I think it's less an issue of the average programmer using FFI and more an issue of common libraries leveraging it.
With python, why is it so popular currently? For large part because of its very good data science and machine learning ecosystem. And why does that exist? Mostly because python libraries like numpy, theano, and scikit-learn were built on top of mature, high-performance C libraries like OpenBLAS, LAPACK, and Cuda.
I very much doubt that anything like scipy would exist if the developers had to reinvent the wheel of the underlying numbers libraries from scratch. C's been around a long-time. There's huge amounts of high-quality mature software that already exists in a C framework. A language's ability to easily "plug-in" to the C ecosystem is a major leg-up when it comes to bootstrapping its own comprehensive library ecosystem.
With python, why is it so popular currently? For large part because of its very good data science and machine learning ecosystem. And why does that exist? Mostly because python libraries like numpy, theano, and scikit-learn were built on top of mature, high-performance C libraries like OpenBLAS, LAPACK, and Cuda.
I very much doubt that anything like scipy would exist if the developers had to reinvent the wheel of the underlying numbers libraries from scratch. C's been around a long-time. There's huge amounts of high-quality mature software that already exists in a C framework. A language's ability to easily "plug-in" to the C ecosystem is a major leg-up when it comes to bootstrapping its own comprehensive library ecosystem.