YARD VS starter-workflows

JSDOC is a predefined method of documenting code for javascript ecosystem created in 1999 that works similar to libraries for other languages such as: Javadoc for java, YARD for ruby, etc..

In addition to project documentation, you've included a lot of code comments. You could adopt a standardized format and use it to generate API documentation. RDoc and YARD are two options. If I were reviewing this code at work, I would probably ask you to remove comments that explain what, not why.

I still just document everything using YARD and focus on designing really obvious Object Models and of course write tests. I have tried using sord to convert my YARD type annotations to RBS or RBI, but you still have to fill in missing bits, then use steep and somehow load in RBS/RBI files for other gems and stdlib, and it's just an uphill battle since Ruby is dynamically typed by default. Obviously Dynamic Typing lends itself more to Dynamic Languages, where you can call an arbitrary method and let the language VM figure it out at runtime. Static or Strong Typing lends itself better to compiled languages where everything needs to be resolved at compile time and converted into object code. If I need to work in a compiled language, then I'll use Crystal, which also supports type inference. TypeScript's type syntax is quite nice, but I tend to avoid writing massive JavaScript code bases where a Type Checker helps catch subtle bugs, and instead prefer sticking to minimal amounts of vanilla JavaScriot in order to keep complexity low and not overwhelm the browser.

I had a dig into the file history, and it looks like we have to go back to 0.7 to find the old tag list. Here we find the info we need to understand the intent of the @option tag:

YARD: http://yardoc.org/

I tend to follow along using the YardDoc comment style. It has many small things I love about it; an example is when yardoc is followed it can be used to generate RBS/Sorbet type files with the sord gem, you can also generate application documents similar to rdoc/sdoc.

That turns out to be a pretty common use case for markdown. Github, for example, renders your README.md is part of a git repo's "home" page. It's also common to have tooling that parses specially formatted comments in your source code and produce a documentation bundle, usually as a web page (ex. RDoc, YARD, JSDoc, etc.).

My first assumption was, that I should be able to generate markdown from the source. Same ruby and rails does now, but only tweaking a couple of parameters to generate .md files instead. YARD is being used for that and it supports any markup rdoc or yard.

I’ve long used the YARD format and chose to use that as my documentation syntax. I suppose I didn’t check with anyone on this decision and slowly started adding documentation. I want to use this post to synthesize my implicit decision and the benefits of using Yard as the documentation format.

That said, YARD is a ruby documentation tool that has a yard graph command you can use to dump a UML graph for your app into a .dot file, which can be used with lots of different graphing tools (usually graphviz but there are a bunch of online tools and open source projects that can visualize them for you).

GitHub Actions is a modern CI/CD tool integrated natively on GitHub. Itenables the rapid automation of build, test, deployment, and other custom workflows on GitHub with no need for external tools.

GitHub Actions is GitHub's CI/CD solution. You can use it to run automated tasks each time you change your code. Although the platform lacks a built-in Kubernetes integration, third-party plugins such as Azure's Deploy to Kubernetes Cluster action can automate deployments and manage different rollout strategies.

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.

# Based on https://github.com/actions/starter-workflows/blob/main/ci/node.js.yml name: CI on: pull_request: branches: - main jobs: ci: runs-on: ubuntu-latest steps: - uses: actions/checkout@v2 - uses: actions/setup-node@v2 with: node-version: lts/* cache: 'npm' - run: npm ci - run: npm run build --if-present - run: npm test

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.