Troubleshooting the use of Python in R

In pangoling: Access to Large Language Model Predictions

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

This vignette provides guidance on troubleshooting issues related to Python module dependencies when using R.

Module not found error in Rstudio

You might encounter an error message similar to this:

Error in py_run_string_impl(code, local, convert) : 
  ModuleNotFoundError: No module named 'torch'
Run `reticulate::py_last_error()` for details.

This might mean that the python dependencies were not installed. pangoling provides a convienence function to install the necessary python dependencies in a conda environment:

install_py_pangoling()

pangoling (as many other R packages) relies on reticulate for Python functionality. Even if the package installation seems successful, the issue may be that reticulate is not correctly loading the correct Python environment. By default, R should use the a conda environment named r-reticulate when managing these configurations automatically.

One can verify this by using py_config, this is the output in a linux computer where the conda environment wasn't loaded:

library(reticulate)

py_config()

#> python:         /usr/local/bin/python
#> libpython:      /usr/lib/python3.10/config-3.10-x86_64-linux-gnu/libpython3.10.so
#> pythonhome:     //usr://usr
#> version:        3.10.12 (main, Jun 11 2023, 05:26:28) [GCC 11.4.0]
#> numpy:           [NOT FOUND]
#> 
#> NOTE: Python version was forced by RETICULATE_PYTHON_FALLBACK

One can anyways configure RStudio to load the correct conda environment (r-reticulate) by default following these steps:

1. In RStudio, navigate to the "Tools" menu.

2. Click on "Global Options" in the "Tools" menu.

3. Click on Python.

knitr::include_graphics("python.png")

1. Click on Select...

2. Click on the Conda Enviornment tab.

3. Click on the r-reticulate path.

knitr::include_graphics("conda.png")

1. Click on the Select button on the bottom.

The path that was selected should appear now when using py_config():

py_config()

HTTPSConnectionPool error

A causal_ or masked_ commands throws an error that starts as follows:

Error in py_run_string_impl(code, local, convert) :
requests.exceptions.SSLError: HTTPSConnectionPool(host='huggingface.co', port=443): 

The first time a model is run, it will download some files that will be available for subsequent runs. So if there is no internet connection (or the huggingface website is down) during the first run, one will experience this problem. Afterwards, it is possible to use pangoling without an internet connection.

pangoling documentation built on April 11, 2025, 6:16 p.m.