Profile and Optimize the codebase

The goal is to do a profiling of the codebase with a simple set of exhaustive examples, to get a good sense of where compute resources are used, and which parts are the most resource heavy. Parts which can be ill-optimized should jump out in that case.

Good to do this before the public release of the package.

Ref:

• https://opensource.com/article/18/7/fun-perf-and-python
• https://stackoverflow.com/questions/582336/how-can-you-profile-a-python-script

TODOs

• benchmark and profile all examples in a new daily scheduled job -> !69 (diffs)
• benchmark and profile all notebooks (since examples will be moved to notebooks)
• coverage of running examples/notebooks/baelines separate from unit test coverage
• run baselines in a new daily scheduled job for integration testing (in the same way as benchmarks and profiling)
• define acceptance limits on benchmarks or use it for further reference only?
• documentation