将支持R代码的代码包装到python模块中? [英] Packaging supporting R code in a python module?

问题描述

我正在尝试使用 rpy2 打包一些调用R代码的Python代码.该R代码当前位于一个单独的文件中，该文件来自Python脚本，我为source.例如，如果python脚本是myscript.py，则R代码存储在myscript_support.R中，而我在myscript.py中有类似以下内容:

I am trying to package some of my Python code that calls R code using rpy2. That R code currently sits in a separate file which I source from the Python script. For example, if the python script is myscript.py, then the R code is stored in myscript_support.R, and I have something like the following in myscript.py:

from rpy2.robjects import *

# Load the R code
r.source(os.path.join(os.path.dirname(__file__), "myscript_support.R"))

# Call the R function
r[["myscript_R_function"]]()

我现在想使用setuptools打包此Python脚本，我有几个问题:

I now want to package this Python script using setuptools, and I have a few questions:

1. 我应该如何打包R支持代码，一旦完成打包，如何找到R文件的路径以便我可以获取它呢?

1. How should I package the R support code, and once I have done so, how do I find the path to the R file so I can source it?

R代码取决于几个 R 软件包.如何确保已安装?如果无法加载这些R软件包，我是否应该提出一个提示性错误?

The R code depends on several R packages. How can I ensure that these are installed? Should I just raise an informative error if these R packages cannot be loaded?

推荐答案

这个问题可能已经过时，但是我今天遇到了同样的问题，想为@ivan_pozdeev建议的问题1解决方案和新解决方案提供更多详细信息问题2.

This question might be dated, but I ran into the same issue today and wanted to provide more detail for the question 1 solution suggested by @ivan_pozdeev and a new solution for question 2.

1)将setup.py文件编辑为:

1) Edit your setup.py file to:

from setuptools import setup, find_packages

setup(
    ...
    # If any package contains *.r files, include them:
    package_data={'': ['*.r', '*.R']},
    include_package_data=True)
    )

2)Conda迅速成为处理python和R程序包依赖关系的好选择.您可以创建一个环境( http://conda.pydata.org/docs/using/envs )，下载您可能需要的所有r和python程序包，然后生成一个environment.yml文件，以便任何人可以复制您的环境.请查看此博客以获取更多信息: https://www.continuum.io/content/conda -data-science

2) Conda is quickly becoming a good option for dealing with package dependencies across both python and R. You can create an environment (http://conda.pydata.org/docs/using/envs), download all the r and python packages that you might need, and then generate an environment.yml file so that anyone can replicate your environment. Check out this blog for more info: https://www.continuum.io/content/conda-data-science

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