api-emotions-dataminig

pulling from docker hub repository

# docker pull bissorm/api-emotions-datamining

executing the docker image

# docker run -p 8000:8000 bissorm/api-emotions-datamining

project structure

The structure of a Django project works by separating the project parts into applications. Normally, the first application receives the name of the project, when it is built. I changed the name to config, as it is responsible for the project settings. For this project, I created two more apps, api and frontend.

api/

App responsible for handling the calls to classify a phrase/text.

api/__init__.py

Called when the application starts. Contains a class Classifier responsible for the training and classification of the phrases.

api/urls.py

Contais the routs for the api app.

api/views.py

api/words_db.py

Contains the database for training and testing the data mining model.

config/

config/settings.py

config/urls.py

frontend/

frontend/urls.py

frontend/views.py

frontend/static/

frontend/staticfiles/

nltk_data/

Folder that contains the nltk data for the training model. This was needed because nltk normally uses a UI for downloading the data, so a manual installation were needed.

Procfile

File used to build the heroku app

Dockerfile

File used to build the docker image