To package a conda environment (Requirement.txt and virtual environment)

condaenv.txt

# For Windows users# Note: <> denotes changes to be made

#Create a conda environment
conda create --name <environment-name> python=<version:2.7/3.5>

#To create a requirements.txt file:
conda list #Gives you list of packages used for the environment

conda list -e > requirements.txt #Save all the info about packages to your folder

#To export environment file
activate <environment-name>
conda env export > <environment-name>.yml

#For other person to use the environment
conda env create -f <environment-name>.yml

gistfile1.txt

# For Windows users

I think that for activating a conda env
conda activate <environment-name>
rather than
activate <environment-name>

@SundeepPidugu

One way to know the list of packages for a specific conda environment is to follow a two-step process:
conda activate <env_you_are_interested_in> # First activate the environment
conda list # List linked packages in a conda environment. See conda --help | grep list

PS: Will be happy to know if there is an alternate way which does not require to activate the env.

conda list -n <environment name>

Dear All,

After creation of requirements.txt, I found the list to long, I think Anaconda adds many unnecessary libraries (I guess default ones), not just what I installed (and its dependencies). Am I correct, is there a way to streamline the requirements file? Many thanks!

The dependent packages will be added to the requirements.txt file hence the bloating of that file. My current advice for everyone is to use poetry for dependency management in a python project (if you aren't using any conda optimized package, then using anaconda/miniconda is your only friend).

You can check out here: https://python-poetry.org/

@JutasiR, conda does not add libraries that you didn't install. The only exception is the base environment.

That's why you should create a new environment for your work and install what you need.

[]'s