# pip install "pinecone[grpc]"
from pinecone.grpc import PineconeGRPC as Pinecone
pc = Pinecone(api_key='API_KEY')
pc.describe_collection(name="tiny-collection")
{
"name": "tiny-collection",
"size": 3126700,
"status": "Ready",
"dimension": 3,
"vector_count": 99,
"environment": "us-east1-gcp"
}Backups
Describe a collection
This operation gets a description of a collection.
Serverless indexes do not support collections.
GET
/
collections
/
{collection_name}
# pip install "pinecone[grpc]"
from pinecone.grpc import PineconeGRPC as Pinecone
pc = Pinecone(api_key='API_KEY')
pc.describe_collection(name="tiny-collection")
{
"name": "tiny-collection",
"size": 3126700,
"status": "Ready",
"dimension": 3,
"vector_count": 99,
"environment": "us-east1-gcp"
}# pip install "pinecone[grpc]"
from pinecone.grpc import PineconeGRPC as Pinecone
pc = Pinecone(api_key='API_KEY')
pc.describe_collection(name="tiny-collection")
Authorizations
Path Parameters
The name of the collection to be described.
Response
Configuration information and status of the collection.
The CollectionModel describes the configuration and status of a Pinecone collection.
The name of the collection.
Example:
"example-collection"
The status of the collection.
Available options:
Initializing, Ready, Terminating Example:
"Initializing"
The environment where the collection is hosted.
Example:
"us-east1-gcp"
The size of the collection in bytes.
Example:
10000000
The dimension of the vectors stored in each record held in the collection.
Required range:
1 <= x <= 2000Example:
1536
The number of records stored in the collection.
Example:
120000
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