Traditionally, high performance kernels (HPKs) have been written in
statically typed languages, such as C/C++ and Fortran.  A recent trend
among scientists--prototyping applications in dynamic languages such
as Python--created a gap between the applications and existing HPKs.
Thus, scientists have to either reimplement necessary kernels or
manually create a connection layer to leverage existing kernels.
Either option requires substantial development effort and slows down
progress in science.  We present a technique, dubbed WAYOUT, which
automatically generates the entire connection layer for HPKs invoked
from Python and written in C/C++.  WAYOUT performs a hybrid analysis:
it statically analyzes header files to generate Python wrapper classes
and functions, and dynamically generates bindings for those kernels.
By leveraging the type information available at run-time, it generates
only the necessary bindings.  We evaluate WAYOUT by rewriting dozens
of existing examples from C/C++ to Python and leveraging HPKs enabled
by WAYOUT.  Our experiments show the feasibility of our technique, as
well as negligible performance overhead on HPKs performance.