Commit c1a36a35 authored by Jason R. Coombs's avatar Jason R. Coombs Committed by GitHub

Merge pull request #2111 from alvyjudy/doc

doc overhaul step 3: update userguide
parents 327eda0c 30db7409
doc overhaul step 3: update userguide
"Eggsecutable" Scripts
----------------------
.. deprecated:: 45.3.0
Occasionally, there are situations where it's desirable to make an ``.egg``
file directly executable. You can do this by including an entry point such
as the following::
setup(
# other arguments here...
entry_points={
"setuptools.installation": [
"eggsecutable = my_package.some_module:main_func",
]
}
)
Any eggs built from the above setup script will include a short executable
prelude that imports and calls ``main_func()`` from ``my_package.some_module``.
The prelude can be run on Unix-like platforms (including Mac and Linux) by
invoking the egg with ``/bin/sh``, or by enabling execute permissions on the
``.egg`` file. For the executable prelude to run, the appropriate version of
Python must be available via the ``PATH`` environment variable, under its
"long" name. That is, if the egg is built for Python 2.3, there must be a
``python2.3`` executable present in a directory on ``PATH``.
IMPORTANT NOTE: Eggs with an "eggsecutable" header cannot be renamed, or
invoked via symlinks. They *must* be invoked using their original filename, in
order to ensure that, once running, ``pkg_resources`` will know what project
and version is in use. The header script will check this and exit with an
error if the ``.egg`` file has been renamed or is invoked via a symlink that
changes its base name.
\ No newline at end of file
====================
Data Files Support
====================
The distutils have traditionally allowed installation of "data files", which
are placed in a platform-specific location. However, the most common use case
for data files distributed with a package is for use *by* the package, usually
by including the data files in the package directory.
Setuptools offers three ways to specify data files to be included in your
packages. First, you can simply use the ``include_package_data`` keyword,
e.g.::
from setuptools import setup, find_packages
setup(
...
include_package_data=True
)
This tells setuptools to install any data files it finds in your packages.
The data files must be specified via the distutils' ``MANIFEST.in`` file.
(They can also be tracked by a revision control system, using an appropriate
plugin. See the section below on `Adding Support for Revision Control
Systems`_ for information on how to write such plugins.)
If you want finer-grained control over what files are included (for example,
if you have documentation files in your package directories and want to exclude
them from installation), then you can also use the ``package_data`` keyword,
e.g.::
from setuptools import setup, find_packages
setup(
...
package_data={
# If any package contains *.txt or *.rst files, include them:
"": ["*.txt", "*.rst"],
# And include any *.msg files found in the "hello" package, too:
"hello": ["*.msg"],
}
)
The ``package_data`` argument is a dictionary that maps from package names to
lists of glob patterns. The globs may include subdirectory names, if the data
files are contained in a subdirectory of the package. For example, if the
package tree looks like this::
setup.py
src/
mypkg/
__init__.py
mypkg.txt
data/
somefile.dat
otherdata.dat
The setuptools setup file might look like this::
from setuptools import setup, find_packages
setup(
...
packages=find_packages("src"), # include all packages under src
package_dir={"": "src"}, # tell distutils packages are under src
package_data={
# If any package contains *.txt files, include them:
"": ["*.txt"],
# And include any *.dat files found in the "data" subdirectory
# of the "mypkg" package, also:
"mypkg": ["data/*.dat"],
}
)
Notice that if you list patterns in ``package_data`` under the empty string,
these patterns are used to find files in every package, even ones that also
have their own patterns listed. Thus, in the above example, the ``mypkg.txt``
file gets included even though it's not listed in the patterns for ``mypkg``.
Also notice that if you use paths, you *must* use a forward slash (``/``) as
the path separator, even if you are on Windows. Setuptools automatically
converts slashes to appropriate platform-specific separators at build time.
If datafiles are contained in a subdirectory of a package that isn't a package
itself (no ``__init__.py``), then the subdirectory names (or ``*``) are required
in the ``package_data`` argument (as shown above with ``"data/*.dat"``).
When building an ``sdist``, the datafiles are also drawn from the
``package_name.egg-info/SOURCES.txt`` file, so make sure that this is removed if
the ``setup.py`` ``package_data`` list is updated before calling ``setup.py``.
