You're spot on with all of this. I've been meaning to do a follow-on article for Scientist that explores this more both for data modification as well as for potentially impacting methods like E-Mail sending or external API calls.
You can use Scientist, but you have to structure your routines in such a way that they're essentially pure.
One more idea that just came to my mind is to have a complete copy of the data, which would enable you to verify afterwards, if the new routine correctly mutates the data as well as returning the expecting result.
So you can run legacy and new routines side by side for a couple days, then make a diff between databases, and see how the new code creates different data. Some of the changes might be within tolerances, for things like timestamps that aren't the same down to the microsecond, but for many fields this would probably work quite well. Just a thought.
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You're spot on with all of this. I've been meaning to do a follow-on article for Scientist that explores this more both for data modification as well as for potentially impacting methods like E-Mail sending or external API calls.
You can use Scientist, but you have to structure your routines in such a way that they're essentially pure.
One more idea that just came to my mind is to have a complete copy of the data, which would enable you to verify afterwards, if the new routine correctly mutates the data as well as returning the expecting result.
So you can run legacy and new routines side by side for a couple days, then make a diff between databases, and see how the new code creates different data. Some of the changes might be within tolerances, for things like timestamps that aren't the same down to the microsecond, but for many fields this would probably work quite well. Just a thought.