打开终端(或CMD为窗口)，然后执行以下命令: (在窗口中，在第二行中删除“source”。)

conda create -n py35 python=3.5
source activate py35
conda install notebook ipykernel
ipython kernel install --user --name=python3.5

我尝试了一些方法，但它不工作，然后我发现这个方法。 这对我很管用。希望能有所帮助。

在ElementaryOS Freya(基于Ubuntu 14.04)上，其他答案都没有立即对我起作用;我得到了

[TerminalIPythonApp]警告|文件不存在:'kernelspec'

quickbug在Matt的回答中描述的错误。我首先要做的是:

Sudo apt-get安装pip3

安装ipython[所有]

这时你就可以运行Matt建议的命令了;即:ipython kernelspec install-self和ipython3 kernelspec install-self

现在，当我启动ipython notebook，然后打开一个notebook时，我能够从kernel菜单中选择Python 3内核。

使用Python2获得ipython笔记本(在Windows7上) 用pip install -U Jupyter升级到Jupyter 安装Python3 使用pip3 install Jupyter再次安装Jupyter 使用ipython3 kernelspec install-self安装Python3内核 我终于有两个工作的玉米粒了。

我也面临着同样的问题。每当我使用以下命令启动jupyter notebook时，我都不会看到创建一个新的Python 3 notebook的选项。

我通过运行以下命令解决了这个问题。

pip install notebook

之后，我开始笔记本与相同的命令之前

jupyter notebook

我能够看到我的主目录并创建新的python3笔记本。

要将特定的python添加到jupyter内核中，首先使用以下命令检查可用的python或python3的路径

$ where python3

假设你有'/usr/local/bin/python3'作为路径之一。要为这个版本的python创建一个名为'name_to_new_kernel'的内核，该内核将显示在jupyter中，

$ /usr/local/bin/python3 -m pip install ipykernel
$ /usr/local/bin/python3 -m ipykernel install --user --name name_to_new_kernel

使用实例检查名称为'name_to_new_kernel'的新内核是否添加到jupyter

jupyter kernelspec list

将多个内核安装到单个虚拟环境(venv)

这些答案中的大多数(如果不是全部的话)假设您乐于在全局范围内安装包。这个答案适合你，如果你:

使用*NIX机器 不喜欢全局安装包 不要使用anaconda <->，你很乐意从命令行运行jupyter服务器 想要知道内核安装“在哪里”。

(注意:这个答案在python3-jupyter安装中添加了一个python2内核，但在概念上很容易交换。)

Prerequisites You're in the dir from which you'll run the jupyter server and save files python2 is installed on your machine python3 is installed on your machine virtualenv is installed on your machine Create a python3 venv and install jupyter Create a fresh python3 venv: python3 -m venv .venv Activate the venv: . .venv/bin/activate Install jupyterlab: pip install jupyterlab. This will create locally all the essential infrastructure for running notebooks. Note: by installing jupyterlab here, you also generate default 'kernel specs' (see below) in $PWD/.venv/share/jupyter/kernels/python3/. If you want to install and run jupyter elsewhere, and only use this venv for organizing all your kernels, then you only need: pip install ipykernel You can now run jupyter lab with jupyter lab (and go to your browser to the url displayed in the console). So far, you'll only see one kernel option called 'Python 3'. (This name is determined by the display_name entry in your kernel.json file.) Add a python2 kernel Quit jupyter (or start another shell in the same dir): ctrl-c Deactivate your python3 venv: deactivate Create a new venv in the same dir for python2: virtualenv -p python2 .venv2 Activate your python2 venv: . .venv2/bin/activate Install the ipykernel module: pip install ipykernel. This will also generate default kernel specs for this python2 venv in .venv2/share/jupyter/kernels/python2 Export these kernel specs to your python3 venv: python -m ipykernel install --prefix=$PWD/.venv. This basically just copies the dir $PWD/.venv2/share/jupyter/kernels/python2 to $PWD/.venv/share/jupyter/kernels/ Switch back to your python3 venv and/or rerun/re-examine your jupyter server: deactivate; . .venv/bin/activate; jupyter lab. If all went well, you'll see a Python 2 option in your list of kernels. You can test that they're running real python2/python3 interpreters by their handling of a simple print 'Hellow world' vs print('Hellow world') command. Note: you don't need to create a separate venv for python2 if you're happy to install ipykernel and reference the python2-kernel specs from a global space, but I prefer having all of my dependencies in one local dir

博士TL;

Optionally install an R kernel. This is instructive to develop a sense of what a kernel 'is'. From the same dir, install the R IRkernel package: R -e "install.packages('IRkernel',repos='https://cran.mtu.edu/')". (This will install to your standard R-packages location; for home-brewed-installed R on a Mac, this will look like /usr/local/Cellar/r/3.5.2_2/lib/R/library/IRkernel.) The IRkernel package comes with a function to export its kernel specs, so run: R -e "IRkernel::installspec(prefix=paste(getwd(),'/.venv',sep=''))". If you now look in $PWD/.venv/share/jupyter/kernels/ you'll find an ir directory with kernel.json file that looks something like this:

{
  "argv": ["/usr/local/Cellar/r/3.5.2_2/lib/R/bin/R", "--slave", "-e", "IRkernel::main()", "--args", "{connection_file}"],
  "display_name": "R",
  "language": "R"
}

总之，内核只是从内核调用特定于语言的可执行文件。Json文件，jupyter在…/share/jupyter/kernels目录和列表在本例中，调用R来运行IRkernel::main()函数，该函数将向Jupiter服务器来回发送消息。类似地，python2内核只是使用ipykernel_launcher模块调用python2解释器，如.venv/share/jupyter/kernels/python2/kernel中所示。json等。

如果您想一下子运行所有这些指令，这里有一个脚本。