I'm honestly hitting a wall with this Claude Code setup and it's driving me nuts. I have this massive Python backend for a delivery app we're launching in like ten days and our test coverage is basically zero right now. I'm torn between two ways of using the CLI tool. One way is just using the execute command to let it script out entire test files from scratch, but then I'm worried it's gonna hallucinate a bunch of mocks that dont actually exist in our repo. My other logic was just sticking to the interactive mode and having it iterate on existing broken tests, but that feels so slow when I have like fifty modules to cover. I'm on a super tight budget too since we're bootstrapping this and I dont want to burn through my API credits in one afternoon just running loops that go nowhere. Ive been trying to figure out if the test skill specifically is better for Pytest integration or if I should just use the general coding skill and point it at my files. It keeps trying to rewrite my conftest.py which is breaking everything. Does anyone know which specific skill set or workflow actually handles Python mocking without losing its mind? I need to get this done by next Friday or our lead dev is gonna kill me...
Saw this earlier but just now responding. Unfortunately, the Claude Code test skill is pretty disappointing with complex Pytest setups since it struggles with fixture scope.
I ran into this with a legacy Flask app last month. I compared using Aider AI Coding Assistant versus a custom loop with OpenAI GPT-4o-2024-05-13.
I went through this mess last year with a Django project. Using the execute command was messy because it hallucinated mocks, but the edit skill combined with Anthropic Claude 3.5 Sonnet API was a decent option. It actually respects your local imports. I found that feeding it specific file paths in interactive mode prevented it from touching my conftest.py and saved me a ton of credits.