I am spoiled by the amount of tooling available with Nodejs, and Ruby. Now that I am primarily coding in Python, I am was looking for something similar, and I came across pipx (equivalent to npx) and poetry (loosely similar to npm, or bundler).

Let’s get started with pipx, and then we will cover poetry.

pipx

It’s really easy to install pipx, and it’s a great way to install Python packages that come with command line tools.

On Mac, you can install it using homebrew:

brew install pipx

Now that you have pipx installed, you can install any Python package, including poetry which comes with a command line tool.

pipx install poetry

That’s it!

Poetry

Poetry is a tool for dependency management and packaging in Python. It allows you to declare, manage and install dependencies of Python projects. It also manages your virtual environment and build system. Also, using poetry is a great way to ensure consistent project structure around different Python projects.

Creating a new project

To create a new project, you can use the following command:

poetry new my_project

This will create a new project in the my_project directory, and create a my_project directory inside it. Btw, that’s the right way to structure a Python project, because your imports will be relative to my_project directory in the project root, which is also the module name.

my_project/
├── pyproject.toml
├── README.md
├── poetry.lock
├── src/
│   └── my_project/
│       └── __init__.py
└── tests/
    └── __init__.py

Converting an existing project

But what if you already have a project, and you want to convert it to poetry?

You can use the following command:

poetry init

This will create a pyproject.toml file, and you can start adding dependencies.

Adding dependencies

poetry add requests

Poetry updates the pyproject.toml file, and you can start adding dependencies, and

It will also take care of doing version locks, and creating a poetry.lock file that could be checked into your repository. This will ensure that everyone in the team, and the upper environments are using the same versions of the dependencies.

So, if you have just cloned the project, you can run:

poetry install

To create a virtual environment and install the dependencies.

Running module as CLI tool

Just like how you would run any module in python using python -m my_module, you can run any command in poetry using poetry run my_command.

poetry run python -m my_project

Note that if you have an executable module, it should have a __main__.py file in the root of the module.

Running tests and other commands

You can run any command in poetry using poetry run my_command. poetry run will take care of running the command in the virtual environment.

So, if you have pytest installed, you can run your tests using:

poetry run pytest

You can also run other commands like poetry run mypy to run mypy, or poetry run isort to run isort.

Running commands in the virtual environment

You can also run commands in the virtual environment using poetry shell. This will give you a shell in the virtual environment, and you can run any command in the shell.

poetry shell

Well, this should be enough to get you started with poetry. If you want to learn more, simply run poetry list and it will list all the available commands – and there are quite a few to have you covered with dependency management, packaging, and more.