> ## Documentation Index > Fetch the complete documentation index at: https://actianvectorai-docs-low-effort-fixes.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # Scroll points > Paginate through all points in a collection. The response includes a `next_page_offset` cursor that you pass as `offset` in subsequent requests to retrieve the next page. Useful for exporting data, iterating large datasets, or processing points in batches. ## OpenAPI ````yaml post /collections/{collection_name}/points/scroll openapi: 3.0.3 info: title: Actian VectorAI DB - Search API description: Vector similarity search operations for Actian VectorAI DB. version: 1.0.0 contact: name: Actian Corporation url: https://www.actian.com servers: - url: http://localhost:6575 description: Local development server (REST API) - url: https://api.vectorai.actian.com description: Production server security: - bearerAuth: [] tags: - name: Search description: Vector similarity search operations - name: Scroll description: Pagination and iteration - name: Count description: Counting operations paths: /collections/{collection_name}/points/scroll: post: tags: - Scroll summary: Scroll points description: >- Paginate through all points in a collection. The response includes a `next_page_offset` cursor that you pass as `offset` in subsequent requests to retrieve the next page. Useful for exporting data, iterating large datasets, or processing points in batches. operationId: scroll_points parameters: - name: collection_name in: path required: true schema: type: string description: The name of the collection to scroll through. requestBody: required: true content: application/json: schema: type: object properties: limit: type: integer default: 100 example: 10 description: >- Maximum number of points to return per page. Must be greater than 0. For example, `20` returns 20 points per page. Defaults to 100. offset: oneOf: - type: integer - type: string nullable: true example: 3 description: >- Cursor from a previous scroll response. Pass the `next_page_offset` value to fetch the next page. Omit or set to null for the first page. filter: type: object description: Optional filter conditions to narrow the scrolled results. with_payload: type: boolean default: true example: true description: Whether to include payload metadata in the response. with_vector: type: boolean default: false example: false description: Whether to include vector data in the response. examples: first_page: summary: First page value: limit: 10 with_payload: true with_vector: false next_page: summary: Next page value: limit: 10 offset: 3 with_payload: true with_vector: false with_filter: summary: Filtered scroll value: limit: 10 filter: must: - key: group match: value: g0 with_payload: true with_vector: false responses: '200': description: Scroll results content: application/json: schema: type: object properties: usage: type: object properties: hardware: type: object nullable: true description: >- Hardware resource counters for the operation, including CPU, payload I/O, payload index I/O, and vector I/O metrics. time: type: number format: double example: 0.000129652 description: Time spent to process this request, in seconds. status: type: string example: ok description: Operation status. result: type: object properties: points: type: array description: Array of point objects in this page. items: type: object properties: id: type: integer example: 1 description: The point's unique identifier. payload: type: object nullable: true example: category: A value: 10 description: >- Payload metadata, or null if `with_payload` is false. vector: type: array nullable: true items: type: number example: null description: Vector data, or null if `with_vector` is false. next_page_offset: oneOf: - type: integer - type: string nullable: true example: 4 description: >- Cursor for the next page. Pass this as `offset` in the next request. Null when there are no more pages. example: usage: hardware: null time: 0.000129652 status: ok result: next_page_offset: 4 points: - id: 1 payload: category: A value: 10 vector: null - id: 2 payload: category: B value: 20 vector: null - id: 3 payload: category: C value: 30 vector: null 4XX: description: Error response content: application/json: schema: $ref: '#/components/schemas/ErrorResponse' x-codeSamples: - lang: Python label: Manual scroll source: | from actian_vectorai_client import VectorAIClient with VectorAIClient("localhost:6574") as client: # Manual cursor-based scroll offset = None page = 0 total_scrolled = 0 while True: batch, next_offset = client.points.scroll( "my_collection", limit=10, offset=offset ) page += 1 total_scrolled += len(batch) print(f"Page {page}: {len(batch)} points") if next_offset is None or len(batch) == 0: break offset = next_offset print(f"Total scrolled: {total_scrolled}") - lang: Python label: Scroll all (convenience) source: | from actian_vectorai_client import VectorAIClient with VectorAIClient("localhost:6574") as client: # Automatically paginate through all points all_points = client.points.scroll_all( "my_collection", batch_size=15 ) print(f"Retrieved {len(all_points)} points total") - lang: Python label: Filtered scroll source: > from actian_vectorai_client import VectorAIClient, Field, FilterBuilder with VectorAIClient("localhost:6574") as client: # Scroll with filter payload_filter = FilterBuilder().must(Field("group").eq("g0")).build() filtered, _ = client.points.scroll( "my_collection", filter=payload_filter, limit=100 ) print(f"Found {len(filtered)} points in group g0") - lang: JavaScript label: Scroll points source: | import { VectorAIClient } from '@actian/vectorai-client'; const client = new VectorAIClient('localhost:6574'); let offset = undefined; let page = 0; while (true) { const result = await client.points.scroll('my_collection', { limit: 10, offset, withPayload: true, }); page++; console.log(`Page ${page}: ${result.points.length} points`); if (!result.nextPageOffset) break; offset = result.nextPageOffset; } client.close(); - lang: cURL label: Scroll source: > curl -X POST "http://localhost:6575/collections/my_collection/points/scroll" \ -H "Content-Type: application/json" \ -H 'Authorization: Bearer ' \ -d '{ "limit": 10, "with_payload": true, "with_vector": false }' components: schemas: ErrorResponse: type: object properties: status: type: object properties: error: type: string time: type: number format: double description: Time spent to process this request, in seconds. securitySchemes: bearerAuth: type: http scheme: bearer bearerFormat: JWT description: Admin JWT or access token for authenticating requests to VectorAI DB. ````