EuropeanIFCBGroup · anderstorstensson · Aug 27, 2026 · Aug 26, 2026 · Aug 27, 2026
diff --git a/.github/workflows/R-CMD-check.yaml b/.github/workflows/R-CMD-check.yaml
@@ -32,24 +32,6 @@ jobs:
     steps:
       - uses: actions/checkout@v7
 
-      - uses: actions/setup-python@v7
-        with:
-          python-version: '3.x'
-
-      - name: Install Python dependencies
-        run: |
-          python -m pip install --upgrade pip
-          pip install scipy numpy
-
-      - name: Set RETICULATE_PYTHON (Unix)
-        if: runner.os != 'Windows'
-        run: echo "RETICULATE_PYTHON=$(which python)" >> $GITHUB_ENV
-
-      - name: Set RETICULATE_PYTHON (Windows)
-        if: runner.os == 'Windows'
-        run: echo "RETICULATE_PYTHON=$((Get-Command python).Source)" >> $env:GITHUB_ENV
-        shell: pwsh
-
       - uses: r-lib/actions/setup-pandoc@v2
 
       - uses: r-lib/actions/setup-r@v2

diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
@@ -19,17 +19,6 @@ jobs:
     steps:
       - uses: actions/checkout@v7
 
-      - name: Setup Python
-        uses: actions/setup-python@v7
-        with:
-          python-version: "3.12"
-
-      - name: Install Python dependencies and set RETICULATE_PYTHON
-        run: |
-          python -m pip install --upgrade pip
-          pip install scipy numpy
-          echo "RETICULATE_PYTHON=$(which python)" >> $GITHUB_ENV
-
       - uses: r-lib/actions/setup-r@v2
         with:
           use-public-rspm: true

diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
@@ -8,7 +8,6 @@ Thank you for your interest in contributing to `ClassiPyR`! This document provid
 
 - R (>= 4.0.0)
 - devtools package for development
-- Python with `scipy` (required for saving .mat annotation files)
 
 ### Setting Up the Development Environment
 
@@ -26,12 +25,6 @@ Thank you for your interest in contributing to `ClassiPyR`! This document provid
    devtools::load_all()
    ```
 
