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Contributing to DepthAI Nodes

It outlines our workflow and standards for contributing to this project.

Table of Contents

Developing parser

Parser should be developed so that it is consistent with other parsers. Check out other parsers to see the required structure. Additionally, pay attention to the naming of the parser's attributes. Check out Developer guide.

NOTE: When adding new features make sure that you extend the tests appropriately. Check out the Testing section for more information.

Pre-commit Hooks

We use pre-commit hooks to ensure code quality and consistency:

  1. Install pre-commit (see pre-commit.com).
  2. Clone the repository and run pre-commit install in the root directory.
  3. The pre-commit hook will now run automatically on git commit.
    • If the hook fails, it will print an error message and abort the commit.
    • It will also modify the files in-place to fix any issues it can.

Documentation

We use the Epytext markup language for documentation. To verify that your documentation is formatted correctly, follow these steps:

  1. Download get-docs.py script
  2. Run python3 get-docs.py luxonis_ml in the root directory.
    • If the script runs successfully and produces docs.json file, your documentation is formatted correctly.
    • NOTE: If the script fails, it might not give the specific error message. In that case, you can run the script for each file individually until you find the one that is causing the error.

Editor Support

  • PyCharm - built in support for generating epytext docstrings
  • Visual Studio Code - AI Docify extension offers support for epytext
  • NeoVim - vim-python-docstring supports epytext style

Testing

We have 3 types of tests:

  • Unit tests (tests/unittests)
  • Integration tests (tests/stability_tests)
  • End-to-end tests (tests/end_to_end)

All tests are located in the tests directory, each in its own subdirectory. Unit tests and integration tests are running on every PR while end-to-end tests are triggered on every push to the main branch, or when manually triggered. In the unit tests we check individual components (messages, parser's functions, etc.). In the integration tests we check if the parser is able to parse the output of the neural network, we have predefined NNData for each parser and expected output message and we check if the output message is correct. Lastly, in the end-to-end tests we check if the parser is running in the complete pipeline with camera, neural network, and parsers on real device.

While end-to-end tests require real device, integration tests and unit tests can be run without it.

Running unit tests

To run unit tests, first install dev dependencies:

pip install -r requirements-dev.txt

Then run the tests from the root directory:

pytest tests

Running integration tests

To run integration tests, first install dev dependencies:

pip install -r requirements-dev.txt

Then you will need access to our bucket to download the predefined NNData for each parser. You can get the credentials from the code owners. Export the credentials as environment variables:

export B2_APPLICATION_KEY=<your_application_key>
export B2_APPLICATION_KEY_ID=<your_application_key_id>

Then run the tests from the tests/stability_tests directory:

python main.py -all --download --duration 2

This will run the integration tests for two seconds for each parser. You can specify the duration with --duration flag.

Running end-to-end tests

To run end-to-end tests, first install dev dependencies:

pip install -r requirements-dev.txt

You will also need to specify the IP addresses of the RVC2 and RVC4 devices. To get the models you want to test on, you will need HubAI credentials.

export RVC2_IP=<your_rvc2_ip>
export RVC4_IP=<your_rvc4_ip>
export HUBAI_TEAM_SLUG=<your_hubai_team_slug>
export HUBAI_API_KEY=<your_hubai_api_key>

Then run the tests from the tests/end_to_end directory:

python main.py -all

This will run the end-to-end tests for all public models. You can specify the models with --model flag, --platform flag to specify the platform to test on and --depthai-nodes-version to specify the version of depthai-nodes to test on.

Making and Reviewing Changes

  1. Make changes in a new branch.
  2. Test your changes locally.
  3. Commit (pre-commit hook will run).
  4. Push to your branch and create a pull request. Always request a review from:
  5. Any other relevant team members can be added as reviewers as well.
  6. The team will review and merge your PR.