starter-workflows VS ripgrep

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.

GitHub Actions

ripgrep - https://github.com/BurntSushi/ripgrep

Basic code searching skills seems like something new developers are never explicitly taught, but which is an absolutely crucial skill to build early on.

I guess the knowledge progression I would recommend would look something kind this:

- Learning about Ctrl+F, which works basically everywhere.

- Transitioning to ripgrep https://github.com/BurntSushi/ripgrep - I wouldn't even call this optional, it's truly an incredible and very discoverable tool. Requires keeping a terminal open, but that's a good thing for a newbie!

- Optional, but highly recommended: Learning one of the powerhouse command line editors. Teenage me recommended Emacs; current me recommends vanilla vim, purely because some flavor of it is installed almost everywhere. This is so that you can grep around and edit in the same window.

- In the same vein, moving back from ripgrep and learning about good old fashioned grep, with a few flags rg uses by default: `grep -r` for recursive search, `grep -ri` for case insensitive recursive search, and `grep -ril` for case insensitive recursive "just show me which files this string is found in" search. Some others too, season to taste.

- Finally hitting the wall with what ripgrep can do for you and switching to an actual indexed, dedicated code search tool.

live grep: ripgrep

The world has moved on though to opinionated tools, and Rust isn't even the furthest in that direction (That would be Go). The equivalent of those two lines in Cargo.toml would be this example of a basic configuration from the jacoco-maven-plugin: https://www.jacoco.org/jacoco/trunk/doc/examples/build/pom.x... - That's 40 lines in the section to do the "defaults".

Yes, you could add a load of config for files to include/exclude from coverage and so on, but the idea that that's a norm is way more common in Java projects than other languages. Like here's some example Cargo.toml files from complicated Rust projects:

Servo: https://github.com/servo/servo/blob/main/Cargo.toml

rust-gdext: https://github.com/godot-rust/gdext/blob/master/godot-core/C...

ripgrep: https://github.com/BurntSushi/ripgrep/blob/master/Cargo.toml

socketio: https://github.com/1c3t3a/rust-socketio/blob/main/socketio/C...

I'm not clear on why you're seeing the results you are. It could be because your haystack is so small that you're mostly just measuring noise. ripgrep 14 did introduce some optimizations in workloads like this by reducing match overhead, but I don't think it's anything huge in this case. (And I just tried ripgrep 13 on the same commands above and the timings are similar if a tiny bit slower.)

[1]: https://github.com/radare/ired

[2]: https://github.com/BurntSushi/ripgrep/discussions/2597

Explore o Ripgrep no repositório oficial: https://github.com/BurntSushi/ripgrep

🔎🗃️ ripgrep or ugrep (search fast, use regex patterns or fuzzy search, pipe output to bash/zsh shell for further processing V coloring)