enhancement - investigate supplying conda environment.yml / requirements.txt with exported python 2.7.6 dependencies

[johndpope]

see here for sample environment https://github.com/johndpope/dev_env/tree/master/conda

this is a sample conda file / rather like requirements.txt / it also encapsulates pip dependencies https://github.com/johndpope/dev_env/blob/master/conda/tensorflow-gpu.yml

with this file / environment on any install linux / windows etc

• python 2 will be forced along with all (legacy) dependencies.

N.B. - to upgrade codebase to python3 is not too bad - just use 2to3 *.py -w

[johndpope]

like this https://github.com/johndpope/summerschool/tree/master/assignment/classifier

Environment and Imports

You can either use the environment.yml file to set up a virtual environment or install the required packages. All experiments and tests can be run inside the required notebooks.

Use the environment.yml file by running:

conda env create -f environment.yml

name: jsalt
channels:
    - anaconda
    - conda-forge
dependencies:
    - jupyter
    - python=3.6
    - tensorflow=1.8.0
    - numpy=1.14.5
    - nltk=3.2.5
    - scikit-learn=0.19.1
    - pandas=0.20.3
    - bokeh=0.12.13
    - pip:
        - graphviz
        - wget

[blancNoir]

A Dockerfile would be appreciated too, or image on dockerhub.