# Installing and Managing Python Environments with `reticulate`

## Overview

The `text` package relies on Python packages. While `textrpp_install()` function offers an automated setup, manually installing the dependencies can help with troubleshooting and provides greater control for advanced users.

This guide explains how to install everything step-by-step using the `reticulate` package in R.

## Step 1: Install reticulate

    install.packages("reticulate")

## Step 2: Create a Conda Environment

Use `reticulate` to install Miniconda:

    reticulate::install_miniconda()

Then create a new conda environment with Python 3.9:

    reticulate::conda_create("textrpp_reticulate", packages = "python=3.9")

## Step 3: Install Python Packages

Install the required python packages (rpp) needed for the text-package:

    rpp_packages <- c(
      "torch==2.2.0",
      "transformers==4.38.0",
      "huggingface_hub==0.20.0",
      "numpy==1.26.0",
      "pandas==2.0.3",
      "nltk==3.8.1",
      "scikit-learn==1.3.0",
      "datasets==2.16.1",
      "evaluate==0.4.0",
      "accelerate==0.26.0",
      "bertopic==0.16.3",
      "jsonschema==4.19.2",
      "sentence-transformers==2.2.2",
      "flair==0.13.0",
      "umap-learn==0.5.6",
      "hdbscan==0.8.33",
      "scipy==1.10.1",
      "aiohappyeyeballs==2.4.4"
    )

    reticulate::conda_install("textrpp_reticulate", packages = rpp_packages, pip = TRUE)

## Step 4: Activate the Environment

To use/initialize the environment in your R session:

    reticulate::use_condaenv("textrpp_reticulate", required = TRUE)

You now have a fully working manual installation of the `text`/`textrpp` Python environment using `reticulate`.

# Show available conda environments

    reticulate::conda_list()

# Remove the conda environment

    # Restart R
    .rs.restartR()  # for RStudio automation

    # Now safely remove the environment
    # WARNING: this is irreversible
    reticulate::conda_remove(envname = "textrpp_reticulate")