## List Spreadsheet Jobs `sheets.list(SheetListParams**kwargs) -> SyncPaginatedCursor[SheetsJob]` **get** `/api/v1/sheets/jobs` List spreadsheet parsing jobs. ### Parameters - `configuration_id: Optional[str]` Filter by saved configuration ID - `created_at_on_or_after: Optional[Union[str, datetime, null]]` Include items created at or after this timestamp (inclusive) - `created_at_on_or_before: Optional[Union[str, datetime, null]]` Include items created at or before this timestamp (inclusive) - `include_results: Optional[bool]` - `job_ids: Optional[Sequence[str]]` Filter by specific job IDs - `organization_id: Optional[str]` - `page_size: Optional[int]` - `page_token: Optional[str]` - `project_id: Optional[str]` - `status: Optional[Literal["CANCELLED", "ERROR", "PARTIAL_SUCCESS", 2 more]]` Filter by job status - `"CANCELLED"` - `"ERROR"` - `"PARTIAL_SUCCESS"` - `"PENDING"` - `"SUCCESS"` ### Returns - `class SheetsJob: …` A spreadsheet parsing job. - `id: str` The ID of the job - `configuration: SheetsParsingConfig` Configuration applied to the parsing job (inline or resolved from a saved preset). - `extraction_range: Optional[str]` A1 notation of the range to extract a single region from. If None, the entire sheet is used. - `flatten_hierarchical_tables: Optional[bool]` Return a flattened dataframe when a detected table is recognized as hierarchical. - `generate_additional_metadata: Optional[bool]` Deprecated: controlled by `tier`. Whether to generate additional metadata (title, description) for each extracted region. Honored only on `agentic`. - `include_hidden_cells: Optional[bool]` Whether to include hidden cells when extracting regions from the spreadsheet. - `sheet_names: Optional[Sequence[str]]` The names of the sheets to extract regions from. If empty, all sheets will be processed. - `specialization: Optional[str]` Deprecated: controlled by `tier`. Optional specialization mode for domain-specific extraction. Supported values: 'financial-standard', 'financial-enhanced', 'financial-precise'. Default None uses the general-purpose pipeline. Honored only on `agentic`. - `table_merge_sensitivity: Optional[Literal["strong", "weak"]]` Deprecated: controlled by `tier`. Influences how likely similar-looking regions are merged into a single table. Honored only on `agentic`. - `"strong"` - `"weak"` - `tier: Optional[Literal["agentic", "cost_effective"]]` Spreadsheet extraction tier. `cost_effective` uses the rule-based/ML-only pipeline; `agentic` uses the full pipeline. - `"agentic"` - `"cost_effective"` - `use_experimental_processing: Optional[bool]` Deprecated: controlled by `tier`. Enables experimental processing. Honored only on `agentic`. - `created_at: str` When the job was created - `file_id: Optional[str]` The ID of the input file - `project_id: str` The ID of the project - `status: Literal["CANCELLED", "ERROR", "PARTIAL_SUCCESS", 2 more]` The status of the parsing job - `"CANCELLED"` - `"ERROR"` - `"PARTIAL_SUCCESS"` - `"PENDING"` - `"SUCCESS"` - `updated_at: str` When the job was last updated - `user_id: str` The ID of the user - `config: Optional[SheetsParsingConfig]` Configuration for spreadsheet parsing and region extraction - `configuration_id: Optional[str]` The saved product configuration ID used at create time, if any. - `errors: Optional[List[str]]` Any errors encountered - `file: Optional[File]` Schema for a file. - `id: str` Unique identifier - `name: str` - `project_id: str` The ID of the project that the file belongs to - `created_at: Optional[datetime]` Creation datetime - `data_source_id: Optional[str]` The ID of the data source that the file belongs to - `expires_at: Optional[datetime]` The expiration date for the file. Files past this date can be deleted. - `external_file_id: Optional[str]` The ID of the file in the external system - `file_size: Optional[int]` Size of the file in bytes - `file_type: Optional[str]` File type (e.g. pdf, docx, etc.) - `last_modified_at: Optional[datetime]` The last modified time of the file - `permission_info: Optional[Dict[str, Union[Dict[str, object], List[object], str, 3 more]]]` Permission information for the file - `Dict[str, object]` - `List[object]` - `str` - `float` - `bool` - `purpose: Optional[str]` The intended purpose of the file (e.g., 'user_data', 'parse', 'extract', 'split', 'classify') - `resource_info: Optional[Dict[str, Union[Dict[str, object], List[object], str, 3 more]]]` Resource information for the file - `Dict[str, object]` - `List[object]` - `str` - `float` - `bool` - `updated_at: Optional[datetime]` Update datetime - `metadata_state_transitions: Optional[Dict[str, object]]` Per-status entry timestamps. Returned only when requested via `?expand=metadata_state_transitions`. - `parameters: Optional[Parameters]` Job-time parameters such as webhook configurations. - `webhook_configurations: Optional[List[ParametersWebhookConfiguration]]` Webhook configurations for job status notifications. - `webhook_events: Optional[List[Literal["classify.cancelled", "classify.error", "classify.partial_success", 25 more]]]` Events to subscribe to (e.g. 