte cache.

This operation searches cached data from Airbyte syncs. Only available in hosted execution mode.

Available filter fields (AdGroupsSearchFilter):

  • ad_account_id: Ad account ID
  • auto_targeting_enabled: Whether auto targeting is enabled
  • bid_in_micro_currency: Bid in microcurrency
  • bid_strategy_type: Bid strategy type
  • billable_event: Billable event type
  • budget_in_micro_currency: Budget in microcurrency
  • budget_type: Budget type
  • campaign_id: Parent campaign ID
  • conversion_learning_mode_type: oCPM learn mode type
  • created_time: Creation timestamp (Unix seconds)
  • end_time: End time (Unix seconds)
  • feed_profile_id: Feed profile ID
  • id: Ad group ID
  • lifetime_frequency_cap: Max impressions per user in 30 days
  • name: Ad group name
  • optimization_goal_metadata: Optimization goal metadata
  • pacing_delivery_type: Pacing delivery type
  • placement_group: Placement group
  • start_time: Start time (Unix seconds)
  • status: Entity status
  • summary_status: Summary status
  • targeting_spec: Targeting specifications
  • tracking_urls: Third-party tracking URLs
  • type_: Always 'adgroup'
  • updated_time: Last update timestamp (Unix seconds)

Args: query: Filter and sort conditions. Supports operators like eq, neq, gt, gte, lt, lte, in, like, fuzzy, keyword, not, and, or. Example: {"filter": {"eq": {"status": "active"}}} limit: Maximum results to return (default 1000) cursor: Pagination cursor from previous response's meta.cursor fields: Field paths to include in results. Each path is a list of keys for nested access. Example: [["id"], ["user", "name"]] returns id and user.name fields.

Returns: AdGroupsSearchResult with typed records, pagination metadata, and optional search metadata

Raises: NotImplementedError: If called in local execution mode

list(self, ad_account_id: str, page_size: int | None = None, bookmark: str | None = None, entity_statuses: list[str] | None = None, order: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.pinterest.models.PinterestExecuteResultWithMeta[list[AdGroup], AdGroupsListResultMeta] : Get a list of ad groups in the specified ad account.

Args: ad_account_id: Unique identifier of the ad account. page_size: Maximum number of items to include in a single page of the response. bookmark: Cursor value for paginating through results. entity_statuses: Filter by entity status. order: Sort order. **kwargs: Additional parameters

Returns: AdGroupsListResult

AdsQuery(connector: PinterestConnector) : Query class for Ads entity operations.

Initialize query with connector reference.

Methods​

context_store_search(self, query: AdsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.pinterest.models.AirbyteSearchResult[AdsSearchData] : Search ads records from Airbyte cache.

This operation searches cached data from Airbyte syncs. Only available in hosted execution mode.

Available filter fields (AdsSearchFilter):

  • ad_account_id: Ad account ID
  • ad_group_id: Ad group ID
  • android_deep_link: Android deep link
  • campaign_id: Campaign ID
  • carousel_android_deep_links: Carousel Android deep links
  • carousel_destination_urls: Carousel destination URLs
  • carousel_ios_deep_links: Carousel iOS deep links
  • click_tracking_url: Click tracking URL
  • collection_items_destination_url_template: Template URL for collection items
  • created_time: Creation timestamp (Unix seconds)
  • creative_type: Creative type
  • destination_url: Main destination URL
  • id: Unique ad ID
  • ios_deep_link: iOS deep link
  • is_pin_deleted: Whether the original pin is deleted
  • is_removable: Whether the ad is removable
  • lead_form_id: Lead form ID
  • name: Ad name
  • pin_id: Associated pin ID
  • rejected_reasons: Rejection reasons
  • rejection_labels: Rejection text labels
  • review_status: Review status
  • status: Entity status
  • summary_status: Summary status
  • tracking_urls: Third-party tracking URLs
  • type_: Always 'pinpromotion'
  • updated_time: Last update timestamp (Unix seconds)
  • view_tracking_url: View tracking URL

Args: query: Filter and sort conditions. Supports operators like eq, neq, gt, gte, lt, lte, in, like, fuzzy, keyword, not, and, or. Example: {"filter": {"eq": {"status": "active"}}} limit: Maximum results to return (default 1000) cursor: Pagination cursor from previous response's meta.cursor fields: Field paths to include in results. Each path is a list of keys for nested access. Example: [["id"], ["user", "name"]] returns id and user.name fields.

