How to share conda environments across platforms

The conda docs at http://conda.pydata.org/docs/using/envs.html 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
dependencies:
  - numpy
  - pandas

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

name: stats-web
channels:
  - javascript
dependencies:
  - 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.

NOTE: You may need to use .* as a version suffix if you're using an older version of conda.

Whilst it is possible to create your environment.yml file by hand, you can ensure that your environment works across platforms by using the conda env export --from-history flag.

This will only include packages that you’ve explicitly asked for, as opposed to including every package in your environment.

For example, if you create an environment and install a package conda install python=3.8 numpy, it will install numerous other dependencies as well as python and numpy.

If you then run conda env export > environment.yml, your environment.yml file will include all the additional dependencies conda automatically installed for you.

On the other hand, running conda env export --from-history will just create environment.yml with python=3.8 and numpy and thus will work across platforms.

Answer adapted from the docs.

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 https://github.com/ESSS/conda-devenv.

An aspect missing from the other answers is that the question asker mentions "spec files" and not "environment.yml" file. These are different.

Spec file

A spec file specifies the exact package URL's and is used to recreate identical environments (on the same platform).

It looks like this:

# This file may be used to create an environment using:
# $ conda create --name <env> --file <this file>
# platform: osx-64
@EXPLICIT
https://repo.anaconda.com/pkgs/free/osx-64/mkl-11.3.3-0.tar.bz2
https://repo.anaconda.com/pkgs/free/osx-64/numpy-1.11.1-py35_0.tar.bz2
https://repo.anaconda.com/pkgs/free/osx-64/openssl-1.0.2h-1.tar.bz2
https://repo.anaconda.com/pkgs/free/osx-64/pip-8.1.2-py35_0.tar.bz2
https://repo.anaconda.com/pkgs/free/osx-64/python-3.5.2-0.tar.bz2
https://repo.anaconda.com/pkgs/free/osx-64/readline-6.2-2.tar.bz2
https://repo.anaconda.com/pkgs/free/osx-64/setuptools-25.1.6-py35_0.tar.bz2

It can be obtained with conda list --explicit from the conda environment of interest.
To create a new environment with it one would use the conda create command:

conda create --name <env_name> --file <spec file path>

environment.yml

The environment.yml file is described well in this answer.

It can be obtained with the following commands from the conda environment of interest:

• conda env export to get all packages in the current environment
• conda env export --from-history to only get the packages explicitly installed (i.e. not automatically added depenedencies)

_{This question is quite old and conda has developed in the meantime. Perhaps the original meaning of spec file was equal to environment.yml files, but for completeness I am adding this answer.}