What Is Swagger and How It Makes Working with APIs Easier

Swagger is a universal set of tools for designing, documenting, testing, and deploying REST APIs based on the widely accepted OpenAPI and AsyncAPI standards.

API vs REST API

API (Application Programming Interface) is a set of rules and tools for interaction between different applications. It defines how one program can request data or functionality from another.

For example, calling a method from the mathematical module of the Python programming language is the simplest form of a local API, through which different components of a program can exchange data with each other:

import math  # importing the math module
result = math.sqrt(16)  # calling the API method of the math module to calculate the square root
print(f"The square root of 16 is {result}")  # outputting the result to the console

In this case, the math module provides a set of functions for working with mathematical operations, and the sqrt() function is part of the interface that hides the internal implementation of the module.

REST API is an API that follows the principles of REST (Representational State Transfer) architecture, in which interaction with the resources of another program is performed via HTTP requests (GET, POST, PUT, DELETE) represented as URLs (endpoints).

For example, retrieving, sending, deleting, and modifying content on websites on the Internet is done by sending corresponding requests to specific URLs with optional additional parameters if required:

• Retrieving the main page
  • GET / HTTP/1.1
  • Host: website.com
• Retrieving the first page of article listings
  • GET /website.com/page/1 HTTP/1.1
  • Host: website.com
• Retrieving the second page of article listings
  • GET /website.com/page/2 HTTP/1.1
  • Host: website.com
• Publishing a new article
  • POST /website.com/newarticle HTTP/1.1
  • Host: website.com
• Deleting an existing article
  • DELETE /website.com/article/some-article HTTP/1.1
  • Host: website.com

Thus, a REST API is an extension of an API that defines a specific type of interaction between programs.

OpenAPI vs AsyncAPI

As network interactions developed, the need arose to unify API descriptions to simplify their development and maintenance. Therefore, standards began to emerge for REST and other API types.

Currently, two standards are popular. One describes synchronous APIs, and the other describes asynchronous ones:

• OpenAPI: Intended for REST APIs. Represents synchronous message exchange (GET, POST, PUT, DELETE) over the HTTP protocol. All messages are processed sequentially by the server. For example, an online store that sends product listing pages for each user request

• AsyncAPI: Intended for event-driven APIs. Represents asynchronous message exchange over protocols such as MQTT, AMQP, WebSockets, STOMP, NATS, SSE, and others. Each individual message is sent by a message broker to a specific handler. For example, a chat application that sends user messages via WebSockets.

Despite architectural differences, both standards allow describing application APIs as specifications in either JSON or YAML. Both humans and computers can read such specifications.

Here is an example of a simple OpenAPI specification in YAML format:

openapi: 3.0.0
info:
  title: Simple Application
  description: This is just a simple application
  version: 1.0.1
servers:
  - url: http://api.website.com/
    description: Main API
  - url: http://devapi.website.com/
    description: Additional API
paths:
  /users:
    get:
      summary: List of users
      description: This is an improvised list of existing users
      responses:
        "200":
          description: List of users in JSON format
          content:
            application/json:
              schema:
                type: array
                items:
                  type: string

The full specification description is available on the official OpenAPI website.

And here is an example of a simple AsyncAPI specification in YAML format:

asyncapi: 3.0.0
info:
  title: 'Simple Application'
  description: 'This is just a simple application'
  version: '1.0.1'
channels:
  some:
    address: 'some'
    messages:
      saySomething:
        payload:
          type: string
          pattern: '^Here’s a little phrase: .+$'
operations:
  something:
    action: 'receive'
    channel:
      $ref: '#/channels/some'

You can find the full specification description on the official AsyncAPI website.

Based on a specification, we can generate various data: documentation, code, tests, etc. In fact, it can have a wide range of applications, to the point where a neural network could generate all the client and server code for an application.  

Thus, a specification is a set of formal rules that governs how an interface to an application operates.

This is exactly where tools like Swagger come into play. With them, you can manage an API specification visually: edit, visualize, and test it.

And most importantly, Swagger allows you to generate and maintain documentation that helps explain how a specific API works to other developers.

Swagger Tools

Aiming to cover a wide range of API-related tasks, Swagger provides tools with different areas of responsibility:

• Swagger UI. A browser-based tool for visualizing the specification. It allows sending requests to the API directly from the browser and supports authorization through API keys, OAuth, JWT, and other mechanisms.

• Swagger Editor. A browser-based tool for editing specifications with real-time visualization. It edits documentation, highlights syntax, performs autocompletion, and validates the API.

• Swagger Codegen. A command-line tool for generating server and client code based on the specification. It can generate code in JavaScript, Java, Python, Go, TypeScript, Swift, C#, and more. It is also responsible for generating interactive documentation accessible from the browser.

• Swagger Hub. A cloud-based tool for team collaboration using Swagger UI and Swagger Editor. It stores specifications on cloud servers, performs versioning, and integrates with CI/CD pipelines.

Thus, with Swagger, we can visualize, edit, generate, and publish an API. 

You can find the full list of the Swagger tools on the official website.

Who Needs Swagger and Why

So far, we have examined what Swagger is and how it relates to REST APIs.  Now is a good time to discuss who needs it and why.

The main users of Swagger are developers, system analysts, and technical writers: the first develop the API, the second analyze it, and the third document it. Accordingly, Swagger can be used for the following tasks:

• API Development. Visual editing of specifications makes using Swagger so convenient that it alone accelerates API development. Moreover, Swagger can generate client and server code implementing the described API in various programming languages.

