pinecone-client 3.0.0rc3

Pinecone client and SDK

pinecone-client

The Pinecone python client

For more information, see the docs at https://www.pinecone.io/docs/

Installation

Install a released version from pip:

pip3 install pinecone-client

Or the gRPC version of the client for tuning performance

pip3 install "pinecone-client[grpc]"

Or the latest development version:

pip3 install git+https://[e-mail]/pinecone-io/pinecone-python-client.git

Or a specific development version:

pip3 install git+https://[e-mail]/pinecone-io/pinecone-python-client.git
pip3 install git+https://[e-mail]/pinecone-io/pinecone-python-client.git@example-branch-name
pip3 install git+https://[e-mail]/pinecone-io/pinecone-python-client.git@259deff

Create a client

The following example creates an authenticated client.

import os
from pinecone import Pinecone

pc = Pinecone(api_key=os.environ.get('PINECONE_API_KEY'))

To use gRPC for interacting with an index, instantiate with PineconeGRPC

import os
from pinecone.grpc import PineconeGRPC

pc = PineconeGRPC(api_key=os.environ.get('PINECONE_API_KEY'))
# Functionality matches non-gRPC client
index = pc.Index('index-name')

Create an index

The following example creates an index without a metadata configuration. By default, Pinecone indexes all metadata.

from pinecone import Pinecone, PodSpec

pc = Pinecone(api_key='<<PINECONE_API_KEY>>')
pc.create_index("example-index", dimension=1536, metric="cosine", spec=PodSpec(environment='us-west-2', pod_type='p1.x1'))

The following example creates an index that only indexes the "color" metadata field. Queries against this index cannot filter based on any other metadata field.

from pinecone import Pinecone, PodSpec
pc = Pinecone(api_key='<<PINECONE_API_KEY>>')

metadata_config = {
    "indexed": ["color"]
}

pc.create_index(
    "example-index-2",
    dimension=1536,
    spec=PodSpec(environment='us-west-2', pod_type='p1.x1', metadata_config=metadata_config)
)

List indexes

The following example returns all indexes in your project.

from pinecone import Pinecone

pc = Pinecone(api_key='<<PINECONE_API_KEY>>')
for index in pc.list_indexes():
    print(index['name'])

Describe index

The following example returns information about the index example-index.

from pinecone import Pinecone

pc = Pinecone(api_key='<<PINECONE_API_KEY>>')

index_description = pc.describe_index("example-index")

Delete an index

The following example deletes example-index.

from pinecone import Pinecone

pc = Pinecone(api_key='<<PINECONE_API_KEY>>')

pc.delete_index("example-index")

Scale replicas

The following example changes the number of replicas for example-index.

from pinecone import Pinecone

pc = Pinecone(api_key='<<PINECONE_API_KEY>>')

new_number_of_replicas = 4
pc.configure_index("example-index", replicas=new_number_of_replicas)

Describe index statistics

The following example returns statistics about the index example-index.

from pinecone import Pinecone

pc = Pinecone(api_key='<<PINECONE_API_KEY>>')
index = pc.Index("example-index")

index_stats_response = index.describe_index_stats()

Upsert vectors

The following example upserts vectors to example-index.

from pinecone import Pinecone

pc = Pinecone(api_key='<<PINECONE_API_KEY>>')
index = pc.Index("example-index")

upsert_response = index.upsert(
    vectors=[
        ("vec1", [0.1, 0.2, 0.3, 0.4], {"genre": "drama"}),
        ("vec2", [0.2, 0.3, 0.4, 0.5], {"genre": "action"}),
    ],
    namespace="example-namespace"
)

Query an index

The following example queries the index example-index with metadata filtering.

from pinecone import Pinecone

pc = Pinecone(api_key='<<PINECONE_API_KEY>>')
index = pc.Index("example-index")

query_response = index.query(
    namespace="example-namespace",
    top_k=10,
    include_values=True,
    include_metadata=True,
    vector=[0.1, 0.2, 0.3, 0.4],
    filter={
        "genre": {"$in": ["comedy", "documentary", "drama"]}
    }
)

Delete vectors

The following example deletes vectors by ID.

from pinecone import Pinecone

pc = Pinecone(api_key='<<PINECONE_API_KEY>>')
index = pc.Index("example-index")

delete_response = index.delete(ids=["vec1", "vec2"], namespace="example-namespace")

Fetch vectors

The following example fetches vectors by ID.

from pinecone import Pinecone

pc = Pinecone(api_key='<<PINECONE_API_KEY>>')
index = pc.Index("example-index")

fetch_response = index.fetch(ids=["vec1", "vec2"], namespace="example-namespace")

Update vectors

The following example updates vectors by ID.

from pinecone import Pinecone

pc = Pinecone(api_key='<<PINECONE_API_KEY>>')
index = pc.Index("example-index")

update_response = index.update(
    id="vec1",
    values=[0.1, 0.2, 0.3, 0.4],
    set_metadata={"genre": "drama"},
    namespace="example-namespace"
)

Create collection

The following example creates the collection example-collection from example-index.

from pinecone import Pinecone

pc = Pinecone(api_key='<<PINECONE_API_KEY>>')

pc.create_collection("example-collection", "example-index")

List collections

The following example returns a list of the collections in the current project.

from pinecone import Pinecone

pc = Pinecone(api_key='<<PINECONE_API_KEY>>')

active_collections = pc.list_collections()

Describe a collection

The following example returns a description of the collection example-collection.

from pinecone import Pinecone

pc = Pinecone(api_key='<<PINECONE_API_KEY>>')

collection_description = pc.describe_collection("example-collection")

Delete a collection

The following example deletes the collection example-collection.

from pinecone import Pinecone

pc = Pinecone(api_key='<<PINECONE_API_KEY>>')

pc.delete_collection("example-collection")

Contributing

If you'd like to make a contribution, or get setup locally to develop the Pinecone python client, please see our contributing guide