Rasta is available as a R package. It isn't on CRAN yet, but you can install it from this repository using the remotes
package,
remotes::install_github("stencila/rasta")
Register Rasta so that it can be discovered by other executors on your machine,
rasta::register()
If you have executa
installed globally, you can then run Rasta using the execute
command and specifying r
as the starting language,
executa execute --repl --lang r
Get started by cloning this repository,
git clone git@github.com:stencila/rasta
cd rasta
Then install the necessary development dependencies,
make setup
Most development tasks can be run from R, using make
shortcuts, or RStudio keyboard shortcuts.
Task | make |
R/RStudio |
---|---|---|
Install development dependencies | make setup |
devtools::install_dev_deps() |
Run linting | make lint |
lintr::lint_package() |
Run R tests | make test-r |
devtools::test() or Ctrl+Shift+T |
Run C++ tests | make test-cpp |
|
Run all tests | make test |
|
Run tests with coverage | make cover |
covr::package_coverage() |
Run benchmarks | make bench |
|
Build documentation | make docs |
|
Check the package | make check |
Ctrl+Shift+E |
Build | make build |
Ctrl+Shift+B |
Clean | make clean |
Unit tests live in the tests
folder. Most of the tests are written using the testthat
package. When writing regression tests for a specific issues, please name the test file accordingly e.g. tests/testthat/test-issue-1.R
. There is also a tests/cpp
folder for C++ tests and a tests/bench
folder for benchmarking.
Documentation is written using roxygen2
and the documentation site is generated by pkgdown
into the docs
folder and published on GitHub pages at https://stencila.github.io/rasta/.
Tests are run on Azure Pipelines and code coverage tracked at Codecov.
-
This package has two functions,
stream_read_message
andstream_write_message
, for reading and writing length prefixed messages from/to streams. These functions are implemented in both R and C++ and there is benchmarking code to compare their performance (runmake bench
and look for the outputs intests/bench
). The C++ implementations are 2-3 times faster. However, the times involved are small (<100µs for 10k messages) and having C++ code does add complexity and a dependency (Rcpp
). Given that, we may remove the C++ implementations in the future. -
This package provides a
StdioServer
class which implements Stencila's execution API over standard input / output streams. It is analogous to theStdioServer
class implemented in Typescript in thestencila/executa
package. A previous version of this repository implemented aPipeServer
class which used named pipes as the transport. However, this was not used in production, and so in the interest of keeping the code base as simple as possible, was removed. This note is intended for developers who might find a need to use the API over named pipes in the future.