Returns: AdsSearchResult with typed records, pagination metadata, and optional search metadata

Raises: NotImplementedError: If called in local execution mode

list(self, ad_account_id: str, page_size: int | None = None, bookmark: str | None = None, entity_statuses: list[str] | None = None, order: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.pinterest.models.PinterestExecuteResultWithMeta[list[Ad], AdsListResultMeta] : Get a list of ads in the specified ad account.

Args: ad_account_id: Unique identifier of the ad account. page_size: Maximum number of items to include in a single page of the response. bookmark: Cursor value for paginating through results. entity_statuses: Filter by entity status. order: Sort order. **kwargs: Additional parameters

Returns: AdsListResult

AudiencesQuery(connector: PinterestConnector) : Query class for Audiences entity operations.

Initialize query with connector reference.

Methods​

context_store_search(self, query: AudiencesSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.pinterest.models.AirbyteSearchResult[AudiencesSearchData] : Search audiences records from Airbyte cache.

This operation searches cached data from Airbyte syncs. Only available in hosted execution mode.

Available filter fields (AudiencesSearchFilter):

  • ad_account_id: Ad account ID
  • audience_type: Audience type
  • created_timestamp: Creation time (Unix seconds)
  • description: Audience description
  • id: Unique audience identifier
  • name: Audience name
  • rule: Audience targeting rules
  • size: Estimated audience size
  • status: Audience status
  • type_: Always 'audience'
  • updated_timestamp: Last update time (Unix seconds)

Args: query: Filter and sort conditions. Supports operators like eq, neq, gt, gte, lt, lte, in, like, fuzzy, keyword, not, and, or. Example: {"filter": {"eq": {"status": "active"}}} limit: Maximum results to return (default 1000) cursor: Pagination cursor from previous response's meta.cursor fields: Field paths to include in results. Each path is a list of keys for nested access. Example: [["id"], ["user", "name"]] returns id and user.name fields.

Returns: AudiencesSearchResult with typed records, pagination metadata, and optional search metadata

Raises: NotImplementedError: If called in local execution mode

list(self, ad_account_id: str, page_size: int | None = None, bookmark: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.pinterest.models.PinterestExecuteResultWithMeta[list[Audience], AudiencesListResultMeta] : Get a list of audiences for the specified ad account.

Args: ad_account_id: Unique identifier of the ad account. page_size: Maximum number of items to include in a single page of the response. bookmark: Cursor value for paginating through results. **kwargs: Additional parameters

Returns: AudiencesListResult

BoardPinsQuery(connector: PinterestConnector) : Query class for BoardPins entity operations.

Initialize query with connector reference.

Methods​

context_store_search(self, query: BoardPinsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.pinterest.models.AirbyteSearchResult[BoardPinsSearchData] : Search board_pins records from Airbyte cache.

This operation searches cached data from Airbyte syncs. Only available in hosted execution mode.

Available filter fields (BoardPinsSearchFilter):

  • alt_text: Alternate text for accessibility
  • board_id: Board the pin belongs to
  • board_owner: Board owner info
  • board_section_id: Section within the board
  • created_at: Timestamp when the pin was created
  • creative_type: Creative type
  • description: Pin description
  • dominant_color: Dominant color from the pin image
  • has_been_promoted: Whether the pin has been promoted
  • id: Unique pin identifier
  • is_owner: Whether the current user is the owner
  • is_standard: Whether the pin is a standard pin
  • link: URL link associated with the pin
  • media: Media content
  • parent_pin_id: Parent pin ID if this is a repin
  • pin_metrics: Pin metrics data
  • title: Pin title

Args: query: Filter and sort conditions. Supports operators like eq, neq, gt, gte, lt, lte, in, like, fuzzy, keyword, not, and, or. Example: {"filter": {"eq": {"status": "active"}}} limit: Maximum results to return (default 1000) cursor: Pagination cursor from previous response's meta.cursor fields: Field paths to include in results. Each path is a list of keys for nested access. Example: [["id"], ["user", "name"]] returns id and user.name fields.

