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7 ways to handle common errors and invalid requests in API pagination

This article discusses 8 effective ways to deal with common pagination errors. (With code snippets)

Note: This is a part of our series on API Pagination where we solve common developer queries in detail with common examples and code snippets. Please read the full guide here where we discuss page size, error handling, pagination stability, caching strategies and more.

It is important to account for edge cases such as reaching the end of the dataset, handling invalid or out-of-range page requests, and to handle this errors gracefully.

Always provide informative error messages and proper HTTP status codes to guide API consumers in handling pagination-related issues.

Here are some key considerations for handling edge cases and error conditions in a paginated API:

How to handle common errors and invalid requests in API pagination

Here are some key considerations for handling edge cases and error conditions in a paginated API:

1. Out-of-range page requests

When an API consumer requests a page that is beyond the available range, it is important to handle this gracefully. 

Return an informative error message indicating that the requested page is out of range and provide relevant metadata in the response to indicate the maximum available page number.

2.  Invalid pagination parameters

Validate the pagination parameters provided by the API consumer. Check that the values are within acceptable ranges and meet any specific criteria you have defined. If the parameters are invalid, return an appropriate error message with details on the issue.

3. Handling empty result sets

If a paginated request results in an empty result set, indicate this clearly in the API response. Include metadata that indicates the total number of records and the fact that no records were found for the given pagination parameters. 

This helps API consumers understand that there are no more pages or data available.

4. Server errors and exception handling

Handle server errors and exceptions gracefully. Implement error handling mechanisms to catch and handle unexpected errors, ensuring that appropriate error messages and status codes are returned to the API consumer. Log any relevant error details for debugging purposes.

5. Rate limiting and throttling

Consider implementing rate limiting and throttling mechanisms to prevent abuse or excessive API requests. 

Enforce sensible limits to protect the API server's resources and ensure fair access for all API consumers. Return specific error responses (e.g., HTTP 429 Too Many Requests) when rate limits are exceeded.

6. Clear and informative error messages

Provide clear and informative error messages in the API responses to guide API consumers when errors occur. 

Include details about the error type, possible causes, and suggestions for resolution if applicable. This helps developers troubleshoot and address issues effectively.

7. Consistent error handling approach

Establish a consistent approach for error handling throughout your API. Follow standard HTTP status codes and error response formats to ensure uniformity and ease of understanding for API consumers.

For example, consider the following API in Django

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from django.http import JsonResponse
from django.views.decorators.http import require_GET

POSTS_PER_PAGE = 10

@require_GET
def get_posts(request):
   # Retrieve pagination parameters from the request
   page = int(request.GET.get('page', 1))
  
   # Retrieve sorting parameter from the request
   sort_by = request.GET.get('sort_by', 'date')

   # Retrieve filtering parameter from the request
   filter_by = request.GET.get('filter_by', None)

   # Get the total count of posts (example value)
   total_count = 100

   # Calculate pagination details
   total_pages = (total_count + POSTS_PER_PAGE - 1) // POSTS_PER_PAGE
   next_page = page + 1 if page < total_pages else None
   prev_page = page - 1 if page > 1 else None

   # Handle out-of-range page requests
   if page < 1 or page > total_pages:
       error_message = 'Invalid page number. Page out of range.'
       return JsonResponse({'error': error_message}, status=400)

   # Retrieve posts based on pagination, sorting, and filtering parameters
   posts = retrieve_posts(page, sort_by, filter_by)

   # Handle empty result set
   if not posts:
       return JsonResponse({'data': [], 'pagination': {'total_records': total_count, 'current_page': page,
                                                        'total_pages': total_pages, 'next_page': next_page,
                                                        'prev_page': prev_page}}, status=200)

   # Construct the API response
   response = {
       'data': posts,
       'pagination': {
           'total_records': total_count,
           'current_page': page,
           'total_pages': total_pages,
           'next_page': next_page,
           'prev_page': prev_page
       }
   }


   return JsonResponse(response, status=200)

def retrieve_posts(page, sort_by, filter_by):
   # Logic to retrieve posts based on pagination, sorting, and filtering parameters
   # Example implementation: Fetch posts from a database
   offset = (page - 1) * POSTS_PER_PAGE
   query = Post.objects.all()

   # Add sorting condition
   if sort_by == 'date':
       query = query.order_by('-date')
   elif sort_by == 'title':
       query = query.order_by('title')

   # Add filtering condition
   if filter_by:
       query = query.filter(category=filter_by)


   # Apply pagination
   query = query[offset:offset + POSTS_PER_PAGE]

   posts = list(query)
   return posts

        
    

8. Consider an alternative

If you work with a large number of APIs but do not want to deal with pagination or errors as such, consider working with a unified API solution like Knit where you only need to connect with the unified API only once, all the authorization, authentication, rate limiting, pagination — everything will be taken care of the unified API while you enjoy the seamless access to data from more than 50 integrations.

