airbyte-source-microsoft-dataverse 0.1.32

Source implementation for Microsoft Dataverse.

Microsoft-Dataverse source connector

This is the repository for the Microsoft-Dataverse source connector, written in Python. For information about how to use this connector within Airbyte, see the documentation.

Local development

Prerequisites

• Python (~=3.9)
• Poetry (~=1.7) - installation instructions here

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 source_microsoft_dataverse/spec.yaml file. Note that any directory named secrets is gitignored across the entire Airbyte repo, so there is no danger of accidentally checking in sensitive information. See sample_files/sample_config.json for a sample config file.

Locally running the connector

poetry run source-microsoft-dataverse spec
poetry run source-microsoft-dataverse check --config secrets/config.json
poetry run source-microsoft-dataverse discover --config secrets/config.json
poetry run source-microsoft-dataverse read --config secrets/config.json --catalog sample_files/configured_catalog.json

Running unit tests

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

poetry run pytest unit_tests

Building the docker image

1. Install airbyte-ci
2. Run the following command to build the docker image:

airbyte-ci connectors --name=source-microsoft-dataverse build

An image will be available on your host with the tag airbyte/source-microsoft-dataverse:dev.

Running as a docker container

Then run any of the connector commands as follows:

docker run --rm airbyte/source-microsoft-dataverse:dev spec
docker run --rm -v $(pwd)/secrets:/secrets airbyte/source-microsoft-dataverse:dev check --config /secrets/config.json
docker run --rm -v $(pwd)/secrets:/secrets airbyte/source-microsoft-dataverse:dev discover --config /secrets/config.json
docker run --rm -v $(pwd)/secrets:/secrets -v $(pwd)/integration_tests:/integration_tests airbyte/source-microsoft-dataverse:dev read --config /secrets/config.json --catalog /integration_tests/configured_catalog.json

Running our CI test suite

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

airbyte-ci connectors --name=source-microsoft-dataverse test

Customizing acceptance Tests

Customize acceptance-test-config.yml file to configure acceptance 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.

Dependency Management

All of your dependencies should be managed via Poetry. To add a new dependency, run:

poetry add <package-name>

Please commit the changes to pyproject.toml and poetry.lock files.

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 our test suite: airbyte-ci connectors --name=source-microsoft-dataverse test
2. Bump the connector version (please follow semantic versioning for connectors):
   • bump the dockerImageTag value in in metadata.yaml
   • bump the version value in pyproject.toml
3. Make sure the metadata.yaml content is up to date.
4. Make sure the connector documentation and its changelog is up to date (docs/integrations/sources/microsoft-dataverse.md).
5. Create a Pull Request: use our PR naming conventions.
6. Pat yourself on the back for being an awesome contributor.
7. Someone from Airbyte will take a look at your PR and iterate with you to merge it into master.
8. Once your PR is merged, the new version of the connector will be automatically published to Docker Hub and our connector registry.