Scroll points | Qdrant | API Reference

Returns all points in a page-by-page manner. By default, all resulting points are sorted by {id}. To query the next page specify the last {id} in the offset field. Additionally, you can specify filters and sorting options.

Authentication

api-keystring

API Key authentication via header

Path parameters

collection_namestringRequired

Name of the collection to retrieve from

Query parameters

consistencyinteger or enumOptional

Define read consistency guarantees for the operation

timeoutintegerOptional>=1

If set, overrides global timeout for this request. Unit is seconds.

Request

Pagination and filter parameters

shard_keystring or uint64 or list of strings or uint64s or anyOptional

Specify in which shards to look for the points, if not specified - look in all shards

offsetuint64 or string or anyOptional

Start ID to read points from.

limitinteger or nullOptional>=1

Page size. Default: 10

filterobject or anyOptional

Look only for points which satisfies this conditions. If not provided - all points.

with_payloadboolean or list of strings or object or anyOptional

Select which payload to return with the response. Default is true.

with_vectorboolean or list of stringsOptional

Options for specifying which vector to include

order_bystring or object or anyOptional

Order the records by a payload field.

Response

successful operation

usageobject or any or null

timedouble or null

Time spent to process this request

statusstring or null

resultobject or null

Result of the points read request

1	from qdrant_client import QdrantClient, models
2
3	client = QdrantClient(url="http://localhost:6333")
4
5	client.scroll(
6	collection_name="{collection_name}",
7	scroll_filter=models.Filter(
8	must=[
9	models.FieldCondition(key="color", match=models.MatchValue(value="red")),
10	]
11	),
12	limit=1,
13	with_payload=True,
14	with_vectors=False,
15	)

1	{
2	"usage": {
3	"cpu": 1,
4	"payload_io_read": 1,
5	"payload_io_write": 1,
6	"payload_index_io_read": 1,
7	"payload_index_io_write": 1,
8	"vector_io_read": 1,
9	"vector_io_write": 1
10	},
11	"time": 0.002,
12	"status": "ok",
13	"result": {
14	"points": [
15	{
16	"id": 40,
17	"payload": {
18	"city": "London",
19	"color": "green"
20	},
21	"vector": [
22	0.875,
23	0.140625,
24	0.897599995136261
25	],
26	"shard_key": "region_1"
27	},
28	{
29	"id": 41,
30	"payload": {
31	"city": "Paris",
32	"color": "red"
33	},
34	"vector": [
35	0.75,
36	0.640625,
37	0.8945000171661377
38	],
39	"shard_key": "region_1"
40	}
41	],
42	"next_page_offset": 42
43	}
44	}