-4. Set up Python environment (required for saving .mat annotation files):
-   ```r
-   library(iRfcb)
-   ifcb_py_install(envname = "./venv")
-   ```
-
 ### Running the App During Development
 
 ```r

diff --git a/DESCRIPTION b/DESCRIPTION
@@ -24,11 +24,11 @@ Imports:
     shinyFiles,
     bslib,
     curl,
-    iRfcb (>= 0.8.1),
+    iRfcb (>= 0.10.0),
+    lifecycle,
     dplyr,
     DT,
     jsonlite,
-    reticulate,
     DBI,
     RSQLite
 Suggests:

diff --git a/NAMESPACE b/NAMESPACE
@@ -86,7 +86,7 @@ importFrom(iRfcb,ifcb_get_mat_variable)
 importFrom(iRfcb,ifcb_zip_matlab)
 importFrom(iRfcb,ifcb_zip_pngs)
 importFrom(jsonlite,fromJSON)
-importFrom(reticulate,py_available)
+importFrom(lifecycle,deprecated)
 importFrom(shiny,shinyApp)
 importFrom(shinyFiles,shinyDirButton)
 importFrom(shinyjs,useShinyjs)
diff --git a/NEWS.md b/NEWS.md
@@ -1,6 +1,9 @@
 # ClassiPyR (development version)
 
 - ClassiPyR now requires R >= 4.4.0 (for base R's `%||%` operator, which the app already relied on).
+- **Python is no longer required.** iRfcb 0.10.0 reads and writes MATLAB `.mat` files with a native R implementation, so ClassiPyR now requires `iRfcb >= 0.10.0` and all Python-related code has been removed: `reticulate` is no longer an Import, the app no longer initializes a Python environment at startup, and the "Python not available" warnings and export blocks are gone — `.mat` saving, SQLite → `.mat` export and MATLAB ZIP export work out of the box for everyone.
+  - `init_python_env()` is deprecated and now a no-op; the `venv_path` argument of `run_app()` is deprecated and ignored (a warning is issued when supplied). The `python_venv_path` entry in saved settings is ignored.
+  - If you need a Python environment for other iRfcb features (e.g. feature extraction), use `iRfcb::ifcb_py_install()` directly.
 
 ## New features
 

diff --git a/R/database.R b/R/database.R
@@ -2,7 +2,7 @@
 #
 # Provides functions to store and retrieve annotations in a local SQLite
 # database as an alternative to .mat files. SQLite is the default storage
-# backend - it works out of the box with no Python dependency.
+# backend.
 
 #' @importFrom DBI dbConnect dbDisconnect dbWriteTable dbGetQuery dbExecute
 #' @importFrom RSQLite SQLite
@@ -656,7 +656,6 @@ import_mat_to_db <- function(mat_path, db_path, sample_name,
 #'
 #' Reads annotations for a single sample from the database and writes a
 #' MATLAB-compatible annotation file using \code{iRfcb::ifcb_create_manual_file}.
-#' Requires Python with scipy.
 #'
 #' @param db_path Path to the SQLite database file
 #' @param sample_name Sample name
@@ -781,7 +780,6 @@ import_all_mat_to_db <- function(mat_folder, db_path,
 #' Bulk export all annotated samples from SQLite to .mat files
 #'
 #' Exports every sample in the database to a MATLAB-compatible annotation file.
-#' Requires Python with scipy.
 #'
 #' @param db_path Path to the SQLite database file
 #' @param output_folder Folder where .mat files will be written

diff --git a/R/run_app.R b/R/run_app.R
@@ -3,14 +3,12 @@
 #' Run the ClassiPyR Shiny Application
 #'
 #' Launches the ClassiPyR Shiny app for manual image classification and validation of IFCB data.
-#' This app relies on the iRfcb package for reading IFCB data files and requires
-#' Python (via reticulate) for saving MATLAB .mat files.
+#' This app relies on the iRfcb package for reading and writing IFCB data files,
+#' including MATLAB .mat files, entirely in R.
 #'
-#' @param venv_path Optional path to a Python virtual environment. When specified,
-#'   this path takes priority over any saved venv path in settings, both for Python
-#'   initialization at startup and in the Settings UI. If NULL (default), the app
-#'   uses any saved venv path from settings, or falls back to a 'venv' folder in
-#'   the current working directory.
+#' @param venv_path `r lifecycle::badge("deprecated")` Ignored. ClassiPyR no
+#'   longer requires Python; .mat files are read and written natively in R
+#'   (iRfcb >= 0.10.0).
 #' @param reset_settings If TRUE, deletes saved settings before starting the app.
 #'   Useful for troubleshooting or starting fresh. Default is FALSE.
 #' @param launch.browser If TRUE (default), opens the app in the system's default
@@ -24,9 +22,6 @@
 #' # Run with default settings (opens in browser)
 #' run_app()
 #'
-#' # Run with a specific Python virtual environment
-#' run_app(venv_path = "/path/to/my/venv")
-#'
 #' # Run on a specific port
 #' run_app(port = 3838)
 #'
@@ -36,7 +31,8 @@
 #' # Reset all settings and start fresh
 #' run_app(reset_settings = TRUE)
 #' }
-run_app <- function(venv_path = NULL, reset_settings = FALSE, launch.browser = TRUE, ...) {
+#' @md
+run_app <- function(venv_path = deprecated(), reset_settings = FALSE, launch.browser = TRUE, ...) {
   app_dir <- system.file("app", package = "ClassiPyR")
