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Back 🌈 Conda vs UV — Detailed Comparison 08 Dec, 2025
Programming Programming
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🧠 What They Are

🐍 Conda

  • A package manager + environment manager.

  • Works for Python + system-level packages (C libraries, ML dependencies).

  • Creates isolated environments with specific Python versions.

  • Comes with Anaconda or Miniconda distribution.

  • Slower in solving dependencies but extremely compatible.

⚡ UV

  • A next-gen ultra-fast Python package manager by Astral.

  • Replaces pip, virtualenv, pip-tools, pyenv, poetry concepts in one tool.

  • Extremely fast (10–100x faster) than pip/conda.

  • Uses pyproject.toml for modern dependency management.

  • Best for lightweight, modern, fast development workflows.

🏗️ Environment Creation 

Task 🐍 Conda Command ⚡ UV Command
Create new environment conda create -n myenv python=3.10 uv venv myenv --python 3.10
Activate environment conda activate myenv source myenv/bin/activate (Linux/Mac) or myenv\Scripts\activate (Windows)
Deactivate environment conda deactivate deactivate
List environments conda env list No global listing (UV creates folder-based envs)
Remove environment conda remove -n myenv --all Just delete the folder → rm -rf myenv

📦 Installing Packages 

Task 🐍 Conda ⚡ UV
Install a package conda install numpy uv pip install numpy
Install multiple packages conda install numpy pandas scipy uv pip install numpy pandas scipy
Install from requirements.txt conda install --file requirements.txt uv pip install -r requirements.txt
Export dependencies conda list --export > req.txt uv pip freeze > requirements.txt
Remove package conda remove numpy uv pip uninstall numpy

🛠️ Dependency Management (Modern)

Feature 🐍 Conda ⚡ UV
Dependency solver Slow but stable ⚡ Extremely fast
pyproject.toml support ❌ No ✅ Yes
Lock file conda-lock (external) Built-in: uv lock
Install from lock file conda-lock install uv sync

🏎️ Speed Comparison (Real Numbers)

Operation Conda UV
Create env ~5–20 seconds ⚡ 0.1–0.5 seconds
Install packages Slow (solver heavy) ⚡ Very fast
Sync dependencies Medium ⚡ Ultra fast

🌍 Use Cases — Which One to Use?

✔️ Use Conda if:

  • You work with ML, Data Science, GPU libraries (TensorFlow, PyTorch, cuDNN).

  • You need system-level dependencies.

  • You want environment isolation with full package control.

✔️ Use UV if:

  • You want maximum speed.

  • You work with modern Python packaging.

  • You don’t need heavy system-level dependencies.

  • You want a replacement for pip + venv + poetry.

📚 Common Commands Summary

🧰 Environment Commands

Operation Conda UV
Create env conda create -n env python=3.10 uv venv env --python 3.10
Activate conda activate env env/Scripts/activate
Deactivate conda deactivate deactivate

📦 Package Commands

Operation Conda UV
Install conda install x uv pip install x
Uninstall conda remove x uv pip uninstall x
Install from file conda install --file req.txt uv pip install -r req.txt

🧩 Project Dependency Management

Operation Conda UV
Init project — uv init
Create lock file External uv lock
Sync project — uv sync
Build wheel — uv build

🎯 Final Verdict 

Feature Conda UV
Speed ❌ Slow ⚡ Fastest
ML support ⭐ Best ❌ Not ideal
Modern packaging ❌ No ⭐ Yes
Ease of use Medium ⭐ Very easy
System packages ⭐ Strong ❌ Weak