caveman VS node

We are going to walk through the examples by building an online Warehouse management system using Caveman

Djula is a port of Python's Django template engine to Common Lisp. It's the default templating engine used by the framework Caveman for building web applications

Appreciate it. Can I ask one last thing. Between Snooze and Caveman2, which is the more current project?

This is interesting from a "look what we can do!" perspective, but practically speaking, I'm not sure there's a good reason for doing it this way. For all practical purposes, it would be better to use one of the "native" Common Lisp libraries for doing this, such as Caveman: http://8arrow.org/caveman/

Even as a big Common Lisp fan, I would really question using it in a situation where the project has strict requirements to use a particular framework for another language.

In this post, I am going to walk you through to setup Tailwind CSS for a Common Lisp web application using Caveman. If you want to know more about creating web applications using Common Lisp and Caveman, please check my previous posts on the topic.

We are going to use Caveman for scaffolding this project. Caveman is a lightweight web application framework created by Eitaro Fukamachi for Common lisp. Caveman is available on Quicklisp, so you can install it with:

Hence I chose Caveman for this project. After having been played around with and without Caveman for building web applications in Common Lisp, I found that it is the best framework out there for developing web apps in Lisp. Caveman is a lightweight web application framework created by Eitaro Fukamachi for Common lisp. Fukamachi has got some serious tools for doing web development in Lisp. Please feel free to check out his Github profile for more useful tools.

I have been trying to come up with a standard template using Caveman to deploy on Heroku. But I am struck with these issues, not quite getting it to work with the available buildpacks. Lot of the related articles are hopelessly outdated. Appreciate any help or pointers? https://github.com/fukamachi/caveman/issues/126 https://gitlab.com/duncan-bayne/heroku-buildpack-common-lisp/-/issues/6

To install and run Ember.js, you'll need to follow these steps: Install Node.js and npm (Node Package Manager) on your computer. You can download the latest version of Node.js from the official website. Once Node.js and npm are installed, open a terminal window and run the following command to install the Ember.js command line interface (CLI):

NodeJS - Link

To get involved in the Node.js developer community, you can join community discussions or begin with learning if you’re new. The community discussion houses a GitHub list of issues related to Node.js' core features. If you want to chat in real time about Node.js development, there are Slack groups, and you can still connect with IRC clients or web clients when using the browser. Node.js has a calendar for public meetings.

Download the latest version from the Node.js website, open the package installer, and follow the instructions Use a package manager like Homebrew with the command brew install node On Linux, you can consult this page to determine how you should install Node.

As with all experimental things, a few things are missing. Some of these might lead to people using dotenv until support for these gets added. I will mention them here and let you see if they are dealbreakers. You can also follow the GitHub issue to track missing feature support.

Node

Depending on the stack of the repository you are cloning, you might have to install additional dependencies. For this demo, I'm using my own website, which is a static website built with Astro.js. It which requires to have Node.js installed and Yarn for package manager.

A working Node.js v20+ environment

We will be using the self-hosted version of Renovate distributed via npm, but you can adapt the scripts in this article to use the Docker version, or others. Make sure you have Node.js installed on your machine.

To execute the algorithm, we will use Node.js (for the JavaScript runtime) and node-fetch (for network requests). This means we will run the code locally from the command line. For this project, we will have an output folder to store all the README data, as well as a list (queue) of repository URLs to visit. Before diving into the code, it is important to plan the input and output of the algorithm. For this web crawler, we will start at a valid GitHub repository page, which would be one URL string. After visiting each page with a README, we will export the data into a new file. Now lets cover the process of requesting a repository page from a URL. For this, we only care about saving the README file that is displayed, and we will ignore any other links that GitHub displays (such as the navbar). We will send a URL request with node-fetch, and retrieve the result of a HTML string. If we convert the HTML string to a DOM Tree, we can search for a specific element. GitHub stores the README file under a div with the class "markdown-body". We can use a library called 'jsdom' to use Browser API methods, and return a specific node.