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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,
  expr,
  additional_files = "",
  user_functions = "",
  nix_env = "default.nix",
  encoder = NULL,
  decoder = NULL,
  env_var = NULL,
  noop_build = FALSE
)

Arguments

name

Symbol, name of the derivation.

expr

Character, Julia code to generate the expression. Ideally it should be a call to a pure function. Multi-line expressions are not supported.

additional_files

Character vector, additional files to include during the build process. For example, if a function expects a certain file to be available, this is where you should include it.

user_functions

Character vector, user-defined functions to include. This should be a script (or scripts) containing user-defined functions to include during the build process for this derivation. It is recommended to use one script per function, and only include the required script(s) in the derivation.

nix_env

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

encoder

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 behaviour uses the built‐in Serialization.serialize API. Define any custom serializer in functions.jl. See vignette("encoding-decoding") for more details.

decoder

Character or named vector/list, defaults to NULL. Can be:

  • A single string for the Julia function to unserialize all upstream objects

  • A named vector/list where names are upstream dependency names and values are their specific unserialize functions If NULL, the default is Serialization.deserialize. See vignette("encoding-decoding") for more details.

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.

noop_build

Logical, defaults to FALSE. If TRUE, the derivation produces a no-op build (a stub output with no actual build steps). Any downstream derivations depending on a no-op build will themselves also become no-op builds.

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_jl_file(), 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,
  expr = "filter(df, :col .> 10)"
)

# Skip building this derivation
rxp_jl(
  name = model_result,
  expr = "train_model(data)",
  noop_build = TRUE
)

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