coveralls-public VS prettier

cpan_coverage: This calculates the coverage of your test suite and reports the results. It also uploads the results to coveralls.io

I will normally use GitHub Actions to automatically run my test suite on each push, on every major version of Perl I support. One of the test runs will load Devel::Cover and use it to upload test coverage data to Codecov and Coveralls.

Several years ago I got into Travis CI and set up lots of my GitHub repos so they automatically ran the tests each time I committed to the repo. Later on, I also worked out how to tie those test runs into Coveralls.io so I got pretty graphs of how my test coverage was looking. I gave a talk about what I had done.

This approach will create two json coverage files, which will be merged together by NYC. Therefore the results will be purely local. If You don't mind using online tools like Codecov or Coveralls for merging data from different tests, then go ahead and use them. They will probably also be more accurate. But if You still want to learn how to get coverage from E2E, then please read through

Ideally, software can quickly go from development to production. Continuous deployment and delivery are some processes that make this possible. Continuous deployment means establishing an automated pipeline from development to production while continuous delivery means maintaining the main branch in a deployable state so that a deployment can be requested at any time. Predecos uses these tools. When a commit goes into master, the code is pushed directly to the public environment. Deployment also occurs when a push is made to a development branch enabling local/e2e testing before push to master. In this manner the master branch can be kept clean and ready for deployment most of the time. Problems that surface resulting from changes are visible before reaching master. Additional automated tools are used. Docker images are built for each microservice on commit to a development or master branch, a static code analysis is performed by SonarCloud revealing quality and security problems, Snyk provides vulnerability analysis and CodeClimate provides feedback on code quality while Coveralls provides test coverage. Finally, a CircleCI build is done. Each of these components use badges which give a heads-up display of the health of the system being developed. Incorporating each of these tools into the development process will keep the code on a trajectory of stability. For example, eliminating code smells, security vulnerabilities, and broken tests before merging a pull-request (PR) into master. Using Husky on development machines to ensure that code is well linted and locally tested before it is allowed to be pushed to source-control management (SCM). Applying additional processes such as writing tests around bugs meaning reintroduction of a given bug would cause a test to fail. The automated tools would then require that test to be fixed before push to SCM meaning fewer bugs will be reintroduced. Proper development processes and automation have a strong synergy.

There is https://coveralls.io/ and https://github.com/marketplace/codecov , but they are both priced for commercial usage. Do you know some free alternatives or approaches to have something similiar?

Add a Code Coverage CI step using Coveralls.io Add Dependency monitoring using Snyk

Since there is no need to reinvent the wheel, I will take advantage of an existing github action in the Continuous integration workflows category: Node.js. With this action I will set up this action in one of my public repositories. I will set up Node.js action for automating my unit test and also integrate with coveralls.io for getting a badge of how much my tests covers relevant lines.

Looks like https://github.com/lemurheavy/coveralls-public/issues/632 this issue based on the log. Try going through their solutions, maybe?

In this post, I also use ESLint + Standard JS as my code formatting tools. Formatting JS/TS code by using ESLint is also subjective and opinionated, arguably most people would rather use Prettier instead, which provides more configurable options.

Let's be honest - setting up tools for a new project can be a frustrating process. Especially when you want to jump straight to coding part. This is often the case with ESLint and Prettier, two popular tools in the JavaScript ecosystem that can sometimes interfere with each other when it comes to code formatting. Fortunately, there's a simple solution to this process, and it's called eslint-plugin-prettier.

From my point of view, Prettier doesn't work well for styling with utility classes. For a discussion see Prettier#7863 or Prettier#5948.

Prettier: An opinionated code formatter that enforces a consistent code style.

Automating code checks with static code analysis allows us to enforce code styling effectively. By integrating tools into our workflow, we can identify errors at an early stage, while coding instead of blocking us at the end. For instance, flake8 checks Python code for style and errors, eslint performs similar checks for JavaScript, and prettier automatically formats code to maintain consistency.

So anyways, I wanted to hook up Emacs with Astro support. For now, I've just been roughing it out there and running Prettier by itself and turning off save on format and auto-complete. It's been scary.

If you're a developer, you're surely familiar with Prettier and ESLint. With over 8 years of existence, they have established themselves as references in the JavaScript ecosystem.

prettier is used to format you text

No formatting inconsistencies: The committed code should follow the organization's code formatting standards(prettier or pretty-quick).

Let’s walk through the steps for a one-time setup to configure husky pre-commit and pre-push hooks, ESLint with code styles conventions, prettier code formatter, and lint-staged. Husky automatically runs a script on each commit or push. This is useful for linting files to enforce code styles that keeps the entire code base following conventions.