From conda create requirements.txt for pip3

Question

Hi I usually use conda to manage my environments, but now I am on a project that needs a little more horsepower than my laptop. So I am trying to use my university's workstations which have new Intel Xeons. But I don't have admin rights and the workstation does not have conda so I am forced to work with virtualenv and pip3.

How do I generate a requirements.txt from conda that will work with pip3 and venv?

conda list -e > requirements.txt 

does not generate a compatible file:

= is not a valid operator. Did you mean == ? 

The conda output is:

# This file may be used to create an environment using: # $ conda create --name <env> --file <this file> # platform: osx-64 certifi=2016.2.28=py36_0 cycler=0.10.0=py36_0 freetype=2.5.5=2 icu=54.1=0 libpng=1.6.30=1 matplotlib=2.0.2=np113py36_0 mkl=2017.0.3=0 numpy=1.13.1=py36_0 openssl=1.0.2l=0 pip=9.0.1=py36_1 pyparsing=2.2.0=py36_0 pyqt=5.6.0=py36_2 python=3.6.2=0 python-dateutil=2.6.1=py36_0 pytz=2017.2=py36_0 qt=5.6.2=2 readline=6.2=2 scikit-learn=0.19.0=np113py36_0 scipy=0.19.1=np113py36_0 setuptools=36.4.0=py36_1 sip=4.18=py36_0 six=1.10.0=py36_0 sqlite=3.13.0=0 tk=8.5.18=0 wheel=0.29.0=py36_0 xz=5.2.3=0 zlib=1.2.11=0 

I thought I would just manually change all = to == but the there are two = in the conda output. Which one to change? Surely there is an easier way?

EDIT: pip freeze > requirements.txt gives:

certifi==2016.2.28 cycler==0.10.0 matplotlib==2.0.2 matplotlib-venn==0.11.5 numpy==1.13.1 pyparsing==2.2.0 python-dateutil==2.6.1 pytz==2017.2 scikit-learn==0.19.0 scipy==0.19.1 six==1.10.0 

Answer 1

As the comment at the top indicates, the output of

conda list -e > requirements.txt

can be used to create a conda virtual environment with

conda create --name <env> --file requirements.txt

but this output isn't in the right format for pip.

If you want a file which you can use to create a pip virtual environment (i.e. a requirements.txt in the right format) you can install pip within the conda environment, then use pip to create requirements.txt.

conda activate <env> conda install pip pip freeze > requirements.txt 

Then use the resulting requirements.txt to create a pip virtual environment:

python3 -m venv env source env/bin/activate pip install -r requirements.txt 

When I tested this, the packages weren't identical across the outputs (pip included fewer packages) but it was sufficient to set up a functional environment.

For those getting odd path references in requirements.txt, use:

pip list --format=freeze > requirements.txt