Managing dependencies Note Since Poetry 2.0, main dependencies can be specified in project.dependencies instead of tool.poetry.dependencies. See Dependency specification for more information. Only main dependencies can be specified in the project section. Other groups must still be specified in the tool.poetry section. Dependency groups Poetry provides a way to organize your dependencies by groups. For instance, you might have dependencies that are only needed to test your project or to build the documentation.

The pyproject.toml file In package mode, the only required fields are name and version (either in the project section or in the tool.poetry section). Other fields are optional. In non-package mode, all fields are optional. Note Run poetry check to print warnings about deprecated fields. The project section The project section of the pyproject.toml file according to the specification of the PyPA. name The name of the package. Required in package mode

Managing environments Poetry makes project environment isolation one of its core features. What this means is that it will always work isolated from your global Python installation. To achieve this, it will first check if it’s currently running inside a virtual environment. If it is, it will use it directly without creating a new one. But if it’s not, it will use one that it has already created or create a brand new one for you.

Community Badge For any projects using Poetry, you may add its official badge somewhere prominent like the README. Markdown [](https://python-poetry.org/) reStructuredText .. image:: https://img.shields.io/endpoint?url=https://python-poetry.org/badge/v0.json :alt: Poetry :target: https://python-poetry.

Configuration Poetry can be configured via the config command (see more about its usage here) or directly in the config.toml file that will be automatically created when you first run that command. This file can typically be found in one of the following directories: macOS: ~/Library/Application Support/pypoetry Windows: %APPDATA%\pypoetry For Unix, we follow the XDG spec and support $XDG_CONFIG_HOME. That means, by default ~/.config/pypoetry. Local configuration Poetry also provides the ability to have settings that are specific to a project by passing the --local option to the config command.

Commands You’ve already learned how to use the command-line interface to do some things. This chapter documents all the available commands. To get help from the command-line, simply call poetry to see the complete list of commands, then --help combined with any of those can give you more information. Global options --verbose (-v|vv|vvv): Increase the verbosity of messages: “-v” for normal output, “-vv” for more verbose output and “-vvv” for debug.

The pyproject.toml file The tool.poetry section of the pyproject.toml file is composed of multiple sections. name The name of the package. Required This should be a valid name as defined by PEP 508. name = "my-package" version The version of the package. Required This should be a valid PEP 440 string. version = "0.1.0" Note If you would like to use semantic versioning for your project, please see here. description A short description of the package.

Libraries This chapter will tell you how to make your library installable through Poetry. Versioning Poetry requires PEP 440-compliant versions for all projects. While Poetry does not enforce any release convention, it used to encourage the use of semantic versioning within the scope of PEP 440 and supports version constraints that are especially suitable for semver. Note As an example, 1.0.0-hotfix.1 is not compatible with PEP 440. You can instead choose to use 1.

Commands You’ve already learned how to use the command-line interface to do some things. This chapter documents all the available commands. To get help from the command-line, simply call poetry to see the complete list of commands, then --help combined with any of those can give you more information. Global options --verbose (-v|vv|vvv): Increase the verbosity of messages: “-v” for normal output, “-vv” for more verbose output and “-vvv” for debug.

Managing environments Poetry makes project environment isolation one of its core features. What this means is that it will always work isolated from your global Python installation. To achieve this, it will first check if it’s currently running inside a virtual environment. If it is, it will use it directly without creating a new one. But if it’s not, it will use one that it has already created or create a brand new one for you.