How to share conda environments across platforms

The conda docs at explain how to share environments with other people.

However, the docs tell us this is not cross platform:

NOTE: These explicit spec files are not usually cross platform, and      
therefore have a comment at the top such as # platform: osx-64 showing the  
platform where they were created. This platform is the one where this spec
file is known to work. On other platforms, the packages specified might not
be available or dependencies might be missing for some of the key packages
already in the spec.

NOTE: Conda does not check architecture or dependencies when installing 
from an explicit specification file. To ensure the packages work correctly,
be sure that the file was created from a working environment and that it is 
used on the same architecture, operating system and platform, such as linux-
64 or osx-64.

Is there a good method to share and recreate a conda environment in one platform (e.g. CentOS) in another platform (e.g. Windows)?



This answer is given with the assumption that you would like to make sure that the same versions of the packages that you generally care about are on different platforms and that you don't care about the exact same versions of all packages in the entire dependency tree. If you are trying to install the exact same version of all packages in your entire dependency tree that has a high likelihood of failure since some conda packages have different dependencies for osx/win/linux. For example, the recipe for otrobopt will install different packages on win vs. osx/linux, so the environment list would be different.

Recommendation: manually create an environment.yaml file and specify or pin only the dependencies that you care about. Let the conda solver do the rest. Probably worth noting is that conda-env (the tool that you use to manage conda environments) explicitly recommends that you "Always create your environment.yml file by hand."

Then you would just do conda env create --file environment.yml

Have a look at the readme for conda-env.

They can be quite simple:

name: basic_analysis
  - numpy
  - pandas

Or more complex where you pin dependencies and specify channels to install from:

name: stats-web
  - javascript
  - python=3.4   # or 2.7 if you are feeling nostalgic
  - bokeh=0.9.2
  - numpy=1.9.*
  - nodejs=0.10.*
  - flask
  - pip:
    - Flask-Testing

In either case, you can create an environment with conda env create --file environment.yaml

If you have a more complex use case or further questions, update the original question and I'll see if I can help you a bit more.

conda-env export should be used used to export your complete environment to file named my_env.yml.

Check the working solution on getting only prefix on OS X instead of complete dependency including pip.

Step 1: deactivate from the environment if activated. else it will create yml file with only prefix.

Step 2: run below command to export conda-env export -n my_env > my_env.yml it will export every required dependency, channel and pip install in a yml file which is importable to share with others.

Step 3: run below command to import conda-env create -n my_env -f= my_env.yml it will create the exact environment as is on sharing fellow machine.

For those interested in a solution to maintain a single environment file that can be used in Linux, macOS, and Windows, please check the conda-devenv tool at

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