This was by design (although perhaps we can still reconsider). Our intention was that, unless the user has explicitly requested a particular version of Python with one of the use_*() helpers, we should prompt the user to install Miniconda and make that the default.

Note that you will only be prompted once, and rejecting that prompt is "sticky" (you won't get bugged about it again on the same account / machine)

I see. Thanks for the clarification ! I guess I should always use use_* to get going. And the message indeed appears only once.

I guess it just feels unexpected when you already have anaconda configured to get advice to download the little brother miniconda. I would have considered to be prompted if no Python was found or if on windows not a python with conda.
But maybe there is a change in reticulate to consider that it should work better and exclusively with miniconda and it means I should switch from Anaconda to miniconda ?

That is completly understandable. This is the approach with TinyTex distribution too, that saves a lot of painful problem with Rmarkdown pdf rendering, regarding LaTex configuration.

This is fine by me as when you say no it is not promped again. I'll document internally to our users to use miniconda with reticulate, also specify explicitly the python version.

Thanks a lot for your precision.

I've now made this change: if an Anaconda environment is available, it will be used in preference to Miniconda.

This was by design (although perhaps we can still reconsider). Our intention was that, unless the user has explicitly requested a particular version of Python with one of the use_*() helpers, we should prompt the user to install Miniconda and make that the default.

Note that you will only be prompted once, and rejecting that prompt is "sticky" (you won't get bugged about it again on the same account / machine)

And what can I do to get that prompt again now that I changed my mind? Thanks!

The response is stored in a file located at the path referenced by:

reticulate:::miniconda_meta_path()

If you remove that file, then reticulate will prompt again.

Hello Kevin @kevinushey
Referring to
"This was by design (although perhaps we can still reconsider). Our intention was that, unless the user has explicitly requested a particular version of Python with one of the use_*() helpers, we should prompt the user to install Miniconda and make that the default."
This is perfectly fine if you use it just in R, where if propmted for installing Miniconda you can simply answer yes and that's it.
The other story is when you use it from let say Scala through RScala library, when you only need to use pyarrow to load parquet files. Then RClient of RScala library is prompted with the question whether to install Miniconda, but the user of RScala API is not able to respond to this question, because it is visible only in the logs on the Azure Databricks cluster, because the application is packed into jar file and has nothing in common with interactive usage like in notebooks.
Having said this mybe you could reconsider this design decision and make it use some existing, default Python installation.

Happens to me just by loading a python script file.
And won´t take no for answer:
would you like to install miniconda? [y/n]: n

I'm on a macbook with Big Sur, and I'm brand new to integrating python into my work. For my current project, I'm trying to build a neural network to compare with gbm, rf, glm, and an ensemble... and the python configuration is confusing because the documentation is missing any reference to the workarounds for all of the errors and warnings that RStudio over-engineered into their python-R integration. These warnings and error messages in the R console are very confusing: So far, the tensorflow package installed just fine, but the call library(tensorflow) returned a message that it couldn't load the tensorflow package because the tensorflow module isn't already installed in the python environment (nothing in the documentation says anything about this)...

Error: package or namespace load failed for ‘tensorflow’: .onLoad failed in loadNamespace() for 'tensorflow', details: call: py_module_import(module, convert = convert) error: ModuleNotFoundError: No module named 'tensorflow'

and then the "install_tensorflow()" command prompts you to install a whole new miniconda installation (again, nothing in the webpage for tensorflow install says anything about this). And I just installed the python module to be able to load the tensorflow package, it now seems that running install_tensorflow() is redundant, and since there are multiple installations of python, I don't even know into which environment R is installing the dependencies and newer tensorflow module. I had very similar problems making all of this work on Windows 10 last Fall (2020), so the fact that this documentation still isn't noting these repeatable hiccups is disappointing.

So next, install_tensorflow() seemed to look up a hundred packages that have conflicts with everything in the base 'r-reticulate' environment. Literally everything says there's a conflict. I have no idea what to do about this. I'm not a python expert... I'm just trying to use R to run tensorflow. Here is just one sample of the 3000 lines of illegible output:

Package libev conflicts for: libnghttp2 -> libev[version='>=4.11|>=4.33,<4.34.0a0'] libcurl -> libnghttp2[version='>=1.41.0,<2.0a0'] -> libev[version='>=4.11|>=4.33,<4.34.0a0'] libev

And to top it all off, install_tensorflow() seems to have tried to install python 3.7 into my 'r-reticulate' environment, which makes no sense to me at all... and nowhere in the documentation am I reading that R's tensorflow installation requires python 3.7.

Error: installation of 'python=3.7' into environment '/Users/eugene/opt/anaconda3/envs/r-reticulate' failed [error code 1]

So now that this neophyte python user just installed a whole bunch of python crap that was essentially the "wrong version" and named an environment 'r-reticulate' to match RStudio's defaults, there is nowhere in the documentation that teaches you how to "back out" of everything that was just installed, so that I can go back and install anaconda3 under a different python version in the hopes that tensorflow will install again.

To say this is incredibly frustrating is an immense understatement.