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Create a Nix expression running a Julia function

Source: R/derivs.R
rxp_jl.Rd

Create a Nix expression running a Julia function

Usage

rxp_jl(
  name,
  jl_expr,
  additional_files = "",
  nix_env = "default.nix",
  serialize_function = NULL,
  unserialize_function = NULL,
  env_var = NULL
)

Arguments

name

Symbol, name of the derivation.

jl_expr

Character, Julia code to generate the expression.

additional_files

Character vector, additional files to include. Custom functions must go into a script called "functions.jl", and additional files that need to be accessible during the build process can be named anything.

nix_env

Character, path to the Nix environment file, default is "default.nix".

serialize_function

Character, defaults to NULL. The name of the Julia function used to serialize the object. It must accept two arguments: the object to serialize (first), and the target file path (second). If NULL, the default behavior uses the built‐in Serialization.serialize API. Define any custom serializer in functions.jl.

unserialize_function

Character, defaults to NULL. The name of the Julia function used to unserialize the object. It must accept one argument: the file path. If NULL, the default is assumed to be Serialization.deserialize.

env_var

Character vector, defaults to NULL. A named vector of environment variables to set before running the Julia script, e.g., c("JULIA_DEPOT_PATH" = "/path/to/depot"). Each entry will be added as an export statement in the build phase.

Value

An object of class derivation which inherits from lists.

Details

At a basic level, rxp_jl(filtered_data, "filter(df, :col .> 10)") is equivalent to filtered_data = filter(df, :col .> 10) in Julia. rxp_jl() generates the required Nix boilerplate to output a so‐called "derivation" in Nix jargon. A Nix derivation is a recipe that defines how to create an output (in this case filtered_data) including its dependencies, build steps, and output paths.

See also

Other derivations: rxp_py(), rxp_py_file(), rxp_qmd(), rxp_r(), rxp_r_file(), rxp_rmd()

Examples

if (FALSE) { # \dontrun{
# Basic usage, no custom serializer
rxp_jl(
  name = filtered_df,
  jl_expr = "filter(df, :col .> 10)"
)

# Custom serialization: assume `save_my_obj(obj, path)` is defined in functions.jl
rxp_jl(
  name = model_output,
  jl_expr = "train_model(data)",
  serialize_function = "save_my_obj",
  additional_files = "functions.jl"
)
} # }