   if (app_dir == "") {
     stop("Could not find app directory. Try re-installing `ClassiPyR`.",
@@ -56,9 +52,14 @@ run_app <- function(venv_path = NULL, reset_settings = FALSE, launch.browser = T
   # Capture user's working directory before Shiny changes it
   options(ClassiPyR.startup_wd = getwd())
 
-  # Set venv path as option for the app to use
-  if (!is.null(venv_path)) {
-    options(ClassiPyR.venv_path = venv_path)
+  if (lifecycle::is_present(venv_path)) {
+    lifecycle::deprecate_warn(
+      "0.3.0", "run_app(venv_path)",
+      details = paste(
+        "The argument is ignored: ClassiPyR no longer requires Python",
+        "(iRfcb >= 0.10.0 reads and writes .mat files natively in R)."
+      )
+    )
   }
 
   shiny::runApp(app_dir, launch.browser = launch.browser, ...)

diff --git a/R/sample_saving.R b/R/sample_saving.R
@@ -8,7 +8,7 @@ NULL
 #' Saves the current annotations for a sample. By default annotations are
 #' stored in a local SQLite database (\code{annotations.sqlite} in the database
 #' folder). Optionally, a MATLAB-compatible \code{.mat} file can also be
-#' written (requires Python + scipy).
+#' written.
 #'
 #' @param sample_name Sample name (e.g., "D20230101T120000_IFCB134")
 #' @param classifications Current classifications data frame
@@ -105,7 +105,7 @@ save_sample_annotations <- function(sample_name,
     output_folder = png_output_folder
   )
 
-  # Save to SQLite (fast, no Python needed)
+  # Save to SQLite
   if (save_format %in% c("sqlite", "both")) {
     # Load class list if not provided
     c2u <- class2use
@@ -116,7 +116,7 @@ save_sample_annotations <- function(sample_name,
     save_annotations_db(db_path, sample_name, classifications, c2u, annotator)
   }
 
-  # Save to .mat (requires Python + scipy)
+  # Save to .mat
   if (save_format %in% c("mat", "both")) {
     # Find ADC folder: use provided path, or fall back to get_sample_paths()
     if (is.null(adc_folder)) {

diff --git a/R/utils.R b/R/utils.R
@@ -9,7 +9,7 @@
 #' @importFrom bslib bs_theme
 #' @importFrom DT renderDT
 #' @importFrom jsonlite fromJSON
-#' @importFrom reticulate py_available
+#' @importFrom lifecycle deprecated
 #' @importFrom dplyr filter
 #' @importFrom DBI dbConnect dbDisconnect dbGetQuery dbWriteTable dbExecute
 #' @importFrom RSQLite SQLite
@@ -796,99 +796,28 @@ create_empty_changes_log <- function() {
 
 #' Initialize Python environment for iRfcb
 #'
-#' Checks if Python is already available via reticulate, otherwise tries to
-#' use or create a virtual environment. Required for reading and writing
-#' MATLAB .mat files.
-#'
-#' The resolution order is:
-#' 1. If Python is already configured via reticulate, use it directly
-#'    (installs scipy if missing).
-#' 2. If \code{venv_path} is provided and the virtual environment exists,
-#'    activate it.
-#' 3. If \code{venv_path} is provided but does not exist, create it via
-#'    \code{\link[iRfcb]{ifcb_py_install}}.
-#' 4. If \code{venv_path} is NULL, default to \code{./venv} in the current
-#'    working directory for steps 2--3.
-#'
-#' @param venv_path Optional path to virtual environment. If NULL (default),
-#'   uses a \code{venv} folder in the current working directory.
-#' @return TRUE if Python is available, FALSE otherwise
-#' @export
-#' @examples
-#' \dontrun{
-#' # Initialize with default venv path (./venv)
-#' success <- init_python_env()
+#' @description
+#' `r lifecycle::badge("deprecated")`
 #'
-#' # Initialize with custom venv path
-#' success <- init_python_env("/path/to/my/venv")
+#' `init_python_env()` was deprecated in ClassiPyR 0.3.0 and is now a no-op.
+#' As of iRfcb 0.10.0, MATLAB .mat files are read and written with a native R
+#' implementation, so ClassiPyR no longer requires Python.
 #'
-#' if (success) {
-#'   message("Python ready for MAT file operations")
-#' }
-#' }
+#' If you need a Python environment for other iRfcb features (e.g. feature
+#' extraction), set one up with [iRfcb::ifcb_py_install()].
+#'
+#' @param venv_path Ignored.
+#' @return FALSE, invisibly
+#' @export
+#' @keywords internal
+#' @md
 init_python_env <- function(venv_path = NULL) {
-
-  tryCatch({
-    # Determine venv path: use provided path, or working directory default
-    if (is.null(venv_path) || venv_path == "") {
-      venv_path <- file.path(getwd(), "venv")
-    }
-
-    # Set RETICULATE_PYTHON *before* initialization so that py_discover_config()
-    # resolves to the correct environment. iRfcb's check_python_and_module()
-    # uses py_discover_config() + py_list_packages() which relies on this.
-    # Without this, py_discover_config() may return system Python even when
-    # reticulate is using a virtualenv, causing scipy checks to fail.
-    .set_reticulate_python <- function(venv) {
-      if (.Platform$OS.type == "windows") {
-        py <- file.path(venv, "Scripts", "python.exe")
