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Running the Entity Recognition Locally

Setting Up the Project Locally

Prerequisites

  • Python 3.11 or newer
  • pip and poetry

Installation

  1. Clone the Project

    First, clone the repository to your local machine:

    git clone https://github.com/warestack/entity-recognition.git
cd entity-recognition

  2. Set Up Your Virtual Environment

    Use pip to install a virtual environment and set up dependencies:

    python -m venv venv
source venv/bin/activate  # On Windows use `venv\Scripts\activate`
pip install -r requirements.txt

    This command installs all necessary packages listed in the requirements.txt file within a virtual environment.

Running Pre-commit Hooks Locally

To ensure code quality and consistency, it's recommended to set up and run pre-commit hooks locally before pushing your changes:

  • Install Pre-commit

    First, ensure that pre-commit is installed within your virtual environment:

    pip install pre-commit

  • Install Git Hooks

    To set up the Git hooks in your local repository, run:

    pre-commit install

    This will ensure that the pre-commit hooks are run on every commit.

  • Manually Running Pre-commit Hooks

    If you want to manually run the pre-commit hooks on all files (useful for initial setup or to check files without committing):

    pre-commit run --all-files

    This command will run all configured hooks against all files in the repository.

Running the Project

Using the Examples Directory

The examples directory contains sample scripts and applications that demonstrate how to use the library code effectively. These examples are particularly useful for testing local changes to the library:

  • Navigate to the examples directory.
  • Run an example script to see how the library performs with your changes:

This approach helps ensure that any modifications you make to the library are reflected and can be tested immediately through practical use cases.

Unit Tests

Run the unit tests included in the tests directory with the following command:

pytest

Or, to run a specific unit test file:

pytest tests/test_specific_feature.py

Bumping and Publishing Versions

This project utilizes GitHub Actions for automated version management and publishing. When a pull request is merged into the main branch, the following happens automatically:

  • Version Bumping: A new version number is generated based on the contents of the PR, adhering to semantic versioning.
  • Package Building: The project is built using poetry, ensuring all package dependencies are properly encapsulated.
  • Publishing: The newly built version is published to PyPI automatically, making it immediately available for use.