如何将R conda env连接到Jupyter Notebook [英] How to connect R conda env to jupyter notebook

问题描述

我正在使用以下代码创建conda环境

I am creating conda environment using following code

 conda create --prefix r_venv_conda r=3.3  r-essentials  r-base --y

然后，我将按照

 conda activate r_venv_conda/

然后我尝试运行Jupyter Notebook(通过运行jupyter notebook以运行jupyter希望可以连接R env.但是，我遇到了以下错误

Then I tried to run Jupyter Notebook (by running jupyter notebook to run jupyter hoping that will connect R env. However, I am getting following error

Traceback (most recent call last):
  File "/home/Documents/project/r_venv_conda/bin/jupyter-notebook", line 7, in <module>
    from notebook.notebookapp import main
  File "/home/Documents/project/r_venv_conda/lib/python3.6/site-packages/notebook/__init__.py", line 25, in <module>
    from .nbextensions import install_nbextension
  File "/home/Documents/project/r_venv_conda/lib/python3.6/site-packages/notebook/nbextensions.py", line 26, in <module>
    from .config_manager import BaseJSONConfigManager
  File "/home/Documents/project/r_venv_conda/lib/python3.6/site-packages/notebook/config_manager.py", line 14, in <module>
    from traitlets.config import LoggingConfigurable
  File "/home/Documents/project/r_venv_conda/lib/python3.6/site-packages/traitlets/config/__init__.py", line 6, in <module>
    from .application import *
  File "/home/Documents/project/r_venv_conda/lib/python3.6/site-packages/traitlets/config/application.py", line 38, in <module>
    import api.helper.background.config_related
ModuleNotFoundError: No module named 'api'

如何解决此问题?

推荐答案

Jupyter不会自动识别已激活或未激活的Conda环境.

Jupyter does not automatically recognize Conda environments, activated or not.

首先，要使环境作为内核运行，需要安装适当的内核程序包.在这种情况下，它是r-irkernel，因此您需要运行

First, for an environment to run as a kernel, it needs to have the appropriate kernel package installed. In this case, that is r-irkernel, so you need to run

conda install -n r_venv_conda r-irkernel

对于Python内核，它是ipykernel.

For Python kernels, it's ipykernel.

第二，需要向Jupyter注册内核.如果您通过Conda安装了Jupyter(例如在Anaconda base env中安装)，那么我建议使用

Second, kernels need to be registered with Jupyter. If you have Jupyter installed via Conda (say in an Anaconda base env), then I recommend using the nb_conda_kernels package, which enables auto-discovery of kernel-ready Conda-envs. This must be installed in the env that has jupyter installed (you only need one!), for example, if this is base, then

conda install -n base nb_conda_kernels

请阅读文档以了解详细信息.

如果您正在使用Jupyter的系统级安装(即不是由Conda安装)，则需要手动注册内核.

If you are using a system-level installation of Jupyter (i.e., not installed by Conda), then you need to manually register your kernel.

conda activate r_venv_conda
Rscript -e 'IRkernel::installspec(name="ir33", displayname="R 3.3")'

，您可以在其中为name和displayname设置自己的值. 有关详细信息，请参阅IRkernel .

where you can set your own values for name and displayname. See IRkernel for details.

如果再次使用Conda安装的Jupyter，则只需将其安装在单个环境中.这是在运行jupyter notebook之前应激活的环境.运行之后，然后选择要使用的内核.

If using a Conda-installed Jupyter, again, it only needs to be installed in a single env. This is the env that should be activated before running jupyter notebook. Once running, then you select the kernel you wish to use.

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