logrx::axecute("logrx_test_file.R")
logrx 0.4.0: logs for your R programs
Ben Straub发表于 2025-05-19 00:00:00
[This article was first published on pharmaverse blog, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
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Introducing logrx 0.4.0: Enhanced Logging for Your R Programs
The A Logging Utility Focus on Clinical Trial Programming Workflows • logrx A Logging Utility Focus on Clinical Trial Programming Workflows • logrx {logrx} R package facilitates logging in a clinical environment with the goal of making code easily traceable and reproducible. If you would like to take the package for a spin, please check out the core function axecute() to quickly make a log of your R file. If you would like even more information on each section of the log and how to further enhance your logs please see the Get Started.
The team from GSK, Atorus, J&J and Pfzier are excited to announce a mini-release of A Logging Utility Focus on Clinical Trial Programming Workflows • logrx A Logging Utility Focus on Clinical Trial Programming Workflows • logrx {logrx} 0.4.0, an update designed to further enrich your logging experience in R. We have three exciting enhancements to share to help users maintain clearer and more efficient logs.
Making your first log with logrx
Before we introduce the new features, let’s first do a quick introduction to A Logging Utility Focus on Clinical Trial Programming Workflows • logrx A Logging Utility Focus on Clinical Trial Programming Workflows • logrx {logrx} with the core function axecute(). You can expand the > R File axecuted by logrx and > Log File created from axecute() from logrx folds to see the file as well as the log that is produced.
R File axecuted by logrx
# Load necessary libraries
library(pharmaversesdtm)
library(dplyr)
# Check if the package is installed
if (!requireNamespace("pharmaversesdtm", quietly = TRUE)) {
stop("The pharmaversesdtm package is not installed. Please install it first.")
}
# Load example data
data("dm", package = "pharmaversesdtm")
# Display a message
message("Starting data manipulation using dplyr...")
# Execute the manipulation
tryCatch({
# Simple dplyr operations
# Filter for males and select specific columns
filtered_data <- dm %>%
filter(RACE == "M") %>%
select(STUDYID, USUBJID, AGE, SEX)
# Print the first few rows of the filtered data
print(filtered_data)
# If the dataset is empty after filtering, provide a warning
if (nrow(filtered_data) == 0) {
warning("The filtered dataset has no data. Please check your filter criteria.")
}
}, error = function(err) {
warning("An error occurred during processing: ", err$message)
})
# Display a message indicating completion
message("Data manipulation completed.")
Log File created from axecute() from logrx
--------------------------------------------------------------------------------
- logrx Metadata -
--------------------------------------------------------------------------------
This log was generated using logrx 0.4.0
logrx package version: 0.4.0
logrx build: RSPM (R 4.4.0)
logrx link to repository: https://github.com/pharmaverse/logrx
--------------------------------------------------------------------------------
- User and File Information -
--------------------------------------------------------------------------------
User: r590548
File Name: logrx_test_file.R
File Path: /cloud/project/posts/zzz_DO_NOT_EDIT_logrx_0.4.0...
File HashSum: 60930bc7b27a4222f6f8e7e5c9f8192127ec32c2
--------------------------------------------------------------------------------
- Session Information -
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─ Session info ───────────────────────────────────────────────────────────────
setting value
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─ Python configuration ───────────────────────────────────────────────────────
Python is not available
──────────────────────────────────────────────────────────────────────────────
--------------------------------------------------------------------------------
- Masked Functions -
--------------------------------------------------------------------------------
function `plot` from {package:base} by package:graphics
function `body<-` from {package:base} by package:methods
function `kronecker` from {package:base} by package:methods
--------------------------------------------------------------------------------
- Used Package and Functions -
--------------------------------------------------------------------------------
{package:base} library, requireNamespace, stop, message, tryCatch, print, nrow, warning
{package:dplyr} %>%, filter, select
{package:utils} data
--------------------------------------------------------------------------------
- Program Run Time Information -
--------------------------------------------------------------------------------
Start time: 2025-05-17 16:13:30 UTC
End time: 2025-05-17 16:13:30 UTC
Run time: 0 seconds
--------------------------------------------------------------------------------
- Errors and Warnings -
--------------------------------------------------------------------------------
Errors:
Warnings:
The filtered dataset has no data. Please check your filter criteria.
--------------------------------------------------------------------------------
- Messages, Output, and Result -
--------------------------------------------------------------------------------
Messages:
Attaching package: 'dplyr'
The following objects are masked from 'package:stats': filter, lag
The following objects are masked from 'package:base': intersect, setdiff, setequal, union
Starting data manipulation using dplyr...
Data manipulation completed.
Output:
# A tibble: 0 × 4
# ℹ 4 variables: STUDYID <chr>, USUBJID <chr>, AGE <dbl>, SEX <chr>
Result:
NULL
--------------------------------------------------------------------------------
- Log Output File -
--------------------------------------------------------------------------------
Log name: logrx_test_file.log
Log path: /cloud/project/posts/zzz_DO_NOT_EDIT_logrx_0.4.0...
It is that easy to make a log for your R program with this lightweight logging package! Also recommend checking out the pharmaverse examples page where a side-by-side comparison is available for 3 R logging packages: Creates Log Files • logr Creates Log Files • logr {logr} , A Logging Utility Focus on Clinical Trial Programming Workflows • logrx A Logging Utility Focus on Clinical Trial Programming Workflows • logrx {logrx} , Log Execution of Scripts • whirl Log Execution of Scripts • whirl {whirl} .
