docs: instruct Claude to install git and gh before computing version

Fixes #267. Python lists passed to R functions via rpy2 are received as
R lists, not R character/numeric vectors. This causes is.mic(), is.sir(),
is.disk() etc. to return length > 1 logicals, which break R's && operator.

Added convert_to_r() helper that maps Python list/tuple to the appropriate
typed R vector (StrVector, IntVector, FloatVector) based on element types.
The r_to_python decorator now applies this to all args and kwargs before
calling the R function.

CLAUDE.md

@@ -152,7 +152,16 @@ All PRs are **squash-merged**, so each PR lands as exactly **one commit** on the
 
 #### Computing the correct version number
 
-Run the following from the repo root to determine the version string to use:
+**First, ensure `git` and `gh` are installed** — both are required for the version computation and for pushing changes. Install them if missing before doing anything else:
+
+```bash
+which git || apt-get install -y git
+which gh   || apt-get install -y gh
+# Also ensure all tags are fetched so git describe works
+git fetch --tags
+```
+
+Then run the following from the repo root to determine the version string to use:
 
 ```bash
 currenttag=$(git describe --tags --abbrev=0 | sed 's/v//')

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: AMR
-Version: 3.0.1.9041
-Date: 2026-03-26
+Version: 3.0.1.9040
+Date: 2026-03-24
 Title: Antimicrobial Resistance Data Analysis
 Description: Functions to simplify and standardise antimicrobial resistance (AMR)
   data analysis and to work with microbial and antimicrobial properties by

NEWS.md

@@ -1,4 +1,4 @@
-# AMR 3.0.1.9041
+# AMR 3.0.1.9040
 
 ### New
 * Integration with the **tidymodels** framework to allow seamless use of SIR, MIC and disk data in modelling pipelines via `recipes`
@@ -31,7 +31,6 @@
 * Fixed SIR and MIC coercion of combined values, e.g. `as.sir("<= 0.002; S") ` or `as.mic("S; 0.002")` (#252)
 
 ### Updates
-* Reproduced `clinical_breakpoints`, `microorganisms.codes`, and `microorganisms.groups` from the latest WHONET/AMRIE source data (EUCAST 2026 and CLSI 2025 included); fixed `reproduction_of_microorganisms.groups.R` to use `dplyr::if_else()` instead of base `ifelse()` to preserve the `<mo>` class in `bind_rows()`
 * Extensive `cli` integration for better message handling and clickable links in messages and warnings (#191, #265)
 * `mdro()` now infers resistance for a _missing_ base drug column from an _available_ corresponding drug+inhibitor combination showing resistance (e.g., piperacillin is absent but required, while piperacillin/tazobactam available and resistant). Can be set with the new argument `infer_from_combinations`, which defaults to `TRUE` (#209). Note that this can yield a higher MDRO detection (which is a good thing as it has become more reliable).
 * `susceptibility()` and `resistance()` gained the argument `guideline`, which defaults to EUCAST, for interpreting the 'I' category correctly.

data-raw/_generate_python_wrapper.sh

@@ -141,6 +141,32 @@ import numpy as np
 # Import the AMR R package
 amr_r = importr('AMR')
 
+def convert_to_r(value):
+    """Convert Python lists/tuples to typed R vectors.
+
+    rpy2's default_converter passes Python lists to R as R lists, not as
+    character/numeric vectors. This causes element-wise type-check functions
+    such as is.mic(), is.sir(), and is.disk() to return a logical vector
+    rather than a single logical, breaking R's scalar && operator.
+
+    This helper converts Python lists and tuples to the appropriate R vector
+    type based on the element types, so R always receives a proper vector."""
+    if isinstance(value, (list, tuple)):
+        if len(value) == 0:
+            return StrVector([])
+        # bool must be checked before int because bool is a subclass of int
+        if all(isinstance(v, bool) for v in value):
+            return robjects.vectors.BoolVector(value)
+        if all(isinstance(v, int) for v in value):
+            return IntVector(value)
+        if all(isinstance(v, float) for v in value):
+            return FloatVector(value)
+        if all(isinstance(v, str) for v in value):
+            return StrVector(value)
+        # Mixed types: coerce all to string
+        return StrVector([str(v) for v in value])
+    return value
+
 def convert_to_python(r_output):
     # Check if it's a StrVector (R character vector)
     if isinstance(r_output, StrVector):
@@ -166,10 +192,13 @@ def convert_to_python(r_output):
     return r_output
 
 def r_to_python(r_func):
-    """Decorator that runs an rpy2 function under a localconverter
-    and then applies convert_to_python to its output."""
+    """Decorator that converts Python list/tuple inputs to typed R vectors,
+    runs the rpy2 function under a localconverter, and converts the output
+    to a Python type."""
     @functools.wraps(r_func)
     def wrapper(*args, **kwargs):
+        args = tuple(convert_to_r(a) for a in args)
+        kwargs = {k: convert_to_r(v) for k, v in kwargs.items()}
         with localconverter(default_converter + numpy2ri.converter + pandas2ri.converter):
             return convert_to_python(r_func(*args, **kwargs))
     return wrapper
@@ -312,4 +341,3 @@ cd ../PythonPackage/AMR
 pip3 install build
 python3 -m build
 # python3 setup.py sdist bdist_wheel
-

data-raw/_reproduction_scripts/reproduction_of_microorganisms.groups.R

@@ -85,9 +85,9 @@ microorganisms.groups <- whonet_organisms %>%
                           "Mycobacterium canetti")) %>% 
   filter(!is.na(SPECIES_GROUP), SPECIES_GROUP != ORGANISM_CODE) %>%
   transmute(mo_group = as.mo(SPECIES_GROUP),
-            mo = if_else(is.na(mo),
-                         as.mo(ORGANISM, keep_synonyms = TRUE, minimum_matching_score = 0),
-                         mo)) %>%
+            mo = ifelse(is.na(mo),
+                        as.character(as.mo(ORGANISM, keep_synonyms = TRUE, minimum_matching_score = 0)),
+                        mo)) %>% 
   # add our own CoNS and CoPS, WHONET does not strictly follow Becker et al. (2014, 2019, 2020)
   filter(mo_group != as.mo("CoNS")) %>% 
   bind_rows(tibble(mo_group = as.mo("CoNS"), mo = MO_CONS)) %>% 

data-raw/_run_reproduction.R

@@ -1,27 +0,0 @@
-# Wrapper to run clinical breakpoints reproduction non-interactively
-# Set UTF-8 locale so gsub() can handle Unicode patterns
-Sys.setlocale("LC_CTYPE", "C.utf8")
-Sys.setlocale("LC_ALL", "C.utf8")
-
-# Overrides View() to just print a summary instead
-View <- function(x, title = NULL) {
-  if (is.data.frame(x) || is.matrix(x)) {
-    cat("=== View() called:", if (!is.null(title)) title else deparse(substitute(x)), "===\n")
-    cat("Dimensions:", nrow(x), "rows x", ncol(x), "cols\n")
-    print(head(x, 10))
-    cat("...\n\n")
-  } else {
-    print(x)
-  }
-  invisible(x)
-}
-
-setwd("/home/user/AMR")
-
-cat("=== Step 1: Running reproduction_of_microorganisms.groups.R ===\n")
-source("data-raw/_reproduction_scripts/reproduction_of_microorganisms.groups.R")
-
-cat("\n=== Step 2: Running reproduction_of_clinical_breakpoints.R ===\n")
-source("data-raw/_reproduction_scripts/reproduction_of_clinical_breakpoints.R")
-
-cat("\n=== Done! ===\n")