Skip to content

mamba

mamba is a fast, drop-in replacement for conda. It uses the same commands but resolves dependencies much faster.

Why mamba?

conda's dependency solver can be very slow, especially with: - Many packages - Complex dependency trees - Large environments

mamba solves the same problems 10-100x faster using: - C++ implementation (libsolv) - Parallel downloads - Better dependency resolution algorithm

Installation

Fresh installation with mamba pre-installed:

# Linux
wget https://github.com/conda-forge/miniforge/releases/latest/download/Mambaforge-Linux-x86_64.sh
bash Mambaforge-Linux-x86_64.sh

# macOS (Apple Silicon)
wget https://github.com/conda-forge/miniforge/releases/latest/download/Mambaforge-MacOSX-arm64.sh
bash Mambaforge-MacOSX-arm64.sh

# macOS (Intel)
wget https://github.com/conda-forge/miniforge/releases/latest/download/Mambaforge-MacOSX-x86_64.sh
bash Mambaforge-MacOSX-x86_64.sh

Option 2: Install mamba in Existing conda

conda install -c conda-forge mamba

Usage

mamba uses identical syntax to conda. Just replace conda with mamba:

Package Management

# Install packages
mamba install numpy pandas scikit-learn

# Install specific version
mamba install numpy=1.24

# Update package
mamba update numpy

# Remove package
mamba remove numpy

# Search packages
mamba search numpy

Environment Management

# Create environment
mamba create -n myenv python=3.11 numpy pandas

# Activate (still use conda)
conda activate myenv

# Install in environment
mamba install matplotlib

# Deactivate (still use conda)
conda deactivate

Note: Use conda activate/deactivate — mamba doesn't replace these commands.

Environment Files

# Create from file
mamba env create -f environment.yml

# Update from file
mamba env update -f environment.yml

# Export (use conda)
conda env export > environment.yml

Speed Comparison

Operation conda mamba
install numpy pandas scikit-learn 30-60s 3-5s
Create environment with 50 packages 5-10 min 30-60s
Resolve complex dependencies Minutes Seconds

The difference is most noticeable with: - Many packages - Version conflicts to resolve - Fresh environments

When to Use mamba vs conda

Task Use
Install packages mamba install
Create environments mamba create
Update packages mamba update
Search packages mamba search
Activate environment conda activate
Deactivate environment conda deactivate
Export environment conda env export
Config changes conda config

Common Commands

conda mamba equivalent
conda install pkg mamba install pkg
conda create -n env mamba create -n env
conda update pkg mamba update pkg
conda remove pkg mamba remove pkg
conda search pkg mamba search pkg
conda env create -f file mamba env create -f file
conda clean --all mamba clean --all

Micromamba

micromamba is an even smaller, standalone version: - No base environment needed - Single static binary (~5MB) - No Python dependency - Great for CI/CD and containers

Install micromamba

# Linux/macOS
"${SHELL}" <(curl -L micro.mamba.pm/install.sh)

# Or download directly
wget https://micro.mamba.pm/api/micromamba/linux-64/latest -O micromamba
chmod +x micromamba

Use micromamba

micromamba create -n myenv python=3.11 numpy
micromamba activate myenv
micromamba install pandas

Troubleshooting

mamba Not Found After Installation

# Restart shell or source config
source ~/.bashrc   # Linux
source ~/.zshrc    # macOS zsh

# Or specify full path
~/mambaforge/bin/mamba install numpy

Still Slow?

Make sure you're using mamba, not conda:

which mamba
mamba --version

Conflicts with conda

If you have both conda and mamba, they share the same environments. No conflict, but be consistent.

Best Practices

1. Use Mambaforge for New Setups

bash Mambaforge-Linux-x86_64.sh

Gets you mamba + conda-forge by default.

2. Create Alias (Optional)

If you always want to use mamba:

# In ~/.bashrc or ~/.zshrc
alias conda='mamba'

Then conda install actually runs mamba install.

3. Use mamba for Heavy Operations

  • Installing multiple packages
  • Creating environments
  • Updating environments

Use conda for: - activate/deactivate - config changes - env export

Summary

Tool Description Speed
conda Original package manager Slow
mamba Fast conda replacement Fast
micromamba Minimal standalone mamba Fast

Key Takeaways

  • mamba is a drop-in replacement for conda
  • Same syntax: mamba install, mamba create, etc.
  • 10-100x faster than conda for dependency resolution
  • Use Mambaforge for new installations
  • Still use conda activate/deactivate
  • micromamba for containers and CI/CD