VSCode安装ipykernel失败求助：编译psutil需Microsoft VC++14.0+

问题背景 #

在VSCode中运行Jupyter Notebook代码时，系统提示需安装ipykernel。运行的代码如下：

# Load the libraries to be used in the Analysis

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import warnings  # 修正原代码拼写错误

# Setup libraries settings and options
## Pandas setup
pd.set_option('display.max_columns', None)

## matplotlib setup
%matplotlib inline

## Seaborn setup
sns.set_context('notebook')
sns.set_style('whitegrid')
sns.set_palette('Blues_r')

# turn off warning for final notebook
warnings.filterwarnings('ignore')

尝试过程中的错误 #

1. 选择VSCode内安装后，系统给出提示：

Running cells with 'Python 3.11.0 64-bit' requires ipykernel package.
Run the following command to install 'ipykernel' into the Python environment.
Command: 'c:/Users/Samir/AppData/Local/Programs/Python/Python311/python.exe -m pip install ipykernel -U --user --force-reinstall'

2. 在Git Bash中执行python -m pip install ipykernel，触发编译错误：

\tests
      running build_ext
      building 'psutil._psutil_windows' extension
      error: Microsoft Visual C++ 14.0 or greater is required. Get it with "Microsoft C++ Build Tools": https://visualstudio.microsoft.com/visual-cpp-build-tools/
      [end of output]

  note: This error originates from a subprocess, and is likely not a problem with pip.
  ERROR: Failed building wheel for psutil
Failed to build psutil
ERROR: Could not build wheels for psutil, which is required to install pyproject.toml-based projects

可行解决办法 #

方法1：安装C++编译工具 #

错误核心是缺少Microsoft Visual C++ 14.0及以上版本的编译环境，psutil依赖它完成编译：

• 打开Microsoft Visual C++ Build Tools安装程序（无需安装完整Visual Studio）
• 勾选「Desktop development with C++」工作负载，确保包含MSVC v14x工具链、Windows SDK等必要组件
• 完成安装后重启终端，重新执行python -m pip install ipykernel

方法2：安装预编译的psutil包 #

如果不想安装编译工具，可直接使用预编译的psutil轮子文件：

• 获取对应Python 3.11、Windows 64位的psutil .whl文件
• 执行pip install 路径/psutil-x.x.x-cp311-none-win_amd64.whl完成psutil安装
• 之后再执行pip install ipykernel

方法3：使用conda环境（已安装Anaconda/Miniconda时） #

conda会自动处理依赖的编译问题，无需手动安装编译工具：

• 打开终端，创建并激活新环境：

  conda create -n py311 python=3.11
  conda activate py311
  

• 安装ipykernel：

  conda install ipykernel
  

• 在VSCode中选择这个conda环境作为Jupyter的运行内核

内容的提问来源于stack exchange，提问作者hamdy-samir