coveralls-public VS lint-staged

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?

We were already using lint-staged and have a pre-commit hook in place using Husky in our project for linter and prettier. So it made sense to add a check here.

Now you can config it in your package.json, here is the guide doc:

In the world of software development, maintaining consistent code quality and ensuring that the codebase adheres to predefined patterns and guidelines is crucial. However, manually enforcing these standards can be time-consuming and error-prone. This is where automation tools like Husky, Lint-Staged, Commitlint, and Commitizen come to the rescue. In this post, we will explore how these tools can be combined to streamline your development workflow.

This is wasted work that can and should be automated. Adding a linter and formatter on CI and a pre-commit hook such as lint-staged can do wonders.

lint-staged is a package that can be used to run formatting and linting commands on staged files in a Git repo.

To answer your next question: I lint and format on save, and I use Git hooks installed by Husky and executed through Lint-Staged (this tool helps ensure your Git hooks only run on modified files, etc) to ensure there are no lint or formatting errors whenever making a commit or pushing code. This is helpful for teams, as some developers tend to forget to run lint tasks, or don't have the Prettier extension installed in their IDE. If there are lint errors, the commit is rejected until fixed. YMMV - you'll need to fine-tune the strictness of this based on the team's needs.

Uses Husky Git hooks and Lint-staged pre-commit hooks.

Something else to consider is applying linting and formatting before every git commit. A package like Lint-staged only lints and formats on staged items, ensuring all pushed code follows the standards in the repo. This allows developers to have their own formatting preferences when developing, while the code homogenizes on push. Linting pre-commit also avoids strict rules like no-console or no-unused-vars restricting a developer when writing code, when it should only apply in production. Imagine not being able to console log anything during development!

Lint-Staged Docs

Additionally, there are pre-commit hooks which can be setup to seamlessly validate and modify the source code before every commit. I followed Prettier documentation to create one. I ran npx mrm@2 lint-staged which installed husky and lint-stagedand added a configuration to the project’s package.json. Then, I modified the commands a little and that's it.