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A Comprehensive Guide To API Pagination Standards And Techniques

Table of contents

Introduction

Pagination just like authentication, is something you need to think about early when building or using APIs (Application Programming Interfaces) [→].

In this blog post, I will explain different some of the different ways you can implement API pagination [→] and discuss the advantages and disadvantages of each one.

What is API Pagination?

Pagination in APIs refers to the process of dividing a large set of data into smaller sections, or "pages." When a client (like a web application) requests data from an API, the server returns only a portion of the data, along with information on how to request the next set of data. This approach improves performance and makes it easier for the client to handle the data.

Example: Imagine you have a database with 10,000 products. Instead of returning all 10,000 products in a single API request, which could be slow and overwhelming, you might return 100 users at a time. The client can then request the next 100 users, and so on, until all the users have been retrieved.

Why is Pagination Important?

  • Performance: Large datasets can be slow to process and transfer. Pagination helps reduce the load on servers and networks by limiting the amount of data sent in each request.
  • User Experience: For applications displaying data to users, showing all the data at once can be overwhelming. Pagination allows users to browse data in a more manageable way.
  • Resource Management: Pagination helps prevent resource exhaustion on both the server and client side by controlling the amount of data being processed at one time.

Types of pagination

There are several ways to implement pagination in APIs. The choice of technique depends on the specific requirements of the API , constraints and how the data is structured.

Offset-Based Pagination

How it works:In offset-based pagination, you specify an offset (the starting point) and a limit (the number of records to return). The server responds with data starting from the offset and up to the limit specified.

Example:Let’s say you want to fetch products 301 to 400 from the list of 10,000 products.

  • Request: GET /products?offset=300&limit=100
  • Response: Users 301 to 400

Advantages:

  • Simple to implement and understand.
  • Works well with small datasets.

Disadvantages:

  • Performance can degrade with large datasets as the offset increases.
  • Data inconsistency can occur if the data changes (e.g., new records are added) while paginating.

Page-Based Pagination

How it works:In page-based pagination, you specify the page number and the number of records per page. The server calculates the offset internally based on these values.

Example:Fetching the second page of products with 100 users per page.

  • Request: GET /products?page=3&per_page=100
  • Response: Users 301 to 400

Advantages:

  • Easy to implement and understand.
  • Works well for displaying data in user interfaces.

Disadvantages:

  • Similar to offset-based pagination, it can slow down with large datasets.
  • Data inconsistency issues may arise with dynamic datasets.

In this implementation the server providing the data will usually also include information on the number of available pages.

Cursor-Based Pagination

How it works:
Cursor-based pagination (or keyset pagination) uses a cursor, which is a unique identifier for the last record retrieved. Instead of using an offset, the server uses this cursor to determine where to start the next page of data.

Example:
Let’s say each product has a unique ID. You can use this ID as the cursor to fetch the next set of products.

  • Request: GET /products?cursor=200&limit=100
  • Response: products after the product with ID 200

Advantages:

  • More efficient with large datasets.
  • Avoids performance issues with high offsets.
  • Consistent results even if the data changes during pagination.

Disadvantages:

  • More complex to implement.
  • Requires a stable and unique ordering of records (e.g., by ID or timestamp).

Time-Based Pagination

How it works:
Time-based pagination is a specific form of cursor-based pagination where the cursor is a timestamp or date. It’s commonly used in APIs that return records in chronological order, like activity logs or social media feeds.

Example:
Fetching records created after a certain timestamp.

  • Request: GET /logs?created_after=2024-08-01T00:00:00Z&limit=100
  • Response: Records created after August 1, 2024

Advantages:

  • Works well with time-sensitive data.
  • Avoids the problems of high offsets.

Disadvantages:

  • Requires consistent and accurate timestamps.
  • Complex implementation, especially when handling time zones.

Best Practices for API Pagination

When implementing pagination in your API, consider these best practices to ensure a smooth experience for developers and users:

a. Use Descriptive Parameters:

Use clear and descriptive query parameters, like page, limit, cursor, or per_page, to make the API easy to understand.

b. Provide Total Count Information:

Include metadata in the response, such as the total number of records, the current page, and the total number of pages. This helps clients know how much data is available.

