Is there any way to call base python function in r using reticulate?-CodePudding

I got a "generator object" from a python function. However, I tried many ways but failed to read the "generator object" in r using reticulate. I know python base function list() can convert "generator object" to "json", which I can then read in r. I wonder how to use base python function in r? (I would not prefer to use py_run_file)

For example:

>library(reticulate)
>foo <- import("foo")
>res <- foo.func()
<generator object at 0x7fd4fe98ee40>

Thank you!

CodePudding user response：

You could use iterate or iter_next.

As an example, consider a python generator firstn.py:

def firstn(n):
  num = 0
  while num < n:
    yield num
    num  = 1

You can traverse the generator either with iterate :

library(reticulate)
source_python('firstn.py')
gen <- firstn(10)
gen
#<generator object firstn at 0x0000020CE536AF10>

result <- iterate(gen)
result
# [1] 0 1 2 3 4 5 6 7 8 9

or with iter_next:

iter_next(gen)
[1] 0
iter_next(gen)
[1] 1
iter_next(gen)
[1] 2

CodePudding user response：

I'm not sure if you can in R directly, but you definitely can in R Markdown. I use R Markdown to flip objects back and forth between the two.

I use a basic html_document YAML output. However, I don't typically knit this type of RMD, so I don't think it really matters what you put there if you use it the same way.

When you use reticulate you need an environment.

So first I'll have an R chunk:

```{r setup}

library(tidyverse) # for random r object creation to use in Python
library(reticulate)
use_virtualenv("KerasEnv") # this is an environment I already have setup

# creating R objects to use with Python
str(diamonds)

cut <- diamonds$cut %>% unique()

```

Then I'll create my Python chunk.

```{r usingPy,results="asis",engine="python"}
    
import numpy as np
import random

diamonds_py = r.diamonds # bring dataset into Python

mxX = max(diamonds_py.x) # create a new Python object to bring into R
print(mxX)
# 10.74

cut_py = r.cut # bring vector into Python 

```

Now let's say I want to bring something from Python back into R.

```{r tellMeMore}
# bring Python object into R
mxX_r = py $ mxX
# [1] 10.74 

```

You can run the Python and R code line by line, by chunk, or knit. To clear the Python environment, I'm pretty sure you have to restart RStudio.