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I would like to have several python sub modules inside a main module, but I want to distribute them as separated python packages. So package A should provide 'my_data.source_a', package B should provide 'my_data.source_b', ... and so on.
I found out that I have to use a namespace package for this, but trying to figuring out the details, I found multiple PEPs covering that problem. PEP 420 seems to be the latest one, which builds upon PEP 402 and PEP 382.
To me it's not clear what the status of the different PEPs an implementations is. So my question is: Is http://pythonhosted.org/distribute/setuptools.html#namespace-packages still the way to go or how should I build my namespace package?
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Namespace packages are a mechanism for splitting a single Python package across multiple directories on disk. In current Python versions, an algorithm to compute the packages __path__ must be formulated.
Importing is a way of pulling a name from somewhere else into the desired namespace. To refer to a variable, function, or class in Python one of the following must be true: The name is in the Python built-in namespace. The name is the current module's global namespace.
Python subpackages To access subpackages, we use the dot operator. This is the __init__.py file in the constants directory. We import the names tuple. This is the data.py module in the constants directory.
A Python package is nothing but a collection of modules along with a __init__.py file. The modules can also be arranged in hierarchy of folders inside a package. Just by adding an empty __init__.py file to the in the folder, Python knows it is a Package.
The Python documentation has a good description of the three ways of creating namespace packages in Python, including guidelines for when to use each of the three methods. Furthermore, this topic is discussed in great depth in a different StackOverflow thread which has a good accepted answer. Finally, if you are someone who would rather read code than documentation, the sample-namespace-packages repo contains examples of namespace packages created using each of the three available methods.
In brief, if you intend your packages to work with Python versions 3.3 and above, you should use the native namespace packages method. If you intend your packages to work with older versions of Python, you should use the pkgutil method. If you intend to add a namespace package to a namespace that is already using the pkg_resources method, you should continue to use method.
With native namespace packages, we can remove __init__.py from both packages and modify our setup.py files to look as follows:
# setup.py file for my_data.source_a
from setuptools import setup, find_namespace_packages
setup(
name="my_data.source_a",
version="0.1",
packages=find_namespace_packages(include=['my_data.*'])
)
# setup.py file for my_data.source_b
from setuptools import setup, find_namespace_packages
setup(
name="my_data.source_b",
version="0.1",
packages=find_namespace_packages(include=['my_data.*'])
)
We need to add the include=['my_data.*'] argument because, by default find_namespace_packages() is rather lenient in the folders that it includes as namespace packages, as described here.
This is the recommended approach for packages supporting Python 3.3 and above.
With pkgutil-style namespace packages, we need to add the following line to the my_data.__init__.py files in each of our packages:
__path__ = __import__('pkgutil').extend_path(__path__, __name__)
This is the approach used by the backports namespace, and by different packages in the google-cloud-python repo, and it is the recommended approach for supporting older versions of Python.
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