How to back up anaconda environment in Windows 10?

Question

Recently, my anaconda environment got broken due to certain bad conda package upgrade. Due to this back experience, I would like to back up my anaconda environment for future easy recovery.

What I did to back up was to zip up the entire folder at C:\ProgramData\Anaconda3. Is this the correct way?

I am using Windows 10, anaconda python v3.6 64-bit.

Answer 1

It doesn't really make sense to zip up a conda environment for back up purposes since there are other ways to do this which may be more appropriate and use the in-built functions designed to do just this.

You can create a .txt version of the conda environment that details each module and version within, and can then be used to re-create the EXACT environment in the future.

# Create list of the environment
conda list --explicit environment_backup.txt

# Use the newly created text file to recreate the environment
conda create --name my_env_name --file environment_backup.txt

See docs for more information on managing conda environments.

N.B. As an additional point, conda environment directories can be fairly large (often >1GB) whereas the txt file created here is ~25KB, offering a clear advantage when archiving something for safe-keeping.

Answer 2

There are numerous ways you can achieve that as the way the anaconda website has shared. However, if you have limited or no internet accessibility, using a tool named "conda-pack" is recommended (unfortunately with the same OS for now).

Follow steps below:

conda install -c conda-forge conda-pack

And then on your 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

Lastly, on your 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