在新conda环境tf中无法启动Jupyter Notebook的问题咨询

我创建了名为tf的TensorFlow conda环境，环境可正常使用，但执行以下安装步骤运行Jupyter Notebook时出现问题：

conda install ipykernel (执行成功)
python -m ipykernel install --user --name=tf (执行成功)
jupyter notebook (执行报错)

执行jupyter命令返回：

(tf) C:\Users\Anonymous>jupyter
usage: jupyter [-h] [--version] [--config-dir] [--data-dir] [--runtime-dir] [--paths] [--json] [--debug] [subcommand]

Jupyter: Interactive Computing

positional arguments:
  subcommand     the subcommand to launch

options:
  -h, --help     show this help message and exit
  --version      show the versions of core jupyter packages and exit
  --config-dir   show Jupyter config dir
  --data-dir     show Jupyter data dir
  --runtime-dir  show Jupyter runtime dir
  --paths        show all Jupyter paths. Add --json for machine-readable format.
  --json         output paths as machine-readable json
  --debug        output debug information about paths

Available subcommands: kernel kernelspec migrate run script troubleshoot

Please specify a subcommand or one of the optional arguments.

执行jupyter notebook命令返回：

(tf) C:\Users\Anonymous>jupyter notebook
usage: jupyter [-h] [--version] [--config-dir] [--data-dir] [--runtime-dir] [--paths] [--json] [--debug] [subcommand]

Jupyter: Interactive Computing

positional arguments:
  subcommand     the subcommand to launch

options:
  -h, --help     show this help message and exit
  --version      show the versions of core jupyter packages and exit
  --config-dir   show Jupyter config dir
  --data-dir     show Jupyter data dir
  --runtime-dir  show Jupyter runtime dir
  --paths        show all Jupyter paths. Add --json for machine-readable format.
  --json         output paths as machine-readable json
  --debug        output debug information about paths

Available subcommands: kernel kernelspec migrate run script troubleshoot

Jupyter command `jupyter-notebook` not found.

问题原因 #

你只安装了ipykernel（用于让Jupyter识别conda环境作为运行内核），但没有在tf环境中安装Jupyter Notebook的核心程序，所以系统找不到jupyter-notebook命令，导致执行失败。

解决步骤 #

1. 确保处于激活的tf环境中：

   conda activate tf
   

2. 在tf环境内安装Jupyter Notebook：

   conda install jupyter notebook
   

   也可以用pip安装：

   pip install jupyter notebook
   

3. 安装完成后，重新执行jupyter notebook即可正常启动。

补充说明 #

如果之前在base环境中安装过Jupyter，也可以直接从base环境启动Jupyter，然后在Notebook中选择tf内核运行代码，但这种方式可能存在路径依赖问题，不如直接在tf环境内安装Jupyter稳定。

内容的提问来源于stack exchange，提问作者Kim