Basic usage
Basic usage #
For the basic usage introduction we will be installing pendulum, a datetime library.
If you have not yet installed Poetry, refer to the Introduction chapter.
Project setup #
First, let’s create our new project, let’s call it poetry-demo:
poetry new poetry-demo
This will create the poetry-demo directory with the following content:
poetry-demo
├── pyproject.toml
├── README.md
├── poetry_demo
│ └── __init__.py
└── tests
└── __init__.py
The pyproject.toml file is what is the most important here. This will orchestrate
your project and its dependencies. For now, it looks like this:
[project]
name = "poetry-demo"
version = "0.1.0"
description = ""
authors = [
{name = "Sébastien Eustace", email = "sebastien@eustace.io"}
]
readme = "README.md"
requires-python = ">=3.8"
[tool.poetry]
packages = [{include = "poetry_demo"}]
[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"
Poetry assumes your package contains a package with the same name as tool.poetry.name located in the root of your
project. If this is not the case, populate tool.poetry.packages to specify
your packages and their locations.
Similarly, the traditional MANIFEST.in file is replaced by the tool.poetry.readme, tool.poetry.include, and
tool.poetry.exclude sections. tool.poetry.exclude is additionally implicitly populated by your .gitignore. For
full documentation on the project format, see the pyproject section of the documentation.
Setting a Python Version #
Poetry will require you to explicitly specify what versions of Python you intend to support, and its universal locking will guarantee that your project is installable (and all dependencies claim support for) all supported Python versions. Again, it’s important to remember that – unlike other dependencies – setting a Python version is merely specifying which versions of Python you intend to support.
For example, in this pyproject.toml file:
[tool.poetry.dependencies]
python = "^3.7.0"
we are allowing any version of Python 3 that is greater than 3.7.0.
When you run poetry install, you must have access to some version of a Python interpreter that satisfies this constraint available on your system.
Poetry will not install a Python interpreter for you.
Initialising a pre-existing project #
Instead of creating a new project, Poetry can be used to ‘initialise’ a pre-populated
directory. To interactively create a pyproject.toml file in directory pre-existing-project:
cd pre-existing-project
poetry init
Operating modes #
Poetry can be operated in two different modes. The default mode is the package mode, which is the right mode
if you want to package your project into an sdist or a wheel and perhaps publish it to a package index.
In this mode, some metadata such as name and version, which are required for packaging, are mandatory.
Further, the project itself will be installed in editable mode when running poetry install.
If you want to use Poetry only for dependency management but not for packaging, you can use the non-package mode:
[tool.poetry]
package-mode = false
In this mode, metadata such as name and version are optional.
Therefore, it is not possible to build a distribution or publish the project to a package index.
Further, when running poetry install, Poetry does not try to install the project itself,
but only its dependencies (same as poetry install --no-root).
Specifying dependencies #
If you want to add dependencies to your project, you can specify them in the
project or tool.poetry.dependencies section.
See the Dependency specification
for more information.
[project]
# ...
dependencies = [
"pendulum (>=2.1,<3.0)"
]
or
[tool.poetry.dependencies]
pendulum = "^2.1"
As you can see, it takes a mapping of package names and version constraints.
Poetry uses this information to search for the right set of files in package “repositories” that you register
in the tool.poetry.source section, or on PyPI by default.
Also, instead of modifying the pyproject.toml file by hand, you can use the add command.
$ poetry add pendulum
It will automatically find a suitable version constraint and install the package and sub-dependencies.
Poetry supports a rich dependency specification syntax, including caret, tilde, wildcard, inequality and multiple constraints requirements.
Using your virtual environment #
By default, Poetry creates a virtual environment in {cache-dir}/virtualenvs.
You can change the cache-dir value
by editing the Poetry configuration.
Additionally, you can use the
virtualenvs.in-project configuration variable to create
virtual environments within your project directory.
There are several ways to run commands within this virtual environment.
External virtual environment management
Poetry will detect and respect an existing virtual environment that has been externally activated. This is a powerful mechanism that is intended to be an alternative to Poetry’s built-in, simplified environment management.
To take advantage of this, simply activate a virtual environment using your preferred method or tooling, before running any Poetry commands that expect to manipulate an environment.
Using poetry run #
To run your script simply use poetry run python your_script.py.
Likewise if you have command line tools such as pytest or black you can run them using poetry run pytest.
If managing your own virtual environment externally, you do not need to use poetry run or poetry shell since
you will, presumably, already have activated that virtual environment and made available the correct python instance.
For example, these commands should output the same python path:
conda activate your_env_name
which python
poetry run which python
poetry shell
which python
Activating the virtual environment #
The easiest way to activate the virtual environment is to create a nested shell with poetry shell.
To deactivate the virtual environment and exit this new shell type exit.
To deactivate the virtual environment without leaving the shell use deactivate.
Why a nested shell?
Child processes inherit their environment from their parents, but do not share them. As such, any modifications made by a child process is not persisted after the child process exits. A Python application (Poetry), being a child process, cannot modify the environment of the shell that it has been called from such that an activated virtual environment remains active after the Poetry command has completed execution.
Therefore, Poetry has to create a sub-shell with the virtual environment activated in order for the subsequent commands to run from within the virtual environment.
