As pointed out in issue #5 the public server isn't very conducive to both confidential sequences or a high-throughput workflow. Thus, the suggestion to dockerize the app was made.
Added a Dockerfile to facilitate local spin-up of an optimization server. Along the way, one bug was found and the PyPi package was updated to allow one to specify if they are using a local server or the production server on Heroku.
In the future, it might be beneficial to separate out a local API interface and a Heroku API interface to prevent server confusion if confidentiality is a big concern.
As pointed out in issue #5 the public server isn't very conducive to both confidential sequences or a high-throughput workflow. Thus, the suggestion to dockerize the app was made.
Added a Dockerfile to facilitate local spin-up of an optimization server. Along the way, one bug was found and the PyPi package was updated to allow one to specify if they are using a local server or the production server on Heroku.
In the future, it might be beneficial to separate out a local API interface and a Heroku API interface to prevent server confusion if confidentiality is a big concern.