Conda create from requirements.txt not finding packages

What I try

conda create --name ml --file ./requirements.txt

I created the requirements.txt file with conda list -e > requirements.txt on another computer in the past. requirements.txt: https://github.com/penguinsAreFunny/bugFinder-machineLearning/blob/master/requirements.txt

Error

PackagesNotFoundError: The following packages are not available from current channels:

protobuf==3.19.1=pypi_0

tensorboard-data-server==0.6.1=pypi_0

pygments==2.10.0=pypi_0

scikit-learn==1.0.1=pypi_0

tensorflow-estimator==2.4.0=pypi_0

flake8==4.0.1=pypi_0

nest-asyncio==1.5.1=pypi_0 [...]

Current channels:

https://conda.anaconda.org/conda-forge/win-64

https://conda.anaconda.org/conda-forge/noarch

https://repo.anaconda.com/pkgs/main/win-64

https://repo.anaconda.com/pkgs/main/noarch

https://repo.anaconda.com/pkgs/r/win-64

https://repo.anaconda.com/pkgs/r/noarch

https://repo.anaconda.com/pkgs/msys2/win-64

https://repo.anaconda.com/pkgs/msys2/noarch

https://conda.anaconda.org/pickle/win-64

https://conda.anaconda.org/pickle/noarch

https://conda.anaconda.org/nltk/win-64

https://conda.anaconda.org/nltk/noarch

Question

Why can´t conda find the packages in the channels? I think the missing packages should be in conda-forge, shouldn´t they?

Used Version

conda 4.11.0

Solution 1:

The packages likely are in Conda Forge as suggested, but the build strings, "pypi_0", indicate that they had been installed from PyPI in the previous environment. The conda list -e command captures this info, but the conda create command cannot handle it.

The quickest fix is probably to edit the file to remove the build string specification on those packages. That is, something like:

## remove all PyPI references
sed -e 's/=pypi_0//' requirements.txt > reqs.nopip.txt

## try creating only from Conda packages
conda create -n m1 --file reqs.nopip.txt

Export YAML

Alternatively, serializing to YAML can handle both capturing and reinstalling Pip-installed packages. So, if you still have the old environment around, consider using:

conda env export > environment.yaml

which can recreate (on the same platform) with

conda env create -n m1 -f environment.yaml