(Note: although the ``package_data`` argument was previously only available in
``setuptools``, it was also added to the Python ``distutils`` package as of
Python 2.4; there is `some documentation for the feature`__ available on the
python.org website. If using the setuptools-specific ``include_package_data``
argument, files specified by ``package_data`` will *not* be automatically
added to the manifest unless they are listed in the MANIFEST.in file.)
__ https://docs.python.org/3/distutils/setupscript.html#installing-package-data
Sometimes, the ``include_package_data`` or ``package_data`` options alone
aren't sufficient to precisely define what files you want included. For
example, you may want to include package README files in your revision control
system and source distributions, but exclude them from being installed. So,
setuptools offers an ``exclude_package_data`` option as well, that allows you
to do things like this::
from setuptools import setup, find_packages
setup(
...
packages=find_packages("src"), # include all packages under src
package_dir={"": "src"}, # tell distutils packages are under src
include_package_data=True, # include everything in source control
# ...but exclude README.txt from all packages
exclude_package_data={"": ["README.txt"]},
)
The ``exclude_package_data`` option is a dictionary mapping package names to
lists of wildcard patterns, just like the ``package_data`` option. And, just
as with that option, a key of ``""`` will apply the given pattern(s) to all
packages. However, any files that match these patterns will be *excluded*
from installation, even if they were listed in ``package_data`` or were
included as a result of using ``include_package_data``.
In summary, the three options allow you to:
``include_package_data``
Accept all data files and directories matched by ``MANIFEST.in``.
``package_data``
Specify additional patterns to match files that may or may
not be matched by ``MANIFEST.in`` or found in source control.
``exclude_package_data``
Specify patterns for data files and directories that should *not* be
included when a package is installed, even if they would otherwise have
been included due to the use of the preceding options.
NOTE: Due to the way the distutils build process works, a data file that you
include in your project and then stop including may be "orphaned" in your
project's build directories, requiring you to run ``setup.py clean --all`` to
fully remove them. This may also be important for your users and contributors
if they track intermediate revisions of your project using Subversion; be sure
to let them know when you make changes that remove files from inclusion so they
can run ``setup.py clean --all``.
Accessing Data Files at Runtime
-------------------------------
Typically, existing programs manipulate a package's ``__file__`` attribute in
order to find the location of data files. However, this manipulation isn't
compatible with PEP 302-based import hooks, including importing from zip files
and Python Eggs. It is strongly recommended that, if you are using data files,
you should use the :ref:`ResourceManager API` of ``pkg_resources`` to access
them. The ``pkg_resources`` module is distributed as part of setuptools, so if
you're using setuptools to distribute your package, there is no reason not to
use its resource management API. See also `Importlib Resources`_ for
a quick example of converting code that uses ``__file__`` to use
``pkg_resources`` instead.
.. _Importlib Resources: https://docs.python.org/3/library/importlib.html#module-importlib.resources
Non-Package Data Files
----------------------
Historically, ``setuptools`` by way of ``easy_install`` would encapsulate data
files from the distribution into the egg (see `the old docs
<https://github.com/pypa/setuptools/blob/52aacd5b276fedd6849c3a648a0014f5da563e93/docs/setuptools.txt#L970-L1001>`_). As eggs are deprecated and pip-based installs
fall back to the platform-specific location for installing data files, there is
no supported facility to reliably retrieve these resources.
Instead, the PyPA recommends that any data files you wish to be accessible at
run time be included in the package.
\ No newline at end of file
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"Development Mode"
==================
Under normal circumstances, the ``distutils`` assume that you are going to
build a distribution of your project, not use it in its "raw" or "unbuilt"
form. If you were to use the ``distutils`` that way, you would have to rebuild
and reinstall your project every time you made a change to it during
development.
Another problem that sometimes comes up with the ``distutils`` is that you may
need to do development on two related projects at the same time. You may need
to put both projects' packages in the same directory to run them, but need to
keep them separate for revision control purposes. How can you do this?
Setuptools allows you to deploy your projects for use in a common directory or
staging area, but without copying any files. Thus, you can edit each project's
code in its checkout directory, and only need to run build commands when you
change a project's C extensions or similarly compiled files. You can even
deploy a project into another project's checkout directory, if that's your
preferred way of working (as opposed to using a common independent staging area
or the site-packages directory).
