How do I find the name of the conda environment in which my code is running?

Question

I\'m looking for a good way to figure out the name of the conda environment I\'m in from within running code or an interactive python instance.

The use-case is that

Answer 1

1. Several answers suggest the use of 'which pip', 'which python', or 'conda env list to grep the default'. This work if the user is doing something like: $ conda activate env_name; $ python ... or $ jupyter notebook/jupyterlab.

2. When a user invokes python directly without conda activate, method #1 would not work: e.g. $ /opt/conda/envs/my_env/bin/python (where my_env is the name of env)

3. In a more general case with jupyter notebook, one can select any one of the available conda env/kernel, and the one selected may not be the same as the default.

4. So the solution is to examine the executable or path of your current python, like several folks have posted before. Basically, sys.path returns the full path of executable, and one can then use split to figure out the name after envs/ which would be the env_name. The person who asked this question gave a pretty good answer, except missing this ....

5. I don't think any post took care of the special case of the base env. Note python from base env is just /opt/conda/bin/python. So one can simply add the following code fragment do a match if /opt/conda/bin/python in sys.path: return 'base'

6. Here we assume conda is installed on /opt/conda. For really generic solution, one can use $ conda info --root to find the installation path.

Answer 2

I am using this:

import sys
sys.executable.split('/')[-3]

it has the advantage that it doesn't assume the env is in the path (and is nested under envs). Also, it does not require the environment to be activated via source activate.

Edit: If you want to make sure it works on Windows, too:

import sys
from pathlib import Path
Path(sys.executable).as_posix().split('/')[-3]

To clarify: sys.executable gives you the path of the current python interpreter (regardless of activate/deactivate) -- for instance '/Users/danielsc/miniconda3/envs/nlp/bin/python'. The rest of the code just takes the 3rd from last path segment, which is the name of the folder the environment is in, which is usually also the name of the python environment.

Answer 3

You want $CONDA_DEFAULT_ENV or $CONDA_PREFIX:

$ source activate my_env
(my_env) $ echo $CONDA_DEFAULT_ENV
my_env

(my_env) $ echo $CONDA_PREFIX
/Users/nhdaly/miniconda3/envs/my_env

$ source deactivate
$ echo $CONDA_DEFAULT_ENV  # (not-defined)

$ echo $CONDA_PREFIX  # (not-defined)

In python:

In [1]: import os
   ...: print (os.environ['CONDA_DEFAULT_ENV'])
   ...:
my_env

---

The environment variables are not well documented. You can find CONDA_DEFAULT_ENV mentioned here: https://www.continuum.io/blog/developer/advanced-features-conda-part-1

The only info on CONDA_PREFIX I could find is this Issue: https://github.com/conda/conda/issues/2764

Answer 4

Since similar searches related to 'how do I determine my python environment' leads to this answer I thought I will also mention a way I find out which environment I am currently running my code from. I check the location of my pip binary which points to a location within the current environment. By looking at the output of the following command you can easily determine which environment you are in. (Please note that this solution is not applicable if you have inherited pip packages from your global environment/other environment)

In Windows command prompt:

where pip

If you are inside a Jupyter Notebook add an exclamation mark(!) before the command to execute the command in your host command prompt:

in[10]: !where pip

The output will look something like this:

C:\Users\YourUsername\.conda\envs\YourEnvironmentName\Scripts\pip.exe
C:\ProgramData\Anaconda3\Scripts\pip.exe

YourEnvironmentName gives out the name of your current environment.

In Linux/Mac, you can use the which command instead of where: (Not tested).

For python3 environment

which pip3

From Jupyter notebook:

in[10]: !which pip3

This should directly point to the location within your current environment.

Answer 5

conda info

directly lists all the information where in the first lines you can see the

active environment: (some name)
active env location: (location of active environment)

I guess this is the most clear way.

In an interactive environment like Jupyter Notebook or Jupyter Lab, you should use % before typing the commands, like the following,

%conda info

Answer 6

Edit: Oops, I hadn't noticed Ivo's answer. Let's say that I am expanding a little bit on it.

---

If you run your python script from terminal:

import os
os.system("conda env list")

This will list all conda environments, as from terminal with conda env list.

Slightly better:

import os
_ = os.system("conda env list | grep '*'")

The _ = bit will silence the exist status of the call to os.system (0 if successful), and grep will only print out the line with the activated conda environment.

If you don't run your script from terminal (e.g. it is scheduled via crontab), then the above won't have anywhere to "print" the result. Instead, you need to use something like python's subprocess module. The simplest solution is probably to run:

import subprocess
output = subprocess.check_output("conda env list | grep '*'", shell=True, encoding='utf-8')
print(output)

Namely output is a string containing the output of the command conda env list, not its exit status (that too can be retrieved, see documentation of the subprocess module).

Now that you have a string with the information on the activated conda environment, you can perform whichever test you need (using regular expressions) to perform (or not) the installs mentioned in your question.

Remark.
Of course, print(output) in the block above will have no effect if your script is not run from terminal, but if you test the block in a script which you run from terminal, then you can verify that it gives you what you want. You can for instance print this information into a log file (using the logging module is recommended).