Returns: BoardPinsSearchResult with typed records, pagination metadata, and optional search metadata

Raises: NotImplementedError: If called in local execution mode

list(self, board_id: str, page_size: int | None = None, bookmark: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.pinterest.models.PinterestExecuteResultWithMeta[list[BoardPin], BoardPinsListResultMeta] : Get a list of pins on a specific board.

Args: board_id: Unique identifier of the board. page_size: Maximum number of items to include in a single page of the response. bookmark: Cursor value for paginating through results. **kwargs: Additional parameters

Returns: BoardPinsListResult

BoardSectionsQuery(connector: PinterestConnector) : Query class for BoardSections entity operations.

Initialize query with connector reference.

Methods​

context_store_search(self, query: BoardSectionsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.pinterest.models.AirbyteSearchResult[BoardSectionsSearchData] : Search board_sections records from Airbyte cache.

This operation searches cached data from Airbyte syncs. Only available in hosted execution mode.

Available filter fields (BoardSectionsSearchFilter):

  • id: Unique identifier for the board section
  • name: Name of the board section

Args: query: Filter and sort conditions. Supports operators like eq, neq, gt, gte, lt, lte, in, like, fuzzy, keyword, not, and, or. Example: {"filter": {"eq": {"status": "active"}}} limit: Maximum results to return (default 1000) cursor: Pagination cursor from previous response's meta.cursor fields: Field paths to include in results. Each path is a list of keys for nested access. Example: [["id"], ["user", "name"]] returns id and user.name fields.

Returns: BoardSectionsSearchResult with typed records, pagination metadata, and optional search metadata

Raises: NotImplementedError: If called in local execution mode

list(self, board_id: str, page_size: int | None = None, bookmark: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.pinterest.models.PinterestExecuteResultWithMeta[list[BoardSection], BoardSectionsListResultMeta] : Get a list of sections for a specific board.

Args: board_id: Unique identifier of the board. page_size: Maximum number of items to include in a single page of the response. bookmark: Cursor value for paginating through results. **kwargs: Additional parameters

Returns: BoardSectionsListResult

BoardsQuery(connector: PinterestConnector) : Query class for Boards entity operations.

Initialize query with connector reference.

Methods​

context_store_search(self, query: BoardsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.pinterest.models.AirbyteSearchResult[BoardsSearchData] : Search boards records from Airbyte cache.

This operation searches cached data from Airbyte syncs. Only available in hosted execution mode.

Available filter fields (BoardsSearchFilter):

  • board_pins_modified_at: Timestamp when pins on the board were last modified
  • collaborator_count: Number of collaborators
  • created_at: Timestamp when the board was created
  • description: Board description
  • follower_count: Number of followers
  • id: Unique identifier for the board
  • media: Media content for the board
  • name: Board name
  • owner: Board owner details
  • pin_count: Number of pins on the board
  • privacy: Board privacy setting

Args: query: Filter and sort conditions. Supports operators like eq, neq, gt, gte, lt, lte, in, like, fuzzy, keyword, not, and, or. Example: {"filter": {"eq": {"status": "active"}}} limit: Maximum results to return (default 1000) cursor: Pagination cursor from previous response's meta.cursor fields: Field paths to include in results. Each path is a list of keys for nested access. Example: [["id"], ["user", "name"]] returns id and user.name fields.

Returns: BoardsSearchResult with typed records, pagination metadata, and optional search metadata

Raises: NotImplementedError: If called in local execution mode

get(self, board_id: str, **kwargs) ‑> airbyte_agent_sdk.connectors.pinterest.models.Board : Get a board by ID.

