Coverage.py vs. Python vs. TaffyDB vs. scikit-image Comparison Chart

Coverage.py is a tool for measuring code coverage of Python programs. It monitors your program, noting which parts of the code have been executed, then analyzes the source to identify code that could have been executed but was not. Coverage measurement is typically used to gauge the effectiveness of tests. It can show which parts of your code are being exercised by tests, and which are not. Use coverage run to run your test suite and gather data. However you normally run your test suite, and you can run your test runner under coverage. If your test runner command starts with “python”, just replace the initial “python” with “coverage run”. To limit coverage measurement to code in the current directory, and also find files that weren’t executed at all, add the source argument to your coverage command line. By default, it will measure line (statement) coverage. It can also measure branch coverage. It can tell you what tests ran which lines.

​TaffyDB is an open source JavaScript library that brings powerful database functionality into your JavaScript applications. It offers a small file size with extremely fast queries and a powerful JavaScript-centric data selection engine. TaffyDB includes database-inspired features such as count, update, and insert, and provides robust cross-browser support. It is easily extended with your own functions and is compatible with any DOM library, as well as server-side JavaScript. Creating a database is straightforward, you can create a new empty database, a database with a single object, an array, or a JSON string. Once you have a database, you can run queries against it by calling the root function and building filter objects. TaffyDB allows you to filter using the database name and object comparison, access data easily, and modify data on the fly. You can also use functions to give you full control over the results of your query.