'parse.success', 'extract.error'). If null, all events are delivered. - `"classify.cancelled"` - `"classify.error"` - `"classify.partial_success"` - `"classify.pending"` - `"classify.running"` - `"classify.success"` - `"extract.cancelled"` - `"extract.error"` - `"extract.partial_success"` - `"extract.pending"` - `"extract.success"` - `"parse.cancelled"` - `"parse.error"` - `"parse.partial_success"` - `"parse.pending"` - `"parse.running"` - `"parse.success"` - `"sheets.cancelled"` - `"sheets.error"` - `"sheets.partial_success"` - `"sheets.pending"` - `"sheets.success"` - `"split.cancelled"` - `"split.error"` - `"split.pending"` - `"split.processing"` - `"split.success"` - `"unmapped_event"` - `webhook_headers: Optional[Dict[str, str]]` Custom HTTP headers sent with each webhook request (e.g. auth tokens) - `webhook_output_format: Optional[str]` Response format sent to the webhook: 'string' (default) or 'json' - `webhook_signing_secret: Optional[str]` Shared signing secret used to sign webhook deliveries. When set, each request includes an HMAC-SHA256 signature of the request body in the 'LC-Signature' header (value 'sha256='). Recompute the HMAC over the raw request body with this secret to verify the delivery is authentic. - `webhook_url: Optional[str]` URL to receive webhook POST notifications - `regions: Optional[List[Region]]` All extracted regions (populated when job is complete) - `location: str` Location of the region in the spreadsheet - `region_type: str` Type of the extracted region - `sheet_name: str` Worksheet name where region was found - `description: Optional[str]` Generated description for the region - `region_id: Optional[str]` Unique identifier for this region within the file - `title: Optional[str]` Generated title for the region - `success: Optional[bool]` Whether the job completed successfully - `worksheet_metadata: Optional[List[WorksheetMetadata]]` Metadata for each processed worksheet (populated when job is complete) - `sheet_name: str` Name of the worksheet - `description: Optional[str]` Generated description of the worksheet - `title: Optional[str]` Generated title for the worksheet ### Example ```python import os from llama_cloud import LlamaCloud client = LlamaCloud( api_key=os.environ.get("LLAMA_CLOUD_API_KEY"), # This is the default and can be omitted ) page = client.sheets.list() page = page.items[0] print(page.id) ``` #### Response ```json { "items": [ { "id": "id", "configuration": { "extraction_range": "extraction_range", "flatten_hierarchical_tables": true, "generate_additional_metadata": true, "include_hidden_cells": true, "sheet_names": [ "string" ], "specialization": "specialization", "table_merge_sensitivity": "strong", "tier": "agentic", "use_experimental_processing": true }, "created_at": "created_at", "file_id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "project_id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "status": "CANCELLED", "updated_at": "updated_at", "user_id": "user_id", "config": { "extraction_range": "extraction_range", "flatten_hierarchical_tables": true, "generate_additional_metadata": true, "include_hidden_cells": true, "sheet_names": [ "string" ], "specialization": "specialization", "table_merge_sensitivity": "strong", "tier": "agentic", "use_experimental_processing": true }, "configuration_id": "configuration_id", "errors": [ "string" ], "file": { "id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "name": "x", "project_id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "created_at": "2019-12-27T18:11:19.117Z", "data_source_id": "182bd5e5-6e1a-4fe4-a799-aa6d9a6ab26e", "expires_at": "2019-12-27T18:11:19.117Z", "external_file_id": "external_file_id", "file_size": 0, "file_type": "x", "last_modified_at": "2019-12-27T18:11:19.117Z", "permission_info": { "foo": { "foo": "bar" } }, "purpose": "purpose", "resource_info": { "foo": { "foo": "bar" } }, "updated_at": "2019-12-27T18:11:19.117Z" }, "metadata_state_transitions": { "foo": "bar" }, "parameters": { "webhook_configurations": [ { "webhook_events": [ "parse.success", "parse.error" ], "webhook_headers": { "Authorization": "Bearer sk-..." }, "webhook_output_format": "json", "webhook_signing_secret": "whsec_...", "webhook_url": "https://example.com/webhooks/llamacloud" } ] }, "regions": [ { "location": "location", "region_type": "region_type", "sheet_name": "sheet_name", "description": "description", "region_id": "region_id", "title": "title" } ], "success": true, "worksheet_metadata": [ { "sheet_name": "sheet_name", "description": "description", "title": "title" } ] } ], "next_page_token": "next_page_token", "total_size": 0 } ```