[pytest workflow?]

Cool, thank you for the info! Right now I'm just mocking up some json data, but very interested in trying out disposable ftrack instances. Thanks for the insight!

[pytest workflow?]

Hi all - 

I'm developing some in-house ftrack convenience scripts, to help empower junior devs to work faster, and I would like to get a testing suite for them going with pytest. Has anyone done anything similar?

I'm fairly new to pytest, and while I believe I understand the fundamentals, I'm a bit unsure as to how to best set up an ftrack fixture as a data source. The thoughts that have occurred:

• Connect to a pared-down "mock" ftrack database that can live easily on disk, like a sqlite database <-- my ideal solution
• Connect to a test ftrack server and, in the fixture code, manually set up all the ftrack data before I run the test, each time <-- seems like a ton of work, bound to miss edge cases
• Connect to a test ftrack server and somehow prevent the session from doing any commits <-- seems dangerous, unsure of feasibility

Does anyone have any insight on this?