python-barn 0.11.0

A wrapper for pip, to give better utils to python projects dependency management

barn

barn is a Python-based command-line interface (CLI) tool that simplifies package management by providing an intuitive set of commands. It was inspired by the yarn counterpart from Javascript. Hence the interface was kept as similar as possible, so that if you are familiar with yarn you should pickup barn relatively fast.

Note Barn is just a pip wrapper, so package resolution is still completely up to pip and your installed pip version

Features

• Install packages
• Add new packages
• Initialize new projects with interactive prompts
• Ability to define script scoped to your project, like you would do with a package.json

⚠️ A small invite to caution

Barn is still in development and can be unstable. More over:

• It currently only supports python 3.9 and it is only officially tested on 3.9.13
• It still lacks core feature that hopefully will be added soon

How to use

You can install barn directly with the following pip command:

Note You are encouraged to install barn globally on your system

pip install python-barn

You can initialise an empty directory to be a barn project by running:

barn init

This will launch an interactive prompt asking for details such as project name, description, author, etc.

In case your project already exists and it's not an empty folder, you can create the project.yaml file with the following content:

name: my-project
description: Some description
version: 0.1.0
author: your-name or your team name
scripts:
  - start: python ./main.py
  - test: echo "Not implemented"
license: your-license

Install project dependencies

barn

or

barn install

Add a new package:

barn add <package-name>

Remove a package:

barn remove <package-name>

To setup custom scripts

In the project.yaml, you can specify bash scripts by adding to the scripts section:

scripts:
  - start: python ./main.py

Once you have your script defined you can run:

barn <script-name>

In this case:

barn start

This will run your script in the context of the project, with the correct python version and pointing to the correct virtual environment

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.