If you’d like to prevent poetry shell from modifying your shell prompt on virtual environment activation, you should
set VIRTUAL_ENV_DISABLE_PROMPT=1 as an environment variable before running the command.
Alternatively, to avoid creating a new shell, you can manually activate the
virtual environment by running source {path_to_venv}/bin/activate ({path_to_venv}\Scripts\activate.ps1 in PowerShell).
To get the path to your virtual environment run poetry env info --path.
You can also combine these into a one-liner, such as source $(poetry env info --path)/bin/activate
(& ((poetry env info --path) + "\Scripts\activate.ps1") in Powershell).
To deactivate this virtual environment simply use deactivate.
| POSIX Shell | Windows (PowerShell) | Exit/Deactivate | |
|---|---|---|---|
| Sub-shell | poetry shell |
poetry shell |
exit |
| Manual Activation | source {path_to_venv}/bin/activate |
{path_to_venv}\Scripts\activate.ps1 |
deactivate |
| One-liner | source $(poetry env info --path)/bin/activate |
& ((poetry env info --path) + "\Scripts\activate.ps1") |
deactivate |
Version constraints #
In our example, we are requesting the pendulum package with the version constraint ^2.1.
This means any version greater or equal to 2.1.0 and less than 3.0.0 (>=2.1.0 <3.0.0).
Please read Dependency specification for more in-depth information on versions, how versions relate to each other, and on the different ways you can specify dependencies.
How does Poetry download the right files?
When you specify a dependency in pyproject.toml, Poetry first takes the name of the package
that you have requested and searches for it in any repository you have registered using the repositories key.
If you have not registered any extra repositories, or it does not find a package with that name in the
repositories you have specified, it falls back to PyPI.
When Poetry finds the right package, it then attempts to find the best match for the version constraint you have specified.
Installing dependencies #
To install the defined dependencies for your project, just run the install command.
poetry install
When you run this command, one of two things may happen:
Installing without poetry.lock #
If you have never run the command before and there is also no poetry.lock file present,
Poetry simply resolves all dependencies listed in your pyproject.toml file and downloads the latest version of their files.
When Poetry has finished installing, it writes all the packages and their exact versions that it downloaded to the poetry.lock file,
locking the project to those specific versions.
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 (more below).
Installing with poetry.lock #
This brings us to the second scenario. If there is already a poetry.lock file as well as a pyproject.toml file
when you run poetry install, it means either you ran the install command before,
or someone else on the project ran the install command and committed the poetry.lock file to the project (which is good).
Either way, running install when a poetry.lock file is present resolves and installs all dependencies that you listed in pyproject.toml,
but Poetry uses the exact versions listed in poetry.lock to ensure that the package versions are consistent for everyone working on your project.
As a result you will have all dependencies requested by your pyproject.toml file,
but they may not all be at the very latest available versions
(some dependencies listed in the poetry.lock file may have released newer versions since the file was created).
This is by design, it ensures that your project does not break because of unexpected changes in dependencies.
Committing your poetry.lock file to version control #
As an application developer #
Application developers commit poetry.lock to get more reproducible builds.
Committing this file to VC is important because it will cause anyone who sets up the project to use the exact same versions of the dependencies that you are using. Your CI server, production machines, other developers in your team, everything and everyone runs on the same dependencies, which mitigates the potential for bugs affecting only some parts of the deployments. Even if you develop alone, in six months when reinstalling the project you can feel confident the dependencies installed are still working even if your dependencies released many new versions since then. (See note below about using the update command.)
[build-system] section to your project’s pyproject.toml then you can successfully install your project and its dependencies into a virtual environment using a command like pip install -e .. However, pip will not use the lock file to determine dependency versions as the poetry-core build system is intended for library developers (see next section).As a library developer #
Library developers have more to consider. Your users are application developers, and your library will run in a Python environment you don’t control.
The application ignores your library’s lock file. It can use whatever dependency version meets the constraints in your pyproject.toml. The application will probably use the latest compatible dependency version. If your library’s poetry.lock falls behind some new dependency version that breaks things for your users, you’re likely to be the last to find out about it.
A simple way to avoid such a scenario is to omit the poetry.lock file. However, by doing so, you sacrifice reproducibility and performance to a certain extent. Without a lockfile, it can be difficult to find the reason for failing tests, because in addition to obvious code changes an unnoticed library update might be the culprit. Further, Poetry will have to lock before installing a dependency if poetry.lock has been omitted. Depending on the number of dependencies, locking may take a significant amount of time.
If you do not want to give up the reproducibility and performance benefits, consider a regular refresh of poetry.lock to stay up-to-date and reduce the risk of sudden breakage for users.
Installing dependencies only #
The current project is installed in editable mode by default.
If you want to install the dependencies only, run the install command with the --no-root flag:
poetry install --no-root
Updating dependencies to their latest versions #
As mentioned above, the poetry.lock file prevents you from automatically getting the latest versions
of your dependencies.
To update to the latest versions, use the update command.
This will fetch the latest matching versions (according to your pyproject.toml file)
and update the lock file with the new versions.
(This is equivalent to deleting the poetry.lock file and running install again.)
poetry.lock and pyproject.toml
are not synchronized.