Setting Jupyter Kernel according to venv of python

Setting Jupyter Kernel with Python Virtual Environment

Curiosity: How can we use different Python virtual environments in Jupyter Notebook? What’s the best way to manage multiple kernels?

This guide explains how to add a Python virtual environment as a Jupyter kernel, allowing you to use different Python environments in your notebooks.

Step 1: Activate Virtual Environment

Retrieve: First, activate your Python virtual environment.

Windows:

activate.bat

Linux/Mac:

source activate
# or
source venv/bin/activate

Step 2: Install Jupyter Notebook

Retrieve: Install Jupyter in your virtual environment.

pip install jupyter jupyter notebook

Step 3: Install ipykernel

Innovate: Install ipykernel to enable kernel registration.

pip install ipykernel

Purpose:

ipykernel

allows you to register Python environments as Jupyter kernels.

Step 4: Add Jupyter Kernel

Retrieve: Register your virtual environment as a Jupyter kernel.

python -m ipykernel install --user --name "virtual env name" --display-name "shown name of display"

Parameters:

• --name
  

  : Internal kernel name (used by Jupyter)

• --display-name
  

  : Name shown in Jupyter UI

• --user
  

  : Install for current user only

Example:

python -m ipykernel install --user --name "myenv" --display-name "Python (myenv)"

Step 5: Uninstall Jupyter Kernel (Optional)

Retrieve: Remove a kernel if needed.

jupyter kernelspec uninstall .venv

Note: Replace

.venv

with your kernel name.

Workflow Summary

Innovate: Complete workflow for managing Jupyter kernels.

graph LR
    A[Create venv] --> B[Activate venv]
    B --> C[Install Jupyter]
    C --> D[Install ipykernel]
    D --> E[Register Kernel]
    E --> F[Use in Jupyter]
    
    style A fill:#e1f5ff
    style E fill:#fff3cd
    style F fill:#d4edda

Benefits

Retrieve: Why use virtual environments with Jupyter.

Benefit	Description	Impact
Isolation	Separate dependencies	⬆️ Clean environments
Flexibility	Multiple Python versions	⬆️ Project-specific
Reproducibility	Consistent environments	⬆️ Reliable results
Organization	Easy to manage	⬆️ Better workflow

Key Takeaways

Retrieve: Setting up Jupyter kernels with virtual environments involves activating the venv, installing Jupyter and ipykernel, then registering the kernel with a display name.

Innovate: By using virtual environments as Jupyter kernels, you can maintain isolated Python environments for different projects, ensuring clean dependencies and reproducible results.

Curiosity → Retrieve → Innovation: Start with curiosity about managing Python environments, retrieve insights from this setup process, and innovate by organizing your Jupyter workflows with multiple kernels for different projects.

Next Steps:

• Set up your virtual environment
• Install required packages
• Register as Jupyter kernel
• Start using in notebooks

Reference

• ipkernel : https://hellodata.tistory.com/38
• Google Colab : https://creatorjo.tistory.com/entry/%EA%B5%AC%EA%B8%80-%EC%BD%94%EB%9E%A9colab-%EA%B8%B0%EC%B4%88-%EC%82%AC%EC%9A%A9%EB%B2%95

Venv Jupyter

This post is licensed under CC BY 4.0 by the author.

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