Packaging#
Once a release is cut, napari is distributed in two main ways:
Packages: both to PyPI and conda-forge.
Installers: bundles that include napari plus its runtime dependencies in a step-by-step executable.
Packages#
Despite its numerous dependencies, napari
itself is a regular Python project that can be packaged using established workflows.
PyPI packages#
Creating and submitting the packages to PyPI (the repository you query when you do pip install
) is handled in the make_release.yml
workflow.
Creation is handled with make dist
(as specified in our Makefile
) and submission is done using the official PyPA GitHub Action.
This workflow will also create a GitHub release. See Release guide for more details.
conda-forge packages#
Once the Python package makes it to PyPI, it will be picked up by the conda-forge
bots.
The bots will automatically submit a PR to the napari-feedstock
repository within a few hours.
This is all automated by the conda-forge
infrastructure (see previous examples).
We only need to check that the metadata in the recipe has been adjusted for the new release.
Pay special attention to the runtime dependencies and version strings!
We keep a copy of the feedstock’s recipe in the
napari/packaging
repo, which is updated manually whenever a change topyproject.toml
is detected. Check the fileconda-recipe/meta.yaml
and make sure itsoutputs
contents are synced to thenapari-feedstock
copy.
Once the conda-forge CI is passing and the PR is approved and merged, the final packages will be built on the default branch and uploaded to the conda-forge
channel.
Due to the staging steps and CDN synchronization delays, the conda packages can take up to 1h to be available after the merge.
Note
Check Release guide for more details about the conda-forge release process and maintenance tasks.
conda packaging split#
We provide three different outputs in the conda package recipe:
napari-base
: This is the package that ships the actual source and data. The runtime requirements only include the basic functionality. This package is recommended as a dependency for plugins and other projects. Most end users will prefer thenapari
package, below, but this one may be useful for those wanting a more minimal environment.napari
: This output is what most users want. It depends onnapari-base
, and adds optional yet recommended dependencies for (performant) GUI usage, like the plugin manager or numba. Note that the Qt backend is not included.napari-menu
: Depends onnapari
, and ships the menuinst JSON file, in case you want a desktop shortcut to start the application easily. This is included as part of the bundled installers for convenience.
conda packages in the napari
channel#
The napari
project also has a napari
channel in anaconda.org.
We mainly use it to provide:
Nightlies built off of
main
, uploaded to thenapari/label/nightly
channel.Release candidates, uploaded to
napari/label/rc
.
Note
The napari
channel happens to contain the final releases too.
However, these are not meant to be used by end users, who should use conda-forge
.
The releases uploaded to our channel are the same ones we use to build our constructor
installers (see below).
Otherwise, we would have to wait for the conda-forge
PR, which is only triggered by the PyPI release.
That means we would not be able to create the installers in the same tagging event.
To do it in a conda-forge
compatible way, we clone napari-feedstock
and patch the source
instructions to use the code from the repository branch.
The version is also patched to match the setuptools-scm
string.
After re-rendering the feedstock, we run conda-build
in the same way conda-forge
would do and upload the resulting tarballs to our Anaconda.org channel.
Additionally, the tarballs are also passed as artifacts to the next stage in the pipeline: building the constructor
installers (more below).
Installers#
Once the packages have been built and uploaded to their corresponding repositories,
we can bundle them along with their dependencies in a single executable that end users can run to install napari on their systems,
with no prior knowledge of pip
, conda
, virtual environments, command line prompts or anything.
A software installer is usually expected to fulfill these requirements:
It will install the application so it can be run immediately after.
It will provide a convenient way of opening the application, like a shortcut or a menu entry.
It will allow the user to uninstall the application, leaving no artifacts behind.
We use constructor
to build the bundled installers, which takes conda
packages.
conda
packages offer several advantages when it comes to bundling dependencies, since it makes very few assumptions about the underlying system installation.
As a result, constructor
bundles include libraries that might be missing in the target system and hence should provide a more robust user experience.
The automation is implemented in the .github/workflows/make_bundle_conda.yml
workflow, which only
specifies the triggers used to call the actual workflow implementation under the napari/packaging
repository. This repository stores all the logic and files needed to create the nightly conda
packages and the constructor
installers.
constructor
allows you to build cross-platform installers out of conda
packages.
It supports the following installer types:
On Linux, a shell-based installer is generated; users can execute it with
bash installer.sh
.On macOS, you can generate both PKG and shell-based installers. PKG files are graphical installers native to macOS, so that’s the method we use with napari.
On Windows, a graphical installer based on NSIS is generated.
The configuration is done through a construct.yaml
file, documented here.
We generate one on the fly in the build_installers.py
script found in napari/packaging
.