To do this, use the ``setup.py develop`` command. It works very similarly to
``setup.py install``, except that it doesn't actually install anything.
Instead, it creates a special ``.egg-link`` file in the deployment directory,
that links to your project's source code. And, if your deployment directory is
Python's ``site-packages`` directory, it will also update the
``easy-install.pth`` file to include your project's source code, thereby making
it available on ``sys.path`` for all programs using that Python installation.
If you have enabled the ``use_2to3`` flag, then of course the ``.egg-link``
will not link directly to your source code when run under Python 3, since
that source code would be made for Python 2 and not work under Python 3.
Instead the ``setup.py develop`` will build Python 3 code under the ``build``
directory, and link there. This means that after doing code changes you will
have to run ``setup.py build`` before these changes are picked up by your
Python 3 installation.
In addition, the ``develop`` command creates wrapper scripts in the target
script directory that will run your in-development scripts after ensuring that
all your ``install_requires`` packages are available on ``sys.path``.
You can deploy the same project to multiple staging areas, e.g. if you have
multiple projects on the same machine that are sharing the same project you're
doing development work.
When you're done with a given development task, you can remove the project
source from a staging area using ``setup.py develop --uninstall``, specifying
the desired staging area if it's not the default.
There are several options to control the precise behavior of the ``develop``
command; see the section on the `develop`_ command below for more details.
Note that you can also apply setuptools commands to non-setuptools projects,
using commands like this::
python -c "import setuptools; with open('setup.py') as f: exec(compile(f.read(), 'setup.py', 'exec'))" develop
That is, you can simply list the normal setup commands and options following
the quoted part.
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==========================================
Entry Points and Automatic Script Creation
==========================================
Packaging and installing scripts can be a bit awkward with the distutils. For
one thing, there's no easy way to have a script's filename match local
conventions on both Windows and POSIX platforms. For another, you often have
to create a separate file just for the "main" script, when your actual "main"
is a function in a module somewhere. And even in Python 2.4, using the ``-m``
option only works for actual ``.py`` files that aren't installed in a package.
``setuptools`` fixes all of these problems by automatically generating scripts
for you with the correct extension, and on Windows it will even create an
``.exe`` file so that users don't have to change their ``PATHEXT`` settings.
The way to use this feature is to define "entry points" in your setup script
that indicate what function the generated script should import and run. For
example, to create two console scripts called ``foo`` and ``bar``, and a GUI
script called ``baz``, you might do something like this::
setup(
# other arguments here...
entry_points={
"console_scripts": [
"foo = my_package.some_module:main_func",
"bar = other_module:some_func",
],
"gui_scripts": [
"baz = my_package_gui:start_func",
]
}
)
When this project is installed on non-Windows platforms (using "setup.py
install", "setup.py develop", or with pip), a set of ``foo``, ``bar``,
and ``baz`` scripts will be installed that import ``main_func`` and
``some_func`` from the specified modules. The functions you specify are
called with no arguments, and their return value is passed to
``sys.exit()``, so you can return an errorlevel or message to print to
stderr.
On Windows, a set of ``foo.exe``, ``bar.exe``, and ``baz.exe`` launchers are
created, alongside a set of ``foo.py``, ``bar.py``, and ``baz.pyw`` files. The
``.exe`` wrappers find and execute the right version of Python to run the
``.py`` or ``.pyw`` file.
You may define as many "console script" and "gui script" entry points as you
like, and each one can optionally specify "extras" that it depends on, that
will be added to ``sys.path`` when the script is run. For more information on
"extras", see the section below on `Declaring Extras`_. For more information
on "entry points" in general, see the section below on `Dynamic Discovery of
Services and Plugins`_.
Dynamic Discovery of Services and Plugins
-----------------------------------------
``setuptools`` supports creating libraries that "plug in" to extensible
applications and frameworks, by letting you register "entry points" in your
project that can be imported by the application or framework.
For example, suppose that a blogging tool wants to support plugins
that provide translation for various file types to the blog's output format.
The framework might define an "entry point group" called ``blogtool.parsers``,
and then allow plugins to register entry points for the file extensions they
support.
This would allow people to create distributions that contain one or more
parsers for different file types, and then the blogging tool would be able to
find the parsers at runtime by looking up an entry point for the file
extension (or mime type, or however it wants to).
