Paginated API For Flagged Reviews: Backend Implementation

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Paginated API for Flagged Reviews: Backend Implementation

Hey guys! Let's dive into building a backend API to fetch a paginated list of recently flagged reviews. This is a crucial part of our P09 task, where we aim to provide a clear view of reviews that have been flagged, along with essential details. Buckle up; this is going to be a fun ride!

Understanding the Requirements

Before we start coding, let's break down what we need to achieve. The core requirement is to create an API endpoint that returns a list of recently flagged reviews. This list needs to be paginated, meaning we'll split it into smaller chunks or pages. Each review in the list should include:

  • A snippet of the review text.
  • The main reasons why the review was flagged.
  • A timestamp indicating when the review was flagged.

Why Pagination?

Pagination is essential for performance, especially when dealing with a large number of flagged reviews. Instead of sending all reviews at once, which can be slow and resource-intensive, we send them in smaller, manageable chunks. This improves the user experience and reduces the load on our server.

Key Components

To implement this, we'll need several key components:

  • Database Model: A way to represent flagged reviews in our database.
  • API Endpoint: The URL that clients will use to request the paginated list.
  • Pagination Logic: The code that splits the reviews into pages.
  • Serialization: Converting the database records into a JSON format that can be sent over the API.

Designing the Database Model

First, let's design the database model for our flagged reviews. We'll need a table (or collection, depending on your database) to store the flagged reviews and their associated information. Here’s a basic example using a relational database:

CREATE TABLE flagged_reviews (
 id INT PRIMARY KEY AUTO_INCREMENT,
 review_id INT NOT NULL,
 review_text TEXT NOT NULL,
 flagging_reasons TEXT NOT NULL,
 flagged_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
);

And here’s how it might look in a NoSQL database like MongoDB:

{
 _id: ObjectId(),
 review_id: ObjectId(),
 review_text: String,
 flagging_reasons: [String],
 flagged_at: Date
}
  • id or _id: A unique identifier for the flagged review.
  • review_id: A reference to the original review.
  • review_text: The text of the review.
  • flagging_reasons: An array or string containing the reasons for flagging.
  • flagged_at: The timestamp when the review was flagged.

The flagging reasons field can be either a simple string or an array of strings, depending on whether we want to allow multiple reasons for a single flagged review. An array provides more flexibility and allows us to capture more detailed information.

Building the API Endpoint

Next, we need to create the API endpoint that clients will use to fetch the paginated list of flagged reviews. This endpoint will typically accept query parameters for specifying the page number and the number of items per page.

For example, the endpoint might look like this:

GET /api/flagged_reviews?page=1&limit=10
  • page: The page number to retrieve (e.g., 1 for the first page).
  • limit: The number of reviews to include per page (e.g., 10 for 10 reviews per page).

Implementation Example (Node.js with Express)

Here’s an example of how you might implement this endpoint using Node.js with Express:

const express = require('express');
const router = express.Router();
const db = require('./db'); // Your database connection

router.get('/flagged_reviews', async (req, res) => {
 const page = parseInt(req.query.page) || 1;
 const limit = parseInt(req.query.limit) || 10;
 const offset = (page - 1) * limit;

 try {
 const { rows, rowCount } = await db.query(
 'SELECT * FROM flagged_reviews ORDER BY flagged_at DESC LIMIT $1 OFFSET $2',
 [limit, offset]
 );

 const totalReviews = await db.query('SELECT COUNT(*) FROM flagged_reviews');
 const totalPages = Math.ceil(totalReviews.rows[0].count / limit);

 res.json({
 page,
 limit,
 totalPages,
 totalReviews: parseInt(totalReviews.rows[0].count),
 reviews: rows,
 });
 } catch (err) {
 console.error(err);
 res.status(500).json({ error: 'Internal Server Error' });
 }
});

module.exports = router;

In this example:

  • We extract the page and limit parameters from the query string.
  • We calculate the offset based on the page and limit.
  • We query the database for the flagged reviews, ordering them by flagged_at in descending order to get the most recent ones first.
  • We return a JSON response containing the current page, limit, total number of pages, total number of reviews, and the list of reviews.

Implementing the Pagination Logic

The pagination logic is at the heart of this API. It involves calculating the offset and limiting the number of results returned from the database. The offset determines where to start fetching records, and the limit determines how many records to fetch.

Calculating the Offset

The offset is calculated using the following formula:

offset = (page - 1) * limit

For example, if we're on page 2 and the limit is 10, the offset will be (2 - 1) * 10 = 10. This means we'll start fetching records from the 11th record in the database.

Limiting the Results

Most databases provide a way to limit the number of results returned from a query. In SQL, this is typically done using the LIMIT clause. In MongoDB, it's done using the limit() method.

For example, in SQL:

SELECT * FROM flagged_reviews ORDER BY flagged_at DESC LIMIT 10 OFFSET 10;

And in MongoDB:

db.collection('flagged_reviews')
 .find()
 .sort({ flagged_at: -1 })
 .skip(10)
 .limit(10)
 .toArray((err, reviews) => {
 // Handle the results
 });

Serializing the Data

Serialization is the process of converting the database records into a JSON format that can be sent over the API. This typically involves mapping the database fields to a JSON structure.

Example

Here’s an example of how you might serialize a flagged review:

{