New Features
It is small release, but we feel it packs a big punch!
Enhanced Functionality with axecute()
The latest update introduces the extra_info parameter in the Creation of a log and axecution of a file — axecute • logrx axecute() function. This optional parameter allows users to pass a list object directly into the extra info section of the log, formatted in YAML. This enhancement opens up new possibilities for adding comprehensive contextual information to your logs, ensuring they are not only detailed but also structured for easy interpretation.
Check out this simple example to see how to add some extra info to your log file.
logrx::axecute(
file = "logrx_test_file.R",
log_name = "logrx_test_file_extra_info1.log",
extra_info = list("orange", paste0("green eggs and ham"))
)
Here is the relevant section from the log file.
-------------------------------------------------------------------------------- - Extra info - -------------------------------------------------------------------------------- - orange - green eggs and ham
You can unfold this section to see the entire log file.
Log File created from axecute() from logrx with extra_info
--------------------------------------------------------------------------------
- logrx Metadata -
--------------------------------------------------------------------------------
This log was generated using logrx 0.4.0
logrx package version: 0.4.0
logrx build: RSPM (R 4.4.0)
logrx link to repository: https://github.com/pharmaverse/logrx
--------------------------------------------------------------------------------
- User and File Information -
--------------------------------------------------------------------------------
User: r590548
File Name: logrx_test_file.R
File Path: /cloud/project/posts/zzz_DO_NOT_EDIT_logrx_0.4.0...
File HashSum: 60930bc7b27a4222f6f8e7e5c9f8192127ec32c2
--------------------------------------------------------------------------------
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--------------------------------------------------------------------------------
- Used Package and Functions -
--------------------------------------------------------------------------------
{package:base} library, requireNamespace, stop, message, tryCatch, print, nrow, warning
{package:dplyr} %>%, filter, select
{package:utils} data
--------------------------------------------------------------------------------
- Program Run Time Information -
--------------------------------------------------------------------------------
Start time: 2025-05-17 16:33:50 UTC
End time: 2025-05-17 16:33:51 UTC
Run time: 1 seconds
--------------------------------------------------------------------------------
- Errors and Warnings -
--------------------------------------------------------------------------------
Errors:
Warnings:
The filtered dataset has no data. Please check your filter criteria.
--------------------------------------------------------------------------------
- Messages, Output, and Result -
--------------------------------------------------------------------------------
Messages:
Starting data manipulation using dplyr...
Data manipulation completed.
Output:
Result:
NULL
--------------------------------------------------------------------------------
- Extra info -
--------------------------------------------------------------------------------
- orange
- green eggs and ham
--------------------------------------------------------------------------------
- Log Output File -
--------------------------------------------------------------------------------
Log name: logrx_test_file_extra_info1.log
Log path: /cloud/project/posts/zzz_DO_NOT_EDIT_logrx_0.4.0...
Create a renv.lock from a logrx .log file
A new vignette has been added to guide users in creating a Project Environments • renv Project Environments • renv {renv} lockfile from a A Logging Utility Focus on Clinical Trial Programming Workflows • logrx A Logging Utility Focus on Clinical Trial Programming Workflows • logrx {logrx} lock file! Now this is reproducible R code!! The vignette provides step-by-step instructions, helping you secure your project dependencies effortlessly and ensuring reproducible development environments.
Shiny Addin Changes
As part of streamlining of logrx’s functionality, the Shiny Addin has been removed from the package. But don’t worry! It hasn’t disappeared entirely. A standalone package called GitHub – pharmaverse/logrxaddin: Addin for the logrx Package GitHub – pharmaverse/logrxaddin: Addin for the logrx Package {logrxaddin} has been developed to house the Shiny Addin independently. This separation allows for more focused development and updates tailored specifically to the Shiny environment. For more details, feel free to explore GitHub – pharmaverse/logrxaddin: Addin for the logrx Package GitHub – pharmaverse/logrxaddin: Addin for the logrx Package {logrxaddin} . The team hopes to experiment and enhance this Addin making it even better!
Conclusion
A Logging Utility Focus on Clinical Trial Programming Workflows • logrx A Logging Utility Focus on Clinical Trial Programming Workflows • logrx {logrx} 0.4.0 continues to evolve how logs are managed and interpreted in R. Whether you’re a seasoned developer or a novice, these new features and updates provide the tools for building more insightful logs and honing your logging practices. We hope to release a 0.5.0 in the late fall of 2025 with the ability to customize the log file to your needs as well as enhance the Shiny Addin to allow for bulk logging of scripts.
Happy logging of those R programs!
Last updated
2025-05-19 09:13:41.025152
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Citation
BibTeX citation:
@online{straub2025,
author = {Straub, Ben},
title = {Logrx 0.4.0: Logs for Your {R} Programs},
date = {2025-05-19},
url = {https://pharmaverse.github.io/blog/posts/2025-05-19_logrx_0.4.0.../logrx_0_4_0_logs_for_your__r_programs.html},
langid = {en}
}
For attribution, please cite this work as:
Straub, Ben. 2025. “Logrx 0.4.0: Logs for Your R Programs.”
May 19, 2025. https://pharmaverse.github.io/blog/posts/2025-05-19_logrx_0.4.0…/logrx_0_4_0_logs_for_your__r_programs.html.
To leave a comment for the author, please follow the link and comment on their blog: pharmaverse blog.
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