Melbourne Datathon 2018
Presented by ANZ
Terrence.Szymanski@anz.com
Before you start, you should have Python (3.6 or greater) installed, as well as virtualenv (pip install virtualenv).
Clone the repository:
git clone git@github.com:tdszyman/datathon-tutorial.git
Then, run the scripts to setup your Python environment (which creates a virtualenv environment and installs some dependencies), then run the pipeline, and then run the app.
Windows:
setup.bat
python pipeline.py
run.bat
Mac / Linux:
./setup.sh
python pipeline.py
./run.sh
You should then be able to view the app at http://localhost:5000.
You can also run the app by building and running the Dockerfile locally:
docker build -t datathon .
docker run -p 5000:5000 datathon
It is also possible to deploy this app to AWS Elastic Beanstalk, using the configuration stored in the
.elasticbeanstalk directory. You will need to have an AWS account and install the EB command line utilities. These
resources are helpful to get started:
- https://docs.aws.amazon.com/elasticbeanstalk/latest/dg/docker-singlecontainer-deploy.html#docker-singlecontainer-pythonsample
- https://github.com/aws-samples/eb-py-flask-signup/tree/docker
You can run these commands to deploy the app:
eb init
eb create dev-env
$ tree -I "data|venv|__pycache__" .
.
├── Dockerfile
├── Dockerrun.aws.json
├── Readme.md
├── awesomeapp
│ ├── __init__.py
│ ├── api.py
│ ├── static
│ │ ├── css
│ │ │ ├── awesomeapp.css
│ │ │ └── bootstrap.css
│ │ ├── img
│ │ │ └── datathonLogoPB.png
│ │ └── js
│ │ ├── awesomeapp.js
│ │ ├── bootstrap.bundle.js
│ │ ├── jquery.js
│ │ └── plotly-latest.min.js
│ └── templates
│ ├── base.html
│ └── index.html
├── deploy_eb.sh
├── notebooks
│ └── Education\ Heatmap.ipynb
├── pipeline.py
├── requirements.txt
├── run.bat
├── run.sh
├── setup.bat
└── setup.sh