POST
/
describe_index_stats
# pip install pinecone-client[grpc]
from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")
index = pc.Index("example-index")

index.describe_index_stats()
{
  "namespaces": {
    "": {
      "vectorCount": 50000
    },
    "example-namespace-2": {
      "vectorCount": 30000
    }
  },
  "dimension": 1024,
  "index_fullness": 0.4
}
# pip install pinecone-client[grpc]
from pinecone.grpc import PineconeGRPC as Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")
index = pc.Index("example-index")

index.describe_index_stats()

Authorizations

Api-Key
string
headerrequired

An API Key is required to call Pinecone APIs. Get yours from the console.

Body

application/json
filter
object

If this parameter is present, the operation only returns statistics for vectors that satisfy the filter. See Filter with metadata.

Serverless indexes do not support filtering describe_index_stats by metadata.

Response

200 - application/json
namespaces
object

A mapping for each namespace in the index from the namespace name to a summary of its contents. If a metadata filter expression is present, the summary will reflect only vectors matching that expression.

dimension
integer

The dimension of the indexed vectors.

indexFullness
number

The fullness of the index, regardless of whether a metadata filter expression was passed. The granularity of this metric is 10%.

Serverless indexes scale automatically as needed, so index fullness is relevant only for pod-based indexes.

The index fullness result may be inaccurate during pod resizing; to get the status of a pod resizing process, use describe_index.

totalVectorCount
integer

The total number of vectors in the index, regardless of whether a metadata filter expression was passed