Why is the dependency resolution process slow? #
While the dependency resolver at the heart of Poetry is highly optimized and should be fast enough for most cases, sometimes, with some specific set of dependencies, it can take time to find a valid solution.
This is due to the fact that not all libraries on PyPI have properly declared their metadata and, as such, they are not available via the PyPI JSON API. At this point, Poetry has no choice but downloading the packages and inspect them to get the necessary information. This is an expensive operation, both in bandwidth and time, which is why it seems this is a long process.
At the moment there is no way around it.
Why are unbound version constraints a bad idea? #
A version constraint without an upper bound such as
>=3.4 will allow updates to any future version of the dependency.
This includes major versions breaking backward compatibility.
Once a release of your package is published, you cannot tweak its dependencies anymore in case a dependency breaks BC – you have to do a new release but the previous one stays broken.
The only good alternative is to define an upper bound on your constraints, which you can increase in a new release after testing that your package is compatible with the new major version of your dependency.
For example instead of using
>=3.4 you should use
~3.4 which allows all versions
^ operator works very well with libraries following semantic versioning.
Is tox supported? #
Yes. By using the isolated builds
you can use it in combination with the PEP 517 compliant build system provided by Poetry.
So, in your
pyproject.toml file, add this section if it does not already exist:
[build-system] requires = ["poetry-core>=1.0.0"] build-backend = "poetry.core.masonry.api"
And use a
tox.ini configuration file similar to this:
[tox] isolated_build = true envlist = py27, py36 [testenv] whitelist_externals = poetry commands = poetry install -v poetry run pytest tests/
I don’t want Poetry to manage my virtual environments. Can I disable it? #
While Poetry automatically creates virtual environments to always work isolated from the global Python installation, there are valid reasons why it’s not necessary and is an overhead, like when working with containers.
In this case, you can disable this feature by setting the
virtualenvs.create setting to
poetry config virtualenvs.create false