Introducing TestScribe, a "low code/no code" tool to make python testing easier by automating the boring and repetitive parts
Here is a quick demo. Here is more context for the demo.
Do you write unit tests but don’t like the overhead (create a file, name a function, write assertions…) or repetitiveness?
Have you experienced adjusting the mocking code multiple times before it allows the test to run? Do you have to refer to documentation from time to time to figure out how to mock or assert complex mock call parameters?
Do you wish to start a debugging session to understand a function better with as little overhead as possible?
Are you looking for an intuitive tool to help improve your code and coding skills?
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TestScribe can help. It will
Please see the project document for more details including more demo videos covering more complex scenarios and a FAQ. If you use Python, give it a try. It’s easy to set up and low-risk to try.?
I created the tool to scratch my own itch since I couldn't find a similar tool. After using this tool for over a year, I can’t go back to the old way of testing.? Believing this is a great way to improve developers’ productivity in general, I open-sourced it to give back to the community.
If you like it, I’d appreciate it if you share the tool/article/demo videos. Feedbacks are welcome. If you use other programming languages and like the concept or have feedback, I’d love to hear from you too.?
Here are a few ways to get in touch.
Retired
2 年TestScribe is reborn!
Analista Programador Senior en Praxis EMR
2 年That looks pretty cool! However I find it somewhat confusing because you every type of fake a "mock" whereas I prefer using Osherove or Fowler's way of calling them (fakes as a generic term, or more specifically stub when they return a fixed value, the calculator would be a stub, or mock when you want to know if the method you are testing called something specific from that mock, plus dummies and spies). Some examples look to be quite simplistic, like testing that your mock (or stub) returned the value you told it to return which is not really a test (but I guess it was just to keep the example very simple). Another thing that confuses me is that when you use a mock you don't usually test that the method return value is valid, for example if the method you want to test calls a service and you fake that service to return something, if that fake is a stub that always returns a value then you test the business logic that comes after that service call and that the method being tested return the correct value but if that fake is a mock then you only care that the call to the service was called, not the return value of the method. Like in the test_object_in_mock_call_param_g.py checking if result is None is unnecessary.