Options for packaging your Python code: Wheels, Conda, Docker, and more

There is also zip app [1] if you already have python installed<p>[1] <a href="https:&#x2F;&#x2F;docs.python.org&#x2F;3&#x2F;library&#x2F;zipapp.html" rel="nofollow">https:&#x2F;&#x2F;docs.python.org&#x2F;3&#x2F;library&#x2F;zipapp.html</a>

This seems to be focused on packaging <i>applications</i>, and suggests that wheel is not good enough if you have a dependency on a C library. I am surprised since I thought you could embed a C library in a wheel.<p>I would like to know, is wheel+pypi an acceptable way to go to package and distributed a Python <i>library</i> that includes a C library (so&#x2F;dll)?<p>I get the impression that big libraries like numpy and tensorflow use this method to pretty good effect. It seems easier than trying to compile the C libraries on the target machine, but is it quite difficult to achieve multiplatform support this way?

&gt; The Conda package system packages both Python packages and C shared libraries and the Python interpreter into Conda packages.<p>This doesn&#x27;t sound correct. Conda packages don&#x27;t actually include the entire Python interpreter in them right?<p>A prerequisite to installing Conda packages is to have Anaconda&#x2F;Miniconda installed which brings in the Python interpreter and a given set of packages depending on the version you install but that doesn&#x27;t mean that each Conda package will be carrying the interpreter with it.