生产力翻倍！JupyterLab 4.0全平台开发环境配置｜从零部署到GPU加速优化指南

# 安装Python 3.12（当前LTS版本） pyenv install 3.12.4 pyenv global 3.12.4

python -m venv ~/.jupyterenv source ~/.jupyterenv/bin/activate

pip install jupyterlab==4.0.0 \ jupyterlab-lsp \ # 语言服务器协议支持 jupyterlab-git \ # 版本控制集成 jupyterlab-ai \ # AI辅助扩展 jupyterlab-vim \ # Vim键位绑定 jupyterlab-drawio # 流程图绘制工具

c.ServerApp.root_dir = '/mnt/d/JupyterProjects' # 项目存储路径 c.LabApp.collaborative = True # 启用实时协作 c.AICodeCompletion.model = 'gpt-5-turbo' # 指定AI模型

jupyter lab --port 8888 --no-browser

浏览器打开 http://localhost:8888 并输入token认证

pip install cupy-cuda12x jupyterlab-cuda-dashboard nvidia-smi --jupyter-integration

# 在notebook中执行 !pip install jupyterlab-sql %load_ext sql %sql postgresql://user:password@localhost/mydb

import ipyvolume as ipv ipv.quickvolshow(np.random.rand(128,128,128))

# 数据加载 -> 特征工程 -> 模型训练 -> 可视化评估 import polars as pl from sklearn.inspection import DecisionBoundaryDisplay df = pl.read_parquet("data.parquet") display(DecisionBoundaryDisplay.from_estimator(model, X, alpha=0.5))

import geemap Map = geemap.Map(center=(40, -100), zoom=4) Map.add_basemap('SATELLITE') Map

mamba install -c conda-forge jupyterlab=4.0.0