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(v3.0.1.9076) document Python installation channels and enforce_method in vignette (#296)

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Matthijs Berends
2026-06-26 15:03:07 +02:00
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DESCRIPTION
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Package: AMR
Version: 3.0.1.9075
Version: 3.0.1.9076
Date: 2026-06-26
Title: Antimicrobial Resistance Data Analysis
Description: Functions to simplify and standardise antimicrobial resistance (AMR)

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NEWS.md
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# AMR 3.0.1.9075
# AMR 3.0.1.9076
Planned as v3.1.0, end of June 2026.
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* Improved console messages with clickable links throughout, powered by `cli` if it is installed (#191, #265)
* `as.disk()`: input validation is now more strict, rejecting values that are not recognisable as a numeric disk zone diameter
* `as.sir()` gains an `enforce_method` argument (`"auto"`, `"mic"`, or `"disk"`) to force the interpretation method when S3 class information is lost, e.g. when called from Python (#291)
* `AMR for Python` vignette: added sections on installation channels (stable CRAN vs. development GitHub via `AMR.beta`) and on using `enforce_method` in `as_sir()` from Python
# AMR 3.0.1

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vignettes/AMR_for_Python.Rmd
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| ZFD | NaN | Zoliflodacin | None | NaN | None | NaN | None |
# Installation Channels
## Stable Release (CRAN)
The default `AMR` Python package uses the latest stable version of the `AMR` R package, published on CRAN. After running `pip install AMR`, import it as usual:
```python
import AMR
AMR.example_isolates
```
## Development Version (GitHub)
To use the latest development version of the `AMR` R package (sourced directly from GitHub), import the `beta` sub-package and alias it as `AMR`:
```python
import AMR.beta as AMR
AMR.example_isolates
```
Aliasing with `as AMR` keeps all downstream code identical to the stable import. Switching between the stable release and the development version requires changing only the import line — nothing else in your script needs to change.
# SIR Classification with `as_sir()`
## Using `enforce_method`
The `as_sir()` function in R uses S3 method dispatch to select the correct calculation method based on the input class: `<mic>` for MIC values and `<disk>` for disk diffusion values. Because Python objects do not carry R class attributes through the `rpy2` bridge, this automatic dispatch may not resolve correctly.
To explicitly specify the input type, use the `enforce_method` argument:
```python
# Treat the column as MIC values — maps to R's as.sir.mic()
AMR.as_sir(df["MIC_col"], mo="E. coli", ab="AMX", guideline="EUCAST", enforce_method="mic")
# Treat the column as disk diffusion values — maps to R's as.sir.disk()
AMR.as_sir(df["disk_col"], mo="E. coli", ab="AMX", guideline="EUCAST", enforce_method="disk")
```
Without `enforce_method`, R falls back to class-based dispatch on the raw Python input, which may fail or return unexpected results. Always supply `enforce_method` when calling `as_sir()` from Python.
# Conclusion
With the `AMR` Python package, Python users can now effortlessly call R functions from the `AMR` R package. This eliminates the need for complex `rpy2` configurations and provides a clean, easy-to-use interface for antimicrobial resistance analysis. The examples provided above demonstrate how this can be applied to typical workflows, such as standardising microorganism and antimicrobial names or calculating resistance.