Sign up for Knit today to try it out yourself in our sandbox environment (getting started with us is completely free)

Sudeshna Roy

Head of Content, Knit

Decoding product and generating users with valuable content

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Insights
Nov 19, 2023

Whitepaper: The Unified API Approach to Building Product Integrations

11
mins

We just published our latest whitepaper "The Unified API Approach to Building Product Integrations". This is a one stop guide for every product owner, CTO, product leader or a C-suite executive building a SaaS product.

If you are working on a SaaS tool, you are invariably developing a load of product/customer-facing integrations. After all, that's what the data says.

Not to worry. This guide will help you better plan your integration strategy and also show you how unified APIs can help you launch integrations 10x faster.

In this guide, we deep dive into the following topics:

  • What is a unified API and when to use one
  • The components of unified API
  • The ROI of using a unified API
  • Factors to consider before choosing a unified API provider
  • Comparative analysis of different approaches to building integrations
  • Build vs Buy: What should be your integration strategy?
  • Integration challenges for startups and how to address them

Download your guide here.

Insights
Nov 18, 2023

Unified API: All you need to know

11
mins

Today, SaaS integrations have become a necessity considering the current market landscape ensuring faster time to market, focus on product innovation and customer retention. A standard SaaS tool today has 350+ integrations, where as an early startup has minimum 15 product integrations in place.  

However, building and managing customer facing integrations in-house can be a daunting task, considering they are complicated, expensive and their volume and scope is ever increasing. With rising customer demands for a connected SaaS ecosystem, product owners are always on the lookout for ways to significantly increase their integration shipping time. Therefore, the integration market has seen the steady rise of API aggregators or unified APIs. 

This article will help you understand the diverse aspects of unified API, benefits and how you can choose the right one. 

Here’s what we will discuss here:

  • What is a unified API
  • Rise of unified API
  • Key components of unified API
  • Benefits of unified API
  • ROI of unified APIs
  • How unified APIs ensure a more secure connection
  • When to choose a unified API vs build integrations in-house
  • Workflow automation tools vs unified APIs
  • How to choose the right unified API provider

Let's get started.

What is a unified API?

A unified API is an aggregator or a single API which allows you to connect with APIs of different software by offering a single, standardized interface for different services, applications, or systems. Furthering SaaS integrations, it adds an additional abstraction layer to ensure that all data models and schemas are normalized into one data model of the unified API. 

Rise of unified API

As the volume of integrations have seen an exponential increase, the use of APIs has become more pronounced. With more APIs, complexity and costs of integrations are also increasing. Therefore, the reliance on unified API has seen an increase, guided by the following factors:

Increased API use

  • 90% of the entire developer population across the world uses APIs
  • 69% developers work with third party APIs
  • 98% of large enterprises consider APIs an essential part of their digital transformation strategy
  • 53% enterprises are consuming 3rd party APIs for developing products and services

To know more about API integration, its growth, benefits, key trends and challenges and increased use, check out our complete guide on What is API integration

High cost of in-house integrations

  • Integrations can take anywhere between 2 weeks to 3 months to build, keeping an average of 4 weeks
  • Building integrations require expertise and bandwidth of engineering teams, including QA engineers, product managers and software developers, whose salary can range from USD 80K to USD 125K
  • Therefore, the average cost per integration comes to USD 10K, and companies generally use 100+ integrations, at least 15-20 at a lower spectrum, leading to USD 150K- 200K of integration costs

Building and managing integrations is complex

  • APIs within the same software category can have different schemas and data models, requiring engineering teams to gain knowledge of different rules and architecture
  • Full version APIs might not be freely available for all applications, some might come at an additional cost or premium upgrade
  • Maintaining integrations can be difficult, especially when an API fails, and customer success teams lack the expertise to address these challenges 

Together these factors have been instrumental in the rise of unified API as a popular approach to facilitate seamless integrations for businesses.  

