Install CFL
Short instructions:
With Python 3.7-3.8:
pip install cfl
Long instructions:
We recommend installing cfl
in a virtual environment to prevent unintended
interactions between different packages. If you don’t already have a virtual
environment system, follow steps 1 and 2. Otherwise, skip to step 3.
1. Install Anaconda
We recommend using the conda
environment management system system. You can
install conda
here. For
our purposes, either the full Anaconda distribution or the smaller Miniconda
should work fine.
2. Create a conda environment
With conda
installed, open a terminal window and run the command:
conda create -n cfl-env python=3.8
where cfl-env
can be replaced with any name of your choice.
This will create a fresh environment, named cfl-env
, that contains the version
of Python we specified (cfl
was developed with Python 3.8, so we’re using
that).
Then activate the environment:
conda activate cfl-env
If no error messages result from this command, then you have successfully activated the new environment.
3. Pip install cfl
With your cfl virtual environment active, run the command:
pip install cfl
The installation may take a few minutes, especially if tensorflow
is not
already installed.
To check that the installation was successful, open a Python interpreter (type
python
into the terminal). Then, from within Python, run the command import cfl
and check the version:
python
>>> import cfl
>>> cfl.__version__
The version number of cfl
should print. If this command executes with no
errors, then you are now ready to use cfl
!