swagger-ui VS starter-workflows

Swagger is a fantastic open-source toolset that's perfect for developing and describing RESTful APIs. It offers you a user-friendly interface to understand a service's capabilities without needing to dig into the code. It even provides a way for you to interact directly with the API, which means you get to test its functionality.

The API had an OpenAPI endpoint built with Swagger where I could download a JSON specification file for the API.

Swagger is a widely used tool for documenting and testing APIs.

Swagger is an open-source software framework that implements the OpenAPI Specification—an API description format for REST APIs. The OpenAPI Specification defines a standard, language-agnostic interface to HTTP APIs, enabling both humans and computers to discover and understand the capabilities of the API.

Mocking and Testing: Once the API design is complete, developers create mock APIs to simulate the behavior of the actual services. This early testing phase helps identify any issues or mismatches between design and implementation before substantial development efforts are invested. Tools like Postman or Swagger are invaluable for API testing and validation.

import fp from "fastify-plugin"; import swagger from "@fastify/swagger"; export default fp(async (fastify) => { fastify.register(swagger, { openapi: { info: { tags: [ { name: "drinks", description: "Drink-related endpoints", externalDocs: { description: "Find out more", url: "http://swagger.io", }, }, ], }, }, }); });

A very requested feature for Sharkio was the auto-generation of OpenAPI documentation using the recorded HTTP requests - to create standardized documentation.

Automation QA is a lot of the same duties as manual QA, but instead of writing and executing the test plans manually, we create and update automated tests that can run those validations programmatically, for example by using Selenium to automatically fill out and submit forms for a web application, or using Postman and/or Swagger to generate an API conversation test.

The code below is now roughly from memory and my controller would usually look something like this (Swashbuckle or NSwag attribute hints removed). There are some gotchas with Swagger and SwaggerUI for supporting multipart/form-data which I haven't included here since they now be fixed, since it's been a while since I checked.

GitHub Actions is a feature-rich CI/CD platform embedded within GitHub, enabling developers to automate, customize, and execute software development workflows directly in their repositories. An Action inside GitHub Actions is a discrete unit of automation that performs a specific task within a workflow. All the Actions are reusable, and there are many to choose from. You can even create your own reusable ones.

actions/starter-workflows

The real power of using PHP code-quality tools is when it’s added to your continuous integration process, which means it automatically checks the code every time someone makes a push or pull request to your project repo. In this section, we'll be looking at how to do just that. GitHub actions is available for free so we'll use it for demo purposes. Note that there are some limits to private repos, so set your test repo to public if you can.

You can even automate the running of this script — hence the directory name automation — to happen every time the data changes, using GitHub Actions.

You might remember that I’ve been taking an interest in GitHub Actions for the last year or so (I even wrote a book on the subject). And at the Perl Conference in Toronto last summer I gave a talk called “GitHub Actions for Perl Development” (here are the slides and the video).

Preevy is designed to be easily run in CI/CD workflows, such as GH Actions, Circle CI and others.

I set out to add further development and contribution tools to my ez-txt2html converter. Specifically, I wanted to introduce an initial Continuous Integration workflow. For this, I used the “Python Application” workflow template in Github Actions to create a CI testing workflow that builds a Py v3.12 environments, builds the project dependencies, runs Flake8 linting and Black formatting and then subsequently runs PyTest using the test suites I’ve written previously.

GitHub Actions

To start, I turned to the starter-workflows repository, a valuable resource housing diverse YAML files for various project types. My project being in .NET, I checked out the dotnet.yml file to get insights into the setup process. Understanding the YAML syntax and keywords like on, push, jobs, and steps is crucial for crafting an effective workflow. In my case, I wanted to the workflow to trigger "on" any "pushes" on the main branch. The job describes the specific task which can be given a name, and steps outline the necessary steps to run the job.

CI requires dedicated machines to checkout our code, built it and run tests. We can either setup our own machines, or we can provision a CI cloud provider to do this for us. GitHub actually provides its own CI service, GitHub Actions, that lets you automate workflows to GitHub repo events, like making a pull request or merging to a main branch.