reticulate-reexports: Wrappers around "reticulate" package

In rpymat: Easy to Configure an Isolated 'Python' Environment

Wrappers around 'reticulate' package

Description

Almost the same with 'reticulate' functions, with rpymat enabled by default and some minor changes (see parameter convert and local)

Usage

import_main(convert = FALSE)

tuple(..., convert = FALSE)

py_tuple(..., convert = FALSE)

py_help(object)

np_array(data, ...)

import(module, as = NULL, convert = FALSE, delay_load = FALSE)

r_to_py(x, convert = FALSE)

py_to_r(x)

py_to_r_wrapper(x)

py_str(object, ...)

py_run_string(code, local = TRUE, convert = FALSE)

py_bool(x)

py_dict(keys, values, convert = FALSE)

py_call(x, ...)

py_del_attr(x, name)

py_del_item(x, name)

py_eval(code, convert = FALSE)

py_get_attr(x, name, silent = FALSE)

py_set_attr(x, name, value)

py_get_item(x, key, silent = FALSE)

py_set_item(x, name, value)

py_len(x, default = NULL)

py_none()

Arguments

convert	whether to convert 'Python' objects to R; default is FALSE. This is different to 'reticulate', but less error prone: users must explicitly convert 'Python' objects to R.
object, data, x, code, keys, values, ...	passed to corresponding 'reticulate' functions as data inputs
module, as, delay_load	import 'Python' module as alias
local	whether to execute code locally so the memory sets free when the function ends; default is true
name, silent, key, value, default	other parameters passing to the 'reticulate' functions

Value

'Python' built-in objects

Examples

library(rpymat)
if(interactive() && dir.exists(env_path())) {

  # tuple
  x <- tuple(1, 2, "a")
  print(x)

  # convert to R object
  py_to_r(x)

  # convert R object to python
  y <- r_to_py(list(a = 1, b = "s"))

  # get element
  py_get_item(y, "a")

  # get missing element
  py_get_item(y, "c", silent = TRUE)

}

rpymat documentation built on Aug. 22, 2023, 9:12 a.m.