airbyte-destination-pgvector 0.1.7

Airbyte destination implementation for PGVector.

PGVector Destination

This is the repository for the PGVector destination connector, written in Python. For information about how to use this connector within Airbyte, see the documentation.

Local development

Prerequisites

To iterate on this connector, make sure to complete this prerequisites section.

Minimum Python version required = 3.9.0

Installing the connector

From this connector directory, run:

poetry install --with dev.

Create credentials

If you are a community contributor, follow the instructions in the documentation to generate the necessary credentials. Then create a file secrets/config.json conforming to the destination_pgvector/spec.json file. Note that the secrets directory is gitignored by default, so there is no danger of accidentally checking in sensitive information. See integration_tests/sample_config.json for a sample config file.

If you are an Airbyte core member, copy the credentials in Lastpass under the secret name destination pgvector test creds and place them into secrets/config.json.

Locally running the connector

poetry run python main.py spec
poetry run python main.py check --config secrets/config.json
cat examples/messages.jsonl | poetry run python main.py write --config secrets/config.json --catalog examples/configured_catalog.json

Locally running the connector docker image

Use airbyte-ci to build your connector

The Airbyte way of building this connector is to use our airbyte-ci tool. You can follow install instructions here. Then running the following command will build your connector:

airbyte-ci connectors --name destination-pgvector build

Once the command is done, you will find your connector image in your local docker registry: airbyte/destination-pgvector:dev.

Customizing our build process

When contributing on our connector you might need to customize the build process to add a system dependency or set an env var. You can customize our build process by adding a build_customization.py module to your connector. This module should contain a pre_connector_install and post_connector_install async function that will mutate the base image and the connector container respectively. It will be imported at runtime by our build process and the functions will be called if they exist.

Here is an example of a build_customization.py module:

from __future__ import annotations

from typing import TYPE_CHECKING

if TYPE_CHECKING:
    # Feel free to check the dagger documentation for more information on the Container object and its methods.
    # https://dagger-io.readthedocs.io/en/sdk-python-v0.6.4/
    from dagger import Container


async def pre_connector_install(base_image_container: Container) -> Container:
    return await base_image_container.with_env_variable("MY_PRE_BUILD_ENV_VAR", "my_pre_build_env_var_value")

async def post_connector_install(connector_container: Container) -> Container:
    return await connector_container.with_env_variable("MY_POST_BUILD_ENV_VAR", "my_post_build_env_var_value")

Build your own connector image

This connector is built using our dynamic built process in airbyte-ci. The base image used to build it is defined within the metadata.yaml file under the connectorBuildOptions. The build logic is defined using Dagger here. It does not rely on a Dockerfile.

If you would like to patch our connector and build your own a simple approach would be to:

1. Create your own Dockerfile based on the latest version of the connector image.

FROM airbyte/destination-pgvector:latest

COPY . ./airbyte/integration_code
RUN pip install ./airbyte/integration_code

# The entrypoint and default env vars are already set in the base image
# ENV AIRBYTE_ENTRYPOINT "python /airbyte/integration_code/main.py"
# ENTRYPOINT ["python", "/airbyte/integration_code/main.py"]

Please use this as an example. This is not optimized.

2. Build your image:

docker build -t airbyte/destination-pgvector:dev .
# Running the spec command against your patched connector
docker run airbyte/destination-pgvector:dev spec

Run

Then run any of the connector commands as follows:

docker run --rm airbyte/destination-pgvector:dev spec
docker run --rm -v $(pwd)/secrets:/secrets airbyte/destination-pgvector:dev check --config /secrets/config.json
# messages.jsonl is a file containing line-separated JSON representing AirbyteMessages
cat messages.jsonl | docker run --rm -v $(pwd)/secrets:/secrets -v $(pwd)/integration_tests:/integration_tests airbyte/destination-pgvector:dev write --config /secrets/config.json --catalog /integration_tests/configured_catalog.json

Testing

You can run our full test suite locally using airbyte-ci:

airbyte-ci connectors --name=destination-pgvector test

Unit Tests

To run unit tests locally, from the connector directory run:

poetry run pytest -s unit_tests

Integration Tests

There are two types of integration tests: Acceptance Tests (Airbyte's test suite for all destination connectors) and custom integration tests (which are specific to this connector).

To run integration tests locally, make sure you have a secrets/config.json as explained above, and then run:

poetry run pytest -s integration_tests

Customizing acceptance Tests

Customize acceptance-test-config.yml file to configure tests. See Connector Acceptance Tests for more information. If your connector requires to create or destroy resources for use during acceptance tests create fixtures for it and place them inside integration_tests/acceptance.py.

Using airbyte-ci to run tests

See airbyte-ci documentation

Dependency Management

All of your dependencies should go in pyproject.toml

• required for your connector to work need to go to [tool.poetry.dependencies] list.
• required for the testing need to go to [tool.poetry.group.dev.dependencies] list

Publishing a new version of the connector

You've checked out the repo, implemented a million dollar feature, and you're ready to share your changes with the world. Now what?

1. Make sure your changes are passing unit and integration tests.
2. Bump the connector version in Dockerfile -- just increment the value of the LABEL io.airbyte.version appropriately (we use SemVer).
3. Create a Pull Request.
4. Pat yourself on the back for being an awesome contributor.
5. Someone from Airbyte will take a look at your PR and iterate with you to merge it into master.