conda-pack is a command line tool for creating archives of conda environments that can be installed on other systems and locations. This is useful for deploying code in a consistent environment—potentially where python and/or conda isn’t already installed.

A tool like conda-pack is necessary because conda environments are not relocatable. Simply moving an environment to a different directory can render it partially or completely inoperable. conda-pack addresses this challenge by building archives from original conda package sources and reproducing conda’s own relocation logic.

Use Cases

  • Bundling an application with its environment for deployment

  • Packaging a conda environment for use with Apache Spark when deploying on YARN (see here for more information).

  • Packaging a conda environment for deployment on Apache YARN. One way to do this is to use Skein.

  • Archiving an environment in a functioning state. Note that a more sustainable way to do this is to specify your environment as a environment.yml, and recreate the environment when needed.

  • BETA: Packaging a conda environment as a standard Cloudera parcel. This is a newly added capability. It has been tested on a live cluster, but different cluster configurations may produce different results. We welcome users to file an issue if necessary. See here for more information).


It’s recommended to install in your root conda environment - the conda pack command will then be available in all sub-environments as well.

Install with conda:

conda-pack is available from Anaconda as well as from conda-forge:

conda install conda-pack
conda install -c conda-forge conda-pack

Install from PyPI:

While conda-pack requires an existing conda install, it can also be installed from PyPI:

pip install conda-pack

Install from source:

conda-pack is available on github and can always be installed from source.

pip install git+

Commandline Usage

conda-pack is primarily a commandline tool. Full CLI docs can be found here.

One common use case is packing an environment on one machine to distribute to other machines that may not have conda/python installed.

On the source machine

# Pack environment my_env into my_env.tar.gz
$ conda pack -n my_env

# Pack environment my_env into out_name.tar.gz
$ conda pack -n my_env -o out_name.tar.gz

# Pack environment located at an explicit path into my_env.tar.gz
$ conda pack -p /explicit/path/to/my_env

On the target machine

# Unpack environment into directory `my_env`
$ mkdir -p my_env
$ tar -xzf my_env.tar.gz -C my_env

# Use python without activating or fixing the prefixes. Most python
# libraries will work fine, but things that require prefix cleanups
# will fail.
$ ./my_env/bin/python

# Activate the environment. This adds `my_env/bin` to your path
$ source my_env/bin/activate

# Run python from in the environment
(my_env) $ python

# Cleanup prefixes from in the active environment.
# Note that this command can also be run without activating the environment
# as long as some version of python is already installed on the machine.
(my_env) $ conda-unpack

# At this point the environment is exactly as if you installed it here
# using conda directly. All scripts should work fine.
(my_env) $ ipython --version

# Deactivate the environment to remove it from your path
(my_env) $ source my_env/bin/deactivate

API Usage

conda-pack also provides a Python API, the full documentation of which can be found here. The API mostly mirrors that of the conda pack commandline. Repeating the examples from above:

import conda_pack

# Pack environment my_env into my_env.tar.gz

# Pack environment my_env into out_name.tar.gz
conda_pack.pack(name="my_env", output="out_name.tar.gz")

# Pack environment located at an explicit path into my_env.tar.gz


This tool has a few caveats.

  • Conda must be installed and be on your path.

  • The OS where the environment was built must match the OS of the target. This means that environments built on Windows can’t be relocated to Linux.

  • Once an environment is unpacked and conda-unpack has been executed, it cannot be relocated. Re-applying conda-pack is unlikely to work.

  • conda-pack is not well-suited for archiving old environments, because it requires that conda’s package cache have all of the environment’s packages present. It is intended for building archives from actively maintained conda environments.