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Learn how to collect coverage data for every request in Python web servers using coverage.py. This approach offers granular insights into code execution, identifies untested paths, and enables deduplication for efficient test suites, enhancing overall code quality and development efficiency.

Code coverage is a poor metric for indicating whether or not your code has been tested well. Instead, we should invert the metric, and use the term “Legacy Code”.

Unit test coverage – the percentage of source code for which unit tests have been written - is a measure of how much of an application’s source code is 'touched' by tests. While 100% coverage is often unattainable (because not all code may be suitable for testing), 70% to 80% coverage are considered a robust testing suite. Automated test generation tools can be especially...