Args: board_id: Unique identifier of the board. **kwargs: Additional parameters

Returns: Board

list(self, page_size: int | None = None, bookmark: str | None = None, privacy: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.pinterest.models.PinterestExecuteResultWithMeta[list[Board], BoardsListResultMeta] : Get a list of the boards owned by the authenticated user.

Args: page_size: Maximum number of items to include in a single page of the response. bookmark: Cursor value for paginating through results. privacy: Filter by board privacy setting. **kwargs: Additional parameters

Returns: BoardsListResult

CampaignsQuery(connector: PinterestConnector) : Query class for Campaigns entity operations.

Initialize query with connector reference.

Methods​

context_store_search(self, query: CampaignsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.pinterest.models.AirbyteSearchResult[CampaignsSearchData] : Search campaigns records from Airbyte cache.

This operation searches cached data from Airbyte syncs. Only available in hosted execution mode.

Available filter fields (CampaignsSearchFilter):

  • ad_account_id: Ad account ID
  • created_time: Creation timestamp (Unix seconds)
  • daily_spend_cap: Maximum daily spend in microcurrency
  • end_time: End timestamp (Unix seconds)
  • id: Campaign ID
  • is_campaign_budget_optimization: Whether CBO is enabled
  • is_flexible_daily_budgets: Whether flexible daily budgets are enabled
  • lifetime_spend_cap: Maximum lifetime spend in microcurrency
  • name: Campaign name
  • objective_type: Campaign objective type
  • order_line_id: Order line ID on invoice
  • start_time: Start timestamp (Unix seconds)
  • status: Entity status
  • summary_status: Summary status
  • tracking_urls: Third-party tracking URLs
  • type_: Always 'campaign'
  • updated_time: Last update timestamp (Unix seconds)

Args: query: Filter and sort conditions. Supports operators like eq, neq, gt, gte, lt, lte, in, like, fuzzy, keyword, not, and, or. Example: {"filter": {"eq": {"status": "active"}}} limit: Maximum results to return (default 1000) cursor: Pagination cursor from previous response's meta.cursor fields: Field paths to include in results. Each path is a list of keys for nested access. Example: [["id"], ["user", "name"]] returns id and user.name fields.

Returns: CampaignsSearchResult with typed records, pagination metadata, and optional search metadata

Raises: NotImplementedError: If called in local execution mode

list(self, ad_account_id: str, page_size: int | None = None, bookmark: str | None = None, entity_statuses: list[str] | None = None, order: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.pinterest.models.PinterestExecuteResultWithMeta[list[Campaign], CampaignsListResultMeta] : Get a list of campaigns in the specified ad account.

Args: ad_account_id: Unique identifier of the ad account. page_size: Maximum number of items to include in a single page of the response. bookmark: Cursor value for paginating through results. entity_statuses: Filter by entity status. order: Sort order. **kwargs: Additional parameters

Returns: CampaignsListResult

CatalogsFeedsQuery(connector: PinterestConnector) : Query class for CatalogsFeeds entity operations.

Initialize query with connector reference.

Methods​

context_store_search(self, query: CatalogsFeedsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.pinterest.models.AirbyteSearchResult[CatalogsFeedsSearchData] : Search catalogs_feeds records from Airbyte cache.

This operation searches cached data from Airbyte syncs. Only available in hosted execution mode.

Available filter fields (CatalogsFeedsSearchFilter):

  • catalog_type: Type of catalog
  • created_at: Timestamp when the feed was created
  • default_availability: Default availability status
  • default_country: Default country
  • default_currency: Default currency for pricing
  • default_locale: Default locale
  • format: Feed format
  • id: Unique feed identifier
  • location: URL where the feed is available
  • name: Feed name
  • preferred_processing_schedule: Preferred processing schedule
  • status: Feed status
  • updated_at: Timestamp when the feed was last updated

Args: query: Filter and sort conditions. Supports operators like eq, neq, gt, gte, lt, lte, in, like, fuzzy, keyword, not, and, or. Example: {"filter": {"eq": {"status": "active"}}} limit: Maximum results to return (default 1000) cursor: Pagination cursor from previous response's meta.cursor fields: Field paths to include in results. Each path is a list of keys for nested access. Example: [["id"], ["user", "name"]] returns id and user.name fields.

