Awesome
Jupyter Packaging
:warning: We recommend using Hatch Jupyter Builder instead of Jupyter Packaging for new and existing projects. See the blog post Packaging for Jupyter in 2022.
About
Tools to help build and install Jupyter Python packages that require a pre-build step that may include JavaScript build steps.
Install
pip install jupyter-packaging
Usage
There are three ways to use jupyter-packaging
in another package.
In general, you should not depend on jupyter_packaging
as a runtime dependency, only as a build dependency.
As a Build Requirement
Use a pyproject.toml
file as outlined in pep-518.
An example:
[build-system]
requires = ["jupyter_packaging>=0.10,<2"]
build-backend = "setuptools.build_meta"
Below is an example setup.py
using the above config.
It assumes the rest of your metadata is in setup.cfg
.
We wrap the import in a try/catch to allow the file to be run without jupyter_packaging
so that python setup.py
can be run directly when not building.
from setuptools import setup
try:
from jupyter_packaging import wrap_installers, npm_builder
builder = npm_builder()
cmdclass = wrap_installers(pre_develop=builder, pre_dist=builder)
except ImportError:
cmdclass = {}
setup(cmdclass=cmdclass))
As a Build Backend
Use the jupyter_packaging
build backend.
The pre-build command is specified as metadata in pyproject.toml
:
[build-system]
requires = ["jupyter_packaging>=0.10,<2"]
build-backend = "jupyter_packaging.build_api"
[tool.jupyter-packaging.builder]
factory = "jupyter_packaging.npm_builder"
[tool.jupyter-packaging.build-args]
build_cmd = "build:src"
The corresponding setup.py
would be greatly simplified:
from setuptools import setup
setup()
The tool.jupyter-packaging.builder
section expects a func
value that points to an importable
module and a function with dot separators. If not given, no pre-build function will run.
The optional tool.jupyter-packaging.build-args
sections accepts a dict of keyword arguments to
give to the pre-build command.
The build backend does not handle the develop
command (pip install -e .
).
If desired, you can wrap just that command:
import setuptools
try:
from jupyter_packaging import wrap_installers, npm_builder
builder = npm_builder(build_cmd="build:dev")
cmdclass = wrap_installers(pre_develop=builder)
except ImportError:
cmdclass = {}
setup(cmdclass=cmdclass))
The optional tool.jupyter-packaging.options
section accepts the following options:
skip-if-exists
: A list of local files whose presence causes the prebuild to skipensured-targets
: A list of local file paths that should exist when the dist commands are run
As a Vendored File
Vendor setupbase.py
locally alongside setup.py
and import the module directly.
import setuptools
from setupbase import wrap_installers, npm_builder
func = npm_builder()
cmdclass = wrap_installers(post_develop=func, pre_dist=func)
setup(cmdclass=cmdclass)
Usage Notes
- This package does not work with the deprecated
python setup.py bdist_wheel
orpython setup.py sdist
commands, PyPA recommends using the build package (pip install build && python -m build .
). - We recommend using
include_package_data=True
andMANIFEST.in
to control the assets included in the package. - Tools like
check-manifest
ormanifix
can be used to ensure the desired assets are included. - Simple uses of
data_files
can be handled insetup.cfg
or insetup.py
. If recursive directories are needed useget_data_files()
from this package. - Unfortunately
data_files
are not supported indevelop
mode (a limitation ofsetuptools
). You can work around it by doing a full install (pip install .
) before the develop install (pip install -e .
), or by adding a script to push the data files tosys.base_prefix
.
Development Install
git clone https://github.com/jupyter/jupyter-packaging.git
cd jupyter-packaging
pip install -e .[test]
pre-commit install
You can test changes locally by creating a pyproject.toml
with the following, replacing the local path to the git checkout:
[build-system]
requires = ["jupyter_packaging@file://<path-to-git-checkout>"]
build-backend = "setuptools.build_meta"
Note: you need to run pip cache remove jupyter_packaging
any time changes are made to prevent pip
from using a cached version of the source.