Overloop Tech Test Backend

Running with Docker

• A sample Dockerfile is provided that will run the application in an isolated environment
• Make sure you have docker installed and that the Docker daemon is running
• Build the image: docker build -t overloop-tech-test-backend .
• Run the image: docker run -it -p 5000:5000 overloop-tech-test-backend
• Start making some requests: curl http://localhost:5000/articles

Running with a virtual environment

• To run the application in a virtual Python environment, follow these instructions. This example will create a virtual Python environment for 3.7.4
• Check you have the pyenv version you need: pyenv versions
• You should see 3.7.4
• If you do not have the correct version of Python, install it like this: pyenv install 3.7.4
• On command line do this: ~/.pyenv/versions/3.7.4/bin/python -m venv env
• This creates a folder called env. Then do this to activate the virtual environment: source env/bin/activate
• Lastly do this to check that you are now on the correct Python version: python --version
• You can install the dependencies with pip install -r requirements.txt
• You should run python setup_and_seed.py to get a local database setup and seeded with lookup data
• You can then run the app with flask run or python app.py in the root directory

Running with Puppet + is_puppet_base

• Declare the node configuration:

node 'overloop-demo' {

    # common baseline for all nodes
    include is_puppet_base::node_base

    # team SSH access
    include passwd_common

    # the necessary overloop environment in the desired branch
    class { 'overloop_env': branch => 'issue04_check_robustness' }

    # firewall rule allowing access from the Internet or a whitelist of IPs
    firewall { '300 API HTTPS     ': proto  => 'tcp', dport  => 443, action => 'accept', }

}

• Initialize the database by running:

cd /home/deployment/overloop
sudo python3 setup_and_seed.py

The initialized database will be at /home/deployment/overloop/database.db.

Project Structure Notes

• The database models are stored in the techtest/models folder
• The routes of the Flask app are in techtest/routes folder

In both cases, the modules are loaded by using the __all__ variable in __init__.py, so be sure to update this if you add new files.

Example invocations

Internally:

curl http://localhost:8080/articles
curl http://localhost:8080/regions
curl http://localhost:8080/authors
curl http://localhost:8080/article/1
curl http://localhost:8080/region/1
curl http://localhost:8080/author/1
curl -X POST  http://localhost:8080/add_author  --form username=USERNAME --form password=PASSWORD --form 'content={"first_name":"Al","last_name":"Packa"}'
curl -X POST  http://localhost:8080/edit_author --form username=USERNAME --form password=PASSWORD --form 'content={ "id:9898989", "first_name":"Al","last_name":"Pacone"}' 
curl -X POST  http://localhost:8080/add_article --form username=USERNAME --form password=PASSWORD \
              --form 'content={ "title":"R0 versus 2020","content":"exponentially spreading literature blala", "authors":["1","2"], "regions":["1", "3"] }'
curl -X POST  http://localhost:8080/edit_article --form username=USERNAME --form password=PASSWORD \
              --form 'content={ "id":"3453455", "title":"R0 versus 2020","content":"exponentially spreading literature blala", "authors":["1","2"], "regions":["1", "3"] }'
curl -X POST  http://localhost:8080/delete_article --form username=USERNAME --form password=PASSWORD --form 'content={ "id":"3453455"}'

From the outside:

curl https://PUBLICURL/articles
curl https://PUBLICURL/regions
[...]

These invocations should return JSON content.