Note that if the blogging tool includes parsers for certain file formats, it
can register these as entry points in its own setup script, which means it
doesn't have to special-case its built-in formats. They can just be treated
the same as any other plugin's entry points would be.
If you're creating a project that plugs in to an existing application or
framework, you'll need to know what entry points or entry point groups are
defined by that application or framework. Then, you can register entry points
in your setup script. Here are a few examples of ways you might register an
``.rst`` file parser entry point in the ``blogtool.parsers`` entry point group,
for our hypothetical blogging tool::
setup(
# ...
entry_points={"blogtool.parsers": ".rst = some_module:SomeClass"}
)
setup(
# ...
entry_points={"blogtool.parsers": [".rst = some_module:a_func"]}
)
setup(
# ...
entry_points="""
[blogtool.parsers]
.rst = some.nested.module:SomeClass.some_classmethod [reST]
""",
extras_require=dict(reST="Docutils>=0.3.5")
)
The ``entry_points`` argument to ``setup()`` accepts either a string with
``.ini``-style sections, or a dictionary mapping entry point group names to
either strings or lists of strings containing entry point specifiers. An
entry point specifier consists of a name and value, separated by an ``=``
sign. The value consists of a dotted module name, optionally followed by a
``:`` and a dotted identifier naming an object within the module. It can
also include a bracketed list of "extras" that are required for the entry
point to be used. When the invoking application or framework requests loading
of an entry point, any requirements implied by the associated extras will be
passed to ``pkg_resources.require()``, so that an appropriate error message
can be displayed if the needed package(s) are missing. (Of course, the
invoking app or framework can ignore such errors if it wants to make an entry
point optional if a requirement isn't installed.)
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========================================================
Using setuptools to package and distribute your project
========================================================
``setuptools`` offers a variety of functionalities that make it easy to
build and distribute your python package. Here we provide an overview on
the commonly used ones.
......@@ -13,8 +13,14 @@ ordinary Python packages based on the ``distutils``.
.. toctree::
:maxdepth: 1
Quickstart <quickstart>
Functionalities <functionalities>
Declarative config <declarative_config>
keyword reference <keywords>
Command reference <commands>
quickstart
package_discovery
entry_point
dependency_management
datafiles
development_mode
distribution
extension
declarative_config
keywords
commands
Automatic Resource Extraction
-----------------------------
If you are using tools that expect your resources to be "real" files, or your
project includes non-extension native libraries or other files that your C
extensions expect to be able to access, you may need to list those files in
the ``eager_resources`` argument to ``setup()``, so that the files will be
extracted together, whenever a C extension in the project is imported.
This is especially important if your project includes shared libraries *other*
than distutils-built C extensions, and those shared libraries use file
extensions other than ``.dll``, ``.so``, or ``.dylib``, which are the
extensions that setuptools 0.6a8 and higher automatically detects as shared
libraries and adds to the ``native_libs.txt`` file for you. Any shared
libraries whose names do not end with one of those extensions should be listed
as ``eager_resources``, because they need to be present in the filesystem when
he C extensions that link to them are used.
The ``pkg_resources`` runtime for compressed packages will automatically
extract *all* C extensions and ``eager_resources`` at the same time, whenever
*any* C extension or eager resource is requested via the ``resource_filename()``
API. (C extensions are imported using ``resource_filename()`` internally.)
This ensures that C extensions will see all of the "real" files that they
expect to see.
Note also that you can list directory resource names in ``eager_resources`` as
well, in which case the directory's contents (including subdirectories) will be
extracted whenever any C extension or eager resource is requested.
Please note that if you're not sure whether you need to use this argument, you
don't! It's really intended to support projects with lots of non-Python
dependencies and as a last resort for crufty projects that can't otherwise
handle being compressed. If your package is pure Python, Python plus data
files, or Python plus C, you really don't need this. You've got to be using
either C or an external program that needs "real" files in your project before
there's any possibility of ``eager_resources`` being relevant to your project.