For a hypothetical napari v1.2.3 we would have built this configuration file:
# os-agnostic configuration
name: napari
version: "0.0.1" # this is the _internal_ version of the installer infrastructure
company: Napari
license: EULA.md
channels:
# - local # only in certain situations, like nightly installers where we build napari locally
- conda-forge
specs: # specs for the 'base' environment
- python # pinned to the version of the running interpreter, configured in the CI
- conda # we add these to manage different napari versions
- mamba # we add these to manage different napari versions
- pip # we add these to manage different napari versions
extra_envs:
napari-1.2.3: # this is the environment that will actually contain the napari packages
specs:
- napari=1.2.3
- napari-menu=1.2.3
- python # pinned to a specific version, configured by CI
- pyside2 # pinned to a specific version, configured by CI
- conda # needed for the plugin manager
- mamba # needed for the plugin manager
- pip # needed for the plugin manager
menu_packages:
- napari-menu # don't create shortcuts for anything else in the environment
# linux-specific config
default_prefix: $HOME/napari-1.2.3 # default installation path
# macos-specific config
default_location_pkg : Library # first component of the default path under ~/
pkg_name: napari-1.2.3 # second component of the default path
installer_type: pkg # otherwise, defaults to sh (Linux-like)
welcome_image: resources/napari_1227x600.png # bg image with the napari logo on bottom-left corner
welcome_file: resources/osx_pkg_welcome.rtf # rendered text in the first screen
conclusion_text: "" # set to an empty string to revert constructor customizations back to system's
readme_text: "" # set to an empty string to revert constructor customizations back to system's
signing_identity_name: "Apple Developer ID: ..." # Name of our installer signing certicate
# windows-specific config
welcome_image: resources/napari_164x314.png # logo image for the first screen
header_image: resources/napari_150x57.png # logo image (top left) for the rest of the installer
icon_image: napari/resources/icon.ico # favicon for the taskbar and title bar
default_prefix: '%USERPROFILE%/napari-1.2.3' # default location for user installs
default_prefix_domain_user: '%LOCALAPPDATA%/napari-1.2.3' # default location for network installs
default_prefix_all_users: '%ALLUSERSPROFILE%/napari-1.2.3' # default location for admin installs
signing_certificate: certificate.pfx # path to signing certificate
The main OS-agnostic keys are:
channels
: where the packages will be downloaded from. We mainly rely onconda-forge
for this, wherenapari
is published. In CI, we locally build our own (development) packages forconda
, without resorting toconda-forge
. To make use of those (which are eventually published to the napari channel), we unpack the GitHub Actions artifact in a specific location thatconstructor
recognizes as a local channel once indexed.extra_envs> napari-0.5.4
: the environment that will actually contain the napari installation. In this key, you will findspecs
, which lists the conda packages to be installed in that environment. Constructor will perform a conda solve here to retrieve the needed dependencies.menu_packages
: restrict which packages can create shortcuts. We only want the shortcuts provided bynapari-menu
, and not any that could come from the (many) dependencies of napari.
Then, depending on the operating systems and the installer format, we customize the configuration a bit more.
Default installation path#
This depends on each OS. Our general strategy is to put the general installation under
~/<hidden>/napari-<VERSION>
, which will eventually contain the napari installations under
envs/
, with environments named as napari-<VERSION>
. However, there are several constrains we
need to take into account to make this happen:
On Windows, users can choose between an “Only me” and “All users” installation. This changes what we understand by “user directory”. This is further complicated by the existence of “domain users”, which are not guaranteed to have a user directory per se.
On macOS, the PKG installer does not offer a lot of flexibility for this configuration. We will put it under
~/Library/napari-<VERSION>
, by default.
This means that if you install napari=0.5.4
using the installer, the actual napari
executable
can be found, by default, on the following locations:
Linux:
~/.local/napari-0.5.4/envs/napari-0.5.4/bin/napari
macOS:
~/Library/napari-0.5.4/envs/napari-0.5.4/bin/napari
`Windows:
~/napari-0.5.4/envs/napari-0.5.4/Library/bin/napari
Branding#
Graphical installers can be customized with logos and icons. These images are stored under the
resources/
directory (outside the source), except for the square logos/icons (which
are stored under napari/resources/
so the shortcuts can find them after the installation).
Some steps are also configured to display a custom text, like the license or the welcome screen on macOS.
Signing#
In order to avoid security warnings on the target platform, we need to sign the generated installer.
On macOS, once Apple’s Installer Certificate has been installed to a keychain and unlocked
for its use, you can have constructor
handle the signing via productsign
automatically.
However, this is not enough for a warning-free installation, since its contents need to be
notarized and stapled too. For this reason, constructor
has been modified to also
codesign
the bundled _conda
executable (the binary provided by conda-standalone, see below) with the Application Certificate. Otherwise, notarization fails. After that, two actions take
care of notarizing and stapling the resulting PKG.
On Windows, any Microsoft-blessed certificate will do. constructor
allows us to specify
a path to a PFX certificate and then have the Windows SDK signtool
add the signature. Note that
signtool
is not installed by default on Windows (but it is on GitHub Actions). Right now, we
simply reuse the Apple certificate just to sign the installer with something. Note that this
certificate is not recognized by Windows as a valid one, so users will still get the SmartScreen
warning. However, it will allow folks to check the signature metadata and see that it comes
from napari.
More details about our packaging infrastructure can be found in the NAP-2 document.
Details of the constructor
stack#
Generating a conda
-based installer requires several components in place:
constructor
is the command-line tool that builds the installer.It depends on
conda
to solve thespecs
request.It also requires a copy of
conda-standalone
(a PyInstaller-frozen version ofconda
) to be present at build time so it can be bundled in the installer. This is needed because thatconda-standalone
copy will handle the extraction, linking and shortcut creation when the user runs the installer on their machine.
menuinst
handles the creation of shortcuts / desktop menu entries across all platforms.conda
depends on this library to handle shortcuts when packages are installed.constructor
delegates the shortcut creation toconda-standalone
’smenuinst
bundled copy at installation time.For performance reasons, uninstalling the shortcut is done via a bundled script that calls
menuinst
directly.