Dunamai is a Python 3.5+ library and command line tool for producing dynamic, standards-compliant version strings, derived from tags in your version control system. This facilitates uniquely identifying nightly or per-commit builds in continuous integration and releasing new versions of your software simply by creating a tag.
Dunamai is also available as a GitHub Action.
- Version control system support:
- Version styles:
- PEP 440
- Semantic Versioning
- Haskell Package Versioning Policy
- Custom output formats
- Can be used for projects written in any programming language. For Python, this means you do not need a setup.py.
Install with pip install dunamai
, and then use as either a CLI:
# Suppose you are on commit g29045e8, 7 commits after the v0.2.0 tag.
# Note that the "v" prefix on the tag is required, unless you specify
# a different tag style using "--pattern".
# Auto-detect the version control system and generate a version:
$ dunamai from any
0.2.0.post7.dev0+g29045e8
# Or use an explicit VCS and style:
$ dunamai from git --no-metadata --style semver
0.2.0-post.7
# Custom formats:
$ dunamai from any --format "v{base}+{distance}.{commit}"
v0.2.0+7.g29045e8
# If you'd prefer to frame the version in terms of progress toward the next
# release rather than distance from the latest one, you can bump it:
$ dunamai from any --bump
0.2.1.dev7+g29045e8
# Validation of custom formats:
$ dunamai from any --format "v{base}" --style pep440
Version 'v0.2.0' does not conform to the PEP 440 style
# Validate your own freeform versions:
$ dunamai check 0.01.0 --style semver
Version '0.01.0' does not conform to the Semantic Versioning style
# More info:
$ dunamai --help
$ dunamai from --help
$ dunamai from git --help
Or as a library:
from dunamai import Version, Style
# Let's say you're on commit g644252b, which is tagged as v0.1.0.
version = Version.from_git()
assert version.serialize() == "0.1.0"
# Let's say there was a v0.1.0rc5 tag 44 commits ago
# and you have some uncommitted changes.
version = Version.from_any_vcs()
assert version.serialize() == "0.1.0rc5.post44.dev0+g644252b"
assert version.serialize(metadata=False) == "0.1.0rc5.post44.dev0"
assert version.serialize(dirty=True) == "0.1.0rc5.post44.dev0+g644252b.dirty"
assert version.serialize(style=Style.SemVer) == "0.1.0-rc.5.post.44+g644252b"
The serialize()
method gives you an opinionated, PEP 440-compliant default
that ensures that versions for untagged commits are compatible with Pip's
--pre
flag. The individual parts of the version are also available for you
to use and inspect as you please:
assert version.base == "0.1.0"
assert version.stage == "rc"
assert version.revision == 5
assert version.distance == 44
assert version.commit == "g644252b"
assert version.dirty is True
# Available if the latest tag includes metadata, like v0.1.0+linux:
assert version.tagged_metadata == "linux"
Versioneer is another great library for dynamic versions, but there are some design decisions that prompted the creation of Dunamai as an alternative:
- Versioneer requires a setup.py file to exist, or else
versioneer install
will fail, rendering it incompatible with non-setuptools-based projects such as those using Poetry or Flit. Dunamai can be used regardless of the project's build system. - Versioneer has a CLI that generates Python code which needs to be committed into your repository, whereas Dunamai is just a normal importable library with an optional CLI to help statically include your version string.
- Versioneer produces the version as an opaque string, whereas Dunamai provides a Version class with discrete parts that can then be inspected and serialized separately.
- Versioneer provides customizability through a config file, whereas Dunamai aims to offer customizability through its library API and CLI for both scripting support and use in other libraries.
-
Setting a
__version__
statically:$ echo "__version__ = '$(dunamai from any)'" > your_library/_version.py
# your_library/__init__.py from your_library._version import __version__
Or dynamically (but Dunamai becomes a runtime dependency):
# your_library/__init__.py import dunamai as _dunamai __version__ = _dunamai.get_version("your-library", third_choice=_dunamai.Version.from_any_vcs).serialize()
-
setup.py (no install-time dependency on Dunamai as long as you use wheels):
from setuptools import setup from dunamai import Version setup( name="your-library", version=Version.from_any_vcs().serialize(), )
Or you could use a static inclusion approach as in the prior example.
-
$ poetry version $(dunamai from any)
Or you can use the poetry-dynamic-versioning plugin.
- When using Git, the initial commit must not be both tagged and empty
(i.e., created with
--allow-empty
). This is related to a reporting issue in Git. For more info, click here.
This project is managed using Poetry. Development requires Python 3.6+ because of Black.
- If you want to take advantage of the default VSCode integration, then first
configure Poetry to make its virtual environment in the repository:
poetry config settings.virtualenvs.in-project true
- After cloning the repository, activate the tooling:
poetry install poetry run pre-commit install
- Run unit tests:
poetry run pytest --cov poetry run tox