Defining Additional Metadata
----------------------------
Some extensible applications and frameworks may need to define their own kinds
of metadata to include in eggs, which they can then access using the
``pkg_resources`` metadata APIs. Ordinarily, this is done by having plugin
developers include additional files in their ``ProjectName.egg-info``
directory. However, since it can be tedious to create such files by hand, you
may want to create a distutils extension that will create the necessary files
from arguments to ``setup()``, in much the same way that ``setuptools`` does
for many of the ``setup()`` arguments it adds. See the section below on
`Creating distutils Extensions`_ for more details, especially the subsection on
`Adding new EGG-INFO Files`_.
Setting the ``zip_safe`` flag
-----------------------------
For some use cases (such as bundling as part of a larger application), Python
packages may be run directly from a zip file.
Not all packages, however, are capable of running in compressed form, because
they may expect to be able to access either source code or data files as
normal operating system files. So, ``setuptools`` can install your project
as a zipfile or a directory, and its default choice is determined by the
project's ``zip_safe`` flag.
You can pass a True or False value for the ``zip_safe`` argument to the
``setup()`` function, or you can omit it. If you omit it, the ``bdist_egg``
command will analyze your project's contents to see if it can detect any
conditions that would prevent it from working in a zipfile. It will output
notices to the console about any such conditions that it finds.
Currently, this analysis is extremely conservative: it will consider the
project unsafe if it contains any C extensions or datafiles whatsoever. This
does *not* mean that the project can't or won't work as a zipfile! It just
means that the ``bdist_egg`` authors aren't yet comfortable asserting that
the project *will* work. If the project contains no C or data files, and does
no ``__file__`` or ``__path__`` introspection or source code manipulation, then
there is an extremely solid chance the project will work when installed as a
zipfile. (And if the project uses ``pkg_resources`` for all its data file
access, then C extensions and other data files shouldn't be a problem at all.
See the `Accessing Data Files at Runtime`_ section above for more information.)
However, if ``bdist_egg`` can't be *sure* that your package will work, but
you've checked over all the warnings it issued, and you are either satisfied it
*will* work (or if you want to try it for yourself), then you should set
``zip_safe`` to ``True`` in your ``setup()`` call. If it turns out that it
doesn't work, you can always change it to ``False``, which will force
``setuptools`` to install your project as a directory rather than as a zipfile.
In the future, as we gain more experience with different packages and become
more satisfied with the robustness of the ``pkg_resources`` runtime, the
"zip safety" analysis may become less conservative. However, we strongly
recommend that you determine for yourself whether your project functions
correctly when installed as a zipfile, correct any problems if you can, and
then make an explicit declaration of ``True`` or ``False`` for the ``zip_safe``
flag, so that it will not be necessary for ``bdist_egg`` to try to guess
whether your project can work as a zipfile.
===================
Package Discovery
===================
``Setuptools`` provide powerful tools to handle package discovery, including
support for namespace package. The following explain how you include package
in your ``setup`` script::
setup(
packages = ['mypkg1', 'mypkg2']
)
To speed things up, we introduce two functions provided by setuptools::
from setuptools import find_packages
or::
from setuptools import find_namespace_packages
Using ``find_packages()``
-------------------------
Let's start with the first tool.
``find_packages()`` takes a source directory and two lists of package name
patterns to exclude and include. If omitted, the source directory defaults to
the same
directory as the setup script. Some projects use a ``src`` or ``lib``
directory as the root of their source tree, and those projects would of course
use ``"src"`` or ``"lib"`` as the first argument to ``find_packages()``. (And
such projects also need something like ``package_dir={"": "src"}`` in their
``setup()`` arguments, but that's just a normal distutils thing.)
Anyway, ``find_packages()`` walks the target directory, filtering by inclusion
patterns, and finds Python packages (any directory). Packages are only
recognized if they include an ``__init__.py`` file. Finally, exclusion
patterns are applied to remove matching packages.
Inclusion and exclusion patterns are package names, optionally including
wildcards. For
example, ``find_packages(exclude=["*.tests"])`` will exclude all packages whose
last name part is ``tests``. Or, ``find_packages(exclude=["*.tests",
"*.tests.*"])`` will also exclude any subpackages of packages named ``tests``,
but it still won't exclude a top-level ``tests`` package or the children
thereof. In fact, if you really want no ``tests`` packages at all, you'll need
something like this::
find_packages(exclude=["*.tests", "*.tests.*", "tests.*", "tests"])
in order to cover all the bases. Really, the exclusion patterns are intended
to cover simpler use cases than this, like excluding a single, specified
package and its subpackages.