Key components of unified API

Let’s quickly walk through some of the top traits or components which form the building blocks for a good unified API. Essentially, if your unified API has the following, you are in good hands:

Data retrieval and aggregation

As the user requests for data, the Unified API efficiently retrieves relevant information from the concerned APIs. It also aggregates data from multiple APIs, consolidating all required information into a single API call. 

For instance, in a scenario where a user seeks an employee's contact and bank account details, the Unified API fetches and aggregates the necessary data from multiple APIs, ensuring a seamless user experience.

Normalization

Each application or software that your users want integration with will have distinct data models and nuances. Even for the same field like customer ID, the syntax can vary from cust_ID ro cus.ID and innumerable other options. 

A unified API will normalize and transform this data into a standard format i.e. a common data model and align it with your data fields to ensure that  no data gets lost because it is not mapped correctly. . 

Developers save engineering efforts for mapping, identifying errors in data exchange and understanding different APIs to facilitate normalization and transfer.  

Data sync

Once the data is normalized, the Unified API prepares it for transmission back to the user. This can be executed either via a webhook or by promptly responding to the API request, ensuring swift and efficient data delivery.

Some unified API requires you to maintain a polling infrastructure for periodically pulling data from the source application. While other unified APIs like Knit, follow a push architecture where in case an event occurs, it automatically sends you fresh data to the webhook registered by you.

Benefits of unified API

Now that you understand what constitutes a good unified API, it is important to understand the benefits that unified API will bring along. 

Faster time to market and scalability

Unified API allows engineering teams to go to the market faster with enhanced core product functionalities as time and bandwidth spent on building in-house integrations is eliminated. It enables accelerated addition or deletion of APIs from your product, creating the right market fit. At the same time, you can easily scale the number and volume of integrations for your product to meet customer demands, without worrying about time and cost associated with integrations. 

Reduced costs

As mentioned, building integrations with different APIs for different applications can be highly cost intensive. However, with a unified API, businesses can significantly save on multiple engineering hours billed towards building and maintaining integrations. There is a clear decrease in the hard and soft costs associated with integrations with a potential to save thousands of dollars per integration.  

Reduced maintenance responsibilities

Maintaining several APIs for integrations can be as difficult or at times more difficult than building integrations, as the former is an ongoing activity. A unified API takes out the friction from maintaining integrations and takes care when an API fails, or the application undergoes an upgrade, etc. Also, maintenance responsibilities involve context switching for engineering teams, which leads to a significant wastage of time and efforts. A unified API bears full responsibility for troubleshooting, handling errors and all other maintenance related activities. 

Managing integrations can be time and cost intensive, leading to unnecessary delays, budget challenges and diversion of engineering resources. Our article on Why You Should Use Unified API for Integration Management discusses how a unified API can cut down your integration maintenance time by 85%

Ease of documentation and KT

A unified API ensures that you don’t need to bury yourself in 1000s of pages of documentation for each and every integration or application API. Rather, it allows you to simply gain knowledge about the architecture and rules of the endpoint and authentication for the unified API. Invariably, the documentation is easy to understand and the knowledge transfer is also seamless because it is limited to one architecture. 

Standardized pagination

Pagination, filtering and sorting is an important element when it comes to integration for businesses. All these three elements help applications breakdown data in a way that is easier to consume and use for exchange. A unified API ensures that there is a standardization and uniformity between different formats of pagination, sorting and filtering among applications and it is extremely consistent. This prevents over-fetching or under-fetching of data, leading to more efficient data exchange. 

If you want to learn more about pagination best practices, read our complete guide on API pagination

New revenue opportunities

Finally, a unified API helps you create new revenue or monetization opportunities for businesses by allowing them to offer premium services of connecting all HRIS or CRM platforms on an integrated platform. A unified API has the potential to help customers save time and cost, something they would be willing to pay a little extra for. 

ROI of a unified API

While we have mentioned some of the top benefits of using unified APIs, it is very important to also understand how unified APIs directly impact your bottom line in terms of the return on investment. To enable SaaS companies to decode the business value of unified APIs, we have created an ROI calculator for unified API. Learn how much building integrations in-house is costing you and compare it with the actual business/monetary impact of unified APIs.