• API Interaction. Swagger assists in API testing, allowing requests with specific parameters to be sent to exact endpoints directly from the browser.

• API Documentation. Swagger helps form an API description that can later be used to create interactive documentation for API users.

That is exactly why we need Swagger and all of its tools: for step-by-step work on an API.

How to Use Swagger

So, how does Swagger work? As an ecosystem, Swagger performs many functions related to API development and maintenance.

Editing a Specification

For interactive editing of REST API specifications in Swagger, there is a special tool, Swagger Editor.

Swagger Editor interface: the left side contains a text field for editing the specification, while the right side shows real-time visualization of the documentation.

You can work on a specification using either the online version of the classic Swagger Editor or the updated Swagger Editor Next.

Both editors visualize live documentation in real time based on the written specification, highlighting any detected errors.

Through the top panel, you can perform various operations with the specification content, such as saving or importing its file.

Swagger Editor Next offers a more informative interface, featuring a code minimap and updated documentation design.

Of course, it is preferable to use a local version of the editor. The installation process for Swagger Editor and Swagger Editor Next is described in detail in the official Swagger documentation.

Specification Visualization

Using the Swagger UI tool, we can visualize a written specification so that any user can observe the structure of an API application.

A detailed guide for installing Swagger UI on a local server is available in the Swagger docs. There, you can also test a demo version of the Swagger UI dashboard.

A demo page of the Swagger UI panel that visualizes a test specification.

It is through Swagger UI that documentation management becomes interactive. Via its graphical interface, a developer can perform API requests as if they were being made by another application.

Generating Documentation

Based on a specification, the Swagger Codegen tool can generate API documentation as an HTML page.

You can download Swagger Codegen from the official Swagger website. An introduction to the data generation process is available in the GitHub repository, while detailed information and examples can be found in the documentation.

However, it is also possible to generate a specification based on special annotations in the application’s source code.

We can perform automatic parsing of annotations using third-party libraries that vary across programming languages. Among them:

• Gin-Swagger for Go with the Gin framework
• Flask-RESTPlus for Python with the Flask framework
• Swashbuckle for C# and .NET with the ASP.NET Core framework
• FastAPI for Python

It works roughly like this:

1. Library connection. The developer links a specification-generation library to the application’s source code.

2. Creating annotations. In the parts of the code where API request handling (routing) occurs, the developer adds special function calls from the connected library, specifying details about each endpoint: address, parameters, description, etc.

3. Generating the specification. The developer runs the application; the functions containing API information execute, and as a result, a ready YAML or JSON specification file is generated. It can then be passed to one of the Swagger tools, for example, to Swagger UI for documentation visualization.

As you can see, a specification file acts as a linking element (mediator) between different documentation tools. This is the power of standardization—a ready specification can be passed to anyone, anywhere, anytime.

For example, you can generate a specification in FastAPI, edit it in Swagger Editor, and visualize it in ReDoc.

Code Generation

Similarly, Swagger Codegen can generate client and server code that implements the logic described in the specification. You can find a full description of the generation capabilities in the official documentation.

However, it’s important to understand that generated code is quite primitive and hardly suitable for production use. There are several fundamental reasons for this:

• No business logic. The generated code does nothing by itself. It’s essentially placeholders, simple request handlers suitable for quick API testing.

• No real processes. Besides general architecture, generated code lacks lower-level operations such as data validation, logging, error handling, database work, etc.

• Low security. There are no checks or protections against various attack types.

Therefore, generated code is best used either as a starting template to be extended manually later or as a temporary solution for hypothesis testing during development.

API Testing

Through Swagger UI, you can select a specific address (endpoint) with given parameters to perform a test request to the software server that handles the API.

In this case, Swagger UI will visually display HTTP responses, clearly showing error codes, headers, and message bodies.

This eliminates the need to write special code snippets to create and process test requests.

Swagger Alternatives

Swagger is not the only tool for working with APIs. There are several others with similar functionality:

• Postman. A powerful tool for developing, testing, and documenting REST and SOAP APIs. It allows sending HTTP requests, analyzing responses, automating tests, and generating documentation.

• Apidog. A modern tool for API development, testing, documentation, and monitoring. It features an extremely beautiful and user-friendly interface in both light and dark themes.

• ReDoc. A tool for generating interactive documentation accessible from a browser, based on an OpenAPI specification.

• Apigee. A platform for developing, managing, and monitoring APIs owned by Google and part of the Google Cloud Platform.

• Mintlify. A full-fledged AI-based platform capable of generating an interactive, stylish documentation website through automatic analysis of a project’s repository code.

API tools differ only in implementation nuances and individual features. However, these differences may be significant for particular developers — it all depends on the project.

That’s why anyone interested in API documentation should first explore all available platforms. It may turn out that a simple tool with few parameters is suitable for one project, while another requires a complex system with many settings.

Conclusion

It’s important to understand that Swagger is a full-fledged framework for REST API development. This means that a developer is provided with a set of tools for maintaining an application’s API —from design through documentation for end users.

At the same time, beyond classic console tools, Swagger visualizes APIs clearly through the browser, making it suitable even for beginners just starting their development journey.

If any Swagger tool does not fit a particular project, it can be replaced with an alternative, since an application’s API is described in standardized OpenAPI or AsyncAPI formats, which are supported by many other tools.

You can find Swagger tutorials and comprehensive information about its tools in the official Swagger documentation.