Python bindings for pgvecto.rs
Usage
Install from PyPI:
pip install pgvecto_rs
See the usage of SDK
Or use it as an extension of postgres clients:
SDK
Our SDK is designed to use the pgvecto.rs out-of-box. You can exploit the power of pgvecto.rs to do similarity search or retrieve with filters, without writing any SQL code.
Install dependencies:
pip install "pgvecto_rs[sdk]"
A minimal example:
from pgvecto_rs.sdk import PGVectoRs, Record
# Create a client
client = PGVectoRs(
db_url="postgresql+psycopg://postgres:mysecretpassword@localhost:5432/postgres",
table_name="example",
dimension=3,
)
try:
# Add some records
client.add_records(
[
Record.from_text("hello 1", [1, 2, 3]),
Record.from_text("hello 2", [1, 2, 4]),
]
)
# Search with default operator (sqrt_euclid).
# The results is sorted by distance
for rec, dis in client.search([1, 2, 5]):
print(rec.text)
print(dis)
finally:
# Clean up (i.e. drop the table)
client.drop()
Output:
hello 2
1.0
hello 1
4.0
See examples/sdk_example.py and tests/test_sdk.py for more examples.
SQLAlchemy
Install dependencies:
pip install "pgvecto_rs[sqlalchemy]"
Then write your code. See examples/sqlalchemy_example.py and tests/test_sqlalchemy.py for example.
All the operators include:
squared_euclidean_distancenegative_dot_product_distancenegative_cosine_distance
psycopg3
Install dependencies:
pip install "pgvecto_rs[psycopg3]"
Then write your code. See examples/psycopg_example.py and tests/test_psycopg.py for example.
Known issue:
- Can not check the length of an vector when inserting it into a table. See: #96.
Development
This package is managed by PDM.
Set up things:
pdm venv create
pdm use # select the venv inside the project path
pdm sync
Run lint:
pdm run format
pdm run fix
pdm run check
Run test in current environment:
pdm run test
Test
Tox is used to test the package locally.
Run test in all environment:
tox run