Some of the key tangible metrics that translate to ROI of unified APIs include:

I) Saved engineering hours and cost

II) Reduced time to market

III) Improved scalability rate

IV) Higher customer retention rate

V) New monetization opportunities

VI) Big deal closure

VII) Access to missed opportunities

VIII) Better security

IX) CTO sentiment

X) Improved customer digital experiences

To better understand the impact of these metrics and more on your bottom line and how it effectively translates to dollars earned, go to our article on What is the Real ROI of Unified API: Numbers You Need to Know.

Can unified API lead to better security?

A key concern for anyone using APIs or integrations is the security posture. As there is an exchange of data between different applications and systems, it is important that there is no unauthorized access or misuse of data which can lead to financial and reputational damage. Some of the key security threats for API include:

  • Unauthorized access
  • Broken authentication tokens
  • Injection attacks
  • Data exposure
  • Rate limiting and Denial of Service (DoS) attacks 
  • Third party dependencies
  • Human error

Learn more about the most common API security threats and risks you are vulnerable to and the potential consequences if you don’t take action. 

A unified API can help achieve better security outcomes for B2B and B2C companies by facilitating:

1) Authentication and authorization

Unified API adopts robust authentication and authorization models which are pivotal in safeguarding data, preventing unauthorized access, and maintaining the integrity and privacy of the information exchanged between applications. Strong authentication mechanisms, such as API keys or OAuth tokens, are critical to securely confirm identity, reducing the risk of unauthorized access. At the same time role-based access control and granular authorization are integral following the principle of least privilege, giving users the least access which is required to perform their roles successfully. 

Check out this article to learn more about the authentication and authorization models for better unified API security. 

2) Continuous monitoring and logging

A unified API is expected to continuously monitor and log all changes, authentication requests and other activities and receive real time alerts by using advanced firewalls. Some of the best practices for monitoring and logging include using logging libraries or frameworks to record API interactions, including request details, response data, timestamps, and client information, leverage API gateways, to capture data like request/response payloads, error codes, and client IPs, configuring alerts and notifications based on predefined security thresholds. 

Our quick guide API Security 101: Best Practices, How-to Guides, Checklist, FAQs can help you master API Security and learn how unified APIs can further accentuate your security posture. Explore common techniques, best practices to code snippets and a downloadable security checklist.

3) Data classification

A good unified API classifies data to restrict and filter access. Data is often categorized between what is highly restricted, confidential and public to ensure tiered level of access and authentication for better security. 

4) Data encryption

Since data protection is a key element for security with a unified API, there are multiple levels of encryption in place. It involves encryption at rest, encryption in transit and application level encryption as well for restricted data. 

5) Infrastructure protection

Finally, a unified API ensures security by facilitating infrastructure protection. Security practices like network segregation, DDoS protection using load balancers, intrusion detection, together helps ensure high levels of security from a unified API. 

6) API rate limiting & throttling

As mentioned, APIs are prone to DDoS attacks due to high intensity of traffic with an attack intention. Rate limiting and throttling help maintain the availability and performance of API services, protect them against abusive usage, and ensure a fair distribution of resources among clients. 

Go to our article on 10 Best Practices for API Rate Limiting and Throttling to understand how they can advance API security and how a unified API can implement preventive mechanisms in place to handle rate limits for all the supported apps to make their effective use. 

When to choose a unified API?

As a business, you can explore several ways in which you can facilitate integrations rather than building them in-house. However, there are a few instances when you should be using a unified API particularly.

Case I: When you want to integrate applications within the same category

A unified API is one of the best integration solutions if you wish to connect APIs or applications within the same category. For instance, there can be several CRM applications like Salesforce, Zoho, etc. that you might want to integrate, the same goes for HRIS, accounting and other categories. Therefore, a unified API can be a great solution if you have similar category applications to integrate. 

Start syncing data with all apps within a category using a single Knit Unified API. Check out all the integrations available.

Case II: When you have different data models

Secondly, a major use case for unified API comes when you have applications which follow different datasets, models and architecture and you want to standardize and normalize data for exchange. A unified API will add an abstraction layer which will help you normalize data from different applications with diverse syntax into a uniform and standardized format. 