-      } else {
-        py <- file.path(venv, "bin", "python")
-      }
-      if (file.exists(py)) {
-        Sys.setenv(RETICULATE_PYTHON = py)
-        return(TRUE)
-      }
-      FALSE
-    }
-
-    # Try the provided/configured venv first, then common reticulate defaults
-    venv_candidates <- unique(c(
-      venv_path,
-      path.expand("~/.virtualenvs/r-reticulate"),
-      path.expand("~/.virtualenvs/iRfcb")
-    ))
-    for (candidate in venv_candidates) {
-      if (reticulate::virtualenv_exists(candidate) && .set_reticulate_python(candidate)) {
-        break
-      }
-    }
-
-    if (reticulate::py_available(initialize = TRUE)) {
-      # Check if scipy is installed (required for MAT file writing)
-      if (!reticulate::py_module_available("scipy")) {
-        message("Installing scipy...")
-        reticulate::py_install("scipy")
-      }
-      message("Python environment ready")
-      return(TRUE)
-    }
-
-    # Try to use existing venv
-    if (reticulate::virtualenv_exists(venv_path)) {
-      reticulate::use_virtualenv(venv_path, required = TRUE)
-      message("Using Python environment: ", venv_path)
-      return(TRUE)
-    }
-
-    # Create venv via iRfcb
-    message("Creating Python environment at: ", venv_path)
-    iRfcb::ifcb_py_install(venv_path)
-    reticulate::use_virtualenv(venv_path, required = TRUE)
-    return(TRUE)
-
-  }, error = function(e) {
-    warning("Failed to initialize Python environment: ", e$message)
-    return(FALSE)
-  })
+  lifecycle::deprecate_warn(
+    "0.3.0", "init_python_env()",
+    details = c(
+      "ClassiPyR no longer requires Python: iRfcb >= 0.10.0 reads and writes .mat files natively in R.",
+      "For other iRfcb features that use Python, see `iRfcb::ifcb_py_install()`."
+    )
+  )
+  invisible(FALSE)
 }
diff --git a/README.md b/README.md
@@ -11,7 +11,7 @@ A Shiny application for manual (human) image classification and validation of Im
 
 ## Background
 
-`ClassiPyR` was created to provide a lightweight, standalone annotation and validation tool that is fully compatible with the [ifcb-analysis](https://github.com/hsosik/ifcb-analysis) toolbox and custom classifiers (e.g. a CNN). The primary design goals were user-friendliness and portability—enabling researchers to work with IFCB data without complex setup requirements or dependencies on specific computing environments (other than Python and R). To achieve these goals efficiently, [Claude Code](https://code.claude.com/) was used for development.
+`ClassiPyR` was created to provide a lightweight, standalone annotation and validation tool that is fully compatible with the [ifcb-analysis](https://github.com/hsosik/ifcb-analysis) toolbox and custom classifiers (e.g. a CNN). The primary design goals were user-friendliness and portability—enabling researchers to work with IFCB data without complex setup requirements or dependencies on specific computing environments (other than R). To achieve these goals efficiently, [Claude Code](https://code.claude.com/) was used for development.
 
 ## Features
 
@@ -21,7 +21,7 @@ A Shiny application for manual (human) image classification and validation of Im
 - **Live Prediction**: One-click CNN classification via a remote Gradio API using [iRfcb](https://github.com/EuropeanIFCBGroup/iRfcb)
 - **Multiple Formats**: Load from CSV, HDF5 or MATLAB classifier output
 - **Flexible Image Source**: Load samples from ROI files or pre-extracted PNG sample folders
-- **SQLite Storage**: Annotations stored in a local SQLite database by default - no Python needed
+- **SQLite Storage**: Annotations stored in a local SQLite database by default
 - **Efficient Workflow**: Drag-select, batch relabeling, class filtering
 - **MATLAB Compatible**: Optional `.mat` export for [ifcb-analysis](https://github.com/hsosik/ifcb-analysis) toolbox
 - **CNN Training Ready**: Organized PNG output by class
@@ -50,24 +50,7 @@ run_app()
 
 See the [Getting Started](https://europeanifcbgroup.github.io/ClassiPyR/articles/getting-started.html) guide for detailed setup instructions.
 
-### Python Setup (optional)
-
-Python is **not required** for the default workflow. Annotations are stored in a local SQLite database that works out of the box.
-
-Python is only needed if you want to export annotations as MATLAB `.mat` files for use with [ifcb-analysis](https://github.com/hsosik/ifcb-analysis). To set up using `iRfcb`:
-
-```r
-library(iRfcb)
-
-# Define a path were the venv will be installed
-venv_path <- "/path/to/your/venv"
-
-# Install the venv
-ifcb_py_install(venv_path)
-
-# Launch with Python support
-run_app(venv_path = venv_path)
-```
+No Python setup is needed: all file formats, including MATLAB `.mat` files for [ifcb-analysis](https://github.com/hsosik/ifcb-analysis), are read and written natively in R (via `iRfcb` >= 0.10.0).
 
 ## Documentation