Template Repository

This repository serves as a template for initializing new Python projects. It includes a configured development environment and essential tools for maintaining code quality.

Environment Setup

To set up the development environment, use the provided environment.yml file. It includes the following dependencies:

• Python 3.12
• Code Quality Tools
  • pylint: A static code analyzer for Python.
  • flake8: A tool for enforcing coding style based on PEP 8.
  • isort: A utility for sorting imports.
  • black: An opinionated code formatter for Python.
• Testing Framework
  • pytest: A framework that makes building simple and scalable test cases easy.
  • pytest-cov: A plugin for measuring test coverage.

Getting Started

To create the environment, replace the { { template } } in the environment.yml file with an appropiate name for your environment and run the following command:

conda env create -f environment.yml

To activate the environment, run the following command:

conda activate { { template } }

Replace { { template } } with the name specified in the environment.yml file.

Dev Containers

This repository supports the use of development containers to streamline your development environment setup. By leveraging Docker and Visual Studio Code's Remote - Containers extension, you can work in a consistent environment that includes all necessary dependencies and tools.

Getting Started with Dev Containers

1. Prerequisites:

   • Ensure you have Docker installed on your machine.
   • Install Visual Studio Code and the Remote - Containers extension.

2. Using the Dev Container:

   • Open this repository in Visual Studio Code.
   • Once the workspace is open, you should see a prompt to reopen the folder in a container. Click on "Reopen in Container."
   • Visual Studio Code will build the dev container defined in the .devcontainer directory, which may include setting up the environment specified in environment.yml.

3. Using the Development Environment:

   • Once the container is running, you can access a terminal within VS Code to run your Python scripts using the specified environment.
   • All code quality tools and testing frameworks will be available as defined in the environment.yml and configured in the devcontainer.json file.

4. Stopping the Dev Container:

   • To stop the container, you can either close Visual Studio Code or use the command palette (Ctrl+Shift+P) and select "Remote-Containers: Rebuild Container" or "Remote-Containers: Close Remote Connection" as needed.