首先你需要激活你的环境。

pip install ipykernel

接下来，您可以通过输入以下命令将虚拟环境添加到Jupyter:

python -m ipykernel install --name = my_env

首先你需要激活你的环境。

pip install ipykernel

接下来，您可以通过输入以下命令将虚拟环境添加到Jupyter:

python -m ipykernel install --name = my_env

nb_conda_kernels包是在conda中使用jupyter的最佳方式。通过最小的依赖关系和配置，它允许您使用运行在不同环境中的jupyter笔记本上的其他conda环境。引用其文件:

Installation This package is designed to be managed solely using conda. It should be installed in the environment from which you run Jupyter Notebook or JupyterLab. This might be your base conda environment, but it need not be. For instance, if the environment notebook_env contains the notebook package, then you would run conda install -n notebook_env nb_conda_kernels Any other environments you wish to access in your notebooks must have an appropriate kernel package installed. For instance, to access a Python environment, it must have the ipykernel package; e.g. conda install -n python_env ipykernel To utilize an R environment, it must have the r-irkernel package; e.g. conda install -n r_env r-irkernel For other languages, their corresponding kernels must be installed.

然后你需要做的就是启动jupyter笔记本服务器:

conda activate notebook_env  # only needed if you are not using the base environment for the server
# conda install jupyter # in case you have not installed it already
jupyter

尽管有太多的答案，@merv也在努力改进，但仍然很难找到一个好的答案。我做了这个CW，所以请投票给它的顶部或改进它!

我也遇到了同样的问题，我的新conda环境myenv不能被选为内核或新笔记本。在env中运行jupter notebook也得到了相同的结果。

我的解决方案，以及我了解到Jupyter笔记本如何识别conda-envs和内核:

使用conda将jupyter和ipython安装到myenv:

conda install -n myenv ipython jupyter

在那之后，在任何env之外运行jupter notebook时，将myenv与我以前的环境一起列为内核。

Python [conda env:old]
Python [conda env:myenv]

启动环境后运行笔记本:

source activate myenv
jupyter notebook

隐藏所有其他环境内核，只显示我的语言内核:

python 2
python 3
R

仅使用环境变量:

python -m ipykernel install --user --name $(basename $VIRTUAL_ENV)

按照iPython文档中的说明，将不同的conda环境添加到Jupyter Notebook中可供选择的内核列表中。总之，安装完ipykernel后，必须在终端中逐个激活conda环境，执行命令python -m ipykernel install——user——name myenv——display-name " python (myenv)"，其中myenv就是要添加的环境(内核)。