dakota-vikdal / mock-cc-researchpapers

Flask Mock Code Challenge - Research papers

For this assessment, you'll be working with a Reasearch Author domain.

In this repo, there is a Flask application with some features built out. There is also a fully built React frontend application, so you can test if your API is working.

Your job is to build out the Flask API to add the functionality described in the deliverables below.

Setup

To download the dependencies for the frontend and backend, run:

pipenv install
npm install --prefix client

There is some starter code in the app/seed.py file so that once you've generated the models, you'll be able to create data to test your application.

You can run your Flask API on localhost:5555 by running:

python app.py

You can run your React app on localhost:4000 by running:

npm start --prefix client

You are not being assessed on React, and you don't have to update any of the React code; the frontend code is available just so that you can test out the behavior of your API in a realistic setting.

There are also tests included which you can run using pytest -x to check your work.

Depending on your preference, you can either check your progress by:

• Running pytest -x and seeing if your code passes the tests
• Running the React application in the browser and interacting with the API via the frontend
• Running the Flask server and using Postman to make requests

Models

You need to create the following relationships:

• A Research has many Authors through ResearchAuthors
• A Author has many Researchs through ResearchAuthors
• A ResearchAuthors belongs to a Research and belongs to a Author

Start by creating the models and migrations for the following database tables:

Add any code needed in the model files to establish the relationships.

Then, run the migrations and seed file:

flask db revision --autogenerate -m'message'
flask db upgrade
python db/seed.py

If you aren't able to get the provided seed file working, you are welcome to generate your own seed data to test the application.

Validations

Add validations to the Research model:

• must have a valid 4 digit year

Add validations to the Author model:

• field_of_study must be within the following list [AI, Robotics, Machine Learning, Vision, Cybersecurity]

Routes

Set up the following routes. Make sure to return JSON data in the format specified along with the appropriate HTTP verb.

GET /research

Return JSON data in the format below:

[
  {
    "id": 1,
    "topic": "AI and Human Interaction",
    "year": 2018,
    "page_count": 500
  },
  {
    "id": 2,
    "name": "Keeping Physical Systems Secure",
    "year": 2013,
    "page_count": 328
  }
]

GET /research/:id

If the Research exists, return JSON data in the format below:

{
  "id": 1,
  "topic": "AI and Human Interaction",
  "year": 2018,
  "page_count": 500,
  "authors": [
    {
      "id": 1,
      "name": "John Science",
      "field_of_study": "AI"
    },
    {
      "id": 2,
      "name": "Phil Man",
      "field_of_study": "Machine Learning"
    }
  ]
}

If the Research does not exist, return the following JSON data, along with the appropriate HTTP status code:

{
  "error": "Research paper not found"
}

DELETE /research/:id

If the Research exists, it should be removed from the database, along with any ResearchAuthorss that are associated with it (a ResearchAuthors belongs to a Research, so you need to delete the ResearchAuthorss before the Research can be deleted).

After deleting the Research, return an empty response body, along with the appropriate HTTP status code.

If the Research does not exist, return the following JSON data, along with the appropriate HTTP status code:

{
  "error": "Research paper not found"
}

GET /authors

Return JSON data in the format below:

[
  {
    "id": 1,
    "name": "John Science",
    "field_of_study": "AI"
  },
  {
    "id": 2,
    "name": "Phil Man",
    "field_of_study": "Machine Learning"
  }
]

POST /research_author

This route should create a new ResearchAuthors that is associated with an existing Author and Research. It should accept an object with the following properties in the body of the request:

{
  "author_id": 1,
  "research_id": 3
}

If the ResearchAuthors is created successfully, send back a response with the data related to the Author:

{
  "id": 1,
  "name": "John Science",
  "field_of_study": "AI"
}

If the ResearchAuthors is not created successfully, return the following JSON data, along with the appropriate HTTP status code:

{
  "errors": ["validation errors"]
}