How to do a meaningful code-coverage analysis of my unit-tests?

Question

I manage the testing for a very large financial pricing system. Recently our HQ have insisted that we verify that every single part of our project has a meaningful test in p

Answer 1

For the code coverage alone, you could use coverage.py.

As for coverage.py vs figleaf:

figleaf differs from the gold standard of Python coverage tools ('coverage.py') in several ways. First and foremost, figleaf uses the same criterion for "interesting" lines of code as the sys.settrace function, which obviates some of the complexity in coverage.py (but does mean that your "loc" count goes down). Second, figleaf does not record code executed in the Python standard library, which results in a significant speedup. And third, the format in which the coverage format is saved is very simple and easy to work with.

You might want to use figleaf if you're recording coverage from multiple types of tests and need to aggregate the coverage in interesting ways, and/or control when coverage is recorded. coverage.py is a better choice for command-line execution, and its reporting is a fair bit nicer.

I guess both have their pros and cons.