Case III: When you want to ensure data security

Next, when it comes to using a unified API, data security becomes a key benefit. Integrations and data exchange are vulnerable to unauthorized access and ensuring high levels of security is important. With factors like least privilege, encryption, infrastructure security, etc. a unified API is a good pathway to integration when security is a key parameter for you for decision making. 

You can easily check the API security posture of any unified API provider using this in-depth checklist on How to Evaluate API Security of a Third Party API Provider.

Case IV: When you have limited domain expertise

There might be times when your team doesn’t have the domain expertise for a particular application you might be using and may not be well versed with the terminologies there. For instance, if you are using an HRIS application and your team lacks expertise in the HR and payroll space, chances are you won’t be able to understand different data nomenclatures being used. Here, using a unified API makes sense because it ensures accurate data mapping across applications. 

Get Knit Unified API Key

Case V: When you don’t want to spend engineering time in understanding several APIs

Finally, a unified API is the right choice if you don’t want to spend your engineering bandwidth in understanding and learning about different API, their endpoints and architecture. Different APIs are built on REST, SOAP, GraphQL, each of which requires a high level of expertise and understanding, pushing companies to invest in developer hiring with relevant skills and experience. However, when it comes to a unified API, the engineering teams only need to learn about one endpoint and develop knowledge of a single architecture. Usually, unified APIs are built on REST. Thus, you should go for a unified API if you don’t want to invest engineering time in API education. 

If you find yourself conflicted between whether building or buying is the best approach to SaaS integrations and how to choose the right one for you, check out our article on Build vs Buy: The Best Approach to SaaS Integrations to make an informed decision. 

Unified API vs Workflow Automation

While building integrations in-house vs leveraging unified API are two approaches you can follow, there are other paths you can tread under the ‘buying’ integrations landscape. One of the leading approaches is workflow automation. Let’s quickly compare these two approaches under the buying integrations banner.

Workflow automation tools facilitate product integration by automating workflow with specific triggers. These are mostly low code tools which can be connected with specific products by engineering teams for integration with third party software or platforms. Choose workflow automation for:

  • A low code integration solution
  • One-off customer facing integration or integrations for internal use
  • Limited functionalities for data normalization
  • Off-the rack workflows and integration syncs

A unified API normalizes data from different applications within a software category and transfers it to your application in real time. Here, data from all applications from a specific category like CRM, HRMS, Payroll, ATS, etc. is normalized into a common data model which your product understands and can offer to your end customers. Use a unified API for:

  • Standardized customer-facing integrations
  • High levels of data normalization and standardization
  • Scalable integrations that can be replicated across customers
  • A native integration experience which can be scaled efficiently

For a more detailed comparison between these two approaches to make an informed choice about which way to go, check out our article on Unified API vs Workflow Automation: Which One Should You Choose?

How to choose the right unified API?

If you have decided that a unified API is the way to go for you to facilitate better integrations for your business, there are a few factors you must keep in mind while selecting the right unified API among the different options available.

1. Coverage of API endpoints and applications

Start by evaluating how many API endpoints does the unified API cover. As you know that APIs can be built of REST, SOAP, GraphQL, it is important that your unified API covers them all and ensures that you have to learn the rules of a single architecture. At the same time, it is vital that it covers all or at least most of the applications or software that fall under the category you are looking for in a unified API. For instance, there can be thousands of applications within the HRIS category, you must evaluate if the unified API ensures that all HRIS applications or the ones that you use/ might need in the future are covered. 

Taking this example forward, here is a quick comparison between Finch and Knit on which unified HR API is most suited for user data, security and management. 

2. Data storage and security

Second, we mentioned that a good unified API provides you with a strong security posture.Therefore, it is important to check for the encryption and authentication models it uses. Furthermore, security parameters on least privilege, etc. must also be accounted for. A related factor to security is data storage. On the one hand, you must ensure that the unified API is compliant with data protection and other confidentiality laws, since they might have access to your and your customer’s data. On the other hand, it is equally important to ensure that the unified API doesn’t create a copy of customer data which can lead to security risks and additional storage costs. 

3. Pricing structure

Next, you need to check the pricing structure or pricing model being offered by the unified API. Pricing structures can be based on per customer along with platform charges, flat rates for a fixed number of employees and API call based charges. Increasingly, API call based charges are considered to be the most popular among developers as they turn out to be the most cost effective. Other pricing models which are not usage based can be very expensive and not sustainable for many companies. 

