I have been working with virtualenv and pip to create isolated Python environments and replicatable builds. However, I have encountered a (probably common) situation that I don't know how to configure, and can't seem to find any examples of.
SCENARIO: The Python project you are developing has a dependency on a (non-Python) shared library (potentially a particular version or range of versions). How do you specify that a specific shared library is to be installed and how do you make sure it is accessible by the virtual environment? Examples: * GDAL Python bindings (which depend on libgdal and numpy) * Shapely (which depends on libgeos_c) Or maybe I shouldn't be worrying about this. Is it a standard practice to just assume a manual installation of a shared libraries on the development or production system? If so, how would you deal with several virtual environments with dependencies on different versions a shared library? - Tyler
