conda-env-replicator

Create portable conda environment files that work across OS and glibc upgrades by removing overly-specific build strings while preserving critical CUDA/GPU requirements.

The Problem

When migrating conda environments across systems (especially during HPC OS/glibc upgrades), environment recreation often fails due to:

• Overly-specific build strings that are no longer available in conda channels
• Platform-specific dependencies that don't exist on new systems
• Missing channel information in exported environment files

This tool solves these issues by creating portable environment files that:

• Remove unnecessary build strings
• Preserve critical CUDA/GPU version constraints with wildcards
• Explicitly specify package channels
• Work across different Linux versions and glibc updates

Installation

From PyPI (recommended)

pip install conda-env-replicator

From source

git clone https://github.com/mpinb/conda-env-replicator.git
cd conda-env-replicator
pip install -e .

Quick Start

Export and process an existing environment

conda-env-replicator -n myenv -o portable_env.yml

Process existing export files

# First, export your environment manually
conda env export -n myenv > env.yml
conda list -n myenv --explicit > explicit.txt

# Then process them
conda-env-replicator -y env.yml -e explicit.txt -o portable_env.yml

Recreate environment on new system

conda env create -n myenv_new -f portable_env.yml

How It Works

The tool processes conda environment files using this logic:

1. Removes build strings: ptxcompiler=0.2.0=py39h107f55c_0 → ptxcompiler=0.2.0
2. Preserves CUDA versions: ucx=1.12.0=cuda11.2_0 → ucx=1.12.0=*cuda11*
3. Preserves GPU builds: package=1.0=gpu_0 → package=1.0=*gpu*
4. Adds explicit channels: ptxcompiler=0.2.0 → rapidsai::ptxcompiler=0.2.0

Example Transformation

Before (fails on new system):

dependencies:
  - ptxcompiler=0.2.0=py39h107f55c_0
  - ucx=1.12.0=cuda11.2_0
  - numpy=1.21.2=py39h20f2e39_0

After (portable):

dependencies:
  - rapidsai::ptxcompiler=0.2.0
  - rapidsai::ucx=1.12.0=*cuda11*
  - conda-forge::numpy=1.21.2

Usage

Command Line Options

conda-env-replicator [-h] [-y YAML] [-e EXPLICIT] [-n NAME] -o OUTPUT [--keep-intermediates]

Options:
  -y, --yaml YAML          Input conda environment YAML file
  -e, --explicit EXPLICIT  Input conda list --explicit output file
  -n, --name NAME          Name of existing conda environment to export
  -o, --output OUTPUT      Output portable YAML file (required)
  --keep-intermediates     Keep intermediate export files (when using -n)
  -h, --help              Show this help message and exit

Examples

Process an existing environment directly

conda-env-replicator -n pytorch-cuda11 -o portable_pytorch.yml

Process existing export files

conda-env-replicator -y my_env.yml -e my_env_explicit.txt -o portable.yml

Keep intermediate files for inspection

conda-env-replicator -n myenv -o portable.yml --keep-intermediates

Use Cases

HPC System Migrations

Perfect for HPC centers upgrading OS or glibc versions:

# On old system
conda-env-replicator -n research_env -o research_portable.yml

# Transfer file to new system
scp research_portable.yml newcluster:~/

# On new system
conda env create -n research_env -f research_portable.yml

Cross-Platform Development

Create environments that work across different Linux distributions:

# On Ubuntu 20.04
conda-env-replicator -n dev_env -o portable_dev.yml

# Works on Rocky Linux 8, Ubuntu 22.04, etc.

CUDA Version Flexibility

Maintain CUDA major version requirements while allowing flexibility:

# Original: cuda11.2_0 → Portable: *cuda11*
# Allows conda to find any cuda 11.x compatible build

Requirements

• Python 3.7+
• PyYAML
• conda (for environment export functionality)

Comparison with Other Tools

Tool	Purpose	Use Case
conda-env-replicator	OS/glibc migration	HPC upgrades, cross-distro
conda clone	Exact environment copy	Same system only
conda-lock	Lockfile generation	Reproducibility with exact versions
conda env export	YAML export	Starting point (not portable)

Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

Development Setup

git clone https://github.com/mpinb/conda-env-replicator.git
cd conda-env-replicator
pip install -e ".[dev]"
pytest tests/

License

This project is licensed under the MIT License - see the LICENSE file for details.

Citation

If you use this tool in your research, please cite:

@software{conda_env_replicator,
  title = {conda-env-replicator: Portable Conda Environment Migration Tool},
  author = {{Max Planck Institute for Neurobiology of Behavior - caesar}},
  year = {2025},
  url = {https://github.com/mpinb/conda-env-replicator}
}

Support

• Issues: GitHub Issues
• Discussions: GitHub Discussions

Acknowledgments

Developed at the Max Planck Institute for Neurobiology of Behavior - caesar to facilitate HPC environment migrations and improve reproducibility in computational neuroscience research.