4. Data sync model

A unified API can have data sync in different ways, either it is polling first or webhooks first. Gradually, developers are preferring a webhooks first approach where customers don’t have to maintain a polling infrastructure as data updates are dispatched to customers' servers as and when they happen. Depending on your needs, you must evaluate the unified API based on the data sync model that you prefer. 

If you are confused between which unified API provider to choose, here’s a quick comparison of Knit and Merge, two leading names in the ecosystem focusing on data syncs, integration management, security and other aspects to help you choose the platform which is right for you. 

5. Monetization opportunities 

Finally, you should look for unified APIs which can provide you with monetization opportunities in addition to reduced costs and other benefits mentioned above. Gauge and evaluate whether or not the unified API can help you provide additional functionalities or efficiencies to your customers for which you can charge a premium. While it might be applicable for every application category you use, it is always good to have a monetization lens on when you are evaluating which unified API to choose. 

6. Scalability

Make sure your unified API can grow as you add more integrations and data load. Check if it can handle your current and future integrations. Also, ensure it can manage large amounts of data quickly. Use batch processing to handle the incoming data from different sources efficiently.

While these are a few parameters, explore our detailed article on What Should You Look For in A Unified API Platform? while evaluating an API management tool for your business.

7. Integration maintenance

It is important the unified API not only helps you build integrations but also enables you to maintain them with detailed Logs, Issues, Integrated Accounts and Syncs page and supports you to keep track of every API calls, data syncs and requests. 

Learn how Knit can help you maintain the health of your integrations without a headache.

Wrapping up: TL:DR

To conclude, it is evident that unified APIs have the potential to completely reinvent the integration market with their underlying potential to reduce costs while making the entire integration lifecycle seamless for businesses. Here are a few key takeaways that you should keep in mind:

  • A unified API adds an abstraction layer to connect different API for software in the same category
  • The high costs of building and maintaining integrations along with the engineering team drain are the major factors leading to the rise of the unified API
  • It is important to ensure that your unified API normalizes and standardizes data for exchange
  • Security in the form of authentication, encryption, least privilege, data classification, etc. are important parameters that make unified API a preferred choice
  • A unified API is the best option when you wish to integrates similar software category applications and don’t wish to spend engineering bandwidth on learning different architectures
  • Using a unified API can help developers take their products to market faster and scale seamlessly, addressing increasing customer integration needs
  • Factors like data storage, pricing, data sync models, coverage, etc. must be considered while choosing the right unified API for your business

Overall, a unified API can help businesses integrate high volumes of applications in a resource-lite manner, ultimately saving thousands of dollars and engineering bandwidth which can be invested in building and improving core product functionalities for better market penetration and business growth.

If you are looking to build multiple HRIS, ATS, CRM or Accounting integrations faster, talk to our experts to learn how we can help your use case

Developers
Nov 18, 2023

API Pagination 101: Best Practices for Efficient Data Retrieval

11
mins

If you are looking to unlock 40+ HRIS and ATS integrations with a single API key, check out Knit API. If not, keep reading

Note: This is our master guide on API Pagination where we solve common developer queries in detail with common examples and code snippets. Feel free to visit the smaller guides linked later in this article on topics such as page size, error handling, pagination stability, caching strategies and more.

In the modern application development and data integration world, APIs (Application Programming Interfaces) serve as the backbone for connecting various systems and enabling seamless data exchange. 

However, when working with APIs that return large datasets, efficient data retrieval becomes crucial for optimal performance and a smooth user experience. This is where API pagination comes into play.

In this article, we will discuss the best practices for implementing API pagination, ensuring that developers can handle large datasets effectively and deliver data in a manageable and efficient manner. (We have linked bite sized how-to guides on all API pagination FAQs you can think of in this article. Keep reading!)

But before we jump into the best practices, let’s go over what is API pagination and the standard pagination techniques used in the present day.

What is API Pagination

API pagination refers to a technique used in API design and development to retrieve large data sets in a structured and manageable manner. When an API endpoint returns a large amount of data, pagination allows the data to be divided into smaller, more manageable chunks or pages. 

Each page contains a limited number of records or entries. The API consumer or client can then request subsequent pages to retrieve additional data until the entire dataset has been retrieved.
Pagination typically involves the use of parameters, such as offset and limit or cursor-based tokens, to control the size and position of the data subset to be retrieved. 

