Merge pull request #195 from pharmaverse/159-185-blank-line-spellcheck

159 185 blank line spellcheck

.github/workflows/spellcheck.yaml

@@ -0,0 +1,33 @@
+---
+name: Spellcheck
+
+on:
+ push:
+ branches:
+ - main
+ - dev
+ pull_request:
+ branches:
+ - main
+ - dev
+
+jobs:
+ spell:
+ runs-on: ubuntu-latest
+ env:
+ GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+ steps:
+ - uses: actions/checkout@v3
+
+ - uses: r-lib/actions/setup-r@v2
+ with:
+ use-public-rspm: true
+
+ - uses: r-lib/actions/setup-r-dependencies@v2
+ with:
+ needs: spelling
+
+ - name: Run Spelling Check test
+ uses: insightsengineering/r-spellcheck-action@v3
+ with:
+ exclude: data/*

NEWS.md

@@ -2,7 +2,7 @@
 
 - Moved website theme to bootstrap 5, enabled search (#179)
 - Add `show_repo_url` option in `axecute()` to capture repo URL(s) into log file (#167)
-- Moved website theme to bootstarp 5, enabled search (#179)
+- Moved website theme to Bootstrap 5, enabled search (#179)
 - Add `include_rds` argument to `axecute()` to export log as rds file
 - Add `library_call_linter()` to ensure all library calls are at the top of the script (#163)
 - Remove argument for remove_log_object from `axecute()` still accessible via `log_write()` (#182)

R/interact.R

@@ -139,7 +139,7 @@ run_safely_loudly <- function(file) {
  set_log_element("result", ret$result$result)
  set_log_element("warnings", ret$warnings)
  set_log_element("errors", ret$result$error)
- set_log_element("hash_sum", digest::sha1(readLines(file)))
+ set_log_element("hash_sum", digest::sha1(readLines(file, warn = FALSE)))
 
  # Session Info
  set_log_element("session_info", get_session_info())

R/log.R

@@ -1,6 +1,6 @@
 ### Functions to initialise, configure, cleanup, and write the log.rx environment
 
-#' Initialisation of the log.rx environment
+#' Initialization of the log.rx environment
 #'
 #' `log_init()` initialises the log.rx environment
 #'

inst/WORDLIST

@@ -15,3 +15,25 @@ SDTM
 tidyr
 rds
 logrx
+addin
+Angly
+axecution
+customizable
+devtools
+hashsum
+Hotfix
+Linter
+linters
+lintr
+logrxpackage
+param
+Patil
+Ren
+repo
+Rosenstock
+Rscript
+rx
+sessionInfo
+tidylog
+initialises
+scrollable

vignettes/articles/tidylog.Rmd

@@ -28,7 +28,7 @@ Below we have a simple script using the `us_rent_income` dataset. We will explo
 
 <br>
 
-Using `axecute(ex1_tidylog.R)` we produce a log file. Below we snapshot just the pertinent information for users interested in the `{tidylog}` feeback. This feedback is placed by the `{logrx}` package into the `Messages, Output, and Result` section of the log.
+Using `axecute(ex1_tidylog.R)` we produce a log file. Below we snapshot just the pertinent information for users interested in the `{tidylog}` feedback. This feedback is placed by the `{logrx}` package into the `Messages, Output, and Result` section of the log.
 
 <br>
 

vignettes/execution.Rmd

@@ -22,10 +22,10 @@ library(logrx)
 `logrx` has been built with both the flexibility of code execution and a number of different use cases in mind. While the basic case has been outlined in our [Get Started](https://pharmaverse.github.io/logrx/articles/logrx.html) vignette, here we will be discussing different methods of execution and creation of log files. These examples are meant to guide users who wish to explore different methods of execution or for those using ```logrx``` to create scripting.
 
 # Methods of Execution
-Below you will find a number of examples for different methods of exectuion, these go in an increasing level of complexity and increasing level of technical knowledge. The below examples are meant to be starting points for those interested in using ```logrx``` in more complex settings.
+Below you will find a number of examples for different methods of execution, these go in an increasing level of complexity and increasing level of technical knowledge. The below examples are meant to be starting points for those interested in using ```logrx``` in more complex settings.
 
 ## `axecute()`
-The easiest of the execution methods to use is `axecute()`. This function can be used to exeucte code from an R terminal or using command line scripts. A log is 
+The easiest of the execution methods to use is `axecute()`. This function can be used to execute code from an R terminal or using command line scripts. A log is 
 set-up around the program, and its code is run safely and loudly (using `safely()` from `{purrr}`).
 ```{r axecute, eval = FALSE}
 axecute("my_script.R")
@@ -45,7 +45,7 @@ messages, output, and result. This must be passed an executable R file to run a
 
 * `log_write()` to generate and format the log
 
-* `log_remove()` to remove the `log.rx` environment created by code exeuction
+* `log_remove()` to remove the `log.rx` environment created by code execution
 
 ```{r log_*, eval = FALSE}
 log_config("my_script.R")
@@ -55,7 +55,7 @@ log_remove()
 ```
 
 ## Command Line Execution
-While exeucting from an R terminal is nice if you have access to one, you can also execute your code using system command line. This is done using the `Rscript -e` command which executes a file using the registered Rscript executable. Below are a few examples of how to use the command line to execute a file and create a log as well as how to manipulate the outputs of the execution. These are likely to be advanced examples for most users.
+While executing from an R terminal is nice if you have access to one, you can also execute your code using system command line. This is done using the `Rscript -e` command which executes a file using the registered Rscript executable. Below are a few examples of how to use the command line to execute a file and create a log as well as how to manipulate the outputs of the execution. These are likely to be advanced examples for most users.
 
 The below chunk will run the file my_script.R and output any standard output that is created by the execution of the file to the default location.
 ```{r, engine = 'bash', eval = FALSE}
@@ -87,11 +87,11 @@ r_script_list <- list.files(path = ".", pattern = "\\.R$")
 lapply(r_script_list, axecute)
 ```
 
-Additionally, if you need your code to run using a shell scripting language such as bash these files can be created to run using the previously outlined Command Line Execution examples.  The above scripting examples can be translated into a variety of different scritping languages. Below is an example where the bash script is executed in a directory of R files, this should execute all R files in the directory using `axecute()` and create a corresponding set of log files.
+Additionally, if you need your code to run using a shell scripting language such as bash these files can be created to run using the previously outlined Command Line Execution examples. The above scripting examples can be translated into a variety of different scripting languages. Below is an example where the bash script is executed in a directory of R files, this should execute all R files in the directory using `axecute()` and create a corresponding set of log files.
 
 ```{r, engine = 'bash', eval = FALSE}
 for file in *.R; do
  [ -f "$file" ] || continue
  Rscript -e "logrx::axecute('$file')"
 done
-```
+```

vignettes/logrx.Rmd

@@ -67,7 +67,7 @@ list of packages and functions
 * **Messages, Output and Results (optional)** - List Messages, Outputs and Results
 * **Log Output File** - Name and path of the log
 
-Below we have a scrollabe example of what is included in a log file for an `adsl.R` script. 
+Below we have a scrollable example of what is included in a log file for an `adsl.R` script. 
 
 
 <style>