### Installing targets from GitHub in R

Source: https://github.com/ropensci-books/targets/blob/main/CONTRIBUTING.md

This R command, using the `remotes` package, installs the latest development version of the `targets` package directly from its GitHub repository. It is a crucial step for bug reporters to verify if an issue persists in the most current codebase before submitting a new bug report, ensuring the problem is not already resolved.

```R
remotes::install_github("ropensci/targets")
```

--------------------------------

### Generating Reproducible Example with Session Info in R

Source: https://github.com/ropensci-books/targets/blob/main/CONTRIBUTING.md

From the `reprex` package, this R command generates a reproducible example of a problem, optionally including the session information (`si = TRUE`). It streamlines the process of creating self-contained bug reports by automatically capturing code, output, and environmental details, making it easier for others to replicate the issue.

```R
reprex(si = TRUE)
```

--------------------------------

### Linting R Package Code with lintr

Source: https://github.com/ropensci-books/targets/blob/main/CONTRIBUTING.md

This function, typically provided by the `lintr` package, checks an R package's code for adherence to a specified style guide, such as the tidyverse style guide. Running `lint_package()` helps contributors ensure their code follows established formatting conventions, promoting consistency and readability across the project's codebase before submitting pull requests.

```R
lint_package()
```

--------------------------------

### Retrieving GitHub SHA-1 Hash of Installed R Package

Source: https://github.com/ropensci-books/targets/blob/main/CONTRIBUTING.md

This R command retrieves the SHA-1 hash of the specific GitHub commit from which the `targets` package was installed. Including this hash in bug reports is critical for maintainers to identify the precise version of the development package being used, ensuring that they are testing against the exact codebase where the issue was observed.

```R
packageDescription("targets")$GithubSHA1
```

--------------------------------

### Citing the targets R package

Source: https://github.com/ropensci-books/targets/blob/main/README.md

This snippet demonstrates how to obtain citation information for the `targets` R package using the `citation()` function. It provides details for academic publications, including a BibTeX entry.

```R
citation("targets")
```

--------------------------------

### Retrieving R Session Information

Source: https://github.com/ropensci-books/targets/blob/main/CONTRIBUTING.md

This base R function provides a comprehensive summary of the current R session, including the R version, operating system, loaded packages, and locale settings. Including `sessionInfo()` output in bug reports is essential for maintainers to reproduce the environment where an issue occurred, aiding in diagnosis and resolution.

```R
sessionInfo()
```

--------------------------------

### Generating a Stack Trace with rlang in R

Source: https://github.com/ropensci-books/targets/blob/main/CONTRIBUTING.md

This function from the `rlang` package offers an enhanced and more informative stack trace compared to base R's `traceback()`. It provides richer details about the function calls, arguments, and environments, making it a powerful tool for advanced debugging and understanding complex error propagation in R applications.

```R
rlang::trace_back()
```

--------------------------------

### Generating a Stack Trace in R

Source: https://github.com/ropensci-books/targets/blob/main/CONTRIBUTING.md

This base R function prints the call stack of the last error that occurred, showing the sequence of function calls that led to the error. Providing the output of `traceback()` in a bug report is vital for debugging, as it helps pinpoint the exact location and sequence of operations where an error originated within the code.

```R
traceback()
```

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