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# Managing Python environments within Bioconductor |Environment|Status| |---|---| |BioC-release|[![Release OK](](| |BioC-devel|[![Devel OK](](| **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: ```r 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`](inst/example/) directory and contains code like: ```r # 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.