These parameters determine the starting point and the number of records to include on each page.

Advantages of API Pagination

By implementing API pagination, developers as well as consumers can have the following advantages - 

1. Improved Performance

Retrieving and processing smaller chunks of data reduces the response time and improves the overall efficiency of API calls. It minimizes the load on servers, network bandwidth, and client-side applications.

2. Reduced Resource Usage 

Since pagination retrieves data in smaller subsets, it reduces the amount of memory, processing power, and bandwidth required on both the server and the client side. This efficient resource utilization can lead to cost savings and improved scalability.

3. Enhanced User Experience

Paginated APIs provide a better user experience by delivering data in manageable portions. Users can navigate through the data incrementally, accessing specific pages or requesting more data as needed. This approach enables smoother interactions, faster rendering of results, and easier navigation through large datasets.

4. Efficient Data Transfer

With pagination, only the necessary data is transferred over the network, reducing the amount of data transferred and improving network efficiency.

5. Scalability and Flexibility

Pagination allows APIs to handle large datasets without overwhelming system resources. It provides a scalable solution for working with ever-growing data volumes and enables efficient data retrieval across different use cases and devices.

6. Error Handling

With pagination, error handling becomes more manageable. If an error occurs during data retrieval, only the affected page needs to be reloaded or processed, rather than reloading the entire dataset. This helps isolate and address errors more effectively, ensuring smoother error recovery and system stability.

Common examples of paginated APIs 

Some of the most common, practical examples of API pagination are: 

  • Platforms like Twitter, Facebook, and Instagram often employ paginated APIs to retrieve posts, comments, or user profiles. 
  • Online marketplaces such as Amazon, eBay, and Etsy utilize paginated APIs to retrieve product listings, search results, or user reviews.
  • Banking or payment service providers often provide paginated APIs for retrieving transaction history, account statements, or customer data.
  • Job search platforms like Indeed or LinkedIn Jobs offer paginated APIs for retrieving job listings based on various criteria such as location, industry, or keywords.

API pagination techniques

There are several common API pagination techniques that developers employ to implement efficient data retrieval. Here are a few useful ones you must know:

  1. Offset and limit pagination
  2. Cursor-based pagination
  3. Page-based pagination
  4. Time-based pagination
  5. Keyset pagination

Read: Common API Pagination Techniques to learn more about each technique

Best practices for API pagination

When implementing API pagination in Python, there are several best practices to follow. For example,  

1. Use a common naming convention for pagination parameters

Adopt a consistent naming convention for pagination parameters, such as "offset" and "limit" or "page" and "size." This makes it easier for API consumers to understand and use your pagination system.

2. Always include pagination metadata in API responses

Provide metadata in the API responses to convey additional information about the pagination. 

This can include the total number of records, the current page, the number of pages, and links to the next and previous pages. This metadata helps API consumers navigate through the paginated data more effectively.

For example, here’s how the response of a paginated API should look like -

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{
 "data": [
   {
     "id": 1,
     "title": "Post 1",
     "content": "Lorem ipsum dolor sit amet.",
     "category": "Technology"
   },
   {
     "id": 2,
     "title": "Post 2",
     "content": "Praesent fermentum orci in ipsum.",
     "category": "Sports"
   },
   {
     "id": 3,
     "title": "Post 3",
     "content": "Vestibulum ante ipsum primis in faucibus.",
     "category": "Fashion"
   }
 ],
 "pagination": {
   "total_records": 100,
   "current_page": 1,
   "total_pages": 10,
   "next_page": 2,
   "prev_page": null
 }
}
        
    

3. Determine an appropriate page size

Select an optimal page size that balances the amount of data returned per page. 

A smaller page size reduces the response payload and improves performance, while a larger page size reduces the number of requests required.

Determining an appropriate page size for a paginated API involves considering various factors, such as the nature of the data, performance considerations, and user experience. 

Here are some guidelines to help you determine the optimal page size.

