Difference Between venv and uv

Shahrukh AhmadShahrukh Ahmad
2 min read

Both uv and venv are used for managing Python virtual environments, but they are not the same. Let me break it down clearly:


1. venv (built-in Python module)

  • What it is: A standard library module that comes with Python (since Python 3.3).

  • Purpose: Creates isolated environments where you can install packages without affecting the system Python.

  • Command example:

      python -m venv myenv
      source myenv/bin/activate   # (Linux/Mac)
      myenv\Scripts\activate      # (Windows)
    
  • Features:

    • Lightweight and built into Python.

    • Doesn’t manage dependencies efficiently (you usually need pip + requirements.txt).

    • No built-in lockfile mechanism.


2. uv (from Astral, 2024+)

  • What it is: A fast Python package and environment manager (a new alternative to pip, poetry, conda, etc.).

  • Purpose: Not just creating virtual environments but also managing dependencies, lockfiles, and reproducible builds.

  • Command example:

      uv venv myenv      # create a virtual environment
      uv pip install numpy
    
  • Features:

    • Much faster than pip and venv (written in Rust).

    • Built-in dependency resolver (like Poetry).

    • Uses lockfiles for reproducibility.

    • Can replace pip, venv, pip-tools, and even poetry in many workflows.

    • Cross-platform and modern.


🔑 Key Differences

Featurevenvuv
Part of Python stdlib?✅ Yes❌ No (needs install)
SpeedNormal⚡ Very fast
Creates virtual envs✅ Yes✅ Yes
Dependency management❌ No✅ Yes
Lockfile support❌ No✅ Yes
Replacement for pip❌ No✅ Yes
Ease of useBasicAdvanced

👉 In short:

  • Use venv if you just want a basic, built-in way to create a virtual environment.

  • Use uv if you want a modern, faster, all-in-one package & environment manager with reproducibility.

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Written by

Shahrukh Ahmad
Shahrukh Ahmad

Passionate about coding and the limitless possibilities of cloud technology. I thrive on turning ideas into scalable, efficient solutions. Let's connect and explore the exciting synergy between code and the cloud! 🤖 AI / ML🧠| 📊 - Data Science |Azure☁️AWS | Linux🐧| Windows🖥️| Python | JAVA | 🐳 Docker | Git | Gitlab | ⚓️Kubernetes | 🚀 Jenkins CI/CD | 🏗️ terraform | SQL.