Returns: CatalogsFeedsSearchResult with typed records, pagination metadata, and optional search metadata

Raises: NotImplementedError: If called in local execution mode

list(self, page_size: int | None = None, bookmark: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.pinterest.models.PinterestExecuteResultWithMeta[list[CatalogsFeed], CatalogsFeedsListResultMeta] : Get a list of catalog feeds for the authenticated user.

Args: page_size: Maximum number of items to include in a single page of the response. bookmark: Cursor value for paginating through results. **kwargs: Additional parameters

Returns: CatalogsFeedsListResult

CatalogsProductGroupsQuery(connector: PinterestConnector) : Query class for CatalogsProductGroups entity operations.

Initialize query with connector reference.

Methods​

context_store_search(self, query: CatalogsProductGroupsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.pinterest.models.AirbyteSearchResult[CatalogsProductGroupsSearchData] : Search catalogs_product_groups records from Airbyte cache.

This operation searches cached data from Airbyte syncs. Only available in hosted execution mode.

Available filter fields (CatalogsProductGroupsSearchFilter):

  • created_at: Creation timestamp (Unix seconds)
  • description: Product group description
  • feed_id: Associated feed ID
  • id: Unique product group identifier
  • is_featured: Whether the product group is featured
  • name: Product group name
  • status: Product group status
  • type_: Product group type
  • updated_at: Last update timestamp (Unix seconds)

Args: query: Filter and sort conditions. Supports operators like eq, neq, gt, gte, lt, lte, in, like, fuzzy, keyword, not, and, or. Example: {"filter": {"eq": {"status": "active"}}} limit: Maximum results to return (default 1000) cursor: Pagination cursor from previous response's meta.cursor fields: Field paths to include in results. Each path is a list of keys for nested access. Example: [["id"], ["user", "name"]] returns id and user.name fields.

Returns: CatalogsProductGroupsSearchResult with typed records, pagination metadata, and optional search metadata

Raises: NotImplementedError: If called in local execution mode

list(self, page_size: int | None = None, bookmark: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.pinterest.models.PinterestExecuteResultWithMeta[list[CatalogsProductGroup], CatalogsProductGroupsListResultMeta] : Get a list of catalog product groups for the authenticated user.

Args: page_size: Maximum number of items to include in a single page of the response. bookmark: Cursor value for paginating through results. **kwargs: Additional parameters

Returns: CatalogsProductGroupsListResult

CatalogsQuery(connector: PinterestConnector) : Query class for Catalogs entity operations.

Initialize query with connector reference.

Methods​

context_store_search(self, query: CatalogsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.pinterest.models.AirbyteSearchResult[CatalogsSearchData] : Search catalogs records from Airbyte cache.

This operation searches cached data from Airbyte syncs. Only available in hosted execution mode.

Available filter fields (CatalogsSearchFilter):

  • catalog_type: Type of catalog
  • created_at: Timestamp when the catalog was created
  • id: Unique catalog identifier
  • name: Catalog name
  • updated_at: Timestamp when the catalog was last updated

Args: query: Filter and sort conditions. Supports operators like eq, neq, gt, gte, lt, lte, in, like, fuzzy, keyword, not, and, or. Example: {"filter": {"eq": {"status": "active"}}} limit: Maximum results to return (default 1000) cursor: Pagination cursor from previous response's meta.cursor fields: Field paths to include in results. Each path is a list of keys for nested access. Example: [["id"], ["user", "name"]] returns id and user.name fields.

