网状 - 在Rmarkdown中运行python块

Maybe I'm missing something, but if the following code is the content of my Rmd file

也许我错过了一些东西，但如果下面的代码是我的Rmd文件的内容

```{r}
library(reticulate)
use_virtualenv("r-reticulate")
py_available(TRUE)
```
```{python}
a = 7
print(a)
```
```{r}
py$a
```

when I Knit the file, the output for the last chunk is 7 (as expected). On the other hand, clicking the run all button in Rstudio (or running chunks one by one), results on NULL for the last chunk.

当我编织文件时，最后一个块的输出是7（如预期的那样）。另一方面，单击Rstudio中的“全部运行”按钮（或逐个运行块），最后一个块的结果为NULL。

Comparing with the R notebook example it seems like assigning something to flights in the python chunk should make py$flights available for R, but that doesn't seem the case.

与R笔记本示例相比，似乎为python块中的航班分配了一些东西，应该为R提供py $航班，但事实并非如此。

Questions:

问题：

Is there a way to access from R a variable created in a Python chunk previously ran (not knit)? How to "export" to R a variable created within a python chunk?
有没有办法从R访问一个先前运行过的Python块中创建的变量（不是编织）？如何“导出”R在python块中创建的变量？
What is a good reference to understand what happens when I click the run button in a python chunk of a Rmarkdown file?
什么是一个很好的参考，以了解当我点击Rmarkdown文件的python块中的运行按钮时会发生什么？

EDIT: Ok so after seeing the first answers here, I did update both knitr and rmarkdown to the latest version, but still had the same problem. I added py_available(TRUE) to my file to make sure it was initialized, still, last chunk results in 7 when knitted, but running chunks one-by-one results in

编辑：好的，所以在看到第一个答案后，我确实更新了knitr和rmarkdown到最新版本，但仍然有同样的问题。我将py_available（TRUE）添加到我的文件中以确保它已被初始化，但是，当针织时，最后一个块结果为7，但是逐个运行块会导致

> py$a
Error in py_get_attr_impl(x, name, silent) : 
  AttributeError: 'module' object has no attribute 'a'

The problem is: Assigning a value to a in the python chunk isn't doing anything to py$a in the R environment. Maybe this "shared" environment between R and python isn't how the package is supposed to work? Also, for some extra information

问题是：为py块中的a赋值不会对R环境中的py $ a做任何事情。也许R和python之间的这个“共享”环境不是这个包应该如何工作的？另外，还有一些额外的信息

> py_config()
python:         /usr/bin/python
libpython:      /usr/lib/python2.7/config-x86_64-linux-gnu/libpython2.7.so
pythonhome:     /usr:/usr
version:        2.7.14 (default, Sep 23 2017, 22:06:14)  [GCC 7.2.0]
numpy:          /usr/lib/python2.7/dist-packages/numpy
numpy_version:  1.12.1

python versions found: 
 /usr/bin/python
 /usr/bin/python3

2 个解决方案

#1

Rmarkdown / knitr:

Rmarkdown / knitr：

Running the chunks:

运行块：

Running the chunks without knitting the document is not supported so far. See here: https://github.com/yihui/knitr/issues/1440 or Reticulate not sharing state between R/Python cells or Python/Python cells in RMarkdown.

到目前为止，不支持在不编织文档的情况下运行块。请参阅此处：https：//github.com/yihui/knitr/issues/1440或网格化不在RM / RM中的R / Python单元格或Python / Python单元格之间共享状态。

Edit: Workaround by Freguglia:

编辑：Freguglia的解决方法：

"Workaround is to turn python chunks into R chunks and just wrap the whole content in the py_run_string() function, so whatever you assign in that piece of code is accessible from R by py$variable_name."

“解决方法是将python块转换为R块，并将整个内容包装在py_run_string（）函数中，因此无论您在该段代码中分配的是什么，都可以通过py $ variable_name从R中访问。”

Knitting the document:

编织文件：

One way is to upgrade knitr as suggested above, but you dont have to and you also dont need RStudio daily build.

一种方法是按照上面的建议升级knitr，但是你没必要，而且你也不需要每天构建RStudio。

If you have a version of knitr prior to 1.18, you can include:

如果你有1.18之前的knitr版本，你可以包括：

```{r setup, include = FALSE} knitr::knit_engines$set(python = reticulate::eng_python) ``` , see here: https://rstudio.github.io/reticulate/articles/r_markdown.html#engine-setup.

```{r setup，include = FALSE} knitr :: knit_engines $ set（python = reticulate :: eng_python）```，见这里：https：//rstudio.github.io/reticulate/articles/r_markdown.html#发动机设置。

Python:

蟒蛇：

If it doesnt work ensure the python connection is running outside of rmarmdown/knitr: py_run_string("x = 10"); py$x.

如果它不起作用，请确保python连接在rmarmdown / knitr之外运行：py_run_string（“x = 10”）; PY $ X。

In case that also doesnt work, you should check: py_available() and py_numpy_available().

如果也不起作用，您应该检查：py_available（）和py_numpy_available（）。

If it returns FALSE: Try to initialize it with: py_available(TRUE).

如果返回FALSE：尝试使用以下命令初始化它：py_available（TRUE）。

If that´s still a no - check your config: py_config()

如果仍然没有 - 检查你的配置：py_config（）

It will give you further hints on the problem:

它将为您提供有关该问题的进一步提示：

Examples for me were: different bit versions of R and python (32 vs 64) or somehow i ran into trouble having installed both Python2.7 and seperately Anaconda.

我的例子是：R和python的不同位版本（32对64）或者不知何故我遇到了安装Python2.7和单独的Anaconda的麻烦。

#2

You must use the Rstudio daily build (source) and upgrade knitr, rmarkdown to the latest version.

您必须使用Rstudio每日构建（源）并将knitr，rmarkdown升级到最新版本。

> packageVersion("rmarkdown")
[1] ‘1.9’
> packageVersion("knitr")
[1] ‘1.20’

#1