Regardless of the parameters, the ``find_packages()``
function returns a list of package names suitable for use as the ``packages``
argument to ``setup()``, and so is usually the easiest way to set that
argument in your setup script. Especially since it frees you from having to
remember to modify your setup script whenever your project grows additional
top-level packages or subpackages.
``find_namespace_packages()``
-----------------------------
In Python 3.3+, ``setuptools`` also provides the ``find_namespace_packages`` variant
of ``find_packages``, which has the same function signature as
``find_packages``, but works with `PEP 420`_ compliant implicit namespace
packages. Here is a minimal setup script using ``find_namespace_packages``::
from setuptools import setup, find_namespace_packages
setup(
name="HelloWorld",
version="0.1",
packages=find_namespace_packages(),
)
Keep in mind that according to PEP 420, you may have to either re-organize your
codebase a bit or define a few exclusions, as the definition of an implicit
namespace package is quite lenient, so for a project organized like so::
├── namespace
│   └── mypackage
│   ├── __init__.py
│   └── mod1.py
├── setup.py
└── tests
└── test_mod1.py
A naive ``find_namespace_packages()`` would install both ``namespace.mypackage`` and a
top-level package called ``tests``! One way to avoid this problem is to use the
``include`` keyword to whitelist the packages to include, like so::
from setuptools import setup, find_namespace_packages
setup(
name="namespace.mypackage",
version="0.1",
packages=find_namespace_packages(include=["namespace.*"])
)
Another option is to use the "src" layout, where all package code is placed in
the ``src`` directory, like so::
├── setup.py
├── src
│   └── namespace
│   └── mypackage
│   ├── __init__.py
│   └── mod1.py
└── tests
└── test_mod1.py
With this layout, the package directory is specified as ``src``, as such::
setup(name="namespace.mypackage",
version="0.1",
package_dir={"": "src"},
packages=find_namespace_packages(where="src"))
.. _PEP 420: https://www.python.org/dev/peps/pep-0420/
Namespace Packages
------------------
Sometimes, a large package is more useful if distributed as a collection of
smaller eggs. However, Python does not normally allow the contents of a
package to be retrieved from more than one location. "Namespace packages"
are a solution for this problem. When you declare a package to be a namespace
package, it means that the package has no meaningful contents in its
``__init__.py``, and that it is merely a container for modules and subpackages.
The ``pkg_resources`` runtime will then automatically ensure that the contents
of namespace packages that are spread over multiple eggs or directories are
combined into a single "virtual" package.
The ``namespace_packages`` argument to ``setup()`` lets you declare your
project's namespace packages, so that they will be included in your project's
metadata. The argument should list the namespace packages that the egg
participates in. For example, the ZopeInterface project might do this::
setup(
# ...
namespace_packages=["zope"]
)
because it contains a ``zope.interface`` package that lives in the ``zope``
namespace package. Similarly, a project for a standalone ``zope.publisher``
would also declare the ``zope`` namespace package. When these projects are
installed and used, Python will see them both as part of a "virtual" ``zope``
package, even though they will be installed in different locations.
Namespace packages don't have to be top-level packages. For example, Zope 3's
``zope.app`` package is a namespace package, and in the future PEAK's
``peak.util`` package will be too.
Note, by the way, that your project's source tree must include the namespace
packages' ``__init__.py`` files (and the ``__init__.py`` of any parent
packages), in a normal Python package layout. These ``__init__.py`` files
*must* contain the line::
__import__("pkg_resources").declare_namespace(__name__)
This code ensures that the namespace package machinery is operating and that
the current package is registered as a namespace package.
You must NOT include any other code and data in a namespace package's
``__init__.py``. Even though it may appear to work during development, or when
projects are installed as ``.egg`` files, it will not work when the projects
are installed using "system" packaging tools -- in such cases the
``__init__.py`` files will not be installed, let alone executed.
You must include the ``declare_namespace()`` line in the ``__init__.py`` of
*every* project that has contents for the namespace package in question, in
order to ensure that the namespace will be declared regardless of which
project's copy of ``__init__.py`` is loaded first. If the first loaded
``__init__.py`` doesn't declare it, it will never *be* declared, because no
other copies will ever be loaded!
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