Returns: CatalogsSearchResult with typed records, pagination metadata, and optional search metadata

Raises: NotImplementedError: If called in local execution mode

list(self, page_size: int | None = None, bookmark: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.pinterest.models.PinterestExecuteResultWithMeta[list[Catalog], CatalogsListResultMeta] : Get a list of catalogs for the authenticated user.

Args: page_size: Maximum number of items to include in a single page of the response. bookmark: Cursor value for paginating through results. **kwargs: Additional parameters

Returns: CatalogsListResult

ConversionTagsQuery(connector: PinterestConnector) : Query class for ConversionTags entity operations.

Initialize query with connector reference.

Methods​

context_store_search(self, query: ConversionTagsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.pinterest.models.AirbyteSearchResult[ConversionTagsSearchData] : Search conversion_tags records from Airbyte cache.

This operation searches cached data from Airbyte syncs. Only available in hosted execution mode.

Available filter fields (ConversionTagsSearchFilter):

  • ad_account_id: Ad account ID
  • code_snippet: JavaScript code snippet for tracking
  • configs: Tag configurations
  • enhanced_match_status: Enhanced match status
  • id: Unique conversion tag identifier
  • last_fired_time_ms: Timestamp of last event fired (milliseconds)
  • name: Conversion tag name
  • status: Status
  • version: Version number

Args: query: Filter and sort conditions. Supports operators like eq, neq, gt, gte, lt, lte, in, like, fuzzy, keyword, not, and, or. Example: {"filter": {"eq": {"status": "active"}}} limit: Maximum results to return (default 1000) cursor: Pagination cursor from previous response's meta.cursor fields: Field paths to include in results. Each path is a list of keys for nested access. Example: [["id"], ["user", "name"]] returns id and user.name fields.

Returns: ConversionTagsSearchResult with typed records, pagination metadata, and optional search metadata

Raises: NotImplementedError: If called in local execution mode

list(self, ad_account_id: str, page_size: int | None = None, bookmark: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.pinterest.models.PinterestExecuteResultWithMeta[list[ConversionTag], ConversionTagsListResultMeta] : Get a list of conversion tags for the specified ad account.

Args: ad_account_id: Unique identifier of the ad account. page_size: Maximum number of items to include in a single page of the response. bookmark: Cursor value for paginating through results. **kwargs: Additional parameters

Returns: ConversionTagsListResult

CustomerListsQuery(connector: PinterestConnector) : Query class for CustomerLists entity operations.

Initialize query with connector reference.

Methods​

context_store_search(self, query: CustomerListsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.pinterest.models.AirbyteSearchResult[CustomerListsSearchData] : Search customer_lists records from Airbyte cache.

This operation searches cached data from Airbyte syncs. Only available in hosted execution mode.

Available filter fields (CustomerListsSearchFilter):

  • ad_account_id: Associated ad account ID
  • created_time: Creation time (Unix seconds)
  • id: Unique customer list identifier
  • name: Customer list name
  • num_batches: Total number of list updates
  • num_removed_user_records: Count of removed user records
  • num_uploaded_user_records: Count of uploaded user records
  • status: Status
  • type_: Always 'customerlist'
  • updated_time: Last update time (Unix seconds)

Args: query: Filter and sort conditions. Supports operators like eq, neq, gt, gte, lt, lte, in, like, fuzzy, keyword, not, and, or. Example: {"filter": {"eq": {"status": "active"}}} limit: Maximum results to return (default 1000) cursor: Pagination cursor from previous response's meta.cursor fields: Field paths to include in results. Each path is a list of keys for nested access. Example: [["id"], ["user", "name"]] returns id and user.name fields.

Returns: CustomerListsSearchResult with typed records, pagination metadata, and optional search metadata

Raises: NotImplementedError: If called in local execution mode

list(self, ad_account_id: str, page_size: int | None = None, bookmark: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.pinterest.models.PinterestExecuteResultWithMeta[list[CustomerList], CustomerListsListResultMeta] : Get a list of customer lists for the specified ad account.

