• D1g1t Back-end Test Assignment
  • Assumptions
    • Method
    • The levels of happiness have the following ranges
    • High Level Solution Design
  • Prerequisites
  • Installation
    • How to run it?
      • Go to the cloned directory
      • Build the application
      • Apply Django migrations
      • Create superuser
      • Run the application
  • Tests
  • Endpoints
    • Authentication /api/token/
      • Response
    • CREATE Daily Check-in /daily/v1/api/
      • The score is calculated by summing up the responses to the following questions/criteria
      • The scale (responses)
      • Example
    • GET Analytics /analytics/v1/api/
    • Authenticated User
      • Response
    • Analytics (Anonymous User) /analytics/v1/api/
      • Response
  • Improvements

• The solution implemented in this assessment has not been optimized for a live production environment with thousands of transactions per minute.
• The solution has not been implemented using Django async. Even though the progress done by the Django community sounds promising, the performance improvements are still maturing compared to sync wsgi.
• Users can get statistical information over the course of one year.
• Users can be members of more than one Team.
• Users who are not members of a team won't be able to do a daily check-in

The method chosen to measure Happiness was The Satisfaction with Life Scale (SWLS) uses a scale of 1 to 7, where 1 represents "strongly disagree," and 7 represents "strongly agree" for statements such as "In most ways, my life is close to my ideal."

• 31 - 35 Extremely happy
• 26 - 30 happy
• 21 - 25 Slightly happy
• 20 Neutral
• 15 - 19 Slightly unhappy
• 10 - 14 unhappy
• 5 - 9 Extremely unhappy

You need to install Docker Desktop and Docker Compose before following the instructions below.

To install Docker Desktop on Windows Home, please follow the instructions.

To clone the repository, run the following command

git clone https://github.com/ridiaz/d1g1t-backend-assignment.git

To enable live code reloading. Without this, Docker Compose will not start:

• Windows/MacOS: Add the cloned d1g1t-backend-assignment directory to Docker shared directories (Preferences -> Resources -> File sharing)
• Linux: No action is required, sharing is already enabled and memory for the Docker engine is not limited.

cd d1g1t-backend-assignment

docker-compose build

docker-compose up db -d && sleep 3 && docker-compose run --rm api python3 manage.py migrate

Create super user with the following command, to access the Django web Admin

docker-compose run --rm api python3 manage.py createsuperuser

docker-compose up

Now you can access the Django web Admin on http://localhost:9001/admin

docker-compose run --rm api python3 pytest

In order to access the API endpoints that require authentication, you should include the access token in the header of all requests. JSON Web Token Authentication

curl --request POST \
  --url http://localhost:9001/api/token/ \
  --header 'Content-Type: application/json' \
  --data '{
"username": "<username>",
"password": "<password>"
}'

{
  "refresh": "<generated token>",
  "access": "<generated token>"
}

• __ In most ways my life is close to my ideal.
• __ The conditions of my life are excellent.
• __ I am satisfied with my life.
• __ So far I have gotten the important things I want in life.
• __ If I could live my life over, I would change almost nothing.

• 7 - Strongly agree
• 6 - Agree
• 5 - Slightly agree
• 4 - Neither agree nor disagree
• 3 - Slightly disagree
• 2 - Disagree
• 1 - Strongly disagree

curl --request POST \
  --url http://localhost:9001/daily/v1/api/ \
  --header 'Authorization: Bearer <generated token>' \
  --header 'Content-Type: application/json' \
  --data '{
"responses": [6,6,6,5,6]
}'

curl --request GET \
  --url http://localhost:9001/analytics/v1/api/ \
  --header 'Authorization: Bearer <token>'

Returns the list of all user's team statistics

[
  {
    "name": "team_3",
    "team_statistics": [
      {
        "number_of_people": 1,
        "average_happiness": 29.0,
        "level_happiness": "Happy"
      },
      {
        "number_of_people": 1,
        "average_happiness": 22.0,
        "level_happiness": "Slightly Happy"
      }
    ],
    "average_happiness": 25.5
  }
]

Returns average happiness across all teams

curl --request GET \
  --url http://localhost:9001/analytics/v1/api/

[
  {
    "name": "all teams",
    "average_happiness": 29.0
  }
]

• Add cache layer
• Remove signals
• Implement task queue (i.e. Celery) to handle the loading of the data to the Analytics DB
• Writing statistical/analytics calculations with Django ORM could be difficult and inefficient (i.e. unnecessary calls to the database), sometimes is better to write raw SQL queries to take full advantage of the RDBMS engine
• Add Db indexes
• Add more type hints
• Add more tests
• Add logging
• Add support of global exception handling in APIs
• Add rate limiting to the api endpoints