async_expr: Apply R expressions in a parallel way

In dipsaus: A Dipping Sauce for Data Analysis and Visualizations

Apply R expressions in a parallel way

Description

Apply R expressions in a parallel way

Usage

async_expr(
  .X,
  .expr,
  .varname = "x",
  envir = parent.frame(),
  .pre_run = NULL,
  .ncore = future::availableCores(),
  ...
)

Arguments

.X	a vector or a list to apply evaluation on
.expr	R expression, unquoted
.varname	variable name representing element of each .X
envir	environment to evaluate expressions
.pre_run	expressions to be evaluated before looping.
.ncore	number of CPU cores
...	passed to future::future

Details

async_expr uses lapply and future::future internally. Within each loop, an item in ".X" will be assigned to variable "x" (defined by ".varname") and enter the evaluation. During the evaluation, function async is provided. Expressions within async will be evaluated in another session, otherwise will be evaluated in current session. Below is the workflow:

• Run .pre_run

• For i in seq_along(.X):

  • 1. Assign x with .X[[i]], variable name x is defined by .varname

  • 2. Evaluate expr in current session.

    • a. If async is not called, return evaluated expr

    • b. If async(aync_expr) is called, evaluate aync_expr in another session, and return the evaluation results if aync_expr

Value

a list whose length equals to .X. The value of each item returned depends on whether async is called. See details for workflow.

dipsaus documentation built on July 9, 2023, 5:43 p.m.