abbeyseto / udacity-trivia-app

Full Stack Trivia API

Introduction

Flaskr Backend API gets the list of categories of questions in the trivia app. The Trivia questions are sorted into categories and also rated based on difficulty

This API will give the functionality to:

1. Display questions - both all questions and by category. Questions should show the question, category and difficulty rating by default and can show/hide the answer.
2. Delete questions.
3. Add questions and require that they include question and answer text.
4. Search for questions based on a text query string.
5. Play the quiz game, randomizing either all questions or within a specific category.

Overview

This API majorly uses 3 methods as listed in the table below Most of the get requested do not require arguments.

• Request Arguments: None

You can read more about HTTP request methods

About the Stack

This is a full stack application desiged with some key functional areas:

Backend

The ./backend directory contains a completed Flask and SQLAlchemy server. You will work primarily in app.py to define your endpoints and can reference models.py for DB and SQLAlchemy setup. It uses a Postgress database

Getting Started

Installing Dependencies

Python 3.7

Follow instructions to install the latest version of python for your platform in the python docs

Virtual Enviornment

We recommend working within a virtual environment whenever using Python for projects. This keeps your dependencies for each project separate and organaized. Instructions for setting up a virual enviornment for your platform can be found in the python docs

PIP Dependencies

Once you have your virtual environment setup and running, install dependencies by naviging to the /backend directory and running:

pip install -r requirements.txt

This will install all of the required packages we selected within the requirements.txt file.

Key Dependencies

• Flask is a lightweight backend microservices framework. Flask is required to handle requests and responses.

• SQLAlchemy is the Python SQL toolkit and ORM we'll use handle the lightweight sqlite database. You'll primarily work in app.py and can reference models.py.

• Flask-CORS is the extension we'll use to handle cross origin requests from our frontend server.

Database Setup

With Postgres running, restore a database using the trivia.psql file provided. From the backend folder in terminal run:

psql trivia < trivia.psql

Running the server

From within the backend directory first ensure you are working using your created virtual environment.

To run the server, execute:

export FLASK_APP=flaskr
export FLASK_ENV=development
flask run

Setting the FLASK_ENV variable to development will detect file changes and restart the server automatically.

Setting the FLASK_APP variable to flaskr directs flask to use the flaskr directory and the __init__.py file to find the application.

Frontend

The ./frontend directory contains a complete React frontend to consume the data from the Flask server.

Getting Setup

tip: this frontend is designed to work with Flask-based Backend. It is recommended you stand up the backend first, test using Postman or curl, update the endpoints in the frontend, and then the frontend should integrate smoothly.

Installing Dependencies

Installing Node and NPM

This project depends on Nodejs and Node Package Manager (NPM). Before continuing, you must download and install Node (the download includes NPM) from https://nodejs.com/en/download.

Installing project dependencies

This project uses NPM to manage software dependencies. NPM Relies on the package.json file located in the frontend directory of this repository. After cloning, open your terminal and run:

npm install

tip: npm i is shorthand for npm install

Required Tasks

Running Your Frontend in Dev Mode

The frontend app was built using create-react-app. In order to run the app in development mode use npm start. You can change the script in the package.json file.

Open http://localhost:3000 to view it in the browser. The page will reload if you make edits.

npm start

Authentication

There are currently no authentication methods for this API. This will come in the subsequent versions.

You can call these endpoints from your domain as CORS is enabled and you should not have issues getting responses.

If there are issues, contact the details as seen at the Authors subheading.

END POINT USAGE

Below is an example for your endpoint to get all categories.

GET '/api/categories'
- Fetches a dictionary of categories in which the keys are the ids and the value is the corresponding string of the category
- Request Arguments: None
- Returns: An object with a single key, categories, that contains a object of id: category_string key:value pairs. 
{
  "categories": {
    "1": "Science",
    "2": "Art",
    "3": "Geography",
    "4": "History",
    "5": "Entertainment",
    "6": "Sports"
  },
  "success": true,
  "total_categories": 6
}

GET '/api/questions'
- Fetches a dictionary of questions in which the keys are the ids and the value is the corresponding string of the category
- Request Arguments: None
- Returns: An object question, which is well paginated to aid easy navigation: category_string key:value pairs. 
{
  "categories": {
    "1": "Science",
    "2": "Art",
    "3": "Geography",
    "4": "History",
    "5": "Entertainment",
    "6": "Sports"
  },
  "current_category": {
    "id": 1,
    "type": "Science"
  },
  "next_page": "http://127.0.0.1:5000/api/questions?page=2",
  "previous": null,
  "questions": [
    {
      "answer": "Apollo 13",
      "category": 5,
      "difficulty": 4,
      "id": 2,
      "question": "What movie earned Tom Hanks his third straight Oscar nomination, in 1996?"
    },
    {
      "answer": "Tom Cruise",
      "category": 5,
      "difficulty": 4,
      "id": 4,
      "question": "What actor did author Anne Rice first denounce, then praise in the role of her beloved Lestat?"
    }
}

POST '/api/questions'
- Adds a dictionary of questions in which the keys are the ids and the value is the corresponding string of the category

- Request Arguments: 
{
    "question": "question here",
    "answer": "answer here",
    "difficulty": 1,
    "category": 3
}

- Returns: A status message indicating if the request is successful or not. 
{
  "created": 28,
  "message": "Question created",
  "success": true
}

DEL '/api/questions/<question-id>'
- Deletes a dictionary of question with a specific id
- Request Arguments
{
  "search_term": "movie"
}

- Returns: A collection of result objects based on the searched term.
{
  "questions": [
    {
      "answer": "Apollo 13",
      "category": 5,
      "difficulty": 4,
      "id": 2,
      "question": "What movie earned Tom Hanks his third straight Oscar nomination, in 1996?"
    }
  ],
  "success": true,
  "total_questions": 1
}

DEL '/api/questions/<question-id>'
- Deletes a dictionary of question with a specific id
- Request Arguments: None

- Returns: A status message indicating if the request is successful or not. 
{
  "message": "Deleted",
  "success": true
}

Full Documentation on how to use the API can be found here API Documentation

Error Codes

Flaskr Backend API uses standard error codes. Some of which are listed below with their meaning.

Error Code	Error Message
200	Succesful
404	Not Found
405	Method not allowed
422	Unprocessable Entity
500	Internat server error

Rate limit

There are currently no rate limits to the API calls for Flaskr Backend API

Author

Adenle Abiodun [email protected]