Offset-based pagination in Rest API

Introduction

Offset-based pagination helps you get a small part of a big list of data, so you don't load everything at once.

When showing search results page by page on a website.

When loading posts in a social media feed little by little.

When displaying products in an online store in chunks.

When you want users to jump to any page of data easily.

When your data source supports skipping items by number.

Syntax

Rest API

GET /items?offset=number&limit=number

offset tells how many items to skip from the start.

limit tells how many items to get after skipping.

Examples

Get the first 10 items, starting from the beginning.

Rest API

GET /items?offset=0&limit=10

Skip the first 10 items, then get the next 10 items (items 11 to 20).

Rest API

GET /items?offset=10&limit=10

Skip 20 items, then get 5 items (items 21 to 25).

Rest API

GET /items?offset=20&limit=5

Sample Program

This small web app shows how to use offset and limit to return parts of a list. You can try URLs like /items?offset=10&limit=5 to get items 11 to 15.

Rest API

from flask import Flask, request, jsonify

app = Flask(__name__)

# Sample data: list of 100 numbers
items = list(range(1, 101))

@app.route('/items')
def get_items():
    # Get offset and limit from query parameters, with defaults
    offset = int(request.args.get('offset', 0))
    limit = int(request.args.get('limit', 10))

    # Get the slice of items
    paged_items = items[offset:offset+limit]

    # Return as JSON
    return jsonify({
        'offset': offset,
        'limit': limit,
        'items': paged_items
    })

if __name__ == '__main__':
    app.run(debug=True)

Important Notes

Offset-based pagination is simple but can be slow if the offset is very large because the server skips many items.

It works well when users want to jump to any page number directly.

Remember to validate offset and limit to avoid errors or too large requests.

Summary

Offset-based pagination uses offset to skip items and limit to get a chunk.

It helps load data in small parts for better speed and user experience.

Common in REST APIs for showing pages of results.

Practice

1. What does offset represent in offset-based pagination?

easy

A. The maximum number of pages available

B. The total number of items to return in the response

C. The current page number being requested

D. The number of items to skip before starting to collect results

Solution

1. Step 1: Understand the role of offset

   Offset tells the system how many items to skip before starting to return data.

2. Step 2: Differentiate offset from limit and page

   Limit controls how many items to return; page number is a different pagination method.

3. Final Answer:

   The number of items to skip before starting to collect results -> Option D

4. Quick Check:

   Offset = items skipped before results [OK]

Hint: Offset means how many items to skip before fetching [OK]

Common Mistakes:

• Confusing offset with limit
• Thinking offset is the page number
• Assuming offset is total items count

2. Which of the following is the correct way to request the second page of results with 10 items per page using offset-based pagination?

easy

A. GET /items?start=10&count=10

B. GET /items?offset=10&limit=10

C. GET /items?page=2&limit=10

D. GET /items?offset=2&limit=10

Solution

1. Step 1: Calculate offset for page 2 with 10 items per page

   Offset = (page number - 1) * limit = (2 - 1) * 10 = 10.

2. Step 2: Identify correct query parameters

   Offset and limit are standard; page parameter is not used in offset-based pagination.

3. Final Answer:

   GET /items?offset=10&limit=10 -> Option B

4. Quick Check:

   Offset = 10 for page 2 with 10 items [OK]

Hint: Offset = (page - 1) x limit for correct pagination [OK]

Common Mistakes:

• Using page instead of offset
• Setting offset to page number directly
• Using non-standard parameter names

3. Given the API call GET /products?offset=5&limit=3 and the product list ["A", "B", "C", "D", "E", "F", "G", "H"], what will be the returned products?

medium

A. ["D", "E", "F"]

B. ["E", "F", "G"]

C. ["F", "G", "H"]

D. ["G", "H"]

Solution

1. Step 1: Identify starting index using offset

   Offset 5 means skip first 5 items: A(0), B(1), C(2), D(3), E(4) skipped; start at index 5.

2. Step 2: Select limit number of items from offset

   Limit is 3, so select items at indices 5, 6, 7: F, G, H.

3. Final Answer:

   ["F", "G", "H"] -> Option C

4. Quick Check:

   Offset 5 + limit 3 = F, G, H [OK]

Hint: Start at offset index, take limit items [OK]

Common Mistakes:

• Starting at offset - 1 index
• Including offset item in skipped items
• Returning fewer or more items than limit

4. You have this API call: GET /users?offset=20&limit=10. The API returns an empty list even though there are 25 users total. What is the likely problem?

medium

A. Offset is too large, skipping all remaining users

B. Limit is too small to return any users

C. Offset and limit parameters are swapped

D. API does not support offset-based pagination

Solution

1. Step 1: Calculate remaining items after offset

   Offset 20 skips first 20 users; only 5 users remain (25 - 20 = 5).

2. Step 2: Understand why empty list is returned

   API returns empty list likely because it expects at least 10 items (limit), but only 5 remain; some APIs may return empty if offset exceeds total count.

3. Final Answer:

   Offset is too large, skipping all remaining users -> Option A

4. Quick Check:

   Offset > total users - limit causes empty results [OK]

Hint: Check if offset skips beyond total items [OK]

Common Mistakes:

• Assuming limit controls start position
• Swapping offset and limit values
• Ignoring total item count in pagination

5. You want to implement offset-based pagination for a large dataset but want to avoid performance issues with very large offsets. Which approach is best to improve performance?

hard

A. Use keyset pagination by filtering with a unique indexed column instead of offset

B. Increase the limit value to reduce the number of pages

C. Cache all pages in memory to avoid database queries

D. Use offset with very large values and rely on database optimization

Solution

1. Step 1: Understand offset performance issues

   Large offsets cause the database to scan many rows before returning results, slowing queries.

2. Step 2: Identify better pagination method

   Keyset pagination uses a unique indexed column (like ID) to fetch next pages efficiently without scanning skipped rows.

3. Step 3: Evaluate other options

   Increasing limit or caching is not scalable; relying on database optimization alone is insufficient.

4. Final Answer:

   Use keyset pagination by filtering with a unique indexed column instead of offset -> Option A

5. Quick Check:

   Keyset pagination avoids large offset performance issues [OK]

Hint: Use keyset pagination to avoid slow large offsets [OK]

Common Mistakes:

• Relying on large offset values for deep pages
• Increasing limit without considering user experience
• Assuming caching solves pagination performance