Quickstart¶

Prerequisites¶

conda (Anaconda / Miniconda), used to manage python dependencies in a virtual environment
python >= 3.5 (installed through conda)
datascience libraries: matplotlib, numpy, sklearn, etc… (installed through conda)

Install Anaconda or Miniconda. Select the python 3 version. We recommend Anaconda for development and Miniconda for production.

Update to the latest version:

conda update conda -c conda-forge

Follow these instructions if you want to deploy atnlp for production (ie without developing).

Download the atnlp conda production environment configuration:

wget https://raw.githubusercontent.com/wedavey/atnlp/master/envprod.yml

Create atnlp environment (including dependencies):

conda env create -f envprod.yml -n atnlp

If you prefer, Anaconda also provides a GUI for managing environments.

Activate the environment:

conda activate atnlp

Note

on older versions of conda you may need to use source activate atnlp

Make sure you activate this environment anytime you want to use the atnlp package or manage dependencies.

To deactivate the environment issue conda deactivate (source deactivate on older conda versions).

Follow these instructions if you want to develop the atnlp package.

Create a fork of wedavey/atnlp (button at top right).

Clone your fork:

git clone git@github.com:<your-user-name>/atnlp.git

Note

make sure to replace <your-user-name> with your github user name!

Create atnlp-dev environment (including dependencies):

conda env create -f atnlp/envdev.yml -n atnlp-dev

If you prefer, Anaconda also provides a GUI for managing environments.

Activate the environment:

conda activate atnlp-dev

Note

on older versions of conda you may need to use source activate atnlp-dev

Make sure you do this anytime you want to use the atnlp package or manage any dependencies.

To deactivate the environment issue conda deactivate (source deactivate on older conda versions).

Install atnlp:

cd atnlp; python setup.py develop

Now start developing! When you’re happy with the changes on your fork and want to merge into the main repo, make a pull request.