Cheryl... I do everything from conda to ensure that I have the right environment selected. Ignore the updates available in the Package Manager, it doesn't appear to 'see' what conda 'knows'
Now... having said that. If you have full rights to your computer (ie not muzzled by work limitations'), I no longer 'clone', hence my other blog
/blogs/dan_patterson/2018/12/28/clone
What I do when a new version of ArcGIS Pro comes out is look at it as an opportunity to freshen up my computer.
I remove all vestiges of Arc* from my machine (keeping a copy of 'pinned' and 'environments.yaml'). Spyder keeps its state in your users folder. But I do remove anything Arc* related from c:\Users....
- I download the *.exe to disk into a know folder, where I keep the previous 2 version of Pro.
- I execute the *.exe as administrator in that folder which will yield a *.cab and a *.msi file. I run the *.msi and install Pro in C:\arc_pro (or C:\arcpro... whatever)
- I crank up conda and you will be in the default ArcGIS environment
C:\arc_pro\bin\Python\envs\arcgispro-py3>
- I always do a 'test' install of any package by doing a 'dry-run
C:\arc_pro\bin\Python\envs\arcgispro-py3>conda install spyder --dry-run
- Sometimes esri has 'pinned' a package that I want to upgrade. For instance in one of the recent versions, numpy was pinned at version 1.15.x, I wanted 1.16, soooo
C:\arc_pro\bin\Python\envs\arcgispro-py3>conda update numpy --no-pin --dry-run
- Living on the edge, I will proceed to...
C:\arc_pro\bin\Python\envs\arcgispro-py3>conda update numpy --no-pin
- I will list the packages that it will upgrade, downgrade and install where applicable. Copy that list! to Notepad++ or Notepad so you have a record.
- I test to make sure spyder works. I then begin upgrading packages as I need them, typically esri runs a version or more behind in numpy, scipy and some of the other packages in the sci stack.
Now if things go realllll bad, you have some options.
- Roll back an install. First you need to get a list of revisions you have made to track down which something went south
C:\arc_pro\bin\Python\envs\arcgispro-py3> conda list --revisions
That will give you a listing of all the revisions you have made and you can determine where the bad install or improper package dependency wasn't good.
This is usually to do with a particular package depending on another package. Recently, a 'bug' in one package that I updated to the most recent version (Sphinx)
caused issues with numpy doc strings. So I had to rollback the update.
C:\arc_pro\bin\Python\envs\arcgispro-py3> conda install --revision [revision number]
Where revision number will be an integer (no brackets either)
Now... for practice and if you really muddle everything up completely, you just go back delete everything except the *.exe (for safekeeping) and rerun the *.msi and start again.
I have followed this procedure and we even create an 'image' without a clone which we deploy to our network labs since we don't want students cloning stuff (we wipe and
reimage the computers regularly to clean up after the 'clever' ones .
After this long missive. If you do not have control over your computer, you will have to get the IT person a chair to sit beside you to go through this. When they feel comfortable that the world won't come to an end, they might agree to deploy an image suitable to all and you can skip the cloning all together. The purpose of cloning was/is to ensure that you have a useable Pro setup if the clone cause issues. hmmmm, cleaning up and running the *.msi only takes a coffee in time, so weighing your options is up to you.
On a final note... If I want to try a radical deployment full of totally untested fun stuff (think machine learning, AI, numba and other unknown packages). I do all that stuff on a separate machine because computers are way cheaper than my time.
Have fun and good luck