Install only available packages using “conda install --yes --file requirements.txt” without error

Question

While installing packages in requirements.txt using Conda through the following command

conda install --yes --file requirements.txt

If a pack

Answer 1

For those looking, I used this as @TillHoffmann 's solution for the fish shell:

$ while read requirement; conda install --yes $requirement; end < requirements.txt

And

$ while read requirement; conda install --yes $requirement;or pip install $requirement; end < requirements.txt

Answer 2

I ended up just iterating over the lines of the file

$ while read requirement; do conda install --yes $requirement; done < requirements.txt

Edit: If you would like to install a package using pip if it is not available through conda, give this a go:

$ while read requirement; do conda install --yes $requirement || pip install $requirement; done < requirements.txt

Edit: If you are using Windows (credit goes to @Clay):

$ FOR /F "delims=~" %f in (requirements.txt) DO conda install --yes "%f" || pip install "%f"

Answer 3

Pbms's answer here is the right way to do it, assuming you have an existing environment to copy off of. Conda is fully capable of installing both Conda packages and pip packages, as listed in environment.yml. I wanted to document the whole process in more detail. Note that I am using folder-based environments, which is why I added --prefix [path to environment folder] to most of the commands.

Say you installed an environment for an existing project to a folder called env in the current folder, like this:

conda create --prefix ./env

You'd generate environment.yml for that project's environment like this:

conda env export --prefix ./env > environment.yml

You'd create a new environment within some other folder by copying environment.yml to there and then running this from there:

conda env create --prefix ./env --file environment.yml

You'd get an already-existing environment to match environment.yml by once again copying environment.yml to there and then running this from there:

conda env update --prefix ./env --file environment.yml --prune

With the environment in question active, you'd verify the state of its packages like this:

conda list

This is an abridged version of what that command might print (note that the pip packages are marked pypi):

# Name                    Version                   Build  Channel
pip                       19.2.2                   py37_0
python                    3.7.4                h5263a28_0
numpy                     1.16.4           py37h19fb1c0_0
pandas                    0.25.1           py37ha925a31_0
pyodbc                    4.0.27           py37ha925a31_0
ibm-db                    3.0.1                    pypi_0    pypi
ibm-db-sa                 0.3.5                    pypi_0    pypi

Finally, this is an abridged version of what environment.yml might look like (note that the pip packages are listed in their own category):

dependencies:
  - pip=19.2.2=py37_0
  - python=3.7.4=h5263a28_0
  - numpy=1.16.4=py37h19fb1c0_0
  - pandas=0.25.1=py37ha925a31_0
  - pyodbc=4.0.27=py37ha925a31_0
  - pip:
    - ibm-db==3.0.1
    - ibm-db-sa==0.3.5

Be aware that using Conda and pip together can cause some heartburn because they can unknowingly blow away each other's dependencies. You are supposed to install all of your Conda packages first and then all of your pip packages afterward, rather than alternating between the two. If your environment breaks, the official recommendation is to delete and recreate it (from your environment.yml file). For more details, see this guide:

https://www.anaconda.com/using-pip-in-a-conda-environment/

Answer 4

You can do this as mentioned in this

Export to .yml file

conda env export > freeze.yml

To reproduce:

conda env create -f freeze.yml