Example:

01: {
02:   "total": 1000,
03:   "page": 2,
04:   "per_page": 100,
05:   "data": [ /* products 200 to 300 */ ]
06: }

c. Handle Edge Cases:

Consider edge cases like the first page, last page, and empty results. Make sure your API handles these gracefully and returns appropriate responses.

d. Optimize for Performance:

Use database indexes to speed up queries for pagination, especially with large datasets. For cursor-based pagination, make sure the column used for the cursor is indexed.

e. Document Pagination Clearly:

Provide clear documentation on how pagination works in your API, including how to use the different parameters and what to expect in the response.

f. Avoid Using Offset with Large Datasets:

If your dataset is very large, prefer cursor-based pagination over offset-based pagination to avoid performance issues.

5. Introducing HATEOAS in Pagination

HATEOAS stands for Hypermedia As The Engine Of Application State. It’s a concept in RESTful API design where the client interacts with the API entirely through links provided in the responses, rather than relying on hard-coded URL paths. This can be especially useful in pagination.

How HATEOAS Enhances Pagination

When using HATEOAS with pagination, the API not only returns the current set of data but also includes links (URLs) to the previous and next pages, and sometimes the first and last pages. This makes it easier for clients to navigate through the paginated data without needing to manually construct the URLs for the next or previous pages.

Example:

01: {
02:   "total": 1000,
03:   "page": 2,
04:   "per_page": 100,
05:   "data": [ /* Users 101 to 200 */ ],
06:   "links": {
07:     "self": "/users?page=2&per_page=100",
08:     "next": "/users?page=3&per_page=100",
09:     "prev": "/users?page=1&per_page=100",
10:     "first": "/users?page=1&per_page=100",
11:     "last": "/users?page=10&per_page=100"
12:   }
13: }

Advantages:

  • Easier Navigation: Clients don’t need to figure out how to construct URLs for other pages; they can just follow the links provided.
  • Decoupled Client and Server: The client doesn’t need to know the structure of the API URLs; it just follows the links, which the server controls.
  • Improved Flexibility: If the API’s URL structure changes, clients don’t need to be updated as long as they rely on the provided links.

Implementing HATEOAS with Pagination

To implement HATEOAS in your paginated API, make sure that each response includes links to relevant actions or pages. For example:

  • self: The URL for the current page.
  • next: The URL for the next page (if it exists).
  • prev: The URL for the previous page (if it exists).
  • first: The URL for the first page.
  • last: The URL for the last page.

This approach makes your API more user-friendly and adaptable, especially as the API evolves over time.

Examples of API Pagination with HATEOAS

Let’s look at how some popular APIs implement pagination with HATEOAS.

a. GitHub API:

  • Request: GET /repos/{owner}/{repo}/issues?page=2&per_page=30
  • Response: The second page of issues, with links to the next and previous pages.
01: {
02:   "total_count": 105,
03:   "items": [ /* Issues 31 to 60 */ ],
04:   "links": {
05:     "self": "/repos/{owner}/{repo}/issues?page=2&per_page=30",
06:     "next": "/repos/{owner}/{repo}/issues?page=3&per_page=30",
07:     "prev": "/repos/{owner}/{repo}/issues?page=1&per_page=30"
08:   }
09: }

b. Twitter API:

  • Request: GET /friends/list.json?cursor=-1&screen_name=twitterapi&count=100
  • Response: A list of friends, with a cursor for fetching the next set and links provided for easy navigation.
01: {
02:   "users": [ /* List of users */ ],
03:   "next_cursor": "1429294874484558827",
04:   "previous_cursor": "0",
05:   "links": {
06:     "next": "/friends/list.json?cursor=1429294874484558827&screen_name=twitterapi&count=100",
07:     "prev": "/friends/list.json?cursor=0&screen_name=twitterapi&count=100"
08:   }
09: }

Conclusion

Most API pagination methods are easy to set up, but the challenge is choosing the right one for your specific needs. It's also important to think about how familiar your users are with the method you pick, use clear names, and stay consistent in your implementation.

I hope this tutorial gives you a helpful starting point.

Here is another article you might like 😊 Setting An Attribute To Null In OpenAPI

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