I’ve been using this function lsst.pipe.tasks.fakes over the past summer and had no issues doing so. However, I’m running into a case where the module is not found. The error is: ModuleNotFoundError: No module named ‘lsst.pipe.tasks.fakes’. My question is, did something get updated in the DM Stack that changed how the
fakes package gets called?
The old fakes code was deprecated a year and a half ago in DM-34452 (w_2022_17) and removed completely in DM-34496 for w_2023_27. It should have been issuing warnings for a long time. What version did you upgrade from?
Let us know what you’re trying to achieve @asvoboda, and we can help get you up to speed using the new tooling for
fake synthetic source injection now. As @timj mentioned above, you’re using a rather old instance of the fake source injection code base which has recently been completely removed.
Future synthetic source injection will make use of tooling in this repo: GitHub - lsst/source_injection: Synthetic Source Injection (SSI) tasks for the LSST Science Pipelines.
Thank you for getting back to me! So the notebook is modified from one of the delegate contributions for DP0.1, and it ran on the weekly 2022_12 version of the DM stack. It was running on the most recent version of the stack until it quit. What would be the best way to progress from here?
I’m not familiar with the notebook you’re referring to, so please do point me to it if you can. It should be possible for you to upgrade your tooling to work with our newer source injection framework, if that’s the way you want to go.
However, do you need to be running on the most recent version of the Science Pipelines? If not, an easier solution in your case may be to use an older version of the stack instead. The fakes code you’d been using was removed in the
w_2023_27 version, and my understanding is that the recommended weekly was just changed on the RSP from
w_2023_37. In this case, when spinning up your RSP instance, instead of selecting the recommended weekly you can click the drop-down list and select an older weekly instead.
Again, rolling back to an older version of the software may not be appropriate for the investigation you’re attempting. If not, please do let us know more information.
Thank you for the reply, and apologies for my delayed response. That’s helpful to know the fake code I’ve been using was removed in the w_2023_27 version. It was the solution I was looking for. I was able to roll back to an older version, specifically w_2023_26, and run through the notebook without error. Thank you very much for the help!