Remove splitting into passing and failing test suite.

Previously, we consider a test case passing if it did not raise any exception during its execution; it was considered failing otherwise. Pynguin did a split of the test cases into two test suites before exporting them. This was mainly an artefact from implementing the random algorithm in the very beginning of the project. Due to the improved assertion export for exception assertions we can now get rid of the split and export only one test module containing all generated test cases.

Remove the option to use a log file (--log_file or --log-file).

Pynguin writes its output to STDOUT/STDERR now, if requested by the -v/-vv switch. This output is formatted by @willmcgugan‘s amazing rich library. A user can disable the output formatting by setting the --no-rich flag. Of course, because we believe that rich is such an awesome library, we also provide an alias for this flag, called --poor 😉

Distinguish between expected and unexpected exceptions.

We consider an exception to be expected if it is explicitly raised in the code under test or is documented in the code’s docstring. For those exceptions we build an with pytest.raises block around the exception-raising statement. All other exceptions are considered to be unexpected. We decorate the test method with the @pytest.mark.xfail decorator and let the exception happen. It is up to the user to decide whether such an exception is expected. An exception here is the AssertionError: it is considered to be expected as soon as there is an assert statement in the code under test.

Improve installation description to explicitly point to using a virtual environment (see GitHub issue #23, thanks to @tuckcodes).

Improve variable names and exception assertions

The assertion generation got an improved handling for asserting on exceptions, which creates more meaningful and (hopefully) better understandable assertions for exceptions.

Enhance the module analysis

This is basically a rewrite of our previously existing test cluster, which keeps track of all the callables from the subject under test as well as the subject’s dependencies. It also incorporates an analysis of the subject’s AST (if present) and allows for more and more precise information about the subject which can then improve the quality of the generated tests.

To distinguish bytecode instructions during instrumentation we add an ArtificialInstr for our own added instructions.

Fix a bug in the tracing of runtime types.

During assertion generation Pynguin tracks the variable types to decide for which values it actually is able to generate assertions. Creating an assertion on a generator function does not work, as the type is not exposed by Python but only present during runtime—thus generating an object of this type always fail. We mitigate this by ignoring objects of type builtins.generator from the assertion generation.

Improve documentation regarding coverage measurement and the coverage report