| Environment | Status |
|---|---|
| BioC-release |  |
| BioC-devel |  |
basilisk provides a standardized mechanism for handling Python dependencies within Bioconductor packages.
It does so by automatically provisioning and managing one or more Conda environments per BioC package,
ensuring that the end-user is not burdened with the responsibility of meeting any Python-based SystemRequirements.
We integrate with reticulate to allow intuitive calling of Python code within R,
with additional protection to ensure that multiple Python environments can be called within the same R session.
Most "users" of this package are expected to be Bioconductor package developers; end users should not need to interact with the basilisk machinery, all going well. Users can follow the typical installation process for Bioconductor packages:
install.packages("BiocManager") # if not already installed
BiocManager::install("basilisk")
# Bioconductor package developers may prefer to use the devel version:
BiocManager::install("basilisk", version="devel") The vignette provides instructions on how to adapt a client package to use basilisk.
A minimal example is provided in the inst/example directory and contains code like:
# Provision an environment.
my_env <- BasiliskEnvironment(envname="my_env_name",
pkgname="name.of.package",
packages=c("pandas==0.25.1")
)
# Run reticulate code using that environment.
res <- basiliskRun(env=my_env, fun=function(args) {
out <- reticulate::import("pandas")
# Do something with pandas
return(some_r_object)
})Detailed documentation for each function is available through the usual methods, i.e., ?basiliskRun.
See the Bioconductor landing page for more links;
some examples of basilisk client packages include crisprScore and velociraptor.
Bugs can be posted to the Issues of this repository. Pull requests are welcome.