jasmine VS pyenv

Jasmine is a behavior-driven development framework for testing JavaScript code. It's known for its clean, straightforward syntax and does not rely on any other JavaScript frameworks or a Document Object Model (DOM). Jasmine is often praised for its simplicity and ease of use in both frontend and backend testing environments.

The test frameworks section provides an in-depth look at MochaJS, Jest, Jasmine, Puppeteer, Selenium, and Playwright. We review each framework's ease of use, community support, and overall robustness, supplemented with example unit tests.

Vitest makes it effortless to migrate from Jest. It supports the same Jasmine like API.

JavaScript Popular tools for testing: Mocha, Jasmine, Unit JS, Jest

Internet Explorer is not actively tested anymore due to Internet Explorer retiring on June 15, 2022 and jasmine v4 has dropped IE support https://github.com/jasmine/jasmine/blob/main/release_notes/4.0.0.md

To execute your tests, you can create test scripts using popular testing frameworks like Mocha, Jasmine, or Jest. These frameworks provide a structured way to organize and run your tests, report results, and handle assertions.

Testing frameworks like Jest, Mocha, and Jasmine are crucial for software development, ensuring code reliability and correctness. They offer features like test suites, test cases, assertions, and asynchronous testing support.

The test framework used does matter for naming, because in some frameworks you'd use different naming conventions (i.e. the fluent naming used with https://jasmine.github.io/)

Learn more about Jasmine and Karma

If you have a requirement for multiple, specific Python versions, why not just use pyenv?

https://github.com/pyenv/pyenv

For more information visit: pyenv repository

Note that virtual environments assume you are using the same global version of Python. Often, this is not the case and additional tools like pyenv can be used alongside virtual environments when you need to switch between versions of Python itself on your local machine.

Python version manager pyenv

First of all, install the Python virtual environment from these links: 1 and 2. I developed my GPT-based API in Python version 3.8.18. Pick any Python versions >= 3.7.

Note: Most modern systems will probably have a system environment that meets this requirement, but if yours does not or if you prefer not to install anything in your system environment (even if it's just PDM) check out asdf or pyenv to help install and manage additional Python environments.

When dealing with software development, reproducibility is key. This is why we encourage you to use Python virtual environments to set up an isolated environment for your project. Virtual environments allow the isolation of dependencies, which plays a crucial role to avoid breaking compatibility between different projects. We cannot cover all the details about virtual environments in this post, but we encourage you to learn more about venv, pyenv or conda for a better understanding on how to create and manage virtual environments.

For Python, with your use case I would avoid system packages, no matter the distro. It sounds like it would be worth setting up pyenv and working exclusively with virtual environments.

For OSX there is homebrew or pyenv (pyenv is another solution on Linux). As pyenv compiles from source it will require setting up XCode (the Apple IDE) tools to support this which can be pretty bulky. Windows users have chocolatey but the issue there is it works off the binaries. That means it won't have the latest security release available since those are source only. Conda is also another solution which can be picked up by Visual Studio Code as available versions of Python making development easier. In the end it might be best to consider using WSL on Windows for installing a Linux version and using that instead.