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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 installedBiocManager::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 pandasreturn(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.
About
Clone of the Bioconductor repository for the basilisk package.