searcher package (CRAN,
GitHub) provides a search interface to look up terms on popular websites
such as Google, Bing,
GitHub, and BitBucket.
Upon calling a
search_*() function, a browser window will open with the
search results for the query.
That said, a new year means new
searcher capabilities! The
received its biggest ever overhaul to date in its quest to provide a stable
and customizable API. In particular, the
search_*() functions are now
generated using a function factory alongside pre-defined values. By changing
the underlying structure,
searcher gains future-proofing and a lower maintenance
cost as code is no longer repeated multiple for each search portal.
Furthermore, this release gains a new set of customization toggles accessible
that allow for improved package experiences. In particular, the default search
term used can be switched from a “base R” perspective to a “tidyverse” perspective
searcher.default_keyword = "tidyverse" in
Lastly, in a long overdue sense,
searcher now has the ability to search
#rstats community! The
hash tag is a central location for discussions on R within Twitter. Try
it out with:
For more details, please see the full NEWS entry below.
searcher news file entry for version 0.0.5 (2020-02-06)
- Added search portal:
- Added ability to set default package actions.
searcher.launch_delaycontrols how long the user remains in R prior to the browser opening. Default is
searcher.use_rstudio_viewerspecifies whether RStudio’s viewer pane should open the link instead of a web browser. Default is
FALSEuntil RStudio’s sandbox issue is resolved.
searcher.default_keyword: Suffix keyword to focus search results between either
"tidyverse". Default is
- Added option to launch RStudio’s Viewer pane to display search results.
- Function factory or a closure approach-based approach is now used to create
search portal functions
searcher()function has lost the ability to specify
rlangto address an unevaluated promise issue.
- Addressed internal vignette index name being used as the title.
- Switched from using TravisCI to using GitHub Actions for R. (#25, #27)
- Improved code coverage of unit tests (#29)