In a second article, we will see more Poetry commands, add our Virtual Environment to VSCode and use the dev packages we installed to lint (Flake8), format (Black) and test (Pytest) our code inside the editor. Update poetry to the latest stable version. Remove a dev package from a Virtual Environment. Remove a package from a Virtual Environment. Install the packages inside the pyproject.toml file.Īdd a dev package to a Virtual Environment. In this first part, we have started a new project, created a Virtual Environment and added and removed dependencies by using the following commands: CommandĬreate a pyproject.toml file interactively. Now mypy which is a dev dependency: $ poetry remove -D mypy Start by removing coo, a normal dependency of our project: $ poetry remove coo You know what, I changed my mind, this project will use nor coo nor mypy. But I really want it, so let’s install it anyway with the -allow-prereleases flag: $ poetry add -D black -allow-prereleases This error happens because black is in a pre-release state, so Poetry cannot find any stable version for us. We’ll go with black: $ poetry add -D blackĬould not find a matching version of package blackĪdd (). Now that I think about it, I forgot to add a formatter. We already installed Pytest, but we will also use flake8 for linting and mypy for static typing: $ poetry add -D flake8 mypy These dependencies will be available only during development, Poetry will not include them when building and publishing the project. Open pyproject.toml and poetry.lock and see how they have updated. Let’s add two packages to the project, pendulum, and coo: $ poetry add pendulum coo We will instead use the add and remove commands to avoid manual modifications. One way to add or remove dependencies is to directly edit pyproject.toml and then run poetry install to apply the changes. You should commit the poetry.lock file to your project repo so that all people working on the project are locked to the same versions of dependencies. When Poetry has finished installing, it writes all the packages and the exact versions of them that it downloaded to the poetry.lock file, locking the project to those specific versions. To create a Virtual Environment and install Pytest, we will use the poetry install command: $ poetry installĪfter is done, a new file, poetry.lock will be created. By default, Poetry includes Pytest, so we will use it to test our project later on. These packages are only for development and will not be included when we publish our project. Furthermore, from now on, every package we install that is meant to be used in production will be listed here. Basically, this project will be compatible with Python 3.7 and up. Adding a license and a README might be a good idea: įirst is the Python version. The pyproject.toml file will manage the details and dependencies of the project: ĭescription = "A simple decorator to measure a function execution time." Note: To be able to publish your project, you need an available name. The directory how-long is created and inside is a basic project structure: how-long Note: For existing projects, you can use the poetry init command and interactively create a pyproject.toml. I will call it how-long and will be a simple library to measure the execution time of a function: $ poetry new how-long We can now start a new Python project by using the poetry new command. This way, we will later be able to update poetry to the latest stable version with the poetry self update command. This is the recommended way of installing poetry: $ curl -sSL | python. The easiest way is to use pip: $ pip install poetryīut we will use Poetry own installer to isolate it from the rest of the system by vendorizing its dependencies. In this series of articles, we’ll use Poetry to manage our dependencies, build a simple project and, with a single command, publish it on PyPI. In other words, poetry uses pyproject.toml to replace setup.py, requirements.txt, setup.cfg, MANIFEST.in and the newly added Pipfile. It only needs one file to do all of that: the new, standardized pyproject.toml`. Poetry is a tool to handle dependency installation as well as building and packaging of Python packages.
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