Updating Anaconda and Tensorflow breaks the execute Python extension.

I solved the problem by downgrading Python to 3.6.5. The question is.....what is happening? Obviously, not upgrading Anaconda can only last so long as a workaround. Is there anything on the Anaconda side that needs to be done?

Hi @hughesfleming68,

I'm running on 3.7.2 without problems.

When you install a new Python distribution with conda update, you create a bare one as if you would have installed Miniconda. The problem isn't solved by downgrading but by installing Pandas on the new version after upgrading.

What I normally do:

• Install Anaconda.
• Create an environment solely for RapidMiner:
  $ conda create --name=rapidminer python=3.7 
• Activate the environment for RapidMiner:
  $ conda activate rapidminer
• Install pandas for the new environment:
  $ conda install pandas
• List the environments I have:
  $ conda env list
• Copy the path of the environment I created, add /bin/python to the end and use that path to configure the Python extension.
• Deactivate the environment:
  $ conda deactivate
  

That way, nothing of what I do with other environments affect the one I use for RapidMiner.

Hope this helps,

Rodrigo.

Thanks Rodrigo. This looks like an Anaconda problem. I have an older RM version installed as well with older versions of the extensions and it is doing the same thing so this has nothing to do with Rapidminer. Worse, this is Sunday, I should be doing something else!

I have it working now with 3.7.2 so setting up a new environment works while updating an older one breaks. Thanks again Rodrigo.

Hi @hughesfleming68,

The idea behind anaconda is to have different environments per project or kind of project at least. I do have this separation:

• base
• rapidminer
• servers
• selenium
• fileparsing
• datamining
• webapps
• daemons
• project***

That way, I can try different things with certain stable libraries, and if I have to fix something because an update wreaked havoc, it's just a project or a small piece of code, not the entire work of a lifetime. (ok, 9 months, 5 projects a week, it's not that big of a tragedy).

All the best,

Rodrigo.

Thank you Rodrigo. I understand the benefits of different environments. I already had Rapidminer working in a custom tensorflow env. It is unfortunate that the solution is to create a new env and basically set everything up again because a tensorflow update broke the connection with Rapidminer.

regards,

Alex