Read: How to determine the appropriate page size for a paginated API 

4. Implement sorting and filtering options

Provide sorting and filtering parameters to allow API consumers to specify the order and subset of data they require. This enhances flexibility and enables users to retrieve targeted results efficiently. Here's an example of how you can implement sorting and filtering options in a paginated API using Python:

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# Dummy data
products = [
    {"id": 1, "name": "Product A", "price": 10.0, "category": "Electronics"},
    {"id": 2, "name": "Product B", "price": 20.0, "category": "Clothing"},
    {"id": 3, "name": "Product C", "price": 15.0, "category": "Electronics"},
    {"id": 4, "name": "Product D", "price": 5.0, "category": "Clothing"},
    # Add more products as needed
]


@app.route('/products', methods=['GET'])
def get_products():
    # Pagination parameters
    page = int(request.args.get('page', 1))
    per_page = int(request.args.get('per_page', 10))


    # Sorting options
    sort_by = request.args.get('sort_by', 'id')
    sort_order = request.args.get('sort_order', 'asc')


    # Filtering options
    category = request.args.get('category')
    min_price = float(request.args.get('min_price', 0))
    max_price = float(request.args.get('max_price', float('inf')))


    # Apply filters
    filtered_products = filter(lambda p: p['price'] >= min_price and p['price'] <= max_price, products)
    if category:
        filtered_products = filter(lambda p: p['category'] == category, filtered_products)


    # Apply sorting
    sorted_products = sorted(filtered_products, key=lambda p: p[sort_by], reverse=sort_order.lower() == 'desc')


    # Paginate the results
    start_index = (page - 1) * per_page
    end_index = start_index + per_page
    paginated_products = sorted_products[start_index:end_index]


    return jsonify(paginated_products)

        
    

5. Preserve pagination stability

Ensure that the pagination remains stable and consistent between requests. Newly added or deleted records should not affect the order or positioning of existing records during pagination. This ensures that users can navigate through the data without encountering unexpected changes.

Read: 5 ways to preserve API pagination stability

6. Handle edge cases and error conditions

Account for edge cases such as reaching the end of the dataset, handling invalid or out-of-range page requests, and gracefully handling errors. 

Provide informative error messages and proper HTTP status codes to guide API consumers in handling pagination-related issues.

Read: 7 ways to handle common errors and invalid requests in API pagination

7. Consider caching strategies

Implement caching mechanisms to store paginated data or metadata that does not frequently change. 

Caching can help improve performance by reducing the load on the server and reducing the response time for subsequent requests.

Here are some caching strategies you can consider: 

1. Page level caching

Cache the entire paginated response for each page. This means caching the data along with the pagination metadata. This strategy is suitable when the data is relatively static and doesn't change frequently.

2. Result set caching

Cache the result set of a specific query or combination of query parameters. This is useful when the same query parameters are frequently used, and the result set remains relatively stable for a certain period. You can cache the result set and serve it directly for subsequent requests with the same parameters.

3. Time-based caching

Set an expiration time for the cache based on the expected freshness of the data. For example, cache the paginated response for a certain duration, such as 5 minutes or 1 hour. Subsequent requests within the cache duration can be served directly from the cache without hitting the server.

4. Conditional caching

Use conditional caching mechanisms like HTTP ETag or Last-Modified headers. The server can respond with a 304 Not Modified status if the client's cached version is still valid. This reduces bandwidth consumption and improves response time when the data has not changed.

5. Reverse proxy caching

Implement a reverse proxy server like Nginx or Varnish in front of your API server to handle caching. 

Reverse proxies can cache the API responses and serve them directly without forwarding the request to the backend API server. 

This offloads the caching responsibility from the application server and improves performance.

Simplify API pagination 

In conclusion, implementing effective API pagination is essential for providing efficient and user-friendly access to large datasets. But it isn’t easy, especially when you are dealing with a large number of API integrations.

Using a unified API solution like Knit ensures that your API pagination requirements is handled without you requiring to do anything anything other than embedding Knit’s UI component on your end. 

Once you have integrated with Knit for a specific software category such as HRIS, ATS or CRM, it automatically connects you with all the APIs within that category and ensures that you are ready to sync data with your desired app. 

In this process, Knit also fully takes care of API authorization, authentication, pagination, rate limiting and day-to-day maintenance of the integrations so that you can focus on what’s truly important to you i.e. building your core product.

By incorporating these best practices into the design and implementation of paginated APIs, Knit creates highly performant, scalable, and user-friendly interfaces for accessing large datasets. This further helps you to empower your end users to efficiently navigate and retrieve the data they need, ultimately enhancing the overall API experience.

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