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POST
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describe_index_stats
from pinecone import Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")

# To get the unique host for an index, 
# see https://docs.pinecone.io/guides/manage-data/target-an-index
index = pc.Index(host="INDEX_HOST")

index.describe_index_stats()

Documentation Index

Fetch the complete documentation index at: https://docs.pinecone.io/llms.txt

Use this file to discover all available pages before exploring further.

from pinecone import Pinecone

pc = Pinecone(api_key="YOUR_API_KEY")

# To get the unique host for an index, 
# see https://docs.pinecone.io/guides/manage-data/target-an-index
index = pc.Index(host="INDEX_HOST")

index.describe_index_stats()

Authorizations

​
Api-Key
string
header
required

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

Headers

​
X-Pinecone-Api-Version
string
default:202601-alpha
required

Required date-based version header

Body

application/json

The request for the describe_index_stats operation.

​
filter
object

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

Serverless indexes do not support filtering describe_index_stats by metadata.

Response

A successful response.

The response for the describe_index_stats operation.

​
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<int64>

The dimension of the indexed vectors. Not specified if sparse index.

Example:

1024

​
indexFullness
number<float>

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.

Example:

0.4

​
totalVectorCount
integer<int64>

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

Example:

80000

​
metric
string

The metric used to measure similarity.

Example:

"cosine"

​
vectorType
string

The type of vectors stored in the index.

Example:

"dense"

​
memory_fullness
number<float>

The amount of memory used by a dedicated index

​
storage_fullness
number<float>

The amount of storage used by a dedicated index