Args: ad_account_id: Unique identifier of the ad account. page_size: Maximum number of items to include in a single page of the response. bookmark: Cursor value for paginating through results. **kwargs: Additional parameters

Returns: CustomerListsListResult

KeywordsQuery(connector: PinterestConnector) : Query class for Keywords entity operations.

Initialize query with connector reference.

Methods​

context_store_search(self, query: KeywordsSearchQuery, limit: int | None = None, cursor: str | None = None, fields: list[list[str]] | None = None) ‑> airbyte_agent_sdk.connectors.pinterest.models.AirbyteSearchResult[KeywordsSearchData] : Search keywords records from Airbyte cache.

This operation searches cached data from Airbyte syncs. Only available in hosted execution mode.

Available filter fields (KeywordsSearchFilter):

  • archived: Whether the keyword is archived
  • bid: Bid value in microcurrency
  • id: Unique keyword identifier
  • match_type: Match type
  • parent_id: Parent entity ID
  • parent_type: Parent entity type
  • type_: Always 'keyword'
  • value: Keyword text value

Args: query: Filter and sort conditions. Supports operators like eq, neq, gt, gte, lt, lte, in, like, fuzzy, keyword, not, and, or. Example: {"filter": {"eq": {"status": "active"}}} limit: Maximum results to return (default 1000) cursor: Pagination cursor from previous response's meta.cursor fields: Field paths to include in results. Each path is a list of keys for nested access. Example: [["id"], ["user", "name"]] returns id and user.name fields.

Returns: KeywordsSearchResult with typed records, pagination metadata, and optional search metadata

Raises: NotImplementedError: If called in local execution mode

list(self, ad_account_id: str, ad_group_id: str, page_size: int | None = None, bookmark: str | None = None, **kwargs) ‑> airbyte_agent_sdk.connectors.pinterest.models.PinterestExecuteResultWithMeta[list[Keyword], KeywordsListResultMeta] : Get a list of keywords for the specified ad account. Requires an ad_group_id filter.

Args: ad_account_id: Unique identifier of the ad account. ad_group_id: Ad group ID to filter keywords by. page_size: Maximum number of items to include in a single page of the response. bookmark: Cursor value for paginating through results. **kwargs: Additional parameters

Returns: KeywordsListResult

PinterestConnector(auth_config: PinterestAuthConfig | AirbyteAuthConfig | BaseModel | None = None, on_token_refresh: Any | None = None) : Type-safe Pinterest API connector.

Auto-generated from OpenAPI specification with full type safety.

Initialize a new pinterest connector instance.

Supports both local and hosted execution modes:

  • Local mode: Provide connector-specific auth config (e.g., PinterestAuthConfig)
  • 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 = PinterestConnector(auth_config=PinterestAuthConfig(refresh_token="...", client_id="...", client_secret="..."))

Hosted mode with explicit connector_id (no lookup needed)

connector = PinterestConnector( 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 = PinterestConnector( 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: "'PinterestAuthConfig' | None" = None, server_side_oauth_secret_id: str | None = None, name: str | None = None, replication_config: "'PinterestReplicationConfig' | 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 PinterestConnector 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 PinterestConnector.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=PinterestAuthConfig(refresh_token="...", client_id="...", client_secret="..."), )

With replication config (required for this connector):

connector = await PinterestConnector.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=PinterestAuthConfig(refresh_token="...", client_id="...", client_secret="..."), replication_config=PinterestReplicationConfig(start_date="..."), )

With server-side OAuth:

connector = await PinterestConnector.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=PinterestReplicationConfig(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: "'PinterestReplicationConfig' | 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 PinterestConnector.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 Pinterest Source", replication_config=PinterestReplicationConfig(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() @PinterestConnector.tool_utils async def execute(entity: str, action: str, params: dict): ...

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

@mcp.tool() @PinterestConnector.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 PinterestConnector.create(...) print(f"Created connector: {connector.connector_id}")

Methods​

check(self) ‑> airbyte_agent_sdk.connectors.pinterest.models.PinterestCheckResult : 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: PinterestCheckResult 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']}")

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