Installation Steps

HINA is available on PyPI and can be installed using pip, which will include the dependencies automatically: To ensure running in a working environment please make sure the python version >=3.9

pip install hina

For users who prefer installing dependencies manually, we provide a requirements.txt file on GitHub. To install HINA and its dependencies using this file:

git clone https://github.com/SHF-NAILResearchGroup/HINA.git
cd HINA
pip install -e .
pip install -r requirements.txt

HINA Dashboard APP is available to build and run locally with Docker:

git clone https://github.com/SHF-NAILResearchGroup/HINA.git
cd HINA
docker compose up --build

Then, open the web browser and navigate to http://localhost:8080 to access the HINA Dashboard.

Source Code and Discussion Channel

Available on Github, SHF-NAILResearchGroup/HINA. Please report bugs, issues and feature extensions there. We also have discussion channel available to discuss anything related to HINA:

Testing and Continuous Integration

HINA is equipped with automated testing on GitHub Actions to ensure that all functionalities work as expected. As part of CI/CD pipeline, this process helps maintain code quality and quickly catches any issues.

To run the tests manually, users need to clone the HINA GitHub repository.

  1. Clone the Repository: First, clone the HINA GitHub repository to access the Tests folder.

    git clone https://github.com/SHF-NAILResearchGroup/HINA.git
cd HINA

  2. Install the Required Packages: Ensure all dependencies, including pytest, are installed by running the following commands:

    pip install -r requirements.txt
pip install hina
pip install httpx
pip install pytest
hash -r  #Refresh shell's executable cache (needed if pytest was previously installed)

  3. Run the Tests: Use pytest to execute all tests cases in the HINA folder.

    pytest hina/

  4. View the Results: The output will display any failed tests and provide detailed information on each failed test case.

GitHub Actions runs these tests automatically with the latest stable versions of Python and relevant dependencies each time code is pushed to the repository or a pull request is made. For more information about workflows runs, see Workflows in the repository.